Lei Xing

Abstract

PURPOSE: To assess the prostate intrafraction motion in volumetric modulated arc therapy treatments using cine megavoltage (MV) images acquired with an electronic portal imaging device (EPID). METHODS AND MATERIALS: Ten prostate cancer patients were treated with volumetric modulated arc therapy using a Varian TrueBeam linear accelerator equipped with an EPID for acquiring cine MV images during treatment. Cine MV images acquisition was scheduled for single or multiple treatment fractions (between 1 and 8). A novel automatic fiducial detection algorithm that can handle irregular multileaf collimator apertures, field edges, fast leaf and gantry movement, and MV image noise and artifacts in patient anatomy was used. All sets of images (approximately 25,000 images in total) were analyzed to measure the positioning accuracy of implanted fiducial markers and assess the prostate movement. RESULTS: Prostate motion can vary greatly in magnitude among different patients. Different motion patterns were identified, showing its unpredictability. The mean displacement and standard deviation of the intrafraction motion was generally less than 2.0 ± 2.0 mm in each of the spatial directions. In certain patients, however, the percentage of the treatment time in which the prostate is displaced more than 5 mm from its planned position in at least 1 spatial direction was 10% or more. The maximum prostate displacement observed was 13.3 mm. CONCLUSION: Prostate tracking and motion assessment was performed with MV imaging and an EPID. The amount of prostate motion observed suggests that patients will benefit from its real-time monitoring. Megavoltage imaging can provide the basis for real-time prostate tracking using conventional linear accelerators.

View details for DOI 10.1016/j.ijrobp.2013.03.007

View details for PubMedID 23608236

Abstract

Purpose: Metal artifact reduction has long been an important topic in x-ray CT image reconstruction. In this work, the authors propose an iterative method that sequentially minimizes a reweighted total variation (TV) of the image and produces substantially artifact-reduced reconstructions.Methods: A sequentially reweighted TV minimization algorithm is proposed to fully exploit the sparseness of image gradients (IG). The authors first formulate a constrained optimization model that minimizes a weighted TV of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available projection measurements, with image non-negativity enforced. The authors then solve a sequence of weighted TV minimization problems where weights used for the next iteration are computed from the current solution. Using the complete projection data, the algorithm first reconstructs an image from which a binary metal image can be extracted. Forward projection of the binary image identifies metal traces in the projection space. The metal-free background image is then reconstructed from the metal-trace-excluded projection data by employing a different set of weights. Each minimization problem is solved using a gradient method that alternates projection-onto-convex-sets and steepest descent. A series of simulation and experimental studies are performed to evaluate the proposed approach.Results: Our study shows that the sequentially reweighted scheme, by altering a single parameter in the weighting function, flexibly controls the sparsity of the IG and reconstructs artifacts-free images in a two-stage process. It successfully produces images with significantly reduced streak artifacts, suppressed noise and well-preserved contrast and edge properties.Conclusions: The sequentially reweighed TV minimization provides a systematic approach for suppressing CT metal artifacts. The technique can also be generalized to other "missing data" problems in CT image reconstruction.

View details for DOI 10.1118/1.4811129

View details for Web of Science ID 000321272200044

View details for PubMedID 23822444

Abstract

Purpose: This study presents an improved technique to further simplify the fluence-map in intensity modulated radiation therapy (IMRT) inverse planning, thereby reducing plan complexity and improving delivery efficiency, while maintaining the plan quality.Methods: First-order total-variation (TV) minimization (min.) based on L1-norm has been proposed to reduce the complexity of fluence-map in IMRT by generating sparse fluence-map variations. However, with stronger dose sparing to the critical structures, the inevitable increase in the fluence-map complexity can lead to inefficient dose delivery. Theoretically, L0-min. is the ideal solution for the sparse signal recovery problem, yet practically intractable due to its nonconvexity of the objective function. As an alternative, the authors use the iteratively reweighted L1-min. technique to incorporate the benefits of the L0-norm into the tractability of L1-min. The weight multiplied to each element is inversely related to the magnitude of the corresponding element, which is iteratively updated by the reweighting process. The proposed penalizing process combined with TV min. further improves sparsity in the fluence-map variations, hence ultimately enhancing the delivery efficiency. To validate the proposed method, this work compares three treatment plans obtained from quadratic min. (generally used in clinic IMRT), conventional TV min., and our proposed reweighted TV min. techniques, implemented by a large-scale L1-solver (template for first-order conic solver), for five patient clinical data. Criteria such as conformation number (CN), modulation index (MI), and estimated treatment time are employed to assess the relationship between the plan quality and delivery efficiency.Results: The proposed method yields simpler fluence-maps than the quadratic and conventional TV based techniques. To attain a given CN and dose sparing to the critical organs for 5 clinical cases, the proposed method reduces the number of segments by 10-15 and 30-35, relative to TV min. and quadratic min. based plans, while MIs decreases by about 20%-30% and 40%-60% over the plans by two existing techniques, respectively. With such conditions, the total treatment time of the plans obtained from our proposed method can be reduced by 12-30 s and 30-80 s mainly due to greatly shorter multileaf collimator (MLC) traveling time in IMRT step-and-shoot delivery.Conclusions: The reweighted L1-minimization technique provides a promising solution to simplify the fluence-map variations in IMRT inverse planning. It improves the delivery efficiency by reducing the entire segments and treatment time, while maintaining the plan quality in terms of target conformity and critical structure sparing.

View details for DOI 10.1118/1.4811100

View details for Web of Science ID 000321272200023

View details for PubMedID 23822423

Abstract

Intraoperative fluorescence imaging especially near-infrared fluorescence (NIRF) imaging has the potential to revolutionize neurosurgery by providing high sensitivity and real-time image guidance to surgeons for defining gliomas margins. Fluorescence probes including targeted nanoprobes are expected to improve the specificity and selectivity for intraoperative fluorescence or NIRF tumor imaging. The main focus of this article is to provide a brief overview of intraoperative fluorescence imaging systems and probes including fluorescein sodium, 5-aminolevulinic acid, dye-containing nanoparticles, and targeted NIRF nanoprobes for their applications in image-guided resection of malignant gliomas. Moreover, photoacoustic imaging is a promising molecular imaging modality, and its potential applications for brain tumor imaging are also briefly discussed.

View details for DOI 10.1002/wnan.1212

View details for PubMedID 23378052

Abstract

Conventional volumetric modulated arc therapy (VMAT) discretizes the angular space into equally spaced control points during planning and then optimizes the apertures and weights of the control points. The aperture at an angle in between two control points is obtained through interpolation. This approach tacitly ignores the differential need for intensity modulation of different angles. As such, multiple arcs are often required, which may oversample some angle(s) and undersample others. The purpose of this work is to develop a segmentally boosted VMAT scheme to eliminate the need for multiple arcs in VMAT treatment with improved dose distribution and?or delivery efficiency.The essence of the new treatment scheme is how to identify the need of individual angles for intensity modulation and to provide the necessary beam intensity modulation for those beam angles that need it. We introduce a "demand metric" at each control point to decide which station or control points need intensity modulation. To boost the modulation at selected stations, additional segments are added in the vicinity of the selected stations. The added segments are then optimized together with the original set of station or control points as a whole. The authors apply the segmentally boosted planning technique to four previously treated clinical cases: two head and neck (HN) cases, one prostate case, and one liver case. The proposed planning technique is compared with conventional one-arc and two-arc VMAT.The proposed segmentally boosted VMAT technique achieves better critical structure sparing than one-arc VMAT with similar or better target coverage in all four clinical cases. The segmentally boosted VMAT also outperforms two-arc VMAT for the two complicated HN cases, yet with ?30% reduction in the machine monitor units (MUs) relative to two-arc VMAT, which leads to less leakage?scatter dose to the patient and can potentially translate into faster dose delivery. For the less challenging prostate and liver cases, similar critical structure sparing as the two-arc VMAT plans was obtained using the segmentally boosted VMAT. The benefit for the two simpler cases is the reduction of MUs and improvement of treatment delivery efficiency.Segmentally boosted VMAT achieves better dose conformality and?or reduced MUs through effective consideration of the need of individual beam angles for intensity modulation. Elimination of the need for multiple arcs in rotational arc therapy while improving the dose distribution should lead to improved workflow and treatment efficacy, thus may have significant implication to radiation oncology practice.

View details for DOI 10.1118/1.4802748

View details for PubMedID 23635247

Abstract

To obtain on-treatment volumetric patient anatomy during respiratory gated volumetric modulated arc therapy (VMAT).On-board imaging device integrated with Linacs offers a viable tool for obtaining patient anatomy during radiation treatment delivery. In this study, the authors acquired beam-level kV images during gated VMAT treatments using a Varian TrueBeam?STx Linac. These kV projection images are triggered by a respiratory gating signal and can be acquired immediately before treatment MV beam on at every breathing cycle during delivery. Because the kV images are acquired with an on-board imaging device during a rotational arc therapy, they provide the patient anatomical information from many different angles or projection views (typically 20-40). To reconstruct the volumetric image representing patient anatomy during the VMAT treatment, the authors used a compressed sensing method with a fast first-order optimization algorithm. The conventional FDK reconstruction was also used for comparison purposes. The method was tested on a dynamic anthropomorphic physical phantom as well as a lung patient.The reconstructed volumetric images for a dynamic anthropomorphic physical phantom and a lung patient showed clearly visible soft-tissue target as well as other anatomical structures, with the proposed compressed sensing-based image reconstruction method. Compared with FDK, the compressed sensing method leads to a ? two and threefold increase in contrast-to-noise ratio around the target area in the phantom and patient case, respectively.The proposed technique provides on-treatment volumetric patient anatomy, with only a fraction (<10%) of the imaging dose used in conventional CBCT procedures. This anatomical information may be valuable for geometric verification and treatment guidance, and useful for verification of treatment dose delivery, accumulation, and adaptation in the future.

View details for DOI 10.1118/1.4794925

View details for PubMedID 23556870

Abstract

To determine how the respiratory phase impacts dose to normal organs during stereotactic body radiation therapy (SBRT) for pancreatic cancer.Eighteen consecutive patients with locally advanced, unresectable pancreatic adenocarcinoma treated with SBRT were included in this study. On the treatment planning 4-dimensional computed tomography (CT) scan, the planning target volume (PTV), defined as the gross tumor volume plus 3-mm margin, the duodenum, and the stomach were contoured on the end-expiration (CTexp) and end-inspiration (CTinsp) phases for each patient. A separate treatment plan was constructed for both phases with the dose prescription of 33 Gy in 5 fractions with 95% coverage of the PTV by the 100% isodose line. The dose-volume histogram (DVH) endpoints, volume of duodenum that received 20 Gy (V20), V25, and V30 and maximum dose to 5 cc of contoured organ (D5cc), D1cc, and D0.1cc, were evaluated.Dosimetric parameters for the duodenum, including V25, V30, D1cc, and D0.1cc improved by planning on the CTexp compared to those on the CTinsp. There was a statistically significant overlap of the PTV with the duodenum but not the stomach during the CTinsp compared to the CTexp (0.38 ± 0.17 cc vs 0.01 ± 0.01 cc, P=.048). A larger expansion of the PTV, in accordance with a Danish phase 2 trial, showed even more overlapping volume of duodenum on the CTinsp compared to that on the CTexp (5.5 ± 0.9 cc vs 3.0 ± 0.8 cc, P=.0003) but no statistical difference for any stomach dosimetric DVH parameter.Dose to the duodenum was higher when treating on the inspiratory than on the expiratory phase. These data suggest that expiratory gating may be preferable to inspiratory breath-hold and free breathing strategies for minimizing risk of toxicity.

View details for DOI 10.1016/j.ijrobp.2012.07.2366

View details for PubMedID 23273994

Abstract

Developing an imaging method to directly monitor the spatial distribution of platinum-based (Pt) drugs at the tumor region is of critical importance for early assessment of treatment efficacy and personalized treatment. In this study, the authors investigated the feasibility of imaging platinum (Pt)-based drug distribution using x-ray fluorescence (XRF, a.k.a. characteristic x ray) CT (XFCT).A 5-mm-diameter pencil beam produced by a polychromatic x-ray source equipped with a tungsten anode was used to stimulate emission of XRF photons from Pt drug embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The x-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used for the K-shell XRF peak isolation and sinogram generation for Pt. The distribution and concentration of Pt were reconstructed with an iterative maximum likelihood expectation maximization algorithm. The capability of XFCT to multiplexed imaging of Pt, gadolinium (Gd), and iodine (I) within a water phantom was also investigated.Measured XRF spectrum showed a sharp peak characteristic of Pt with a narrow full-width at half-maximum (FWHM) (FWHMK?1 = 1.138 keV, FWHMK?2 = 1.052 keV). The distribution of Pt drug in the water phantom was clearly identifiable on the reconstructed XRF images. Our results showed a linear relationship between the XRF intensity of Pt and its concentrations (R(2) = 0.995), suggesting that XFCT is capable of quantitative imaging. A transmission CT image was also obtained to show the potential of the approach for providing attenuation correction and morphological information. Finally, the distribution of Pt, Gd, and I in the water phantom was clearly identifiable in the reconstructed images from XFCT multiplexed imaging.XFCT is a promising modality for monitoring the spatial distribution of Pt drugs. The technique may be useful in tailoring tumor treatment regimen in the future.

View details for DOI 10.1118/1.4789917

View details for Web of Science ID 000316369400003

View details for PubMedID 23464279

Abstract

Real-time tracking of implanted fiducials in cine megavoltage (MV) imaging during volumetric modulated arc therapy (VMAT) delivery is complicated due to the inherent low contrast of MV images and potential blockage of dynamic leaves configurations. The purpose of this work is to develop a clinically practical autodetection algorithm for motion management during VMAT.The expected field-specific segments and the planned fiducial position from the Eclipse (Varian Medical Systems, Palo Alto, CA) treatment planning system were projected onto the MV images. The fiducials were enhanced by applying a Laplacian of Gaussian filter in the spatial domain for each image, with a blob-shaped object as the impulse response. The search of implanted fiducials was then performed on a region of interest centered on the projection of the fiducial when it was within an open field including the case when it was close to the field edge or partially occluded by the leaves. A universal template formula was proposed for template matching and normalized cross correlation was employed for its simplicity and computational efficiency. The search region for every image was adaptively updated through a prediction model that employed the 3D position of the fiducial estimated from the localized positions in previous images. This prediction model allowed the actual fiducial position to be tracked dynamically and was used to initialize the search region. The artifacts caused by electronic interference during the acquisition were effectively removed. A score map was computed by combining both morphological information and image intensity. The pixel location with the highest score was selected as the detected fiducial position. The sets of cine MV images taken during treatment were analyzed with in-house developed software written in MATLAB (The Mathworks, Inc., Natick, MA). Five prostate patients were analyzed to assess the algorithm performance by measuring their positioning accuracy during treatment.The algorithm was able to accurately localize the fiducial position on MV images with success rates of more than 90% per case. The percentage of images in which each fiducial was localized in the studied cases varied between 23% and 65%, with at least one fiducial having been localized between 40% and 95% of the images. This depended mainly on the modulation of the plan and fiducial blockage. The prostate movement in the presented cases varied between 0.8 and 3.5 mm (mean values). The maximum displacement detected among all patients was of 5.7 mm.An algorithm for automatic detection of fiducial markers in cine MV images has been developed and tested with five clinical cases. Despite the challenges posed by complex beam aperture shapes, fiducial localization close to the field edge, partial occlusion of fiducials, fast leaf and gantry movement, and inherently low MV image quality, good localization results were achieved in patient images. This work provides a technique for enabling real-time accurate fiducial detection and tumor tracking during VMAT treatments without the use of extra imaging dose.

View details for DOI 10.1118/1.4791646

View details for Web of Science ID 000316369400011

View details for PubMedID 23464303

Abstract

Simultaneous imaging of multiple probes or biomarkers represents a critical step toward high specificity molecular imaging. In this work, we propose to utilize the element-specific nature of the X-ray fluorescence (XRF) signal for imaging multiple elements simultaneously (multiplexing) using XRF computed tomography (XFCT). A 5-mm-diameter pencil beam produced by a polychromatic X-ray source (150 kV, 20 mA) was used to stimulate emission of XRF photons from 2% (weight/volume) gold (Au), gadolinium (Gd), and barium (Ba) embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The X-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used to isolate the K shell XRF peak and to generate sinograms for the three elements of interest. The distribution and concentration of the three elements were reconstructed with the iterative maximum likelihood expectation maximization algorithm. The linearity between the XFCT intensity and the concentrations of elements of interest was investigated. We found that measured XRF spectra showed sharp peaks characteristic of Au, Gd, and Ba. The narrow full-width at half-maximum (FWHM) of the peaks strongly supports the potential of XFCT for multiplexed imaging of Au, Gd, and Ba ( FWHM(Au,K?1) = 0.619 keV, FWHM(Au,K?2)=1.371 keV , FWHM(Gd,K?)=1.297 keV, FWHM(Gd,K?)=0.974 keV , FWHM(Ba,K?)=0.852 keV, and FWHM(Ba,K?)=0.594 keV ). The distribution of Au, Gd, and Ba in the water phantom was clearly identifiable in the reconstructed XRF images. Our results showed linear relationships between the XRF intensity of each tested element and their concentrations ( R(2)(Au)=0.944 , R(Gd)(2)=0.986, and R(Ba)(2)=0.999), suggesting that XFCT is capable of quantitative imaging. Finally, a transmission CT image was obtained to show the potential of the approach for providing attenuation correction and morphological information. In conclusion, XFCT is a promising modality for multiplexed imaging of high atomic number probes.

View details for DOI 10.1109/TMI.2012.2223709

View details for Web of Science ID 000314367100011

View details for PubMedID 23076031

Abstract

X-ray scatter results in a significant degradation of image quality in computed tomography (CT), representing a major limitation in cone-beam CT (CBCT) and large field-of-view diagnostic scanners. In this work, a novel scatter estimation and correction technique is proposed that utilizes peripheral detection of scatter during the patient scan to simultaneously acquire image and patient-specific scatter information in a single scan, and in conjunction with a proposed compressed sensing scatter recovery technique to reconstruct and correct for the patient-specific scatter in the projection space.The method consists of the detection of patient scatter at the edges of the field of view (FOV) followed by measurement based compressed sensing recovery of the scatter through-out the projection space. In the prototype implementation, the kV x-ray source of the Varian TrueBeam OBI system was blocked at the edges of the projection FOV, and the image detector in the corresponding blocked region was used for scatter detection. The design enables image data acquisition of the projection data on the unblocked central region of and scatter data at the blocked boundary regions. For the initial scatter estimation on the central FOV, a prior consisting of a hybrid scatter model that combines the scatter interpolation method and scatter convolution model is estimated using the acquired scatter distribution on boundary region. With the hybrid scatter estimation model, compressed sensing optimization is performed to generate the scatter map by penalizing the L1 norm of the discrete cosine transform of scatter signal. The estimated scatter is subtracted from the projection data by soft-tuning, and the scatter-corrected CBCT volume is obtained by the conventional Feldkamp-Davis-Kress algorithm. Experimental studies using image quality and anthropomorphic phantoms on a Varian TrueBeam system were carried out to evaluate the performance of the proposed scheme.The scatter shading artifacts were markedly suppressed in the reconstructed images using the proposed method. On the Catphan©504 phantom, the proposed method reduced the error of CT number to 13 Hounsfield units, 10% of that without scatter correction, and increased the image contrast by a factor of 2 in high-contrast regions. On the anthropomorphic phantom, the spatial nonuniformity decreased from 10.8% to 6.8% after correction.A novel scatter correction method, enabling unobstructed acquisition of the high frequency image data and concurrent detection of the patient-specific low frequency scatter data at the edges of the FOV, is proposed and validated in this work. Relative to blocker based techniques, rather than obstructing the central portion of the FOV which degrades and limits the image reconstruction, compressed sensing is used to solve for the scatter from detection of scatter at the periphery of the FOV, enabling for the highest quality reconstruction in the central region and robust patient-specific scatter correction.

View details for DOI 10.1118/1.4769421

View details for Web of Science ID 000313033200032

View details for PubMedID 23298098

Abstract

Radiotracers play an important role in interrogating molecular processes both in vitro and in vivo. However, current methods are limited to measuring average radiotracer uptake in large cell populations and, as a result, lack the ability to quantify cell-to-cell variations. Here we apply a new technique, termed radioluminescence microscopy, to visualize radiotracer uptake in single living cells, in a standard fluorescence microscopy environment. In this technique, live cells are cultured sparsely on a thin scintillator plate and incubated with a radiotracer. Light produced following beta decay is measured using a highly sensitive microscope. Radioluminescence microscopy revealed strong heterogeneity in the uptake of [(18)F]fluoro-deoxyglucose (FDG) in single cells, which was found consistent with fluorescence imaging of a glucose analog. We also verified that dynamic uptake of FDG in single cells followed the standard two-tissue compartmental model. Last, we transfected cells with a fusion PET/fluorescence reporter gene and found that uptake of FHBG (a PET radiotracer for transgene expression) coincided with expression of the fluorescent protein. Together, these results indicate that radioluminescence microscopy can visualize radiotracer uptake with single-cell resolution, which may find a use in the precise characterization of radiotracers.

View details for DOI 10.1371/journal.pone.0046285

View details for Web of Science ID 000309454000029

View details for PubMedID 23056276

Abstract

Cerenkov luminescence imaging (CLI) is an emerging new molecular imaging modality that is relatively inexpensive, easy to use, and has high throughput. CLI can image clinically available PET and SPECT probes using optical instrumentation. Cerenkov luminescence endoscopy (CLE) is one of the most intriguing applications that promise potential clinical translation. We developed a prototype customized fiberscopic Cerenkov imaging system to investigate the potential in guiding minimally invasive surgical resection.All experiments were performed in a dark chamber. Cerenkov luminescence from (18)F-FDG samples containing decaying radioactivity was transmitted through an optical fiber bundle and imaged by an intensified charge-coupled device camera. Phantoms filled with (18)F-FDG were used to assess the imaging spatial resolution. Finally, mice bearing subcutaneous C6 glioma cells were injected intravenously with (18)F-FDG to determine the feasibility of in vivo imaging. The tumor tissues were exposed, and CLI was performed on the mouse before and after surgical removal of the tumor using the fiber-based imaging system and compared with a commercial optical imaging system.The sensitivity of this particular setup was approximately 45 kBq (1.21 ?Ci)/300 ?L. The 3 smallest sets of cylindric holes in a commercial SPECT phantom were identifiable via this system, demonstrating that the system has a resolution better than 1.2 mm. Finally, the in vivo tumor imaging study demonstrated the feasibility of using CLI to guide the resection of tumor tissues.This proof-of-concept study explored the feasibility of using fiber-based CLE for the detection of tumor tissue in vivo for guided surgery. With further improvements of the imaging sensitivity and spatial resolution of the current system, CLE may have a significant application in the clinical setting in the near future.

View details for DOI 10.2967/jnumed.111.098541

View details for Web of Science ID 000309432400017

View details for PubMedID 22904353

Abstract

Respiratory motion poses a major challenge in lung radiotherapy. Based on 4D CT images, a variety of intensity-based deformable registration techniques have been proposed to study the pulmonary motion. However, the accuracy achievable with these approaches can be sub-optimal because the deformation is defined globally in space. Therefore, the accuracy of the alignment of local structures may be compromised. In this work, we propose a novel method to detect a large collection of natural junction structures in the lung and use them as the reliable markers to track the lung motion. Specifically, detection of the junction centers and sizes is achieved by analysis of local shape profiles on one segmented image. To track the temporal trajectory of a junction, the image intensities within a small region of interest surrounding the center are selected as its signature. Under the assumption of the cyclic motion, we describe the trajectory by a closed B-spline curve and search for the control points by maximizing a metric of combined correlation coefficients. Local extrema are suppressed by improving the initial conditions using random walks from pair-wise optimizations. Several descriptors are introduced to analyze the motion trajectories. Our method was applied to 13 real 4D CT images. More than 700 junctions in each case are detected with an average positive predictive value of greater than 90%. The average tracking error between automated and manual tracking is sub-voxel and smaller than the published results using the same set of data.

View details for DOI 10.1088/0031-9155/57/15/4905

View details for Web of Science ID 000306521900015

View details for PubMedID 22796656

Abstract

Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ?15 mm and average duration of ?115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95th percentile error of 3.4 mm on unseen test data. The average 3D error was further reduced to 1.4 mm when the model was tuned to its optimal setting for each respiratory trace. In one trace where a few outliers are present in the training data, the proposed method achieved an error reduction of as much as ?50% compared with the best linear model (1.0 mm versus 2.1 mm). The memory-based learning technique is able to accurately capture the highly complex and nonlinear relations between tumor and surrogate motion in an efficient manner (a few milliseconds per estimate). Furthermore, the algorithm is particularly suitable to handle situations where the training data are contaminated by large errors or outliers. These desirable properties make it an ideal candidate for accurate and robust tumor gating/tracking using respiratory surrogates.

View details for DOI 10.1088/0031-9155/57/15/4771

View details for Web of Science ID 000306521900007

View details for PubMedID 22772042

Abstract

To verify the geometric accuracy of gated RapidArc treatment using kV images acquired during dose delivery.Twenty patients were treated using the gated RapidArc technique with a Varian TrueBeam STx linear accelerator. One to 7 metallic fiducial markers were implanted inside or near the tumor target before treatment simulation. For patient setup and treatment verification purposes, the internal target volume (ITV) was created, corresponding to each implanted marker. The gating signal was generated from the Real-time Position Management (RPM) system. At the beginning of each fraction, individualized respiratory gating amplitude thresholds were set based on fluoroscopic image guidance. During the treatment, we acquired kV images immediately before MV beam-on at every breathing cycle, using the on-board imaging system. After the treatment, all implanted markers were detected, and their 3-dimensional (3D) positions in the patient were estimated using software developed in-house. The distance from the marker to the corresponding ITV was calculated for each patient by averaging over all markers and all fractions.The average 3D distance between the markers and their ITVs was 0.8 ± 0.5 mm (range, 0-1.7 mm) and was 2.1 ± 1.2 mm at the 95th percentile (range, 0-3.8 mm). On average, a left-right margin of 0.6 mm, an anterior-posterior margin of 0.8 mm, and a superior-inferior margin of 1.5 mm is required to account for 95% of the intrafraction uncertainty in RPM-based RapidArc gating.To our knowledge, this is the first clinical report of intrafraction verification of respiration-gated RapidArc treatment in stereotactic ablative radiation therapy. For some patients, the markers deviated significantly from the ITV by more than 2 mm at the beginning of the MV beam-on. This emphasizes the need for gating techniques with beam-on/-off controlled directly by the actual position of the tumor target instead of external surrogates such as RPM.

View details for DOI 10.1016/j.ijrobp.2012.03.006

View details for Web of Science ID 000306128100022

View details for PubMedID 22554582

Abstract

Intensity modulated radiation therapy (IMRT) inverse planning using total-variation (TV) regularization has been proposed to reduce the complexity of fluence maps and facilitate dose delivery. Conventionally, the optimization problem with L-1 norm is solved with quadratic programming (QP), which is time consuming and memory expensive due to the second-order Newton update. This study proposes to use a new algorithm, template for first-order conic solver (TFOCS), for fast and memory-efficient optimization in IMRT inverse planning. The TFOCS utilizes dual-variable updates and first-order approaches for TV minimization without the need to compute and store the enlarged Hessian matrix required for Newton update in the QP technique. To evaluate the effectiveness and efficiency of the proposed method, two clinical cases were used for IMRT inverse planning: a head and neck case and a prostate case. For comparison, the conventional QP-based method for the TV form was adopted to solve the fluence map optimization problem in the above two cases. The convergence criteria and algorithm parameters were selected to achieve similar dose conformity for a fair comparison between the two methods. Compared with conventional QP-based approach, the proposed TFOCS-based method shows a remarkable improvement in computational efficiency for fluence map optimization, while maintaining the conformal dose distribution. Compared with QP-based algorithms, the computational speed using TFOCS for fluence optimization is increased by a factor of 4 to 6, and at the same time the memory requirement is reduced by a factor of 3 to 4. Therefore, TFOCS provides an effective, fast and memory-efficient method for IMRT inverse planning. The unique features of the approach should be particularly important in inverse planning involving a large number of beams, such as in VMAT and dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT).

View details for DOI 10.1088/0031-9155/57/13/4139

View details for Web of Science ID 000305803600006

View details for PubMedID 22683930

Abstract

A new treatment scheme coined as dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT) has recently been proposed to bridge the gap between IMRT and VMAT. By increasing the angular sampling of radiation beams while eliminating dispensable segments of the incident fields, DASSIM-RT is capable of providing improved conformity in dose distributions while maintaining high delivery efficiency. The fact that DASSIM-RT utilizes a large number of incident beams represents a major computational challenge for the clinical applications of this powerful treatment scheme. The purpose of this work is to provide a practical solution to the DASSIM-RT inverse planning problem.The inverse planning problem is formulated as a fluence-map optimization problem with total-variation (TV) minimization. A newly released L1-solver, template for first-order conic solver (TFOCS), was adopted in this work. TFOCS achieves faster convergence with less memory usage as compared with conventional quadratic programming (QP) for the TV form through the effective use of conic forms, dual-variable updates, and optimal first-order approaches. As such, it is tailored to specifically address the computational challenges of large-scale optimization in DASSIM-RT inverse planning. Two clinical cases (a prostate and a head and neck case) are used to evaluate the effectiveness and efficiency of the proposed planning technique. DASSIM-RT plans with 15 and 30 beams are compared with conventional IMRT plans with 7 beams in terms of plan quality and delivery efficiency, which are quantified by conformation number (CN), the total number of segments and modulation index, respectively. For optimization efficiency, the QP-based approach was compared with the proposed algorithm for the DASSIM-RT plans with 15 beams for both cases.Plan quality improves with an increasing number of incident beams, while the total number of segments is maintained to be about the same in both cases. For the prostate patient, the conformation number to the target was 0.7509, 0.7565, and 0.7611 with 80 segments for IMRT with 7 beams, and DASSIM-RT with 15 and 30 beams, respectively. For the head and neck (HN) patient with a complicated target shape, conformation numbers of the three treatment plans were 0.7554, 0.7758, and 0.7819 with 75 segments for all beam configurations. With respect to the dose sparing to the critical structures, the organs such as the femoral heads in the prostate case and the brainstem and spinal cord in the HN case were better protected with DASSIM-RT. For both cases, the delivery efficiency has been greatly improved as the beam angular sampling increases with the similar or better conformal dose distribution. Compared with conventional quadratic programming approaches, first-order TFOCS-based optimization achieves far faster convergence and smaller memory requirements in DASSIM-RT.The new optimization algorithm TFOCS provides a practical and timely solution to the DASSIM-RT or other inverse planning problem requiring large memory space. The new treatment scheme is shown to outperform conventional IMRT in terms of dose conformity to both the targetand the critical structures, while maintaining high delivery efficiency.

View details for DOI 10.1118/1.4729717

View details for Web of Science ID 000306893000029

View details for PubMedID 22830765

Abstract

To evaluate the geometric accuracy of beam targeting in external surrogate-based gated volumetric modulated arc therapy (VMAT) using kilovoltage (kV) x-ray images acquired during dose delivery.Gated VMAT treatments were delivered using a Varian TrueBeam STx Linac for both physical phantoms and patients. Multiple gold fiducial markers were implanted near the target. The reference position was created for each implanted marker, representing its correct position at the gating threshold. The gating signal was generated from the RPM system. During the treatment, kV images were acquired immediately before MV beam-on at every breathing cycle, using the on-board imaging system. All implanted markers were detected and their 3D positions were estimated using in-house developed software. The positioning error of a marker is defined as the distance of the marker from its reference position for each frame of the images. The overall error of the system is defined as the average over all markers. For the phantom study, both sinusoidal motion (1D and 3D) and real human respiratory motion was simulated for the target and surrogate. In the baseline case, the two motions were synchronized for the first treatment fraction. To assess the effects of surrogate-target correlation on the geometric accuracy, a phase shift of 5% and 10% between the two motions was introduced. For the patient study, intrafraction kV images of five stereotactic body radiotherapy (SBRT) patients were acquired for one or two fractions.For the phantom study, a high geometric accuracy was achieved in the baseline case (average error: 0.8 mm in the superior-inferior or SI direction). However, the treatment delivery is prone to geometric errors if changes in the target-surrogate relation occur during the treatment: the average error was increased to 2.3 and 4.7 mm for the phase shift of 5% and 10%, respectively. Results obtained with real human respiratory curves show a similar trend. For a target with 3D motion, the technique is able to detect geometric errors in the left-right (LR) and anterior-posterior (AP) directions. For the patient study, the average intrafraction positioning errors are 0.8, 0.9, and 1.4 mm and 95th percentile errors are 1.7, 2.1, and 2.7 mm in the LR, AP, and SI directions, respectively.The correlation between external surrogate and internal target motion is crucial to ensure the geometric accuracy of surrogate-based gating. Real-time guidance based on kV x-ray images overcomes the potential issues in surrogate-based gating and can achieve accurate beam targeting in gated VMAT.

View details for DOI 10.1118/1.4704729

View details for Web of Science ID 000303604300039

View details for PubMedID 22559639

Abstract

X-ray scatter incurred to detectors degrades the quality of cone-beam computed tomography (CBCT) and represents a problem in volumetric image guided and adaptive radiation therapy. Several methods using a beam blocker for the estimation and subtraction of scatter have been proposed. However, due to missing information resulting from the obstruction of the blocker, such methods require dual scanning or dynamically moving blocker to obtain a complete volumetric image. Here, we propose a half beam blocker-based approach, in conjunction with a total variation (TV) regularized Feldkamp-Davis-Kress (FDK) algorithm, to correct scatter-induced artifacts by simultaneously acquiring image and scatter information from a single-rotation CBCT scan.A half beam blocker, comprising lead strips, is used to simultaneously acquire image data on one side of the projection data and scatter data on the other half side. One-dimensional cubic B-Spline interpolation/extrapolation is applied to derive patient specific scatter information by using the scatter distributions on strips. The estimated scatter is subtracted from the projection image acquired at the opposite view. With scatter-corrected projections where this subtraction is completed, the FDK algorithm based on a cosine weighting function is performed to reconstruct CBCT volume. To suppress the noise in the reconstructed CBCT images produced by geometric errors between two opposed projections and interpolated scatter information, total variation regularization is applied by a minimization using a steepest gradient descent optimization method. The experimental studies using Catphan504 and anthropomorphic phantoms were carried out to evaluate the performance of the proposed scheme.The scatter-induced shading artifacts were markedly suppressed in CBCT using the proposed scheme. Compared with CBCT without a blocker, the nonuniformity value was reduced from 39.3% to 3.1%. The root mean square error relative to values inside the regions of interest selected from a benchmark scatter free image was reduced from 50 to 11.3. The TV regularization also led to a better contrast-to-noise ratio.An asymmetric half beam blocker-based FDK acquisition and reconstruction technique has been established. The proposed scheme enables simultaneous detection of patient specific scatter and complete volumetric CBCT reconstruction without additional requirements such as prior images, dual scans, or moving strips.

View details for DOI 10.1118/1.3691901

View details for Web of Science ID 000303604300008

View details for PubMedID 22559608

Abstract

Volumetric cone-beam CT (CBCT) images are acquired repeatedly during a course of radiation therapy and a natural question to ask is whether CBCT images obtained earlier in the process can be utilized as prior knowledge to reduce patient imaging dose in subsequent scans. The purpose of this work is to develop an adaptive prior image constrained compressed sensing (APICCS) method to solve this problem. Reconstructed images using full projections are taken on the first day of radiation therapy treatment and are used as prior images. The subsequent scans are acquired using a protocol of sparse projections. In the proposed APICCS algorithm, the prior images are utilized as an initial guess and are incorporated into the objective function in the compressed sensing (CS)-based iterative reconstruction process. Furthermore, the prior information is employed to detect any possible mismatched regions between the prior and current images for improved reconstruction. For this purpose, the prior images and the reconstructed images are classified into three anatomical regions: air, soft tissue and bone. Mismatched regions are identified by local differences of the corresponding groups in the two classified sets of images. A distance transformation is then introduced to convert the information into an adaptive voxel-dependent relaxation map. In constructing the relaxation map, the matched regions (unchanged anatomy) between the prior and current images are assigned with smaller weight values, which are translated into less influence on the CS iterative reconstruction process. On the other hand, the mismatched regions (changed anatomy) are associated with larger values and the regions are updated more by the new projection data, thus avoiding any possible adverse effects of prior images. The APICCS approach was systematically assessed by using patient data acquired under standard and low-dose protocols for qualitative and quantitative comparisons. The APICCS method provides an effective way for us to enhance the image quality at the matched regions between the prior and current images compared to the existing PICCS algorithm. Compared to the current CBCT imaging protocols, the APICCS algorithm allows an imaging dose reduction of 10-40 times due to the greatly reduced number of projections and lower x-ray tube current level coming from the low-dose protocol.

View details for DOI 10.1088/0031-9155/57/8/2287

View details for Web of Science ID 000302567100013

View details for PubMedID 22460008

View details for DOI 10.1118/1.3687906

View details for Web of Science ID 000301503400053

View details for PubMedID 22380399

Abstract

The Varian's new digital linear accelerator (LINAC), TrueBeam STx, is equipped with a high dose rate flattening filter free (FFF) mode (6 MV and 10 MV), a high definition multileaf collimator (2.5 mm leaf width), as well as onboard imaging capabilities. A series of end-to-end phantom tests were performed, TrueBeam-based image guided radiation therapy (IGRT), to determine the geometric accuracy of the image-guided setup and dose delivery process for all beam modalities delivered using intensity modulated radiation therapy (IMRT) and RapidArc. In these tests, an anthropomorphic phantom with a Ball Cube II insert and the analysis software (FilmQA (3cognition)) were used to evaluate the accuracy of TrueBeam image-guided setup and dose delivery. Laser cut EBT2 films with 0.15 mm accuracy were embedded into the phantom. The phantom with the film inserted was first scanned with a GE Discovery-ST CT scanner, and the images were then imported to the planning system. Plans with steep dose fall off surrounding hypothetical targets of different sizes were created using RapidArc and IMRT with FFF and WFF (with flattening filter) beams. Four RapidArc plans (6 MV and 10 MV FFF) and five IMRT plans (6 MV and 10 MV FFF; 6 MV, 10 MV and 15 MV WFF) were studied. The RapidArc plans with 6 MV FFF were planned with target diameters of 1 cm (0.52 cc), 2 cm (4.2 cc) and 3 cm (14.1 cc), and all other plans with a target diameter of 3 cm. Both onboard planar and volumetric imaging procedures were used for phantom setup and target localization. The IMRT and RapidArc plans were then delivered, and the film measurements were compared with the original treatment plans using a gamma criteria of 3%/1 mm and 3%/2 mm. The shifts required in order to align the film measured dose with the calculated dose distributions was attributed to be the targeting error. Targeting accuracy of image-guided treatment using TrueBeam was found to be within 1 mm. For irradiation of the 3 cm target, the gammas (3%, 1 mm) were found to be above 90% in all plan deliveries. For irradiations of smaller targets (2 cm and 1 cm), similar accuracy was achieved for 6 MV and 10 MV beams. Slightly degraded accuracy was observed for irradiations with higher energy beam (15 MV). In general, gammas (3%, 2 mm) were found to be above 97% for all the plans. Our end-to-end tests showed an excellent relative dosimetric agreement and sub-millimeter targeting accuracy for 6 MV and 10 MV beams, using both FFF and WFF delivery methods. However, increased deviations in spatial and dosimetric accuracy were found when treating lesions smaller than 2 cm or with 15 MV beam.

View details for DOI 10.1088/0031-9155/57/3/757

View details for Web of Science ID 000299542000013

View details for PubMedID 22252134

Abstract

Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT?CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment.In this work, we accelerated the Feldcamp-Davis-Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT?CT reconstruction algorithm.Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10(-7). Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed successfully with identical results even when half of the nodes were manually terminated in the middle of the process.An ultrafast, reliable and scalable 4D CBCT?CT reconstruction method was developed using the MapReduce framework. Unlike other parallel computing approaches, the parallelization and speedup required little modification of the original reconstruction code. MapReduce provides an efficient and fault tolerant means of solving large-scale computing problems in a cloud computing environment.

View details for DOI 10.1118/1.3660200

View details for Web of Science ID 000298250100028

View details for PubMedID 22149842

Abstract

Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes.

View details for DOI 10.1117/1.3656964

View details for Web of Science ID 000299490300011

View details for PubMedID 22191916

Abstract

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

View details for DOI 10.1088/0031-9155/56/17/N02

View details for Web of Science ID 000294786400003

View details for PubMedID 21841211

Abstract

To propose an alternative radiation therapy (RT) planning and delivery scheme with optimal angular beam sampling and intrabeam modulation for improved dose distribution while maintaining high delivery efficiency.In the proposed approach, coined as dense angularly sampled and sparse intensity modulated RT (DASSIM-RT), a large number of beam angles are used to increase the angular sampling, leading to potentially more conformal dose distributions as compared to conventional IMRT. At the same time, intensity modulation of the incident beams is simplified to eliminate the dispensable segments, compensating the increase in delivery time caused by the increased number of beams and facilitating the plan delivery. In a sense, the proposed approach shifts and transforms, in an optimal fashion, some of the beam segments in conventional IMRT to the added beams. For newly available digital accelerators, the DASSIM-RT delivery can be made very efficient by concatenating the beams so that they can be delivered sequentially without operator's intervention. Different from VMAT, the level of intensity modulation in DASSIS-RT is field specific and optimized to meet the need of each beam direction. Three clinical cases (a head and neck (HN) case, a pancreas case, and a lung case) are used to evaluate the proposed RT scheme. DASSIM-RT, VMAT, and conventional IMRT plans are compared quantitatively in terms of the conformality index (CI) and delivery efficiency.Plan quality improves generally with the number and intensity modulation of the incident beams. For a fixed number of beams or fixed level of intensity modulation, the improvement saturates after the intensity modulation or number of beams reaches to a certain level. An interplay between the two variables is observed and the saturation point depends on the values of both variables. For all the cases studied here, the CI of DASSIM-RT with 15 beams and 5 intensity levels (0.90, 0.79, and 0.84 for the HN, pancreas, and lung cases, respectively) is similar with that of conventional IMRT with seven beams and ten intensity levels (0.88, 0.79, and 0.83) and is higher than that of single-arc VMAT (0.75, 0.75, and 0.82). It is also found that the DASSIM-RT plans generally have better sparing of organs-at-risk than IMRT plans. It is estimated that the dose delivery time of DASSIM-RT with 15 beams and 5 intensity levels is about 4.5, 4.4, and 4.2 min for the HN, pancreas, and lung case, respectively, similar to that of IMRT plans with 7 beams and 10 intensity levels.DASSIS-RT bridges the gap between IMRT and VMAT and allows optimal sampling of angular space and intrabeam modulation, thus it provides improved conformity in dose distributions while maintaining high delivery efficiency.

View details for DOI 10.1118/1.3618736

View details for Web of Science ID 000294482900002

View details for PubMedID 21978036

Abstract

A novel commercial medical linac system (TrueBeam?, Varian Medical Systems, Palo Alto, CA) allows respiratory-gated volumetric modulated arc therapy (VMAT), a new modality for treating moving tumors with high precision and improved accuracy by allowing for regular motion associated with a patient's breathing during VMAT delivery. The purpose of this work is to adapt a previously-developed dose reconstruction technique to evaluate the fidelity of VMAT treatment during gated delivery under clinic-relevant periodic motion related to patient breathing. A Varian TrueBeam system was used in this study. VMAT plans were created for three patients with lung or pancreas tumors. Conventional 6 and 15 MV beams with flattening filter and high-dose-rate 10 MV beams with no flattening filter were used in these plans. Each patient plan was delivered to a phantom first without gating and then with gating for three simulated respiratory periods (3, 4.5 and 6 s). Using the adapted log-file-based dose reconstruction procedure supplemented with ion chamber array (Seven29?, PTW, Freiburg, Germany) measurements, the delivered dose was used to evaluate the fidelity of gated VMAT delivery. Comparison of Seven29 measurements with and without gating showed good agreement with gamma-index passing rates above 99% for 1%/1 mm dose accuracy/distance-to-agreement criteria. With original plans as reference, gamma-index passing rates were 100% for the reconstituted plans (1%/1 mm criteria) and 93.5-100% for gated Seven29 measurements (3%/3 mm criteria). In the presence of leaf error deliberately introduced into the gated delivery of a pancreas patient plan, both dose reconstruction and Seven29 measurement consistently indicated substantial dosimetric differences from the original plan. In summary, a dose reconstruction procedure was demonstrated for evaluating the accuracy of respiratory-gated VMAT delivery. This technique showed that under clinical operation, the TrueBeam system faithfully realized treatment plans with gated delivery. This methodology affords a useful tool for machine- and patient-specific quality assurance of the newly available respiratory-gated VMAT.

View details for DOI 10.1088/0031-9155/56/15/013

View details for Web of Science ID 000292885000014

View details for PubMedID 21753232

Abstract

Monoscopic x-ray imaging with on-board kV devices is an attractive approach for real-time image guidance in modern radiation therapy such as VMAT or IMRT, but it falls short in providing reliable information along the direction of imaging x-ray. By effectively taking consideration of projection data at prior times and/or angles through a Bayesian formalism, the authors develop an algorithm for real-time and full 3D tumor localization with a single x-ray imager during treatment delivery.First, a prior probability density function is constructed using the 2D tumor locations on the projection images acquired during patient setup. Whenever an x-ray image is acquired during the treatment delivery, the corresponding 2D tumor location on the imager is used to update the likelihood function. The unresolved third dimension is obtained by maximizing the posterior probability distribution. The algorithm can also be used in a retrospective fashion when all the projection images during the treatment delivery are used for 3D localization purposes. The algorithm does not involve complex optimization of any model parameter and therefore can be used in a "plug-and-play" fashion. The authors validated the algorithm using (1) simulated 3D linear and elliptic motion and (2) 3D tumor motion trajectories of a lung and a pancreas patient reproduced by a physical phantom. Continuous kV images were acquired over a full gantry rotation with the Varian TrueBeam on-board imaging system. Three scenarios were considered: fluoroscopic setup, cone beam CT setup, and retrospective analysis.For the simulation study, the RMS 3D localization error is 1.2 and 2.4 mm for the linear and elliptic motions, respectively. For the phantom experiments, the 3D localization error is < 1 mm on average and < 1.5 mm at 95th percentile in the lung and pancreas cases for all three scenarios. The difference in 3D localization error for different scenarios is small and is not statistically significant.The proposed algorithm eliminates the need for any population based model parameters in monoscopic image guided radiotherapy and allows accurate and real-time 3D tumor localization on current standard LINACs with a single x-ray imager.

View details for DOI 10.1118/1.3598435

View details for Web of Science ID 000292521100037

View details for PubMedID 21859022

View details for DOI 10.1002/adma.201100919

View details for Web of Science ID 000293046600018

View details for PubMedID 21557339

Abstract

X-ray luminescence tomography (XLT) has recently been proposed as a new imaging modality for biological imaging applications. This modality utilizes phosphor nanoparticles which luminesce near-infrared light when excited by x-ray photons. The advantages of this modality are that it uniquely combines the high sensitivity of radioluminescent nanoparticles and the high spatial localization of collimated x-ray beams. Currently, XLT has been demonstrated using x-ray spatial encoding to resolve the imaging volume. However, there are applications where the x-ray excitation may be limited by geometry, where increased temporal resolution is desired, or where a lower dose is mandatory. This paper extends the utility of XLT to meet these requirements by incorporating a photon propagation model into the reconstruction algorithm in an x-ray limited-angle (LA) geometry. This enables such applications as image-guided surgery, where the ability to resolve lesions at depths of several centimeters can be the key to successful resection. The hybrid x-ray/diffuse optical model is first formulated and then demonstrated in a breast-sized phantom, simulating a breast lumpectomy geometry. Both numerical and experimental phantoms are tested, with lesion-simulating objects of various sizes and depths. Results show localization accuracy with median error of 2.2 mm, or 4% of object depth, for small 2-14 mm diameter lesions positioned from 1 to 4.5 cm in depth. This compares favorably with fluorescence optical imaging, which is not able to resolve such small objects at this depth. The recovered lesion size has lower size bias in the x-ray excitation direction than the optical direction, which is expected due to the increased optical scatter. However, the technique is shown to be quite invariant in recovered size with respect to depth, as the standard deviation is less than 2.5 mm. Sensitivity is a function of dose; radiological doses are found to provide sufficient recovery for µg ml(-1) concentrations, while therapy dosages provide recovery for ng ml(-1) concentrations. Experimental phantom results agree closely with the numerical results, with positional errors recovered within 8.6% of the effective depth for a 5 mm object, and within 5.2% of the depth for a 10 mm object. Object-size median error is within 2.3% and 2% for the 5 and 10 mm objects, respectively. For shallow-to-medium depth applications where optical and radio-emission imaging modalities are not ideal, such as in intra-operative procedures, LAXLT may be a useful tool to detect molecular signatures of disease.

View details for DOI 10.1088/0031-9155/56/12/003

View details for Web of Science ID 000291095700004

View details for PubMedID 21606553

Abstract

Hepatocellular carcinoma (HCC), the primary form of human adult liver malignancy, is a highly aggressive tumor with average survival rates that are currently less than 1 year following diagnosis. Most patients with HCC are diagnosed at an advanced stage, and no efficient marker exists for the prediction of prognosis and/or response(s) to therapy. We have reported previously a high level of [1-(13)C]alanine in an orthotopic HCC using single-voxel hyperpolarized [1-(13)C]pyruvate MRS. In the present study, we implemented a three-dimensional MRSI sequence to investigate this potential hallmark of cellular metabolism in rat livers bearing HCC (n?=?7 buffalo rats). In addition, quantitative real-time polymerase chain reaction was used to determine the mRNA levels of lactate dehydrogenase A, nicotinamide adenine (phosphate) dinucleotide dehydrogenase quinone 1 and alanine transaminase. The enzyme levels were significantly higher in tumor than in normal liver tissues within each rat, and were associated with the in vivo MRSI signal of [1-(13)C]alanine and [1-(13)C]lactate after a bolus intravenous injection of [1-(13)C]pyruvate. Histopathological analysis of these tumors confirmed the successful growth of HCC as a nodule in buffalo rat livers, revealing malignancy and hypervascular architecture. More importantly, the results demonstrated that the metabolic fate of [1-(13)C]pyruvate conversion to [1-(13)C]alanine significantly superseded that of [1-(13)C]pyruvate conversion to [1-(13)C]lactate, potentially serving as a marker of HCC tumors.

View details for DOI 10.1002/nbm.1616

View details for Web of Science ID 000291597200009

View details for PubMedID 21674652

Abstract

The graphics processing unit (GPU) has emerged as a competitive platform for computing massively parallel problems. Many computing applications in medical physics can be formulated as data-parallel tasks that exploit the capabilities of the GPU for reducing processing times. The authors review the basic principles of GPU computing as well as the main performance optimization techniques, and survey existing applications in three areas of medical physics, namely image reconstruction, dose calculation and treatment plan optimization, and image processing.

View details for DOI 10.1118/1.3578605

View details for Web of Science ID 000290625700044

View details for PubMedID 21776805

Abstract

The streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. In this work, the authors propose an iterative metal artifact reduction algorithm based on constrained optimization.After the shape and location of metal objects in the image domain is determined automatically by the binary metal identification algorithm and the segmentation of "metal shadows" in projection domain is done, constrained optimization is used for image reconstruction. It minimizes a predefined function that reflects a priori knowledge of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The minimization problem is solved through the alternation of projection-onto-convex-sets and the steepest gradient descent of the objective function. The constrained optimization algorithm is evaluated with a penalized smoothness objective.The study shows that the proposed method is capable of significantly reducing metal artifacts, suppressing noise, and improving soft-tissue visibility. It outperforms the FBP-type methods and ART and EM methods and yields artifacts-free images.Constrained optimization is an effective way to deal with CT reconstruction with embedded metal objects. Although the method is presented in the context of metal artifacts, it is applicable to general "missing data" image reconstruction problems.

View details for DOI 10.1118/1.3533711

View details for Web of Science ID 000286945000017

View details for PubMedID 21452707

Abstract

Junction structures, as the natural anatomical markers, are useful to study the organ or tumor motion. However, detection and tracking of the junctions in four-dimensional (4D) images are challenging. The paper presents a novel framework to automate this task. Detection of their centers and sizes is first achieved by an analysis of local shape profiles on one segmented reference image. Junctions are then separately tracked by simultaneously using neighboring intensity features from all images. Defined by a closed B-spline space curve, the individual trajectory is assumed to be cyclic and obtained by maximizing the metric of combined correlation coefficients. Local extrema are suppressed by improving the initial conditions using random walks from pair-wise optimizations. Our approach has been applied to analyze the vessel junctions in five real 4D respiration-gated computed tomography (CT) image datasets with promising results. More than 500 junctions in the lung are detected with an average accuracy of greater than 85% and the mean error between the automated and the manual tracking is sub-voxel.

View details for PubMedID 21761680

Abstract

Radiation therapy with high dose rate and flattening filter-free (FFF) beams has the potential advantage of greatly reduced treatment time and out-of-field dose. Current inverse planning algorithms are, however, not customized for beams with nonuniform incident profiles and the resultant IMRT plans are often inefficient in delivery. The authors propose a total-variation regularization (TVR)-based formalism by taking the inherent shapes of incident beam profiles into account.A novel TVR-based inverse planning formalism is established for IMRT with nonuniform beam profiles. The authors introduce a TVR term into the objective function, which encourages piecewise constant fluence in the nonuniform FFF fluence domain. The proposed algorithm is applied to lung and prostate and head and neck cases and its performance is evaluated by comparing the resulting plans to those obtained using a conventional beamlet-based optimization (BBO).For the prostate case, the authors' algorithm produces acceptable dose distributions with only 21 segments, while the conventional BBO requires 114 segments. For the lung case and the head and neck case, the proposed method generates similar coverage of target volume and sparing of the organs-at-risk as compared to BBO, but with a markedly reduced segment number.TVR-based optimization in nonflat beam domain provides an effective way to maximally leverage the technical capacity of radiation therapy with FFF fields. The technique can generate effective IMRT plans with improved dose delivery efficiency without significant deterioration of the dose distribution.

View details for DOI 10.1118/1.3521465

View details for Web of Science ID 000285769800008

View details for PubMedID 21361175

View details for DOI 10.1080/17415977.2011.603050

View details for Web of Science ID 000299615200005

Abstract

To establish an inverse planning framework with adjustable voxel penalty for more conformal IMRT dose distribution as well as improved interactive controllability over the regional dose distribution of the resultant plan.In the proposed coarse-to-fine planning scheme, a conventional inverse planning with organ specific parameters is first performed. The voxel penalty scheme is then "switched on" by allowing the prescription dose to change on an individual voxel scale according to the deviation of the actual voxel dose from the ideally desired dose. The rationale here is intuitive: when the dose at a voxel does not meet its ideal dose, it simply implies that this voxel is not competitive enough when compared with the ones that have met their planning goal. In this case, increasing the penalty of the voxel by varying the prescription can boost its competitiveness and thus improve its dose. After the prescription adjustment, the plan is re-optimized. The dose adjustment/re-optimization procedure is repeated until the resultant dose distribution cannot be improved anymore. The prescription adjustment on a finer scale can be accomplished either automatically or manually. In the latter case, the regions/voxels where a dose improvement is needed are selected visually, unlike in the automatic case where the selection is done purely based on the difference of the actual dose at a given voxel and its ideal prescription. The performance of the proposed method is evaluated using a head and neck and a prostate case.An inverse planning framework with the voxel-specific penalty is established. By adjusting voxel prescriptions iteratively to boost the region where large mismatch between the actual calculated and desired doses occurs, substantial improvements can be achieved in the final dose distribution. The proposed method is applied to a head and neck case and a prostate case. For the former case, a significant reduction in the maximum dose to the brainstem is achieved while the PTV dose coverage is greatly improved. The doses to other organs at risk are also reduced, ranging from 10% to 30%. For the prostate case, the use of the voxel penalty scheme also results in vast improvements to the final dose distribution. The PTV experiences improved dose uniformity and the mean dose to the rectum and bladder is reduced by as much as 15%.Introduction of the spatially non-uniform and adjustable prescription provides room for further improvements of currently achievable dose distributions and equips the planner with an effective tool to modify IMRT dose distributions interactively. The technique is easily implementable in any existing inverse planning platform, which should facilitate clinical IMRT planning process and, in future, off-line/on-line adaptive IMRT.

View details for Web of Science ID 000284971100011

View details for PubMedID 21070085

Abstract

X-ray luminescence computed tomography (XLCT) is proposed as a new molecular imaging modality based on the selective excitation and optical detection of X-ray-excitable phosphor nanoparticles. These nano-sized particles can be fabricated to emit near-infrared (NIR) light when excited with X-rays, and, because because both X-rays and NIR photons propagate long distances in tissue, they are particularly well suited for in vivo biomedical imaging. In XLCT, tomographic images are generated by irradiating the subject using a sequence of programmed X-ray beams, while sensitive photo-detectors measure the light diffusing out of the subject. By restricting the X-ray excitation to a single, narrow beam of radiation, the origin of the optical photons can be inferred regardless of where these photons were detected, and how many times they scattered in tissue. This study presents computer simulations exploring the feasibility of imaging small objects with XLCT, such as research animals. The accumulation of 50 nm phosphor nanoparticles in a 2-mm-diameter target can be detected and quantified with subpicomolar sensitivity using less than 1 cGy of radiation dose. Provided sufficient signal-to-noise ratio, the spatial resolution of the system can be made as high as needed by narrowing the beam aperture. In particular, 1 mm spatial resolution was achieved for a 1-mm-wide X-ray beam. By including an X-ray detector in the system, anatomical imaging is performed simultaneously with molecular imaging via standard X-ray computed tomography (CT). The molecular and anatomical images are spatially and temporally co-registered, and, if a single-pixel X-ray detector is used, they have matching spatial resolution.

View details for DOI 10.1109/TMI.2010.2055883

View details for Web of Science ID 000284848700004

View details for PubMedID 20615807

Abstract

The purpose of this work is to demonstrate that physical constraints on fluence gradients in 3D radiation therapy (RT) planning can be incorporated into beamlet optimization explicitly by direct constraint on the spatial variation of the fluence maps or implicitly by using total-variation regularization (TVR). The former method forces the fluence to vary in accordance with the known form of a wedged field and latter encourages the fluence to take the known form of the wedged field by requiring the derivatives of the fluence maps to be piece-wise constant. The performances of the proposed methods are evaluated by using a brain cancer case and a head and neck case. It is found that both approaches are capable of providing clinically sensible 3D RT solutions with monotonically varying fluence maps. For currently available 3D RT delivery schemes based on the use of customized physical or dynamic wedges, constrained optimization seems to be more useful because the optimized fields are directly deliverable. Working in the beamlet domain provides a natural way to model the spatial variation of the beam fluence. The proposed methods take advantage of the fact that 3D RT is a special form of intensity-modulated radiation therapy (IMRT) and finds the optimal plan by searching for fields with a certain type of spatial variation. The approach provides a unified framework for 3D CRT and IMRT plan optimization.

View details for DOI 10.1088/0031-9155/55/22/N01

View details for Web of Science ID 000283789700001

View details for PubMedID 21030744

Abstract

To develop a binary image reconstruction method for the autolocalization of metallic object(s) in CT with sparse projections.The authors divide the system into two types of contents: Metal(s) and nonmetal(s). The boundaries of metallic objects are obtained by using a penalized weighted least-squares algorithm with the adequate intensity gradient-controlled. A novel mechanism of "amplifying" the difference between metal(s) and nonmetallic substances is introduced by preprocessing the sinogram data, which is shown to be necessary in dealing with a case with sparse projection data. A series of experimental studies are performed to evaluate the proposed approach.A novel binary CT image reconstruction formalism is established for the autodetermination of the shape and location of metallic objects in the presence of limited number of projections. Experimental studies reveal that the presented algorithm works well even when the embedded metal object(s) has different shape(s). It is also shown that when the projection data are sparse, a differential manipulation of projection data can greatly facilitate the binary reconstruction process and allow the authors to obtain accurate binary CT images that would otherwise be unattainable.Binary CT reconstruction provides a viable method for determining the geometric distribution information of the implanted metal objects in CT imaging.

View details for DOI 10.1118/1.3505294

View details for Web of Science ID 000283747600033

View details for PubMedID 21158299

Abstract

To develop a 4D volumetric modulated arc therapy (VMAT) inverse planning framework.4D VMAT inverse planning aims to derive an aperture and weight modulated arc therapy treatment plan that optimizes the accumulated dose distribution from all gantry angles and breathing phases. Under an assumption that the gantry rotation and patient breathing are synchronized (i.e., there is a functional relationship between the phase of the patient breathing cycle and the beam angle), the authors compute the contribution from different respiration phases through the registration of the phased CT images. The accumulative dose distribution is optimized by iteratively adjusting the aperture shape and weight of each beam through the minimization of the planning objective function. For comparison, traditional 3D VMAT plans are also performed for the two cases and the performance of the proposed technique is demonstrated.A framework for 4D VMAT inverse planning has been proposed. With the consideration of the extra dimension of time in VMAT, a tighter target margin can be achieved with a full duty cycle, which is otherwise not achievable simultaneously by either 3D VMAT optimization or gated VMAT.The 4D VMAT planning formulism proposed here provides useful insight on how the "time" dimension can be exploited in rotational arc therapy to maximally compensate for the intrafraction organ motion.

View details for DOI 10.1118/1.3497271

View details for Web of Science ID 000283747600008

View details for PubMedID 21158274

Abstract

X-ray luminescence computed tomography (XLCT) is proposed as a new dual molecular/anatomical imaging modality. XLCT is based on the selective excitation and optical detection of x-ray-excitable nanoparticles. As a proof of concept, we built a prototype XLCT system and imaged near-IR-emitting Gd(2)O(2)S:Eu phosphors in various phantoms. Imaging in an optically diffusive medium shows that imaging performance is not affected by optical scatter; furthermore, the linear response of the reconstructed images suggests that XLCT is capable of quantitative imaging.

View details for Web of Science ID 000283048100013

View details for PubMedID 20967061

Abstract

To implement and evaluate clinic-ready adaptive imaging protocols for online patient repositioning (motion tracking) during prostate IMRT using treatment beam imaging supplemented by minimal, as-needed use of on-board kV.The authors examine the two-step decision-making strategy: (1) Use cine-MV imaging and online-updated characterization of prostate motion to detect target motion that is potentially beyond a predefined threshold and (2) use paired MV-kV 3D localization to determine overthreshold displacement and, if needed, reposition the patient. Two levels of clinical implementation were evaluated: (1) Field-by-field based motion correction for present-day linacs and (2) instantaneous repositioning for new-generation linacs with capabilities of simultaneous MV-kV imaging and remote automatic couch control during treatment delivery. Experiments were performed on a Varian Trilogy linac in clinical mode using a 4D motion phantom programed with prostate motion trajectories taken from patient data. Dosimetric impact was examined using a 2D ion chamber array. Simulations were done for 536 trajectories from 17 patients.Despite the loss of marker detection efficiency caused by the MLC leaves sometimes obscuring the field at the marker's projected position on the MV imager, the field-by-field correction halved (from 23% to 10%) the mean percentage of time that target displacement exceeded a 3 mm threshold, as compared to no intervention. This was achieved at minimal cost in additional imaging (average of one MV-kV pair per two to three treatment fractions) and with a very small number of repositionings (once every four to five fractions). Also with low kV usage (approximation 2/fraction), the instantaneous repositioning approach reduced overthreshold time by more than 75% (23% to 5%) even with severe MLC blockage as often encountered in current IMRT and could reduce the overthreshold time tenfold (to < 2%) if the MLC blockage problem were relieved. The information acquired for repositioning using combined MV-kV images was found to have submillimeter accuracy.This work demonstrated with a current clinical setup that substantial reduction of adverse targeting effects of intrafraction prostate motion can be realized. The proposed adaptive imaging strategy incurs minimal imaging dose to the patient as compared to other stereoscopic imaging techniques.

View details for DOI 10.1118/1.3488887

View details for Web of Science ID 000283483700016

View details for PubMedID 21089763

Abstract

This article considers the problem of reconstructing cone-beam computed tomography (CBCT) images from a set of undersampled and potentially noisy projection measurements.The authors cast the reconstruction as a compressed sensing problem based on l1 norm minimization constrained by statistically weighted least-squares of CBCT projection data. For accurate modeling, the noise characteristics of the CBCT projection data are used to determine the relative importance of each projection measurement. To solve the compressed sensing problem, the authors employ a method minimizing total-variation norm, satisfying a prespecified level of measurement consistency using a first-order method developed by Nesterov.The method converges fast to the optimal solution without excessive memory requirement, thanks to the method of iterative forward and back-projections. The performance of the proposed algorithm is demonstrated through a series of digital and experimental phantom studies. It is found a that high quality CBCT image can be reconstructed from undersampled and potentially noisy projection data by using the proposed method. Both sparse sampling and decreasing x-ray tube current (i.e., noisy projection data) lead to the reduction of radiation dose in CBCT imaging.It is demonstrated that compressed sensing outperforms the traditional algorithm when dealing with sparse, and potentially noisy, CBCT projection views.

View details for DOI 10.1118/1.3481510

View details for Web of Science ID 000281906000063

View details for PubMedID 20964231

Abstract

The feasibility of x-ray luminescence imaging is investigated using a dual-modality imaging system that merges x-ray and optical imaging. This modality utilizes x-ray activated nanophosphors that luminesce when excited by ionizing photons. By doping phosphors with lanthanides, which emit light in the visible and near infrared range, the luminescence is suitable for biological applications. This study examines practical aspects of this new modality including phosphor concentration, light emission linearity, detector damage, and spectral emission characteristics. Finally, the contrast produced by these phosphors is compared to that of x-ray fluoroscopy.Gadolinium and lanthanum oxysulfide phosphors doped with terbium (green emission) or europium (red emission) were studied. The light emission was imaged in a clinical x-ray scanner with a cooled CCD camera and a spectrophotometer; dose measurements were determined with a calibrated dosimeter. Using these properties, in addition to luminescence efficiency values found in the literature for a similar phosphor, minimum concentration calculations are performed. Finally, a 2.5 cm agar phantom with a 1 cm diameter cylindrical phosphor-filled inclusion (diluted at 10 mg/ml) is imaged to compare x-ray luminescence contrast with x-ray fluoroscopic contrast at a superficial location.Dose to the CCD camera in the chosen imaging geometry was measured at less than 0.02 cGy/s. Emitted light was found to be linear with dose (R(2)= 1) and concentration (R(2)= 1). Emission peaks for clinical x-ray energies are less than 3 nm full width at half maximum, as expected from lanthanide dopants. The minimum practical concentration necessary to detect luminescent phosphors is dependent on dose; it is estimated that subpicomolar concentrations are detectable at the surface of the tissue with typical mammographic doses, with the minimum detectable concentration increasing with depth and decreasing with dose. In a reflection geometry, x-ray luminescence had nearly a 430-fold greater contrast to background than x-ray fluoroscopy.X-ray luminescence has the potential to be a promising new modality for enabling molecular imaging within x-ray scanners. Although much work needs to be done to ensure biocompatibility of x-ray exciting phosphors, the benefits of this modality, highlighted in this work, encourage further study.

View details for DOI 10.1118/1.3457332

View details for Web of Science ID 000281112900011

View details for PubMedID 20879562

Abstract

Volumetric modulated arc therapy (VMAT) has recently emerged as a new clinical modality for conformal radiation therapy. The aim of this work is to establish a methodology and procedure for retrospectively reconstructing the actual dose delivered in VMAT based on the pre-treatment cone-beam computed tomography (CBCT) and dynamic log files. CBCT was performed before the dose delivery and the system's log files were retrieved after the delivery. Actual delivery at a control point including MLC leaf positions, gantry angles and cumulative monitor units (MUs) was recorded in the log files and the information was extracted using in-house developed software. The extracted information was then embedded into the original treatment DICOM-radiation therapy (RT) file to replace the original control point parameters. This reconstituted DICOM-RT file was imported into the Eclipse treatment planning system (TPS) and dose was computed on the corresponding CBCT. A series of phantom experiments was performed to show the feasibility of dose reconstruction, validate the procedure and demonstrate the efficacy of this methodology. The resultant dose distributions and dose-volume histograms (DVHs) were compared with those of the original treatment plan. The studies indicated that CBCT-based VMAT dose reconstruction is readily achievable and provides a valuable tool for monitoring the dose actually delivered to the tumor target as well as the sensitive structures. In the absence of setup errors, the reconstructed dose shows no significant difference from the original pCT-based plan. It is also elucidated that the proposed method is capable of revealing the dosimetric changes in the presence of setup errors. The method reported here affords an objective means for dosimetric evaluation of VMAT delivery and is useful for adaptive VMAT in future.

View details for DOI 10.1088/0031-9155/55/13/002

View details for Web of Science ID 000279004300002

View details for PubMedID 20526034

Abstract

This paper presents a fast and accurate marker-based automatic registration technique for aligning uncalibrated projections taken from a transmission electron microscope (TEM) with different tilt angles and orientations. Most of the existing TEM image alignment methods estimate the similarity between images using the projection model with least-squares metric and guess alignment parameters by computationally expensive nonlinear optimization schemes. Approaches based on the least-squares metric which is sensitive to outliers may cause misalignment since automatic tracking methods, though reliable, can produce a few incorrect trajectories due to a large number of marker points. To decrease the influence of outliers, we propose a robust similarity measure using the projection model with a Gaussian weighting function. This function is very effective in suppressing outliers that are far from correct trajectories and thus provides a more robust metric. In addition, we suggest a fast search strategy based on the non-gradient Powell's multidimensional optimization scheme to speed up optimization as only meaningful parameters are considered during iterative projection model estimation. Experimental results show that our method brings more accurate alignment with less computational cost compared to conventional automatic alignment methods.

View details for DOI 10.1088/0031-9155/55/12/010

View details for Web of Science ID 000278147800010

View details for PubMedID 20508322

Abstract

The presence of metals in patients causes streaking artifacts in X-ray CT and has been recognized as a problem that limits various applications of CT imaging. Accurate localization of metals in CT images is a critical step for metal artifacts reduction in CT imaging and many practical applications of CT images. The purpose of this work is to develop a method of auto-determination of the shape and location of metallic object(s) in the image space. The proposed method is based on the fact that when a metal object is present in a patient, a CT image can be divided into two prominent components: high density metal and low density normal tissues. This prior knowledge is incorporated into an objective function as the regularization term whose role is to encourage the solution to take a form of two intensity levels. A computer simulation study and four experimental studies are performed to evaluate the proposed approach. Both simulation and experimental studies show that the presented algorithm works well even in the presence of complicated shaped metal objects. For a hexagonally shaped metal embedded in a water phantom, for example, it is found that the accuracy of metal reconstruction is within sub-millimeter.

View details for DOI 10.3233/XST-2010-0271

View details for Web of Science ID 000283777900006

View details for PubMedID 21045277

Abstract

To use angular beam's-eye-view dosimetrics (BEVD) information to improve the computational efficiency and plan quality of inverse planning of aperture-modulated arc therapy (AMAT).In BEVD-guided inverse planning, the angular space spanned by a rotational arc is represented by a large number of fixed-gantry beams with angular spacing of approximately 2.5 degrees. Each beam is assigned with an initial aperture shape determined by the beam's-eye-view (BEV) projection of the planning target volume (PTV) and an initial weight. Instead of setting the beam weights arbitrarily, which slows down the subsequent optimization process and may result in a suboptimal solution, a priori knowledge about the quality of the beam directions derived from a BEVD is adopted to initialize the weights. In the BEVD calculation, a higher score is assigned to directions that allow more dose to be delivered to the PTV without exceeding the dose tolerances of the organs at risk (OARs) and vice versa. Simulated annealing is then used to optimize the segment shapes and weights. The BEVD-guided inverse planning is demonstrated by using two clinical cases, and the results are compared with those of a conventional approach without BEVD guidance.An a priori knowledge-guided inverse planning scheme for AMAT is established. The inclusion of BEVD guidance significantly improves the convergence behavior of AMAT inverse planning and results in much better OAR sparing as compared with the conventional approach.BEVD-guidance facilitates AMAT treatment planning and provides a comprehensive tool to maximally use the technical capacity of the new arc therapeutic modality.

View details for DOI 10.1016/j.ijrobp.2009.05.003

View details for Web of Science ID 000272341800043

View details for PubMedID 19733446

Abstract

Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

View details for DOI 10.1088/0031-9155/54/19/005

View details for Web of Science ID 000270051600006

View details for PubMedID 19729711

Abstract

To utilize image-guided radiotherapy (IGRT) in near real time by obtaining and evaluating the online positions of implanted fiducials from continuous electronic portal imaging device (EPID) imaging of prostate intensity-modulated radiotherapy (IMRT) delivery.Upon initial setup using two orthogonal images, the three-dimensional (3D) positions of all implanted fiducial markers are obtained, and their expected two-dimensional (2D) locations in the beam's-eye-view (BEV) projection are calculated for each treatment field. During IMRT beam delivery, EPID images of the megavoltage treatment beam are acquired in cine mode and subsequently analyzed to locate 2D locations of fiducials in the BEV. Simultaneously, 3D positions are estimated according to the current EPID image, information from the setup portal images, and images acquired at other gantry angles (the completed treatment fields). The measured 2D and 3D positions of each fiducial are compared with their expected 2D and 3D setup positions, respectively. Any displacements larger than a predefined tolerance may cause the treatment system to suspend the beam delivery and direct the therapists to reposition the patient.Phantom studies indicate that the accuracy of 2D BEV and 3D tracking are better than 1 mm and 1.4 mm, respectively. A total of 7330 images from prostate treatments were acquired and analyzed, showing a maximum 2D displacement of 6.7 mm and a maximum 3D displacement of 6.9 mm over 34 fractions.This EPID-based, real-time IGRT method can be implemented on any external beam machine with portal imaging capabilities without purchasing any additional equipment, and there is no extra dose delivered to the patient.

View details for DOI 10.1016/j.ijrobp.2009.04.068

View details for Web of Science ID 000269941600040

View details for PubMedID 19735886

Abstract

To quantify pancreas tumor motion on both a planning 4D-CT and during a single fraction treatment using the CyberKnife linear accelerator and Synchrony respiratory tracking software, and to investigate whether a single 4D-CT study is reliable for determining radiation treatment margins for patients with locally advanced pancreas cancer.Twenty patients underwent fiducial placement, biphasic pancreatic protocol CT scan and 4D-CT scan in the treatment position while free-breathing. Patients were then treated with a single 25 Gy fraction of stereotactic body radiotherapy. Predicted pancreas motion in the superior-inferior (SI), left-right (LR), and anterior-posterior (AP) directions was calculated from the maximum inspiration and maximum expiration 4D-CT scan. For CyberKnife treatments, mean respiratory cycle motion and maximum respiratory cycle motion was determined in the SI, LR, and AP directions.The range of centroid movement based on 4D-CT in the SI, LR, and AP directions were 0.9 to 28.8 mm, 0.1 to 13.7 mm, and 0.2 to 7.6 mm, respectively. During CyberKnife treatment, in the SI direction, the mean motion of the centroid ranged from 0.5 to 12.7 mm. In the LR direction, the mean motion range was 0.4 to 9.4 mm. In the AP direction, the mean motion range was 0.6 to 5.5 mm. The maximum range of movement (mean) during CyberKnife treatment in the SI, LR, and AP directions were 4.5 to 48.8 mm (mean 20.8 mm), 1.5 to 41.3 mm (mean 11.3 mm), and 1.6 to 68.1 mm (mean 13.4 mm), respectively. Neither the maximum or mean motion correlated with the 4D-CT movement.There is substantial respiratory associated motion of pancreatic tumors. The 4D-CT planning scans cannot accurately predict the movement of pancreatic tumors during actual treatment on CyberKnife.

View details for DOI 10.1097/COC.0b013e31818da9e0

View details for Web of Science ID 000268761600007

View details for PubMedID 19398901

Abstract

To report a tissue feature-based image registration strategy with explicit inclusion of the differential motions of thoracic structures.The proposed technique started with auto-identification of a number of corresponding points with distinct tissue features. The tissue feature points were found by using the scale-invariant feature transform method. The control point pairs were then sorted into different "colors" according to the organs in which they resided and used to model the involved organs individually. A thin-plate spline method was used to register a structure characterized by the control points with a given "color." The proposed technique was applied to study a digital phantom case and 3 lung and 3 liver cancer patients.For the phantom case, a comparison with the conventional thin-plate spline method showed that the registration accuracy was markedly improved when the differential motions of the lung and chest wall were taken into account. On average, the registration error and standard deviation of the 15 points against the known ground truth were reduced from 3.0 to 0.5 mm and from 1.5 to 0.2 mm, respectively, when the new method was used. A similar level of improvement was achieved for the clinical cases.The results of our study have shown that the segmented deformable approach provides a natural and logical solution to model the discontinuous organ motions and greatly improves the accuracy and robustness of deformable registration.

View details for DOI 10.1016/j.ijrobp.2009.02.023

View details for Web of Science ID 000267505000040

View details for PubMedID 19545792

Abstract

The purpose of this study is to develop a 4D inverse planning strategy capable of controlling the appearance of the implanted fiducial(s) in segmented IMRT fields for cine MV or combined MV/kV image-guided IMRT. This work is focused on enhancing the visibility of the implanted fiducial(s) in 4D IMRT inverse planning, whose goal is to derive a set of time-resolved (or phase-tagged) MLC segments to cater for the motion of the patient anatomy extracted from the emerging 4D images. The task is to optimize the shapes and weights of all the segments for each incident beam, with the fiducial(s) being forced/encouraged to be inside the segmented fields. The system is modeled by a quadratic objective function with inclusion of a hard/soft constraint characterizing the authors' level of preference for the fiducial(s) to be included in the segmented fields. A simulated annealing algorithm is employed to optimize the system. The proposed technique is demonstrated using two clinical cases. A segment-based inverse planning framework for 4D radiation therapy, capable of providing tempospatially optimized IMRT plans, has been established. Furthermore, using the described 4D optimization approach, it is demonstrated that the MLC blockage of the implanted fiducial(s) during the segmented delivery is avoided without severely compromising the final dose distribution. The visibility of implanted fiducials in 4D IMRT can be improved without significantly deteriorating final dose distribution. This is a foundation for the authors to use cine MV or combined MV/KV to effectively guide the 4D IMRT delivery.

View details for DOI 10.1118/1.3121425

View details for Web of Science ID 000266442000030

View details for PubMedID 19610310

Abstract

Cone-beam CT (CBCT) is being increasingly used in modern radiation therapy for patient setup and adaptive replanning. However, due to the large volume of x-ray illumination, scatter becomes a rather serious problem and is considered as one of the fundamental limitations of CBCT image quality. Many scatter correction algorithms have been proposed in literature, while a standard practical solution still remains elusive. In radiation therapy, the same patient is scanned repetitively during a course of treatment, a natural question to ask is whether one can obtain the scatter distribution on the first day of treatment and then use the data for scatter correction in the subsequent scans on different days. To realize this scatter removal scheme, two technical pieces must be in place: (i) A strategy to obtain the scatter distribution in on-board CBCT imaging and (ii) a method to spatially match a prior scatter distribution with the on-treatment CBCT projection data for scatter subtraction. In this work, simple solutions to the two problems are provided. A partially blocked CBCT is used to extract the scatter distribution. The x-ray beam blocker has a strip pattern, such that partial volume can still be accurately reconstructed and the whole-field scatter distribution can be estimated from the detected signals in the shadow regions using interpolation/extrapolation. In the subsequent scans, the patient transformation is determined using a rigid registration of the conventional CBCT and the prior partial CBCT. From the derived patient transformation, the measured scatter is then modified to adapt the new on-treatment patient geometry for scatter correction. The proposed method is evaluated using physical experiments on a clinical CBCT system. On the Catphan 600 phantom, the errors in Hounsfield unit (HU) in the selected regions of interest are reduced from about 350 to below 50 HU; on an anthropomorphic phantom, the error is reduced from 15.7% to 5.4%. The proposed method is attractive in applications where a high CBCT image quality is critical, for example, dose calculation in adaptive radiation therapy.

View details for DOI 10.1118/1.3130047

View details for Web of Science ID 000266442000035

View details for PubMedID 19610315

Abstract

An intensity-modulated radiation therapy (IMRT) field is composed of a series of segmented beams. It is practically important to reduce the number of segments while maintaining the conformality of the final dose distribution. In this article, the authors quantify the complexity of an IMRT fluence map by introducing the concept of sparsity of fluence maps and formulate the inverse planning problem into a framework of compressing sensing. In this approach, the treatment planning is modeled as a multiobjective optimization problem, with one objective on the dose performance and the other on the sparsity of the resultant fluence maps. A Pareto frontier is calculated, and the achieved dose distributions associated with the Pareto efficient points are evaluated using clinical acceptance criteria. The clinically acceptable dose distribution with the smallest number of segments is chosen as the final solution. The method is demonstrated in the application of fixed-gantry IMRT on a prostate patient. The result shows that the total number of segments is greatly reduced while a satisfactory dose distribution is still achieved. With the focus on the sparsity of the optimal solution, the proposed method is distinct from the existing beamlet- or segment-based optimization algorithms.

View details for DOI 10.1118/1.3110163

View details for Web of Science ID 000265526800050

View details for PubMedID 19544809

Abstract

Scatter correction is crucial to the quality of reconstructed images in x-ray cone-beam computed tomography (CBCT). Most of existing scatter correction methods assume smooth scatter distributions. The high-frequency scatter noise remains in the projection images even after a perfect scatter correction. In this paper, using a clinical CBCT system and a measurement-based scatter correction, the authors show that a scatter correction alone does not provide satisfactory image quality and the loss of the contrast-to-noise ratio (CNR) of the scatter corrected image may overwrite the benefit of scatter removal. To circumvent the problem and truly gain from scatter correction, an effective scatter noise suppression method must be in place. They analyze the noise properties in the projections after scatter correction and propose to use a penalized weighted least-squares (PWLS) algorithm to reduce the noise in the reconstructed images. Experimental results on an evaluation phantom (Catphan600) show that the proposed algorithm further reduces the reconstruction error in a scatter corrected image from 10.6% to 1.7% and increases the CNR by a factor of 3.6. Significant image quality improvement is also shown in the results on an anthropomorphic phantom, in which the global noise level is reduced and the local streaking artifacts around bones are suppressed.

View details for DOI 10.1118/1.3063001

View details for Web of Science ID 000263718100008

View details for PubMedID 19378735

Abstract

The integration of onboard kV imaging together with a MV electronic portal imaging device (EPID) on linear accelerators (LINAC) can provide an easy to implement real-time 3D organ position monitoring solution for treatment delivery. Currently, real-time MV-kV tracking has only been demonstrated by simultaneous imagining by both MV and kV imaging devices. However, modalities such as step-and-shoot IMRT (SS-IMRT), which inherently contain MV beam interruptions, can lead to loss of target information necessary for 3D localization. Additionally, continuous kV imaging throughout the treatment delivery can lead to high levels of imaging dose to the patient. This work demonstrates for the first time how full 3D target tracking can be maintained even in the presence of such beam interruption, or MV/kV beam interleave, by use of a relatively simple correlation model together with MV-kV tracking. A moving correlation model was constructed using both present and prior positions of the marker in the available MV or kV image to compute the position of the marker on the interrupted imager. A commercially available radiotherapy system, equipped with both MV and kV imaging devices, was used to deliver typical SS-IMRT lung treatment plans to a 4D phantom containing internally embedded metallic markers. To simulate actual lung tumor motion, previous recorded 4D lung patient motion data were used. Lung tumor motion data of five separate patients were inputted into the 4D phantom, and typical SS-IMRT lung plans were delivered to simulate actual clinical deliveries. Application of the correlation model to SS-IMRT lung treatment deliveries was found to be an effective solution for maintaining continuous 3D tracking during 'step' beam interruptions. For deliveries involving five or more gantry angles with 50 or more fields per plan, the positional errors were found to have < or =1 mm root mean squared error (RMSE) in all three spatial directions. In addition to increasing the robustness of MV-kV tracking against beam interruption, it was also found that use of correlation can be an effective way of lowering kV dose to the patient and for increasing kV image quality by reduction of MV scatter interference.

View details for DOI 10.1088/0031-9155/54/1/006

View details for Web of Science ID 000261597400006

View details for PubMedID 19060356

Abstract

On-board cone-beam computed tomography (CBCT) is a new imaging technique for radiation therapy guidance, which provides volumetric information of a patient at treatment position. CBCT improves the setup accuracy and may be used for dose reconstruction. However, there is great concern that the repeated use of CBCT during a treatment course delivers too much of an extra dose to the patient. To reduce the CBCT dose, one needs to lower the total mAs of the x-ray tube current, which usually leads to reduced image quality. Our goal of this work is to develop an effective method that enables one to achieve a clinically acceptable CBCT image with as low as possible mAs without compromising quality. An iterative image reconstruction algorithm based on a penalized weighted least-squares (PWLS) principle was developed for this purpose. To preserve edges in the reconstructed images, we designed an anisotropic penalty term of a quadratic form. The algorithm was evaluated with a CT quality assurance phantom and an anthropomorphic head phantom. Compared with conventional isotropic penalty, the PWLS image reconstruction algorithm with anisotropic penalty shows better resolution preservation.

View details for DOI 10.1118/1.3036112

View details for Web of Science ID 000262105200028

View details for PubMedID 19235393

Abstract

To minimize the adverse dosimetric effect caused by tumor motion, it is desirable to have real-time knowledge of the tumor position throughout the beam delivery process. A promising technique to realize the real-time image guided scheme in external beam radiation therapy is through the combined use of MV and onboard kV beam imaging. The success of this MV-kV triangulation approach for fixed-gantry radiation therapy has been demonstrated. With the increasing acceptance of modern arc radiotherapy in the clinics, a timely and clinically important question is whether the image guidance strategy can be extended to arc therapy to provide the urgently needed real-time tumor motion information. While conceptually feasible, there are a number of theoretical and practical issues specific to the arc delivery that need to be resolved before clinical implementation. The purpose of this work is to establish a robust procedure of system calibration for combined MV and kV imaging for internal marker tracking during arc delivery and to demonstrate the feasibility and accuracy of the technique. A commercially available LINAC equipped with an onboard kV imager and electronic portal imaging device (EPID) was used for the study. A custom built phantom with multiple ball bearings was used to calibrate the stereoscopic MV-kV imaging system to provide the transformation parameters from imaging pixels to 3D world coordinates. The accuracy of the fiducial tracking system was examined using a 4D motion phantom capable of moving in accordance with a pre-programmed trajectory. Overall, spatial accuracy of MV-kV fiducial tracking during the arc delivery process for normal adult breathing amplitude and period was found to be better than 1 mm. For fast motion, the results depended on the imaging frame rates. The RMS error ranged from approximately 0.5 mm for the normal adult breathing pattern to approximately 1.5 mm for more extreme cases with a low imaging frame rate of 3.4 Hz. In general, highly accurate real-time tracking of implanted markers using hybrid MV-kV imaging is achievable and the technique should be useful to improve the beam targeting accuracy of arc therapy.

View details for DOI 10.1088/0031-9155/53/24/013

View details for Web of Science ID 000261310200013

View details for PubMedID 19043177

Abstract

Currently, there are two types of treatment planning algorithms for intensity modulated radiation therapy (IMRT). The beamlet-based algorithm generates beamlet intensity maps with high complexity, resulting in large numbers of segments in the delivery after a leaf-sequencing algorithm is applied. The segment-based direct aperture optimization (DAO) algorithm includes the physical constraints of the deliverable apertures in the calculation, and achieves a conformal dose distribution using a small number of segments. However, the number of segments is pre-fixed in most of the DAO approaches, and the typical random search scheme in the optimization is computationally intensive. A regularization-based algorithm is proposed to overcome the drawbacks of the DAO method. Instead of smoothing the beamlet intensity maps as in many existing methods, we include a total-variation term in the optimization objective function to reduce the number of signal levels of the beam intensity maps. An aperture rectification algorithm is then applied to generate a significantly reduced number of deliverable apertures. As compared to the DAO algorithm, our method has an efficient form of quadratic optimization, with an additional advantage of optimizing field-specific numbers of segments based on the modulation complexity. The proposed approach is evaluated using two clinical cases. Under the condition that the clinical acceptance criteria of the treatment plan are satisfied, for the prostate patient, the total number of segments for five fields is reduced from 61 using the Eclipse planning system to 35 using the proposed algorithm; for the head and neck patient, the total number of segments for seven fields is reduced from 107 to 28. The head and neck result is also compared to that using an equal number of four segments for each field. The comparison shows that using field-specific numbers of segments achieves a much improved dose distribution.

View details for DOI 10.1088/0031-9155/53/23/002

View details for Web of Science ID 000260859000002

View details for PubMedID 18997262

Abstract

For intensity modulated radiation treatment (IMRT) dose reconstruction, multileaf collimator (MLC) log files have been shown applicable for deriving delivered fluence maps. However, MLC log files are dependent on the accuracy of leaf calibration and only available from one linear accelerator manufacturer. This paper presents a proof of feasibility and principles in (1) using an amorphous silicon electronic portal imaging device (aSi-EPID) to capture the MLC segments during an IMRT delivery and (2) reconstituting a leaf sequence (LS) file based on the leaf end positions calculated from the MLC segments and their associated fractional monitor units. These EPID-measured LS files are then used to derive delivered fluence maps for dose reconstruction. The developed approach was tested on a pelvic phantom treated with a typical prostate IMRT plan. The delivered fluence maps, which were derived from the EPID-measured LS files, showed slight differences in the intensity levels compared with the corresponding planned ones. The dose distribution calculated with the delivered fluence maps showed a discernible difference in the high dose region when compared to that calculated with the planned fluence maps. The maximum dose in the former distribution was also 2.5% less than that in the latter one. The EPID-measured LS file can serve the same purpose as a MLC log files does for the derivation of the delivered fluence map and yet is independent of the leaf calibration. The approach also allows users who do not have access to MLC log files to probe the actual IMRT delivery and translate the information gained for dose reconstruction in adaptive radiation therapy.

View details for DOI 10.1118/1.2990782

View details for Web of Science ID 000260484400029

View details for PubMedID 19070236

Abstract

Nowadays magnetic resonance imaging (MRI) has been profoundly used in radiotherapy (RT) planning to aid the contouring of targets and critical organs in brain and intracranial cases, which is attributable to its excellent soft tissue contrast and multi-planar imaging capability. However, the lack of electron density information in MRI, together with the image distortion issues, precludes its use as the sole image set for RT planning and dose calculation. The purpose of this preliminary study is to probe the feasibility and evaluate an MRI-based radiation dose calculation process by providing MR images the necessary electron density (ED) information from a patient's readily available diagnostic/staging computed tomography (CT) images using an image registration model. To evaluate the dosimetric accuracy of the proposed approach, three brain and three intracranial cases were selected retrospectively for this study. For each patient, the MR images were registered to the CT images, and the ED information was then mapped onto the MR images by in-house developed software generating a modified set of MR images. Another set of MR images with voxel values assigned with the density of water was also generated. The original intensity modulated radiation treatment (IMRT) plan was then applied to the two sets of MR images and the doses were calculated. The dose distributions from the MRI-based calculations were compared to that of the original CT-based calculation. In all cases, the MRI-based calculations with mapped ED yielded dose values very close (within 2%) to that of the CT-based calculations. The MRI-based calculations with voxel values assigned with water density indicated a dosimetric error of 3-5%, depending on the treatment site. The present approach offers a means of utilizing MR images for accurate dose calculation and affords a potential to eliminate the redundant simulation CT by planning a patient's treatment with only simulation MRI and any available diagnostic/staging CT data.

View details for Web of Science ID 000259799000001

View details for PubMedID 18783283

Abstract

The purpose of this work is to develop a novel feature-based registration strategy to automatically map the rectal contours from planning computed tomography (CT) (pCT) to cone beam CT (CBCT). The rectal contours were manually outlined on the pCT. A narrow band with the outlined contour as its interior surface was then constructed, so that we can exclude the volume inside the rectum in the registration process. The corresponding contour in the CBCT was found by using a feature-based registration algorithm, which consists of two steps: (1) automatically searching for control points in the pCT and CBCT based on the features of the surrounding tissue and matching the homologous control points using the scale invariance feature transformation; and (2) using the control points for a thin plate spline transformation to warp the narrow band and mapping the corresponding contours from pCT to CBCT. The proposed contour propagation technique is applied to digital phantoms and clinical cases and, in all cases, the contour mapping results are found to be clinically acceptable. For clinical cases, the method yielded satisfactory results even when there were significant rectal content changes between the pCT and CBCT scans. As a consequence, the accordance between the rectal volumes after deformable registration and the manually segmented rectum was found to be more than 90%. The proposed technique provides a powerful tool for adaptive radiotherapy of prostate, rectal, and gynecological cancers in the future.

View details for DOI 10.1118/1.2975230

View details for Web of Science ID 000259591800021

View details for PubMedID 18975692

Abstract

The purpose of this work is to develop an effective technique to automatically propagate contours from planning CT to cone beam CT (CBCT) to facilitate CBCT-guided prostate adaptive radiation therapy. Different from other disease sites, such as the lungs, the contour mapping here is complicated by two factors: (i) the physical one-to-one correspondence may not exist due to the insertion or removal of some image contents within the region of interest (ROI); and (ii) reduced contrast to noise ratio of the CBCT images due to increased scatter. To overcome these issues, we investigate a strategy of excluding the regions with variable contents by a careful design of a narrow shell signifying the contour of an ROI. For rectum, for example, a narrow shell with the delineated contours as its interior surface was constructed to avoid the adverse influence of the day-to-day content change inside the rectum on the contour mapping. The corresponding contours in the CBCT were found by warping the narrow shell through the use of BSpline deformable model. Both digital phantom experiments and clinical case testing were carried out to validate the proposed ROI mapping method. It was found that the approach was able to reliably warp the constructed narrow band with an accuracy better than 1.3 mm. For all five clinical cases enrolled in this study, the method yielded satisfactory results even when there were significant rectal content changes between the planning CT and CBCT scans. The overlapped area of the auto-mapped contours over 90% to the manually drawn contours is readily achievable. The proposed approach permits us to take advantage of the regional calculation algorithm yet avoiding the nuisance of rectum/bladder filling and provide a useful tool for adaptive radiotherapy of prostate in the future.

View details for DOI 10.1088/0031-9155/53/17/005

View details for Web of Science ID 000258537000006

View details for PubMedID 18677041

Abstract

To report the characteristics of prostate motion as tracked by the stereoscopic X-ray images of the implanted fiducials during hypofractionated radiotherapy with CyberKnife.Twenty-one patients with prostate cancer who were treated with CyberKnife between January 2005 and September 2007 were selected for this retrospective study. The CyberKnife uses a stereoscopic X-ray system to obtain the position of the prostate target through the monitoring of implanted gold fiducial markers. If there is a significant deviation, the treatment is paused while the patient is repositioned by moving the couch. The deviations calculated from X-ray images acquired within the time interval between two consecutive couch motions constitute a data set.Included in the analysis were 427 data sets and 4,439 time stamps of X-ray images. The mean duration for each data set was 697 sec. At 30 sec, a motion >2 mm exists in about 5% of data sets. The percentage is increased to 8%, 11%, and 14% at 60 sec, 90 sec, and 120 sec, respectively. A similar trend exists for other values of prostate motion.With proper monitoring and intervention during treatment, the prostate shifts observed among patients can be kept within the tracking range of the CyberKnife. On average, a sampling rate of approximately 40 sec between consecutive X-rays is acceptable to ensure submillimeter tracking. However, there is significant movement variation among patients, and a higher sampling rate may be necessary in some patients.

View details for DOI 10.1016/j.ijrobp.2008.04.051

View details for Web of Science ID 000258741700036

View details for PubMedID 18722274

Abstract

The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm/s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024 x 768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal or be used for intra-fractional tumor tracking on a Linac equipped with a kV imaging system. Any motion exceeding a preset threshold can warn the therapist to suspend a treatment session and reposition the patient.

View details for DOI 10.1118/1.2953563

View details for Web of Science ID 000258038900017

View details for PubMedID 18777916

Abstract

Kilovotage cone-beam computed tomography (kV-CBCT) has shown potentials to improve the accuracy of a patient setup in radiotherapy. However, daily and repeated use of CBCT will deliver high extra radiation doses to patients. One way to reduce the patient dose is to lower mAs when acquiring projection data. This, however, degrades the quality of low mAs CBCT images dramatically due to excessive noises. In this work, we aim to improve the CBCT image quality from low mAs scans. Based on the measured noise properties of the sinogram, a penalized weighted least-squares (PWLS) objective function was constructed, and the ideal sinogram was then estimated by minimizing the PWLS objection function. To preserve edge information in the projection data, an anisotropic penalty term was designed using the intensity difference between neighboring pixels. The effectiveness of the presented algorithm was demonstrated by two experimental phantom studies. Noise in the reconstructed CBCT image acquired with a low mAs protocol was greatly suppressed after the proposed sinogram domain image processing, without noticeable sacrifice of the spatial resolution.

View details for DOI 10.1088/0031-9155/53/11/009

View details for Web of Science ID 000256352000010

View details for PubMedID 18460749

Abstract

Intrafraction organ motion can limit the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT) due to target position uncertainty. To ensure high accuracy in beam targeting, real-time knowledge of the target location is highly desired throughout the beam delivery process. This knowledge can be gained through imaging of internally implanted radio-opaque markers with fluoroscopic or electronic portal imaging devices (EPID). In the case of MV based images, marker detection can be problematic due to the significantly lower contrast between different materials in comparison to their kV-based counterparts. This work presents a fully automated algorithm capable of detecting implanted metallic markers in both kV and MV images with high consistency. Using prior CT information, the algorithm predefines the volumetric search space without manual region-of-interest (ROI) selection by the user. Depending on the template selected, both spherical and cylindrical markers can be detected. Multiple markers can be simultaneously tracked without indexing confusion. Phantom studies show detection success rates of 100% for both kV and MV image data. In addition, application of the algorithm to real patient image data results in successful detection of all implanted markers for MV images. Near real-time operational speeds of approximately 10 frames/sec for the detection of five markers in a 1024 x 768 image are accomplished using an ordinary PC workstation.

View details for DOI 10.1118/1.2905225

View details for Web of Science ID 000255456500035

View details for PubMedID 18561670

Abstract

In the presence of intrafraction organ motion, target localization uncertainty can greatly hamper the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT). To minimize the adverse dosimetric effect caused by tumor motion, a real-time knowledge of the tumor position is required throughout the beam delivery process. The recent integration of onboard kV diagnostic imaging together with MV electronic portal imaging devices on linear accelerators can allow for real-time three-dimensional (3D) tumor position monitoring during a treatment delivery. The aim of this study is to demonstrate a near real-time 3D internal fiducial tracking system based on the combined use of kV and MV imaging. A commercially available radiotherapy system equipped with both kV and MV imaging systems was used in this work. A hardware video frame grabber was used to capture both kV and MV video streams simultaneously through independent video channels at 30 frames per second. The fiducial locations were extracted from the kV and MV images using a software tool. The geometric tracking capabilities of the system were evaluated using a pelvic phantom with embedded fiducials placed on a moveable stage. The maximum tracking speed of the kV/MV system is approximately 9 Hz, which is primarily limited by the frame rate of the MV imager. The geometric accuracy of the system is found to be on the order of less than 1 mm in all three spatial dimensions. The technique requires minimal hardware modification and is potentially useful for image-guided radiation therapy systems.

View details for DOI 10.1118/1.2842072

View details for Web of Science ID 000254510700004

View details for PubMedID 18491510

Abstract

The medical linear accelerator (linac) integrated with a kilovoltage (kV) flat-panel imager has been emerging as an important piece of equipment for image-guided radiation therapy. Due to the sagging of the linac head and the flexing of the robotic arms that mount the x-ray tube and flat-panel detector, geometric nonidealities generally exist in the imaging geometry no matter whether it is for the two-dimensional projection image or three-dimensional cone-beam computed tomography. Normally, the geometric parameters are established during the commissioning and incorporated in correction software in respective image formation or reconstruction. A prudent use of an on-board imaging system necessitates a routine surveillance of the geometric accuracy of the system like the position of the x-ray source, imager position and orientation, isocenter, rotation trajectory, and source-to-imager distance. Here we describe a purposely built phantom and a data analysis software for monitoring these important parameters of the system in an efficient and automated way. The developed tool works equally well for the megavoltage (MV) electronic portal imaging device and hence allows us to measure the coincidence of the isocenters of the MV and kV beams of the linac. This QA tool can detect an angular uncertainty of 0.1 degrees of the x-ray source. For spatial uncertainties, such as the source position, the imager position, or the kV/MV isocenter misalignment, the demonstrated accuracy of this tool was better than 1.6 mm. The developed tool provides us with a simple, robust, and objective way to probe and monitor the geometric status of an imaging system in a fully automatic process and facilitate routine QA workflow in a clinic.

View details for DOI 10.1118/1.2885719

View details for Web of Science ID 000254510700039

View details for PubMedID 18491545

View details for DOI 10.1016/j.laa.2007.06.019

View details for Web of Science ID 000253519800008

Abstract

To develop a regional narrow-band algorithm to auto-propagate the contour surface of a region of interest (ROI) from one phase to other phases of four-dimensional computed tomography (4D-CT).The ROI contours were manually delineated on a selected phase of 4D-CT. A narrow band encompassing the ROI boundary was created on the image and used as a compact representation of the ROI surface. A BSpline deformable registration was performed to map the band to other phases. A Mattes mutual information was used as the metric function, and the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm was used to optimize the function. After registration the deformation field was extracted and used to transform the manual contours to other phases. Bidirectional contour mapping was introduced to evaluate the proposed technique. The new algorithm was tested on synthetic images and applied to 4D-CT images of 4 thoracic patients and a head-and-neck Cone-beam CT case.Application of the algorithm to synthetic images and Cone-beam CT images indicates that an accuracy of 1.0 mm is achievable and that 4D-CT images show a spatial accuracy better than 1.5 mm for ROI mappings between adjacent phases, and 3 mm in opposite-phase mapping. Compared with whole image-based calculations, the computation was an order of magnitude more efficient, in addition to the much-reduced computer memory consumption.A narrow-band model is an efficient way for contour mapping and should find widespread application in future 4D treatment planning.

View details for DOI 10.1016/j.ijrobp.2007.09.057

View details for Web of Science ID 000252521700038

View details for PubMedID 18207035

Abstract

Head-and-neck (HN) cone-beam computed tomography (CBCT) can be exploited to probe the IMRT dose delivered to a patient taking into account the interfraction anatomic variation and any potential inaccuracy in the IMRT delivery. The aim of this work is to reconstruct the intensity-modulated radiation therapy dose delivered to an HN patient using the CBCT and multileaf collimator (MLC) log-files.A cylindrical CT phantom was used for calibrating the electron density and validating the procedures of the dose reconstruction. Five HN patients were chosen, and for each patient, CBCTs were performed on three separate fractions spaced every 2 weeks starting from the first fraction. The respective MLC log-files were retrieved and converted into fluence maps. The dose was then reconstructed on the corresponding CBCT with the regenerated fluence maps. The reconstructed dose distribution, dosimetric endpoints, and DVHs were compared with that of the treatment plan.Phantom study showed that HN CBCT can be directly used for dose reconstruction. For most treatment sessions, the CBCT-based dose reconstructions yielded DVHs of the targets close (within 3%) to that of the original treatment plans. However, dosimetric changes (within 10%) due to anatomic variations caused by setup inaccuracy, organ deformation, tumour shrinkage, or weight loss (or a combination of these) were observed for the critical organs.The methodology we established affords an objective dosimetric basis for the clinical decision on whether a replanning is necessary during the course of treatment and provides a valuable platform for adaptive therapy in future.

View details for DOI 10.1016/j.ijrobp.2007.09.054

View details for Web of Science ID 000252521700042

View details for PubMedID 18207036

Abstract

The purpose of this work is to relate the gating window and displacement of a moving tumor target and develop a systematic method to individualize the gating window for respiration-gated radiation therapy (RT). As the relationship between patient anatomy and respiration phase is contained in 4D images, we aim to quantify this information and utilize the data to guide gated treatment planning. After 4D image acquisition, the target and organs at risk were delineated manually on the selected gating phase. The contours were propagated automatically onto every phase-specific image set using a control volume-based contour mapping technique. The mean and maximum distances between the contours in the gating phase and each of other phases were evaluated in three dimensions. The gating window was determined in such a way that the residual movement of the target within the window is smaller or equal to the patient's setup error. The proposed method was applied to plan the gated treatments of 12 lung cancer patients. As a result of this work, a method to calculate patient-specific gating windows has been developed. The general reference drawn from this study is that, with the aide of 4D images and automated 4D contour propagation, it is feasible to individualize the gating widow selection. As compared with the current practice, the proposed technique has a potential to eliminate the guesswork involved in choosing a gating window and avoid dosimetric error in planning gated RT. In conclusion, individualization of gating windows reduces the subjectivity in respiration-gated RT and improves the treatment of moving targets.

View details for DOI 10.1088/0031-9155/53/1/011

View details for Web of Science ID 000252792400011

View details for PubMedID 18182694

Abstract

Recent advances in radiation delivery techniques, such as intensity-modulated radiation therapy, provide unprecedented ability to exquisitely control three-dimensional dose distribution. Development of on-board imaging and other image-guidance methods significantly improved our ability to better target a radiation beam to the tumor volume. However, in reality, accurate definition of the location and boundary of the tumor target is still problematic. Biologic and physiologic imaging promises to solve the problem in a fundamental way and has a more and more important role in patient staging, treatment planning, and therapeutic assessment in radiation therapy clinics. The last decade witnessed a dramatic increase in the use of positron emission tomography and computed tomography in radiotherapy practice. To ensure safe and effective use of nuclide imaging, a rigorous quality assurance (QA) protocol of the imaging tools and integration of the imaging data must be in place. The application of nuclide imaging in radiation oncology occurs at different levels of sophistication. Quantitative use of the imaging data in treatment planning through image registration and standardized uptake value calculation is often involved. Thus, QA should not be limited to the performance of the scanner, but should also include the process of implementing image data in treatment planning, such as data transfer, image registration, and quantitation of data for delineation of tumors and sensitive structures. This presentation discusses various aspects of nuclide imaging as applied to radiotherapy and describes the QA procedures necessary for the success of biologic image-guided radiation therapy.

View details for DOI 10.1016/j.ijrobp.2007.05.091

View details for Web of Science ID 000255154300008

View details for PubMedID 18406935

View details for PubMedID 18196781

Abstract

The purpose of this work is to develop a novel strategy to automatically map organ contours from one phase of respiration to all other phases on a four-dimensional computed tomography (4D CT). A region of interest (ROI) was manually delineated by a physician on one phase specific image set of a 4D CT. A number of cubic control volumes of the size of approximately 1 cm were automatically placed along the contours. The control volumes were then collectively mapped to the next phase using a rigid transformation. To accommodate organ deformation, a model-based adaptation of the control volume positions was followed after the rigid mapping procedure. This further adjustment of control volume positions was performed by minimizing an energy function which balances the tendency for the control volumes to move to their correspondences with the desire to maintain similar image features and shape integrity of the contour. The mapped ROI surface was then constructed based on the central positions of the control volumes using a triangulated surface construction technique. The proposed technique was assessed using a digital phantom and 4D CT images of three lung patients. Our digital phantom study data indicated that a spatial accuracy better than 2.5 mm is achievable using the proposed technique. The patient study showed a similar level of accuracy. In addition, the computational speed of our algorithm was significantly improved as compared with a conventional deformable registration-based contour mapping technique. The robustness and accuracy of this approach make it a valuable tool for the efficient use of the available spatial-tempo information for 4D simulation and treatment.

View details for DOI 10.1118/1.2780105

View details for Web of Science ID 000250330100035

View details for PubMedID 17985648

Abstract

Due to the complicated technical nature of gated radiation therapy, electronic and mechanical limitations may affect the precision of delivery. The purpose of this study is to investigate the geometric and dosimetric accuracies of gated step-and-shoot intensity modulated radiation treatments (SS-IMRT). Unique segmental MLC plans are designed, which allow quantitative testing of the gating process. Both ungated and gated deliveries are investigated for different dose sizes, dose rates, and gating window times using a commercial treatment system (Varian Trilogy) together with a respiratory gating system [Varian Real-Time Position Management system]. Radiographic film measurements are used to study the geometric accuracy, where it is found that with both ungated and gated SS-IMRT deliveries the MLC leaf divergence away from planned is less than or equal to the MLC specified leaf tolerance value for all leafs (leaf tolerance being settable from 0.5-5 mm). Nevertheless, due to the MLC controller design, failure to define a specific leaf tolerance value suitable to the SS-IMRT plan can lead to undesired geometric effects, such as leaf motion of up to the maximum 5 mm leaf tolerance value occurring after the beam is turned on. In this case, gating may be advantageous over the ungated case, as it allows more time for the MLC to reach the intended leaf configuration. The dosimetric precision of gated SS-IMRT is investigated using ionization chamber methods. Compared with the ungated case, it is found that gating generally leads to increased dosimetric errors due to the interruption of the "overshoot phenomena." With gating the average timing deviation for intermediate segments is found to be 27 ms, compared to 18 ms for the ungated case. For a plan delivered at 600 MU/min this would correspond to an average segment dose error of approximately 0.27 MU and approximately 0.18 MU for gated and ungated deliveries, respectively. The maximum dosimetric errors for individual intermediate segments are found to deviate by up to approximately 0.64 MU from their planned value when delivered at 600 MU/min using gating, this compares to only approximately 0.32 MU for the ungated case.

View details for DOI 10.1118/1.2776671

View details for Web of Science ID 000250330100028

View details for PubMedID 17985641

Abstract

It is arguable that the imaging and delivery hardware necessary for delivering real-time adaptive image-guided radiotherapy is available on high-end linear accelerators. Robust and computationally efficient software is the limiting factor in achieving highly accurate and precise radiotherapy to the constantly changing anatomy of a cancer patient. The limitations are not caused by the availability of algorithms but rather issues of reliability, integration, and calculation time. However, each of the software components is an active area of research and development at academic and commercial centers. This article describes the software solutions in 4 broad areas: deformable image registration, adaptive replanning, real-time image guidance, and dose calculation and accumulation. Given the pace of technological advancement, the integration of these software solutions to develop real-time adaptive image-guided radiotherapy and the associated challenges they bring will be implemented to varying degrees by all major manufacturers over the coming years.

View details for DOI 10.1016/j.semradonc.2007.07.004

View details for Web of Science ID 000250060100002

View details for PubMedID 17903702

Abstract

Four-dimensional (4D) cone-beam CT (CBCT) is commonly obtained by respiratory phase binning of the projections, followed by independent reconstructions of the rebinned data in each phase bin. Due to the significantly reduced number of projections per reconstruction, the quality of the 4DCBCT images is often degraded by view-aliasing artifacts easily seen in the axial view. Acquisitions using multiple gantry rotations or slow gantry rotation can increase the number of projections and substantially improve the 4D images. However, the extra cost of the scan time may set fundamental limits to their applications in clinics. Improving the trade-off between image quality and scan time is the key to making 4D onboard imaging practical and more useful. In this article, we present a novel technique toward high-quality 4DCBCT imaging without prolonging the acquisition time, referred to as the "enhanced 4DCBCT". The method correlates the data in different phase bins and integrates the internal motion into the 4DCBCT image formulation. Several strategies of the motion derivation are discussed, and the resultant images are assessed with numerical simulations as well as a clinical case.

View details for DOI 10.1118/1.2767144

View details for Web of Science ID 000249547200031

View details for PubMedID 17926972

Abstract

Object displacement in a CT scan is generally reflected in CT projection data or sinogram. In this work, the direct relationship between object motion and the change of CT projection data (sinogram) is investigated and this knowledge is applied to create a novel algorithm for sinogram registration. Calculated and experimental results demonstrate that the registration technique works well for registering rigid 2D or 3D motion in parallel and fan beam samplings. Problem and solution for 3D sinogram-based registration of metallic fiducials are also addressed. Since the motion is registered before image reconstruction, the presented algorithm is particularly useful when registering images with metal or truncation artifacts. In addition, this algorithm is valuable for dealing with situations where only limited projection data are available, making it appealing for various applications in image guided radiation therapy.

View details for DOI 10.1118/1.2767402

View details for Web of Science ID 000249547200022

View details for PubMedID 17926963

Abstract

While ART has been studied for years, the specific quantitative implementation details have not. In order for this new scheme of radiation therapy (RT) to reach its potential, an effective ART treatment planning strategy capable of taking into account the dose delivery history and the patient's on-treatment geometric model must be in place. This paper performs a theoretical study of dynamic closed-loop control algorithms for ART and compares their utility with data from phantom and clinical cases. We developed two classes of algorithms: those Adapting to Changing Geometry and those Adapting to Geometry and Delivered Dose. The former class takes into account organ deformations found just before treatment. The latter class optimizes the dose distribution accumulated over the entire course of treatment by adapting at each fraction, not only to the information just before treatment about organ deformations but also to the dose delivery history. We showcase two algorithms in the class of those Adapting to Geometry and Delivered Dose. A comparison of the approaches indicates that certain closed-loop ART algorithms may significantly improve the current practice. We anticipate that improvements in imaging, dose verification and reporting will further increase the importance of adaptive algorithms.

View details for DOI 10.1088/0031-9155/52/14/008

View details for Web of Science ID 000247400000008

View details for PubMedID 17664599

Abstract

A hypofractionation treatment protocol for prostate cancer was initiated in our department in December 2003. The treatment regimen consists of a total dose of 36.25 Gy delivered at 7.25 Gy per fraction over 10 days. We discuss the rationale for such a prostate hypofractionation protocol and the need for frequent prostate imaging during treatment. The CyberKnife (Accuray Inc., Sunnyvale, CA), a linear accelerator mounted on a robotic arm, is currently being used as the radiation delivery device for this protocol, due to its incorporation of near real-time kV imaging of the prostate via 3 gold fiducial seeds. Recently introduced conventional linac kV imaging with intensity modulated planning and delivery may add a new option for these hypofractionated treatments. The purpose of this work is to investigate the use of intensity modulated radiotherapy (IMRT) and the Varian Trilogy Accelerator with on-board kV imaging (Varian Medical Systems Inc., Palo Alto, CA) for treatment of our hypofractionated prostate patients. The dose-volume histograms and dose statistics of 2 patients previously treated on the CyberKnife were compared to 7-field IMRT plans. A process of acquiring images to observe intrafraction prostate motion was achieved in an average time of about 1 minute and 40 seconds, and IMRT beam delivery takes about 40 seconds per field. A complete 7-field IMRT plan can therefore be imaged and delivered in 10 to 17 minutes. The Varian Trilogy Accelerator with on-board imaging and IMRT is well suited for image-guided hypofractionated prostate treatments. During this study, we have also uncovered opportunities for improvement of the on-board imaging hardware/software implementation that would further enhance performance in this regard.

View details for DOI 10.1016/j.meddos.2007.01.004

View details for Web of Science ID 000246485600002

View details for PubMedID 17472885

Abstract

The goal of this study is to demonstrate the feasibility of chemically modified human adenovirus (Ad) vectors for tumor retargeting.E1- and E3-deleted Ad vectors carrying firefly luciferase reporter gene under cytomegalovirus promoter (AdLuc) was surface-modified with cyclic arginine-glycine-aspartic acid (RGD) peptides through a bifunctional poly(ethyleneglycol) linker (RGD-PEG-AdLuc) for integrin alpha(v)beta(3) specific delivery. The Coxsackie and adenovirus viral receptor (CAR) and integrin alpha(v)beta(3) expression in various tumor cell lines was determined by reverse transcriptase PCR and fluorescence-activated cell sorting. Bioluminescence imaging was performed in vitro and in vivo to evaluate RGD-modified AdLuc infectivity.RGD-PEG-AdLuc abrogated the native CAR tropism and exhibited significantly enhanced transduction efficiency of integrin-positive tumors than AdLuc through intravenous administration.This approach provides a robust platform for site-specific gene delivery and noninvasive monitoring of the transgene delivery efficacy and homing.

View details for DOI 10.1007/s11307-007-0079-2

View details for Web of Science ID 000246175500005

View details for PubMedID 17297551

Abstract

Four-dimensional cone-beam computed tomography (4D-CBCT) imaging is sensitive to parameters such as gantry rotation speed, number of gantry rotations, X-ray pulse rate, and tube current, as well as a patient's breathing pattern. The aim of this study is to optimize the image acquisition on a patient-specific basis while minimizing the scan time and the radiation dose.More than 60 sets of 4D-CBCT images, each with a temporal resolution of 10 phases, were acquired using multiple-gantry rotation and slow-gantry rotation techniques. The image quality was quantified with a relative root mean-square error (RE) and correlated with various acquisition settings; specifically, varying gantry rotation speed, varying both the rotation speed and the number of rotations, and varying both the rotation speed and tube current to keep the radiation exposure constant. These experiments were repeated for three different respiratory periods.With similar radiation dose, 4D-CBCT images acquired with low current and low rotation speed have better quality over images obtained with high current and high rotation speed. In general, a one-rotation low-speed scan is superior to a two-rotation double-speed scan, even though they provide the same number of projections. Furthermore, it is found that the image quality behaves monotonically with the relative speed as defined by the gantry rotation speed and the patient respiratory period.The RE curves established in this work can be used to predict the 4D-CBCT image quality before a scan. This allows the acquisition protocol to be optimized individually to balance the desired quality with the associated scanning time and patient radiation dose.

View details for DOI 10.1016/j.ijrobp.2006.10.024

View details for Web of Science ID 000245021100032

View details for PubMedID 17197125

Abstract

Our aim was to correlate patterns of failure with target volume delineations in patients with head and neck squamous cell carcinoma (HNSCC) treated with intensity-modulated radiation therapy (IMRT) and to report subjective xerostomia outcomes after IMRT as compared with conventional radiation therapy (CRT).Between January 2000 and April 2005, 69 patients with newly diagnosed nonmetastatic HNSCC underwent curative parotid-sparing IMRT at Stanford University. Sites included were oropharynx (n = 39), oral cavity (n = 8), larynx (n = 8), hypopharynx (n = 8), and unknown primary (n = 6). Forty-six patients received definitive IMRT (66 Gy, 2.2 Gy/fraction), and 23 patients received postoperative IMRT (60.2 Gy, 2.15 Gy/fraction). Fifty-one patients also received concomitant chemotherapy. Posttreatment salivary gland function was evaluated by a validated xerostomia questionnaire in 29 IMRT and 75 matched CRT patients >6 months after completing radiation treatment.At a median follow-up of 25 months for living patients (range, 10-60), 7 locoregional failures were observed, 5 in the gross target or high-risk postoperative volume, 1 in the clinical target volume, and 1 at the junction of the IMRT and supraclavicular fields. The 2-year Kaplan-Meier estimates for locoregional control and overall survival were 92% and 74% for definitive IMRT and 87% and 87% for postoperative IMRT patients, respectively. The mean total xerostomia questionnaire score was significantly better for IMRT than for CRT patients (p = .006).The predominant pattern of failure in IMRT-treated patients is in the gross tumor volume. Parotid sparing with IMRT resulted in less subjective xerostomia and may improve quality of life in irradiated HNSCC patients.

View details for DOI 10.1002/hed.20505

View details for Web of Science ID 000244459100002

View details for PubMedID 17111429

Abstract

On-board CBCT images are used to generate patient geometric models to assist patient setup. The image data can also, potentially, be used for dose reconstruction in combination with the fluence maps from treatment plan. Here we evaluate the achievable accuracy in using a kV CBCT for dose calculation. Relative electron density as a function of HU was obtained for both planning CT (pCT) and CBCT using a Catphan-600 calibration phantom. The CBCT calibration stability was monitored weekly for 8 consecutive weeks. A clinical treatment planning system was employed for pCT- and CBCT-based dose calculations and subsequent comparisons. Phantom and patient studies were carried out. In the former study, both Catphan-600 and pelvic phantoms were employed to evaluate the dosimetric performance of the full-fan and half-fan scanning modes. To evaluate the dosimetric influence of motion artefacts commonly seen in CBCT images, the Catphan-600 phantom was scanned with and without cyclic motion using the pCT and CBCT scanners. The doses computed based on the four sets of CT images (pCT and CBCT with/without motion) were compared quantitatively. The patient studies included a lung case and three prostate cases. The lung case was employed to further assess the adverse effect of intra-scan organ motion. Unlike the phantom study, the pCT of a patient is generally acquired at the time of simulation and the anatomy may be different from that of CBCT acquired at the time of treatment delivery because of organ deformation. To tackle the problem, we introduced a set of modified CBCT images (mCBCT) for each patient, which possesses the geometric information of the CBCT but the electronic density distribution mapped from the pCT with the help of a BSpline deformable image registration software. In the patient study, the dose computed with the mCBCT was used as a surrogate of the 'ground truth'. We found that the CBCT electron density calibration curve differs moderately from that of pCT. No significant fluctuation was observed in the calibration over the period of 8 weeks. For the static phantom, the doses computed based on pCT and CBCT agreed to within 1%. A notable difference in CBCT- and pCT-based dose distributions was found for the motion phantom due to the motion artefacts which appeared in the CBCT images (the maximum discrepancy was found to be approximately 3.0% in the high dose region). The motion artefacts-induced dosimetric inaccuracy was also observed in the lung patient study. For the prostate cases, the mCBCT- and CBCT-based dose calculations yielded very close results (<2%). Coupled with the phantom data, it is concluded that the CBCT can be employed directly for dose calculation for a disease site such as the prostate, where there is little motion artefact. In the prostate case study, we also noted a large discrepancy between the original treatment plan and the CBCT (or mCBCT)-based calculation, suggesting the importance of inter-fractional organ movement and the need for adaptive therapy to compensate for the anatomical changes in the future.

View details for DOI 10.1088/0031-9155/52/3/011

View details for Web of Science ID 000243684600011

View details for PubMedID 17228114

Abstract

Up-regulation of integrin alpha(v)beta(3) has been shown to play a key role in tumor angiogenesis and metastasis. In this study, we evaluated the role of integrin alpha(v)beta(3) in breast cancer cell resistance to ionizing irradiation (IR) and tested the anti-tumor efficacy of combining integrin alpha(v) siRNA and IR. Colonogenic survival assay, cell proliferation, apoptosis, and cell cycle analysis were carried out to determine the treatment effect of siRNA, IR, or combination of both on MDA-MB-435 cells (integrin alpha(v)beta(3)-positive). Integrin alpha(v)beta(3)-negative MCF-7 cells exert more radiosensitivity than MDA-MB-435 cells. IR up-regulates integrin alpha(v)beta(3) expression in MDA-MB-435 cells and integrin alpha(v) siRNA can effectively reduce both alpha(v) and alpha(v)beta(3) integrin expression, leading to increased radiosensitivity. Integrin alpha(v) siRNA also promotes IR-induced apoptosis and enhances IR-induced G2/M arrest in cell cycle progression. This study, with further optimization, may provide a simple and highly efficient treatment strategy for breast cancer as well as other integrin alpha(v)beta(3)-positive cancer types.

View details for DOI 10.1016/j.bbrc.2006.10.100

View details for Web of Science ID 000242233000025

View details for PubMedID 17087916

Abstract

An X-ray system with a large area detector has high scatter-to-primary ratios (SPRs), which result in severe artifacts in reconstructed computed tomography (CT) images. A scatter correction algorithm is introduced that provides effective scatter correction but does not require additional patient exposure. The key hypothesis of the algorithm is that the high-frequency components of the X-ray spatial distribution do not result in strong high-frequency signals in the scatter. A calibration sheet with a checkerboard pattern of semitransparent blockers (a "primary modulator") is inserted between the X-ray source and the object. The primary distribution is partially modulated by a high-frequency function, while the scatter distribution still has dominant low-frequency components, based on the hypothesis. Filtering and demodulation techniques suffice to extract the low-frequency components of the primary and hence obtain the scatter estimation. The hypothesis was validated using Monte Carlo (MC) simulation, and the algorithm was evaluated by both MC simulations and physical experiments. Reconstructions of a software humanoid phantom suggested system parameters in the physical implementation and showed that the proposed method reduced the relative mean square error of the reconstructed image in the central region of interest from 74.2% to below 1%. In preliminary physical experiments on the standard evaluation phantom, this error was reduced from 31.8% to 2.3%, and it was also demonstrated that the algorithm has no noticeable impact on the resolution of the reconstructed image in spite of the filter-based approach. Although the proposed scatter correction technique was implemented for X-ray CT, it can also be used in other X-ray imaging applications, as long as a primary modulator can be inserted between the X-ray source and the imaged object.

View details for DOI 10.1109/TMI.2006.884636

View details for Web of Science ID 000242650400005

View details for PubMedID 17167993

Abstract

On-board cone-beam computed tomography (CBCT) has recently become available to provide volumetric information of a patient in the treatment position, and holds promises for improved target localization and irradiation dose verification. The design of currently available on-board CBCT, however, is far from optimal. Its quality is adversely influenced by many factors, such as scatter, beam hardening, and intra-scanning organ motion. In this work we quantitatively study the influence of organ motion on CBCT imaging and investigate a strategy to acquire high quality phase-resolved [four-dimensional (4D)] CBCT images based on phase binning of the CBCT projection data. An efficient and robust method for binning CBCT data according to the patient's respiratory phase derived in the projection space was developed. The phase-binned projections were reconstructed using the conventional Feldkamp algorithm to yield 4D CBCT images. Both phantom and patient studies were carried out to validate the technique and to optimize the 4D CBCT data acquisition protocol. Several factors that are important to the clinical implementation of the technique, such as the image quality, scanning time, number of projections, and radiation dose, were analyzed for various scanning schemes. The general references drawn from this study are: (i) reliable phase binning of CBCT projections is accomplishable with the aid of external or internal marker and simple analysis of its trace in the projection space, and (ii) artifact-free 4D CBCT images can be obtained without increasing the patient radiation dose as compared to the current 3D CBCT scan.

View details for DOI 10.1118/1.2349692

View details for Web of Science ID 000241424100024

View details for PubMedID 17089847

Abstract

To evaluate indirect magnetic resonance lymphangiography (MR-LAG) using interstitial injection of conventional gadolinium contrast (gadoteridol and gadopentetate dimeglumine) for delineating the primary lymphatic drainage of head-and-neck sites.We performed head-and-neck MR-LAG in 5 healthy volunteers, with injection of dermal and mucosal sites. We evaluated the safety of the procedure, the patterns of enhancement categorized by injection site and nodal level, the time course of enhancement, the optimal concentration and volume of contrast, and the optimal imaging sequence.The worst side effects of interstitial contrast injection were brief, mild pain and swelling at the injected sites that were self-limited. MR-LAG resulted in consistent visualization of the primary lymphatic drainage pattern specific to each injected site, which was reproducible on repeated examinations. The best enhancement was obtained with injection of small volumes (0.3-0.5 mL) of either agent diluted, imaging within 5-15 min of injection, and a three-dimensional fast spoiled gradient echo sequence with magnetization transfer.We found head-and-neck MR-LAG to be a safe, convenient imaging method that provides functional information about the lymphatic drainage of injected sites. Applied to head-and-neck cancer, it has the potential to identify sites at highest risk of occult metastatic spread for radiotherapy or surgical planning, and possibly to visualize micrometastases.

View details for DOI 10.1016/j.ijrobp.2006.05.045

View details for Web of Science ID 000240699500024

View details for PubMedID 16965993

Abstract

Respiratory motion artifacts in positron emission tomography (PET) imaging can alter lesion intensity profiles, and result in substantially reduced activity and contrast-to-noise ratios (CNRs). We propose a corrective algorithm, coined "retrospective stacking" (RS), to restore image quality without requiring additional scan time. Retrospective stacking uses b-spline deformable image registration to combine amplitude-binned PET data along the entire respiratory cycle into a single respiratory end point. We applied the method to a phantom model consisting of a small, hot vial oscillating within a warm background, as well as to 18FDG-PET images of a pancreatic and a liver patient. Comparisons were made using cross-section visualizations, activity profiles, and CNRs within the region of interest. Retrospective stacking was found to properly restore the lesion location and intensity profile in all cases. In addition, RS provided CNR improvements up to three-fold over gated images, and up to five-fold over ungated data. These phantom and patient studies demonstrate that RS can correct for lesion motion and deformation, while substantially improving tumor visibility and background noise.

View details for DOI 10.1118/1.2207367

View details for Web of Science ID 000239173900035

View details for PubMedID 16898467

Abstract

Radiation therapy has gone through a series of revolutions in the last few decades and it is now possible to produce highly conformal radiation dose distribution by using techniques such as intensity-modulated radiation therapy (IMRT). The improved dose conformity and steep dose gradients have necessitated enhanced patient localization and beam targeting techniques for radiotherapy treatments. Components affecting the reproducibility of target position during and between subsequent fractions of radiation therapy include the displacement of internal organs between fractions and internal organ motion within a fraction. Image-guided radiation therapy (IGRT) uses advanced imaging technology to better define the tumor target and is the key to reducing and ultimately eliminating the uncertainties. The purpose of this article is to summarize recent advancements in IGRT and discussed various practical issues related to the implementation of the new imaging techniques available to radiation oncology community. We introduce various new IGRT concepts and approaches, and hope to provide the reader with a comprehensive understanding of the emerging clinical IGRT technologies. Some important research topics will also be addressed.

View details for DOI 10.1016/j.meddos.2005.12.004

View details for Web of Science ID 000237818000002

View details for PubMedID 16690451

Abstract

Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case.

View details for DOI 10.1118/1.2192581

View details for Web of Science ID 000237673600012

View details for PubMedID 16752564

Abstract

Many image registration algorithms rely on the use of homologous control points on the two input image sets to be registered. In reality, the interactive identification of the control points on both images is tedious, difficult, and often a source of error. We propose a two-step algorithm to automatically identify homologous regions that are used as a priori information during the image registration procedure. First, a number of small control volumes having distinct anatomical features are identified on the model image in a somewhat arbitrary fashion. Instead of attempting to find their correspondences in the reference image through user interaction, in the proposed method, each of the control regions is mapped to the corresponding part of the reference image by using an automated image registration algorithm. A normalized cross-correlation (NCC) function or mutual information was used as the auto-mapping metric and a limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS) was employed to optimize the function to find the optimal mapping. For rigid registration, the transformation parameters of the system are obtained by averaging that derived from the individual control volumes. In our deformable calculation, the mapped control volumes are treated as the nodes or control points with known positions on the two images. If the number of control volumes is not enough to cover the whole image to be registered, additional nodes are placed on the model image and then located on the reference image in a manner similar to the conventional BSpline deformable calculation. For deformable registration, the established correspondence by the auto-mapped control volumes provides valuable guidance for the registration calculation and greatly reduces the dimensionality of the problem. The performance of the two-step registrations was applied to three rigid registration cases (two PET-CT registrations and a brain MRI-CT registration) and one deformable registration of inhale and exhale phases of a lung 4D CT. Algorithm convergence was confirmed by starting the registration calculations from a large number of initial transformation parameters. An accuracy of approximately 2 mm was achieved for both deformable and rigid registration. The proposed image registration method greatly reduces the complexity involved in the determination of homologous control points and allows us to minimize the subjectivity and uncertainty associated with the current manual interactive approach. Patient studies have indicated that the two-step registration technique is fast, reliable, and provides a valuable tool to facilitate both rigid and nonrigid image registrations.

View details for DOI 10.1118/1.2184440

View details for Web of Science ID 000237038300040

View details for PubMedID 16696494

Abstract

A multiscale image registration technique is presented for the registration of medical images that contain significant levels of noise. An overview of the medical image registration problem is presented, and various registration techniques are discussed. Experiments using mean squares, normalized correlation, and mutual information optimal linear registration are presented that determine the noise levels at which registration using these techniques fails. Further experiments in which classical denoising algorithms are applied prior to registration are presented, and it is shown that registration fails in this case for significantly high levels of noise, as well. The hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese [20] is presented, and accurate registration of noisy images is achieved by obtaining a hierarchical multiscale decomposition of the images and registering the resulting components. This approach enables successful registration of images that contain noise levels well beyond the level at which ordinary optimal linear registration fails. Image registration experiments demonstrate the accuracy and efficiency of the multiscale registration technique, and for all noise levels, the multiscale technique is as accurate as or more accurate than ordinary registration techniques.

View details for Web of Science ID 000235978000008

View details for PubMedID 20361831

Abstract

To develop a method for deriving the phase-binned four-dimensional computed tomography (4D CT) image sets through interpolation of the images acquired at some known phases.Four-dimensional computed tomography data sets for 3 patients were acquired. For each patient, the correlation between inhale and exhale phases was studied and quantified using a BSpline deformable model. Images at an arbitrary phase were deduced by an interpolation of the deformation coefficients. The accuracy of the proposed scheme was assessed by comparing marker trajectories and by checkerboard/difference display of the interpolated and acquired images.The images at intermediate phases could be derived by an interpolation of the deformation field. An analysis of marker movements indicated that 3 mm accuracy is achievable by the interpolation. The subtraction of image analysis indicated a similar level of success. The proposed technique was useful also for automatically mapping the organ contours in a known phase to other phases, and for designing patient-specific margins in the presence of respiratory motion. Finally, the technique led to a 90% reduction in the acquired data, because in the BSpline model, a lattice of only a few thousand values is sufficient to describe a CT data set of 25 million pixels.Organ deformation can be well modeled by using a BSpline model. The proposed technique may offer useful means for radiation dose reduction, binning artifacts removal, and disk storage improvement in 4D imaging.

View details for DOI 10.1016/j.ijrobp.2005.11.018

View details for Web of Science ID 000236477200032

View details for PubMedID 16503382

Abstract

The gastrin-releasing peptide receptor (GRPR) is found to be overexpressed in a variety of human tumors. The aim of this study was to develop 18F-labeled bombesin analogs for PET of GRPR expression in prostate cancer xenograft models.[Lys3]Bombesin ([Lys3]BBN) and aminocaproic acid-bombesin(7-14) (Aca-BBN(7-14)) were labeled with 18F by coupling the Lys3 amino group and Aca amino group, respectively, with N-succinimidyl-4-18F-fluorobenzoate (18F-SFB) under slightly basic condition (pH 8.5). Receptor-binding affinity of FB-[Lys3]BBN and FB-Aca-BBN(7-14) was tested in PC-3 human prostate carcinoma cells. Internalization and efflux of both radiotracers were also evaluated. Tumor-targeting efficacy and in vivo kinetics of both radiotracers were examined in male athymic nude mice bearing subcutaneous PC-3 tumors by means of biodistribution and dynamic microPET imaging studies. 18F-FB-[Lys3]BBN was also tested for orthotopic PC-3 tumor delineation. Metabolic stability of 18F-FB-[Lys3]BBN was determined in mouse blood, urine, liver, kidney, and tumor homogenates at 1 h after injection.The typical decay-corrected radiochemical yield was about 30%-40% for both tracers, with a total reaction time of 150 +/- 20 min starting from 18F-. 18F-FB-[Lys3]BBN had moderate stability in the blood and PC-3 tumor, whereas it was degraded rapidly in the liver, kidneys, and urine. Both radiotracers exhibited rapid blood clearance. 18F-FB-[Lys3]BBN had predominant renal excretion. 18F-FB-Aca-BBN(7-14) exhibited both hepatobiliary and renal clearance. Dynamic microPET imaging studies revealed that the PC-3 tumor uptake of 18F-FB-[Lys3]BBN in PC-3 tumor was much higher than that of 18F-FB-Aca-BBN(7-14) at all time points examined (P < 0.01). The receptor specificity of 18F-FB-[Lys3]BBN in vivo was demonstrated by effective blocking of tumor uptake in the presence of [Tyr4]BBN. No obvious blockade was found in PC-3 tumor when 18F-FB-Aca-BBN(7-14) was used as radiotracer under the same condition. 18F-FB-[Lys3]BBN was also able to visualize orthotopic PC-3 tumor at early time points after tracer administration, at which time minimal urinary bladder activity was present to interfere with the receptor-mediated tumor uptake.This study demonstrates that 18F-FB-[Lys3]BBN and PET are suitable for detecting GRPR-positive prostate cancer in vivo.

View details for Web of Science ID 000249695800020

View details for PubMedID 16513619

Abstract

On-board imager (OBI) based cone-beam computed tomography (CBCT) has become available in radiotherapy clinics to accurately identify the target in the treatment position. However, due to the relatively slow gantry rotation (typically about 60 s for a full 360 degrees scan) in acquiring the CBCT projection data, the patient's respiratory motion causes serious problems such as blurring, doubling, streaking and distortion in the reconstructed images, which heavily degrade the image quality and the target localization. In this work, we present a motion compensation method for slow-rotating CBCT scans by incorporating into image reconstruction a patient-specific motion model, which is derived from previously obtained four-dimensional (4D) treatment planning CT images of the same patient via deformable registration. The registration of the 4D CT phases results in transformations representing a temporal sequence of three-dimensional (3D) deformation fields, or in other words, a 4D model of organ motion. The algorithm was developed heuristically in two-dimensional (2D) parallel-beam geometry and extended to 3D cone-beam geometry. By simulations with digital phantoms capable of translational motion and other complex motion, we demonstrated that the algorithm can reduce the motion artefacts locally, and restore the tumour size and shape, which may thereby improve the accuracy of target localization and patient positioning when CBCT is used as the treatment guidance.

View details for DOI 10.1088/0031-9155/51/2/005

View details for Web of Science ID 000235041000005

View details for PubMedID 16394337

Abstract

Four-dimensional (4D) CT is useful in many clinical situations, where detailed abdominal and thoracic imaging is needed over the course of the respiratory cycle. However, it usually delivers a larger radiation dose than the standard three-dimensional (3D) CT, since multiple scans at each couch position are required in order to provide the temporal information. Our purpose in this work is to develop a method to perform 4D CT scans at relatively low current, hence reducing the radiation exposure of the patients. To deal with the increased statistical noise caused by the low current, we proposed a novel 4D penalized weighted least square (4D-PWLS) smoothing method, which can incorporate both spatial and phase information. The 4D images at different phases were registered to the same phase via a deformable model, thereby, a regularization term combining temporal and spatial neighbors can be designed for the 4D-PWLS objective function. The proposed method was tested with phantom experiments and a patient study, and superior noise suppression and resolution preservation were observed. A quantitative evaluation of the benefit of the proposed method to 4D radiotherapy and 4D PET/CT imaging are under investigation.

View details for DOI 10.1118/1.2122567

View details for Web of Science ID 000234643700016

View details for PubMedID 16475764

Abstract

The "four Rs" of radiobiology play an important role in the design of radiation therapy treatment protocol. The purpose of this work is to explore their influence on external beam radiotherapy for fast and slowly proliferating tumors and develop an optimization framework for tumor-biology specific dose-time-fractionation scheme. The linear quadratic model is used to describe radiation response of tumor, in which the time dependence of sublethal damage repair and the redistribution and reoxygenation effects are included. The optimum radiotherapeutic strategy is defined as the treatment scheme that maximizes tumor biologically effective dose (BED) while keeping normal tissue BED constant. The influence of different model parameters on total dose, overall treatment time, fraction size, and intervals is also studied. The results showed that, for fast proliferating tumors, the optimum overall time is similar to the assumed kickoff time T(k) and almost independent of interval patterns. Significant increase in tumor control can be achieved using accelerated schemes for the tumors with doubling time smaller than 3 days, but little is gained for those with doubling time greater than 5 days. The incomplete repair of normal tissues between two consecutive fractions in standard fractionation has almost no influence on the fractional doses, even for the hyperfractionation with an interval time of 8 h. However, when the resensitization effect is included, the fractional doses at the beginning and end of each irradiated week become obviously higher than others in the optimum scheme and the hyperfractionation scheme has little advantage over the standard or hypofractionation one. For slowly proliferating tumors, provided that the alpha/beta ratio of the tumor is comparable to that of the normal tissues, a hypofractionation is more favorable. The overall treatment time should be larger than a minimum, which is predominantly determined by the resensitization time. The proposed technique provides a useful tool to systematically optimize radiotherapy for fast and slow proliferating tumors and sheds important insight into the complex problem of dose-time fractionation.

View details for DOI 10.1118/1.2126167

View details for Web of Science ID 000234643700018

View details for PubMedID 16475766

Abstract

Beam orientation optimization in intensity-modulated radiation therapy (IMRT) is computationally intensive, and various single beam ranking techniques have been proposed to reduce the search space. Up to this point, none of the existing ranking techniques considers the clinically important dose-volume effects of the involved structures, which may lead to clinically irrelevant angular ranking. The purpose of this work is to develop a clinically sensible angular ranking model with incorporation of dose-volume effects and to show its utility for IMRT beam placement.The general consideration in constructing this angular ranking function is that a beamlet/beam is preferable if it can deliver a higher dose to the target without exceeding the tolerance of the sensitive structures located on the path of the beamlet/beam. In the previously proposed dose-based approach, the beamlets are treated independently and, to compute the maximally deliverable dose to the target volume, the intensity of each beamlet is pushed to its maximum intensity without considering the values of other beamlets. When volumetric structures are involved, the complication arises from the fact that there are numerous dose distributions corresponding to the same dose-volume tolerance. In this situation, the beamlets are not independent and an optimization algorithm is required to find the intensity profile that delivers the maximum target dose while satisfying the volumetric constraints. In this study, the behavior of a volumetric organ was modeled by using the equivalent uniform dose (EUD). A constrained sequential quadratic programming algorithm (CFSQP) was used to find the beam profile that delivers the maximum dose to the target volume without violating the EUD constraint or constraints. To assess the utility of the proposed technique, we planned a head-and-neck and abdominal case with and without the guidance of the angular ranking information. The qualities of the two types of IMRT plans were compared quantitatively.An effective angular ranking model with consideration of volumetric effect has been developed. It is shown that the previously reported dose-based angular ranking represents a special case of the general formalism proposed here. Application of the technique to a abdominal and a head-and-neck IMRT case indicated that the proposed technique is capable of producing clinically sensible angular ranking. In both cases, we found that the IMRT plans obtained under the guidance of EUD-based angular ranking were improved in comparison with that obtained using the conventional uniformly spaced beams.The EUD-based function is a general approach for angular ranking and allows us to identify the potentially good and bad angles for clinically complicated cases. The ranking can be used either as a guidance to facilitate the manual beam placement or as prior information to speed up the computer search for the optimal beam configuration. Thus the proposed technique should have positive clinical impact in facilitating the IMRT planning process.

View details for DOI 10.1016/j.ijrobp.2005.06.008

View details for Web of Science ID 000232083700033

View details for PubMedID 16168850

Abstract

It is well known that the spatial biology distribution (e.g., clonogen density, radiosensitivity, tumor proliferation rate, functional importance) in most tumors and sensitive structures is heterogeneous. Recent progress in biological imaging is making the mapping of this distribution increasingly possible. The purpose of this work is to establish a theoretical framework to quantitatively incorporate the spatial biology data into intensity modulated radiation therapy (IMRT) inverse planning. In order to implement this, we first derive a general formula for determining the desired dose to each tumor voxel for a known biology distribution of the tumor based on a linear-quadratic model. The desired target dose distribution is then used as the prescription for inverse planning. An objective function with the voxel-dependent prescription is constructed with incorporation of the nonuniform dose prescription. The functional unit density distribution in a sensitive structure is also considered phenomenologically when constructing the objective function. Two cases with different hypothetical biology distributions are used to illustrate the new inverse planning formalism. For comparison, treatments with a few uniform dose prescriptions and a simultaneous integrated boost are also planned. The biological indices, tumor control probability (TCP) and normal tissue complication probability (NTCP), are calculated for both types of plans and the superiority of the proposed technique over the conventional dose escalation scheme is demonstrated. Our calculations revealed that it is technically feasible to produce deliberately nonuniform dose distributions with consideration of biological information. Compared with the conventional dose escalation schemes, the new technique is capable of generating biologically conformal IMRT plans that significantly improve the TCP while reducing or keeping the NTCPs at their current levels. Biologically conformal radiation therapy (BCRT) incorporates patient-specific biological information and provides an outstanding opportunity for us to truly individualize radiation treatment. The proposed formalism lays a technical foundation for BCRT and allows us to maximally exploit the technical capacity of IMRT to more intelligently escalate the radiation dose.

View details for Web of Science ID 000229908600004

View details for PubMedID 16013703

Abstract

Endorectal (ER) coil-based magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) is often used to obtain anatomic and metabolic images of the prostate and to accurately identify and assess the intraprostatic lesions. Recent advancements in high-field (3 Tesla or above) MR techniques affords significantly enhanced signal-to-noise ratio and makes it possible to obtain high-quality MRI data. In reality, the use of rigid or inflatable endorectal probes deforms the shape of the prostate gland, and the images so obtained are not directly usable in radiation therapy planning. The purpose of this work is to apply a narrow band deformable registration model to faithfully map the acquired information from the ER-based MRI/MRSI onto treatment planning computed tomography (CT) images.A narrow band registration, which is a hybrid method combining the advantages of pixel-based and distance-based registration techniques, was used to directly register ER-based MRI/MRSI with CT. The normalized correlation between the two input images for registration was used as the metric, and the calculation was restricted to those points contained in the narrow bands around the user-delineated structures. The narrow band method is inherently efficient because of the use of a priori information of the meaningful contour data. The registration was performed in two steps. First, the two input images were grossly aligned using a rigid registration. The detailed mapping was then modeled by free form deformations based on B-spline. The limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS), which is known for its superior performance in dealing with high-dimensionality problems, was implemented to optimize the metric function. The convergence behavior of the algorithm was studied by self-registering an MR image with 100 randomly initiated relative positions. To evaluate the performance of the algorithm, an MR image was intentionally distorted, and an attempt was then made to register the distorted image with the original one. The ability of the algorithm to recover the original image was assessed using a checkerboard graph. The mapping of ER-based MRI onto treatment planning CT images was carried out for two clinical cases, and the performance of the registration was evaluated.A narrow band deformable image registration algorithm has been implemented for direct registration of ER-based prostate MRI/MRSI and CT studies. The convergence of the algorithm was confirmed by starting the registration experiment from more than 100 different initial conditions. It was shown that the technique can restore an MR image from intentionally introduced deformations with an accuracy of approximately 2 mm. Application of the technique to two clinical prostate MRI/CT registrations indicated that it is capable of producing clinically sensible mapping. The whole registration procedure for a complete three-dimensional study (containing 256 x 256 x 64 voxels) took less than 15 min on a standard personal computer, and the convergence was usually achieved in fewer than 100 iterations.A deformable image registration procedure suitable for mapping ER-based MRI data onto planning CT images was presented. Both hypothetical tests and patient studies have indicated that the registration is reliable and provides a valuable tool to integrate the ER-based MRI/MRSI information to guide prostate radiation therapy treatment.

View details for DOI 10.1016/j.ijrobp.2005.02.001

View details for Web of Science ID 000229082500038

View details for PubMedID 15890605

Abstract

Endoscopy is a standard procedure for identifying tumors in patients suspected of having gastrointestinal (G.I.) cancer. The early detection of G.I. neoplasms during endoscopy is currently made by a subjective visual inspection that relies to a high degree on the experience of the examiner. This process can be difficult and unreliable, as tumor lesions may be visually indistinguishable from benign inflammatory conditions and the surrounding mucosa. In this study, we evaluated the ability of local ischemia detection using visible light spectroscopy (VLS) to differentiate neoplastic from normal tissue based on capillary tissue oxygenation during endoscopy. Real-time data were collected (i) from human subjects (N = 34) monitored at various sites during endoscopy (enteric mucosa, malignant, and abnormal tissue such as polyps) and (ii) murine animal subjects with human tumor xenografts. Tissue oximetry in human subjects during endoscopy revealed a tissue oxygenation (StO2%, mean +/- SD) of 46 +/- 22% in tumors, which was significantly lower than for normal mucosal oxygenation (72 +/- 4%; P < or = 0.0001). No difference in tissue oxygenation was observed between normal and non-tumor abnormal tissues (P = N.S.). Similarly, VLS tissue oximetry for murine tumors revealed a mean local tumor oxygenation of 45% in LNCaP, 50% in M21, and 24% in SCCVII tumors, all significantly lower than normal muscle tissue (74%, P < 0.001). These results were further substantiated by positive controls, where a rapid real-time drop in tumor oxygenation was measured during local ischemia induced by clamping or epinephrine. We conclude that VLS tissue oximetry can distinguish neoplastic tissue from normal tissue with a high specificity (though a low sensitivity), potentially aiding the endoscopic detection of gastrointestinal tumors.

View details for Web of Science ID 000229787600001

View details for PubMedID 15896077

View details for PubMedID 16013699

Abstract

In vivo magnetic resonance spectroscopic imaging of the prostate using single-voxel and multivoxel two-dimensional (2D) J-resolved sequences is investigated at a main magnetic field strength of 3 T. Citrate, an important metabolite often used to aid the detection of prostate cancer in magnetic resonance spectroscopic exams, can be reliably detected along with the other metabolites using this method. We show simulations and measurements of the citrate metabolite using 2D J-resolved spectroscopy to characterize the spectral pattern. Furthermore, using spiral readout gradients, the single-voxel 2D J-resolved method is extended to provide the spatial distribution information as well all within a reasonable scan time (17 min). Phantom and in vivo data are presented to illustrate the multivoxel 2D J-resolved spiral chemical shift imaging sequence.

View details for DOI 10.1002/mrm.20452

View details for Web of Science ID 000228796900026

View details for PubMedID 15844143

Abstract

In inverse planning, the likelihood for the points in a target or sensitive structure to meet their dosimetric goals is generally heterogeneous and represents the a priori knowledge of the system once the patient and beam configuration are chosen. Because of this intrinsic heterogeneity, in some extreme cases, a region in a target may never meet the prescribed dose without seriously deteriorating the doses in other areas. Conversely, the prescription in a region may be easily met without violating the tolerance of any sensitive structure. In this work, we introduce the concept of dosimetric capability to quantify the a priori information and develop a strategy to integrate the data into the inverse planning process. An iterative algorithm is implemented to numerically compute the capability distribution on a case specific basis. A method of incorporating the capability data into inverse planning is developed by heuristically modulating the importance of the individual voxels according to the a priori capability distribution. The formalism is applied to a few specific examples to illustrate the technical details of the new inverse planning technique. Our study indicates that the dosimetric capability is a useful concept to better understand the complex inverse planning problem and an effective use of the information allows us to construct a clinically more meaningful objective function to improve IMRT dose optimization techniques.

View details for DOI 10.1088/0031-9155/50/7/010

View details for Web of Science ID 000228918500010

View details for PubMedID 15798337

Abstract

Single-walled carbon nanotubes (SWNTs) are a new class of highly promising nanomaterials for future nano-electronics. Here, we present an initial investigation of the feasibility of using SWNT field effect transistors (SWNT-FETs) formed on silicon-oxide substrates and suspended FETs for radiation dosimetry applications. Electrical measurements and atomic force microscopy (AFM) revealed the intactness of SWNT-FET devices after exposure to over 1 Gy of 6 MV therapeutic x-rays. The sensitivity of SWNT-FET devices to x-ray irradiation is elucidated by real-time dose monitoring experiments and accumulated dose reading based on threshold voltage shift. SWNT-FET devices exhibit sensitivities to x-rays that are at least comparable to or orders of magnitude higher than commercial MOSFET (metal-oxide semiconductor field effect transistor) dosimeters and could find applications as miniature dosimeters for microbeam profiling and implantation.

View details for DOI 10.1088/0031-9155/50/3/N02

View details for Web of Science ID 000227288400013

View details for PubMedID 15773731

Abstract

Clinical IMRT treatment plans are currently made using dose-based optimization algorithms, which do not consider the nonlinear dose-volume effects for tumours and normal structures. The choice of structure specific importance factors represents an additional degree of freedom of the system and makes rigorous optimization intractable. The purpose of this work is to circumvent the two problems by developing a biologically more sensible yet clinically practical inverse planning framework. To implement this, the dose-volume status of a structure was characterized by using the effective volume in the voxel domain. A new objective function was constructed with the incorporation of the volumetric information of the system so that the figure of merit of a given IMRT plan depends not only on the dose deviation from the desired distribution but also the dose-volume status of the involved organs. The conventional importance factor of an organ was written into a product of two components: (i) a generic importance that parametrizes the relative importance of the organs in the ideal situation when the goals for all the organs are met; (ii) a dose-dependent factor that quantifies our level of clinical/dosimetric satisfaction for a given plan. The generic importance can be determined a priori, and in most circumstances, does not need adjustment, whereas the second one, which is responsible for the intractable behaviour of the trade-off seen in conventional inverse planning, was determined automatically. An inverse planning module based on the proposed formalism was implemented and applied to a prostate case and a head-neck case. A comparison with the conventional inverse planning technique indicated that, for the same target dose coverage, the critical structure sparing was substantially improved for both cases. The incorporation of clinical knowledge allows us to obtain better IMRT plans and makes it possible to auto-select the importance factors, greatly facilitating the inverse planning process. The new formalism proposed also reveals the relationship between different inverse planning schemes and gives important insight into the problem of therapeutic plan optimization. In particular, we show that the EUD-based optimization is a special case of the general inverse planning formalism described in this paper.

View details for DOI 10.1088/0031-9155/49/22/006

View details for Web of Science ID 000225629200006

View details for PubMedID 15609561

Abstract

The endorectal coil is being increasingly used in magnetic resonance imaging (MRI) and MR spectroscopic imaging (MRSI) to obtain anatomic and metabolic images of the prostate with high signal-to-noise ratio (SNR). In practice, however, the use of endorectal probe inevitably distorts the prostate and other soft tissue organs, making the analysis and the use of the acquired image data in treatment planning difficult. The purpose of this work is to develop a deformable image registration algorithm to map the MRI/MRSI information obtained using an endorectal probe onto CT images and to verify the accuracy of the registration by phantom and patient studies. A mapping procedure involved using a thin plate spline (TPS) transformation was implemented to establish voxel-to-voxel correspondence between a reference image and a floating image with deformation. An elastic phantom with a number of implanted fiducial markers was designed for the validation of the quality of the registration. Radiographic images of the phantom were obtained before and after a series of intentionally introduced distortions. After mapping the distorted phantom to the original one, the displacements of the implanted markers were measured with respect to their ideal positions and the mean error was calculated. In patient studies, CT images of three prostate patients were acquired, followed by 3 Tesla (3 T) MR images with a rigid endorectal coil. Registration quality was estimated by the centroid position displacement and image coincidence index (CI). Phantom and patient studies show that TPS-based registration has achieved significantly higher accuracy than the previously reported method based on a rigid-body transformation and scaling. The technique should be useful to map the MR spectroscopic dataset acquired with ER probe onto the treatment planning CT dataset to guide radiotherapy planning.

View details for DOI 10.1118/1.106292

View details for Web of Science ID 000225372300019

View details for PubMedID 15587662

Abstract

IMRT is being increasingly used for treatment of prostate cancer. In practice, however, the beam orientations used for the treatments are still selected empirically, without any guideline. The purpose of this work was to investigate interpatient variation of the optimal beam configuration and to facilitate intensity modulated radiation therapy (IMRT) prostate treatment planning by proposing a set of beam orientation class-solutions for a range of numbers of incident beams. We used fifteen prostate cases to generate the beam orientation class-solutions. For each patient and a given number of incident beams, a multiobjective optimization engine was employed to provide optimal beam directions. For the fifteen cases considered, the gantry angle of any of the optimized plans were all distributed within a certain range The angular distributions of the optimal beams were analyzed and the most selected directions are identified as optimal directions. The optimal directions for all patients are averaged to obtain the class-solution. The class-solution gantry angles for prostate IMRT were found to be: three beams (0 degrees, 120 degrees, 240 degrees), five beams (35 degrees, 110 degrees, 180 degrees, 250 degrees, 325 degrees), six beams (0 degrees, 60 degrees, 120 degrees, 180 degrees, 240 degrees, 300 degrees), seven beams (25 degrees, 75 degrees, 130 degrees, 180 degrees, 230 degrees, 285 degrees, 335 degrees), eight beams (20 degrees, 70 degrees, 110 degrees, 150 degrees, 200 degrees, 250 degrees, 290 degrees, 340 degrees), and nine beams (20 degrees, 60 degrees, 100 degrees, 140 degrees, 180 degrees, 220 degrees, 260 degrees, 300 degrees, 340 degrees). The level of validity of the class-solutions was tested using an additional clinical prostate case by comparing with the individually optimized beam configurations. The difference between the plans obtained with class-solutions and patient-specific optimizations was found to be clinically insignificant.

View details for DOI 10.1118/1.1797571

View details for Web of Science ID 000224743200021

View details for PubMedID 15543796

Abstract

In current inverse planning algorithms it is common to treat all voxels within a target or sensitive structure equally and use structure specific prescriptions and weighting factors as system parameters. In reality, the voxels within a structure are not identical in complying with their dosimetric goals and there exists strong intrastructural competition. Inverse planning objective function should not only balance the competing objectives of different structures but also that of the individual voxels in various structures. In this work we propose to model the intrastructural tradeoff through the modulation of voxel-dependent importance factors and deal with the challenging problem of how to obtain a sensible set of importance factors with a manageable amount of computing. Instead of letting the values of voxel-dependent importance to vary freely during the search process, an adaptive algorithm, in which the importance factors were tied to the local radiation doses through a heuristically constructed relation, was developed. It is shown that the approach is quite general and the EUD-based optimization is a special case of the proposed framework. The new planning tool was applied to study a hypothetical phantom case and a prostate case. Comparison of the results with that obtained using conventional inverse planning technique with structure specific importance factors indicated that the dose distributions from the conventional inverse planning are at best suboptimal and can be significantly improved with the help of the proposed nonuniform penalty scheme.

View details for DOI 10.1118/1.1799311

View details for Web of Science ID 000224743200017

View details for PubMedID 15543792

Abstract

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment.

View details for DOI 10.1118/1.1785451

View details for Web of Science ID 000224117400041

View details for PubMedID 15487755

Abstract

The success of an IMRT treatment relies on the positioning accuracy of the MLC (multileaf collimator) leaves for both step-and-shoot and dynamic deliveries. In practice, however, there exists no effective and quantitative means for routine MLC QA and this has become one of the bottleneck problems in IMRT implementation. In this work we present an electronic portal image device (EPID) based method for fast and accurate measurement of MLC leaf positions at arbitrary locations within the 40 cm x 40 cm radiation field. The new technique utilizes the fact that the integral signal in a small region of interest (ROI) is a sensitive and reliable indicator of the leaf displacement. In this approach, the integral signal at a ROI was expressed as a weighted sum of the contributions from the displacements of the leaf above the point and the adjacent leaves. The weighting factors or linear coefficients of the system equations were determined by fitting the integral signal data for a group of pre-designed MLC leaf sequences to the known leaf displacements that were intentionally introduced during the creation of the leaf sequences. Once the calibration is done, the system can be used for routine MLC leaf positioning QA to detect possible leaf errors. A series of tests was carried out to examine the functionality and accuracy of the technique. Our results show that the proposed technique is potentially superior to the conventional edge-detecting approach in two aspects: (i) it deals with the problem in a systematic approach and allows us to take into account the influence of the adjacent MLC leaves effectively; and (ii) it may improve the signal-to-noise ratio and is thus capable of quantitatively measuring extremely small leaf positional displacements. Our results indicate that the technique can detect a leaf positional error as small as 0.1 mm at an arbitrary point within the field in the absence of EPID set-up error and 0.3 mm when the uncertainty is considered. Given its simplicity, efficiency and accuracy, we believe that the technique is ideally suitable for routine MLC leaf positioning QA.

View details for DOI 10.1088/0031-9155/49/8/010

View details for Web of Science ID 000221250800010

View details for PubMedID 15152689

Abstract

Spatially resolved metabolite maps, as measured by magnetic resonance spectroscopic imaging (MRSI) methods, are being increasingly used to acquire metabolic information to guide therapy, with metabolite ratio maps perhaps providing the most diagnostic information. We present a quality assurance procedure for MRSI-derived metabolic data acquired ultimately for guiding conformal radiotherapy.An MRSI phantom filled with brain-mimicking solutions was custom-built with an insert holding eight vials containing calibration solutions of precisely varying metabolite concentrations that emulated increasing grade/density of brain tumor. Phantom metabolite ratios calculated from fully relaxed 1D, 2D, and 3D MRS data for each vial were compared with calibrated metabolite ratios acquired at 9.4 T. Additionally, 3D ratio maps were "discretized" to eight pseudoabnormality levels on a slice-by-slice basis and the accuracy of this procedure was verified.Regression analysis revealed expected linear relationships between experimental and calibration metabolite ratios with intercepts close to zero for the three acquisition modes. 1D MRS data agreed most with theoretical considerations (regression coefficient, b = 0.969; intercept 0.008). The 2D (b = 1.049; intercept -0.199) and 3D (correlation coefficient r(2) = 0.9978-0.7336 for five slices) MRSI indicated reduced MRS data quality in regions of degraded B(0) and B(1) homogeneity. Pseudoabnormality levels were found to be consistent with expectations within regions of adequate B(0) homogeneity.This simple phantom-based approach to generate baseline calibration curves for all MRS acquisition modes may be useful to identify temporal deviations from acceptable data quality in a routine clinical environment or for testing new MRS and MRSI acquisition software.

View details for DOI 10.1016/S0630-3016(03)01564-5

View details for Web of Science ID 000186293800031

View details for PubMedID 14575849

Abstract

Independent verification of the MU settings and dose calculation of IMRT treatment plans is an important step in the IMRT quality assurance (QA) procedure. At present, the verification is mainly based on experimental measurements, which are time consuming and labor intensive. Although a few simplified algorithms have recently been proposed for the independent dose (or MU) calculation, head scatter has not been precisely taken into account in all these investigations and the dose validation has mainly been limited to the central axis. In this work we developed an effective computer algorithm for IMRT MU and dose validation. The technique is superior to the currently available computer-based MU check systems in that (1) it takes full consideration of the head scatter and leaf transmission effects; and (2) it allows a precise dose calculation at an arbitrary spatial point instead of merely a point on the central axis. In the algorithm the dose at an arbitrary spatial point is expressed as a summation of the contributions of primary and scatter radiation from all beamlets. Each beamlet is modulated by a dynamic modulation factor (DMF), which is determined by the MLC leaf trajectories, the head scatter, the jaw positions, and the MLC leaf transmission. A three-source model was used to calculate the head scatter distribution for irregular segments shaped by MLC and the scatter dose contributions were computed using a modified Clarkson method. The system reads in MLC leaf sequence files (or RTP files) generated by the Corvus (NOMOS Corporation, Sewickley, PA) inverse planning system and then computes the doses at the desired points. The algorithm was applied to study the dose distributions of several testing intensity modulated fields and two multifield Corvus plans and the results were compared with Corvus plans and experimental measurements. The final dose calculations at most spatial points agreed with the experimental measurements to within 3% for both the specially designed testing fields and the clinical intensity modulated field. Furthermore, excellent agreement (mostly within +/- 3.0%) was also found between our independent calculation and the ion chamber measurements at both central axis and off-axis positions for the multifield Corvus IMRT plans. These results indicate that the approach is robust and valuable for routine clinical IMRT plan validation.

View details for DOI 10.1118/1.1617391

View details for Web of Science ID 000186596900011

View details for PubMedID 14655941

Abstract

Intensity modulated radiation therapy (IMRT) inverse planning is conventionally done in two steps. Firstly, the intensity maps of the treatment beams are optimized using a dose optimization algorithm. Each of them is then decomposed into a number of segments using a leaf-sequencing algorithm for delivery. An alternative approach is to pre-assign a fixed number of field apertures and optimize directly the shapes and weights of the apertures. While the latter approach has the advantage of eliminating the leaf-sequencing step, the optimization of aperture shapes is less straightforward than that of beamlet-based optimization because of the complex dependence of the dose on the field shapes, and their weights. In this work we report a genetic algorithm for segment-based optimization. Different from a gradient iterative approach or simulated annealing, the algorithm finds the optimum solution from a population of candidate plans. In this technique, each solution is encoded using three chromosomes: one for the position of the left-bank leaves of each segment, the second for the position of the right-bank and the third for the weights of the segments defined by the first two chromosomes. The convergence towards the optimum is realized by crossover and mutation operators that ensure proper exchange of information between the three chromosomes of all the solutions in the population. The algorithm is applied to a phantom and a prostate case and the results are compared with those obtained using beamlet-based optimization. The main conclusion drawn from this study is that the genetic optimization of segment shapes and weights can produce highly conformal dose distribution. In addition, our study also confirms previous findings that fewer segments are generally needed to generate plans that are comparable with the plans obtained using beamlet-based optimization. Thus the technique may have useful applications in facilitating IMRT treatment planning.

View details for Web of Science ID 000185973500003

View details for PubMedID 14529206

Abstract

The dose optimization in inverse planning is realized under the guidance of an objective function. The prescription doses in a conventional approach are usually rigid values, defining in most instances an ill-conditioned optimization problem. In this work, we propose a more general dose optimization scheme based on a statistical formalism [Xing et al., Med. Phys. 21, 2348-2358 (1999)]. Instead of a rigid dose, the prescription to a structure is specified by a preference function, which describes the user's preference over other doses in case the most desired dose is not attainable. The variation range of the prescription dose and the shape of the preference function are predesigned by the user based on prior clinical experience. Consequently, during the iterative optimization process, the prescription dose is allowed to deviate, with a certain preference level, from the most desired dose. By not restricting the prescription dose to a fixed value, the optimization problem becomes less ill-defined. The conventional inverse planning algorithm represents a special case of the new formalism. An iterative dose optimization algorithm is used to optimize the system. The performance of the proposed technique is systematically studied using a hypothetical C-shaped tumor with an abutting circular critical structure and a prostate case. It is shown that the final dose distribution can be manipulated flexibly by tuning the shape of the preference function and that using a preference function can lead to optimized dose distributions in accordance with the planner's specification. The proposed framework offers an effective mechanism to formalize the planner's priorities over different possible clinical scenarios and incorporate them into dose optimization. The enhanced control over the final plan may greatly facilitate the IMRT treatment planning process.

View details for DOI 10.1118/1.1561622

View details for Web of Science ID 000182284300020

View details for PubMedID 12722818

Abstract

A commonly known deficiency of currently available inverse planning systems is the difficulty in fine-tuning the final dose distribution. In practice, it is not uncommon that just a few unsatisfactory regions in the planning target volume or an organ at risk prevent an intensity modulated radiation therapy (IMRT) plan from being clinically acceptable. The purpose of this work is to introduce a mechanism for controlling the regional doses after a conventional IMRT plan is obtained and to demonstrate its clinical utility. Two types of importance factors are introduced in the objective function to model the tradeoffs of different clinical objectives. The first is the conventional structure-dependent importance factor, which quantifies the interstructure tradeoff. The second type is the voxel-dependent importance factor which "modulates" the importance of different voxels within a structure. The planning proceeds in two major steps. First a conventional inverse planning is performed, where the structure-dependent importance factors are determined in a trial-and-error fashion. The next level of planning involves fine-tuning the regional doses to meet specific clinical requirements. To achieve this, the voxels where doses need to be modified are identified either graphically on the isodose layouts, or on the corresponding dose-volume histogram (DVH) curves. The importance value of these voxels is then adjusted to increase/decrease the penalty at the corresponding regions. The technique is applied to two clinical cases. It was found that both tumor hot spots and critical structure maximal doses can be easily controlled by varying the regional penalty. One to three trials were sufficient for the conventionally optimized dose distributions to be adjusted to meet clinical expectation. Thus introducing the voxel-dependent penalty scheme provides an effective means for IMRT dose distributions painting and sculpting.

View details for DOI 10.1118/1.1556610

View details for Web of Science ID 000182284300008

View details for PubMedID 12722806

Abstract

Leaf transmission and head scatter are two important factors that influence intensity-modulated radiation therapy (IMRT) delivery and should be correctly taken into account when generating multileaf collimator (MLC) sequences. Significant discrepancies between the desired and delivered intensity profiles could otherwise result. The purpose of this article is to propose a reliable algorithm to minimize the dosimetric effects caused by the two factors in step-and-shoot mode.The goal of the algorithm is to minimize the difference between the desired fluence map and the fluence map actually delivered. For this purpose, an error function, defined as the least-square difference between the desired and the delivered fluence maps, is introduced. The effects of transmission and head scatter are minimized by adjusting the fractional monitor units (MUs) in the initial MLC sequences, created by using the desired fluence map without inclusion of the contributions from the two factors. Computationally, a downhill simplex optimization method is used to minimize the error function with respect to the fractional MUs. A three-source model is used to evaluate the relative head scatter distribution for each segment at the beginning of the calculation. The algorithm has been assessed by comparing the dose distributions delivered by the corrected leaf sequence files and the theoretic predication, calculated by Monte Carlo simulation using the desired fluence maps, for an intuitive test field and several clinical IMRT cases.The deviations between the desired fluence maps and those calculated using the corrected leaf sequence files are <0.3% of the maximum MU for the test field and <1.0% for the clinical IMRT cases. The experimental data show that both absolute and relative dose distributions delivered by the corrected leaf sequences agree with the desired ones within 2.5% of the maximum dose or 2 mm in high-dose gradient regions. Compared with the results obtained by using the leaf sequences in which only the transmission or none of the two effects is corrected, significant improvements in the fluence and dose distributions have been observed.Transmission and head scatter play important roles in the dosimetric behavior of IMRT delivery. A larger error may result if only one factor is considered because of the opposite effects of the two factors. We noted that the influence of the two effects is more pronounced in absolute dose than in the relative dose. The algorithm proposed in this work accurately corrects for these two effects in step-and-shoot delivery and provides a reliable tool for clinical IMRT application.

View details for DOI 10.1016/S0360-3016(02)04417-6

View details for Web of Science ID 000181269600031

View details for PubMedID 12605992

Abstract

Intensity modulated radiation therapy (IMRT) is an advanced form of radiation therapy and promises to improve dose conformation while reducing the irradiation to the sensitive structures. The modality is, however, more complicated than conventional treatment and requires much more stringent quality assurance (QA) to ensure what has been planned can be achieved accurately. One of the main QA tasks is the assurance of positioning accuracy of multileaf collimator (MLC) leaves during IMRT delivery. Currently, the routine quality assurance of MLC in most clinics isbeing done using radiographic films with specially designed MLC leaf sequences. Besides being time consuming, the results of film measurements are difficult to quantify and interpret. In this work, we propose a new and effective technique for routine MLC leaf positioning QA. The technique utilizes the fact that, when a finite-sized detector is placed under a leaf, the relative output of the detector will depend on the relative fractional volume irradiated. A small error in leaf positioning would change the fractional volume irradiated and lead to a deviation of the relative output from the normal reading. For a given MLC and detector system, the relation between the relative output and the leaf displacement can be easily established through experimental measurements and used subsequently as a quantitative means for detecting possible leaf positional errors. The method was tested using a linear accelerator with an 80-leaf MLC. Three different locations, including two locations on central plane (X1 = X2 = 0) and one point on an off-central plane location (X1 = -7.5, X = 7.5), were studied. Our results indicated that the method could accurately detect a leaf positional change of approximately 0.1 mm. The method was also used to monitor the stability of MLC leaf positioning for five consecutive weeks. In this test, we intentionally introduced two positional errors in the testing MLC leaf sequences: -0.2 mm and 1.2 mm. The technique was found to be robust and could detect the positional inaccuracy in each week's test. The influence of other possible error sources, including the ion chamber placement, jaw settings, gantry and collimator angle read-outs, and the positioning errors of the adjacent leaves, on detection accuracy were also investigated. The principle of our method is independent of the types of the MLC and the detector and may have significant practical implications in facilitating routine MLC QA for IMRT delivery.

View details for DOI 10.1118/1.1543150

View details for Web of Science ID 000181587500019

View details for PubMedID 12674244

Abstract

Selection of beam configuration in currently available intensity-modulated radiotherapy (IMRT) treatment planning systems is still based on trial-and-error search. Computer beam orientation optimization has the potential to improve the situation, but its practical implementation is hindered by the excessive computing time associated with the calculation. The purpose of this work is to provide an effective means to speed up the beam orientation optimization by incorporating a priori geometric and dosimetric knowledge of the system and to demonstrate the utility of the new algorithm for beam placement in IMRT.Beam orientation optimization was performed in two steps. First, the quality of each possible beam orientation was evaluated using beam's-eye-view dosimetrics (BEVD) developed in our previous study. A simulated annealing algorithm was then employed to search for the optimal set of beam orientations, taking into account the BEVD scores of different incident beam directions. During the calculation, sampling of gantry angles was weighted according to the BEVD score computed before the optimization. A beam direction with a higher BEVD score had a higher probability of being included in the trial configuration, and vice versa. The inclusion of the BEVD weighting in the stochastic beam angle sampling process made it possible to avoid spending valuable computing time unnecessarily at "bad" beam angles. An iterative inverse treatment planning algorithm was used for beam intensity profile optimization during the optimization process. The BEVD-guided beam orientation optimization was applied to an IMRT treatment of paraspinal tumor. The advantage of the new optimization algorithm was demonstrated by comparing the calculation with the conventional scheme without the BEVD weighting in the beam sampling.The BEVD tool provided useful guidance for the selection of the potentially good directions for the beams to incident and was used to guide the search for the optimal beam configuration. The BEVD-guided sampling improved both optimization speed and convergence of the calculation. A comparison of several five-field IMRT treatment plans obtained with and without BEVD guidance indicated that the computational efficiency was increased by a factor of approximately 10.Incorporation of BEVD information allows for development of a more robust tool for beam orientation optimization in IMRT planning. It enables us to more effectively use the angular degree of freedom in IMRT without paying the excessive computing overhead and brings us one step closer to the goal of automated selection of beam orientations in a clinical environment.

View details for Web of Science ID 000179566100039

Abstract

The purpose of this work was to apply the method of constrained least-squares to inverse treatment planning and to explore its potential for providing a fast interactive planning environment for intensity-modulated radiation therapy (IMRT).The description of the dose inside a patient is a linear matrix transformation of beamlet weights. The constrained least-squares method adds additional matrix operators and produces beamlet weights by a direct linear transformation. These matrix operators contain a priori knowledge about the radiation distribution. The constrained least-squares technique was applied to obtain IMRT plans for prostate and paraspinal cancer patients and compared with the corresponding plans optimized using the CORVUS inverse planning system.It was demonstrated that a constrained least-squares technique is suitable for IMRT plan optimization with significantly increased computing speed. For the two cases we have tested, the constrained least-squares method was an order of magnitude faster than conventional iterative techniques because of the avoidance of the iterative calculations. We also found that the constrained least-squares method is capable of generating clinically acceptable treatment plans with less trial-and-error adjustments of system variables, and with improved target volume coverage as well as sensitive structure sparing in comparison with that obtained using CORVUS.The constrained least-squares method has the advantage that it does not require iterative calculation and thus significantly speeds up the therapeutic plan optimization process. Besides shedding important insight into the inverse planning problem, the technique has strong potential to provide a fast and interactive environment for IMRT treatment planning.

View details for Web of Science ID 000179122400029

View details for PubMedID 12419451

Abstract

Radiation therapy is an image-guided process whose success critically depends on the imaging modality used for treatment planning and the level of integration of the available imaging information. In this work, we establish a dose optimization framework for incorporating metabolic information from functional imaging modalities into the intensity-modulated radiation therapy (IMRT) inverse planning process and to demonstrate the technical feasibility of planning deliberately non-uniform dose distributions in accordance with functional imaging data. For this purpose, a metabolic map from functional images is discretized into a number of abnormality levels (ALs) and then fused with CT images. To escalate dose to the metabolically abnormal regions, we assume, for a given spatial point, a linear relation between the AL and the prescribed dose. But the formalism developed here is independent of the assumption and any other relation between AL and prescription is applicable. For a given AL and prescription relation, it is only necessary to prescribe the dose to the lowest AL in the target and the desired doses to other regions with higher AL values are scaled accordingly. To accomplish differential sparing of a sensitive structure when its functional importance (FI) distribution is known, we individualize the tolerance doses of the voxels within the structure according to their Fl levels. An iterative inverse planning algorithm in voxel domain is used to optimize the system with in homogeneous dose prescription. To model intra-structural trade-off, a mechanism is introduced through the use of voxel-dependent weighting factors, in addition to the conventional structure specific weighting factors which model the inter-structural trade-off. The system is used to plan a phantom case with a few hypothetical functional distributions and a brain tumour treatment with incorporation of magnetic resonance spectroscopic imaging data. The results indicated that it is technically feasible to produce deliberately non-uniform dose distributions according to the functional imaging requirements. Integration of functional imaging information into radiation therapy dose optimization allows for consideration of patient-specific biologic information and provides a significant opportunity to truly individualize radiation treatment. This should enhance our capability to safely and intelligently escalate dose and lays the technical foundation for future clinical studies of the efficacy of functional imaging-guided IMRT.

View details for Web of Science ID 000179171900003

View details for PubMedID 12433120

Abstract

Within the confines of least-squares operations, it is possible to quantify the effect of the addition of treatment fields or beamlets to a treatment plan. Using linear algebra and eigenvalue perturbation theory, the effect of the increase in number of treatments is shown to be equivalent to adding a perturbation operator. The effect of adding additional fields will be negligible if the perturbation operator is small. The correspondence of this approach to an earlier work in beam-orientation optimization is also demonstrated. Results are presented for prostate, spinal and head and neck cases, and the connection to beam-orientation optimization is examined.

View details for Web of Science ID 000178847300004

View details for PubMedID 12408477

Abstract

Intensity-modulated radiation therapy (IMRT) requires the determination of the appropriate multileaf collimator settings to deliver an intensity map. The purpose of this work was to attempt to reduce the number of segments required for IMRT delivery and the number of monitor units required to deliver an intensity map. An intensity map may be written as a matrix. Leaf sequencing was formulated as a problem of decomposing the matrix into a series of sub-matrices. Sets of random intensity matrices were created and the segmentations produced by applying different algorithms were compared. The number of segments, important if verification and record (VR) overhead is significant, and beam on times were examined. It is shown that reducing the value of the matrix entries by the maximum amount at each stage results in the smallest number of steps. Reducing the 2-norm (sum of the squares) of the matrix entries by the maximum amount at each step results in the smallest beam on time. Three new algorithms are introduced, two of which produce results that are superior to those generated by the algorithms of other researchers. The resulting methods can be expanded upon to include tongue and groove effects and leaf inter-digitization. With square random matrices of the order 15, the reduction in beam time and segmentation is up to 30-40%. Compared to previous algorithms, those presented here have demonstrated a reduction in the beam on time required to deliver an intensity map by 30-40%. Similarly, the number of segments needed to deliver an intensity map is also reduced.

View details for Web of Science ID 000178231900005

View details for PubMedID 12361213

Abstract

Accurate determination of the head scatter factor Sc is an important issue, especially for intensity modulated radiation therapy, where the segmented fields are often very irregular and much less than the collimator jaw settings. In this work, we report an Sc calculation algorithm for symmetric, asymmetric, and irregular open fields shaped by the tertiary collimator (a multileaf collimator or blocks) at different source-to-chamber distance. The algorithm was based on a three-source model, in which the photon radiation to the point of calculation was treated as if it originated from three effective sources: one source for the primary photons from the target and two extra-focal photon sources for the scattered photons from the primary collimator and the flattening filter, respectively. The field mapping method proposed by Kim et al. [Phys. Med. Biol. 43, 1593-1604 (1998)] was extended to two extra-focal source planes and the scatter contributions were integrated over the projected areas (determined by the detector's eye view) in the three source planes considering the source intensity distributions. The algorithm was implemented using Microsoft Visual C/C++ in the MS Windows environment. The only input data required were head scatter factors for symmetric square fields, which are normally acquired during machine commissioning. A large number of different fields were used to evaluate the algorithm and the results were compared with measurements. We found that most of the calculated Sc's agreed with the measured values to within 0.4%. The algorithm can also be easily applied to deal with irregular fields shaped by a multileaf collimator that replaces the upper or lower collimator jaws.

View details for DOI 10.1118/1.1500767

View details for Web of Science ID 000178093000010

View details for PubMedID 12349923

Abstract

Intensity modulated radiation therapy (IMRT) inverse planning is usually performed by pre-selecting parameters such as beam modality, beam configuration and importance factors and then optimizing the fluence profiles or beamlet weights. In reality, the IMRT dose optimization problem may be ill-conditioned and there may not be a physical solution to account for the chosen parameters and constraints. Planner intervention is often required to conduct a multiple trial-and-error process where several parameters are sequentially varied until an acceptable compromise is achieved. The resulting solution reflects a balance between the conflicting requirements of the target and the sensitive structures. A major problem of the conventional inverse planning formalism is that there exists no effective mechanism for a planner to fine-tune the dose distribution on a local level or to differentially modify the dose-volume histograms (DVHs) of the involved structures. In this paper we introduce a new inverse planning scheme with voxel-dependent importance factors and demonstrate that it provides us with an effective link between the system parameters and the dosimetric behaviour at a local level. The planning proceeds in two steps. After a conventional trial-and-error inverse planning procedure is completed, we identify the dose interval at which the fractional volume on the DVH curve needs to be changed. The voxels that receive dose in the selected range are then located and their voxel-dependent importance factors are adjusted accordingly. The fine-tuning of the DVHs is iterative in nature and, using widely available computer graphic software tools, the process can be made graphically interactive. The new IMRT planning scheme is applied to two test cases and the results indicate that our control over the differential shapes of the DVHs of the involved structures is,greatly enhanced. Thus the technique may have significant practical implications in facilitating the IMRT treatment planning process.

View details for Web of Science ID 000176029200004

View details for PubMedID 12069085

Abstract

To introduce the concept of pseudo beam's-eye-view (pBEV), to establish a framework for computer-assisted beam orientation selection in intensity-modulated radiation therapy (IMRT), and to evaluate the utility of the proposed technique.To facilitate the selection of beam orientations for IMRT treatment planning, a scoring of beam direction was introduced. The score function was based on the maximum target dose deliverable by the beam without exceeding the tolerance doses of the critical structures. For the score function calculation, the beam portal at given gantry and couch angles was divided into a grid of beamlets. Each beamlet crossing the target was assigned the maximum intensity that could be used without exceeding the dose tolerances of the organs at risk (OARs) and normal tissue. Thereafter, a score was assigned to the beam according to the target dose delivered. The beams for the treatment were selected among those with the highest scores. In a sense, this technique is similar to the beam's-eye-view approach used in conventional radiation therapy, except that the evaluation by a human is replaced by a score function, and beam modulation is taken into account.The pBEV technique was tested on two clinical cases: a paraspinal treatment and a nasopharyngeal cancer with both coplanar and noncoplanar beam configurations. The plans generated under the guidance of pBEV for the paraspinal treatment offered superior target dose uniformity and reduced OAR doses. For the nasopharyngeal cancer case, it was also found that the pBEV-selected coplanar and noncoplanar beams significantly improved the target coverage without compromising the sparing of the OARs.The pBEV technique developed in this work provides a comprehensive tool for beam orientation selection in IMRT. It is especially valuable for complicated cases, where the target is surrounded by several sensitive structures and where it is difficult to select a set of good beam orientations. The pBEV technique has considerable potential for simplifying the IMRT treatment planning process and for maximizing the technical capacity of IMRT.

View details for Web of Science ID 000172495200024

View details for PubMedID 11728698

Abstract

Methods of linear algebra are applied to the choice of beam weights for intensity modulated radiation therapy (IMRT). It is shown that the physical interpretation of the beam weights, target homogeneity and ratios of deposited energy can be given in terms of matrix equations and quadratic forms. The methodology of fitting using linear algebra as applied to IMRT is examined. Results are compared with IMRT plans that had been prepared using a commercially available IMRT treatment planning system and previously delivered to cancer patients.

View details for Web of Science ID 000171866700006

View details for PubMedID 11686277

Abstract

In intensity-modulated radiation therapy (IMRT), the incident beam orientations are often determined by a trial and error search. The conventional beam's-eye view (BEV) tool becomes less helpful in IMRT because it is frequently required that beams go through organs at risk (OARs) in order to achieve a compromise between the dosimetric objectives of the planning target volume (PTV) and the OARs. In this paper, we report a beam's-eye view dosimetrics (BEVD) technique to assist in the selection of beam orientations in IMRT. In our method, each beam portal is divided into a grid of beamlets. A score function is introduced to measure the 'goodness' of each beamlet at a given gantry angle. The score is determined by the maximum PTV dose deliverable by the beamlet without exceeding the tolerance doses of the OARs and normal tissue located in the path of the beamlet. The overall score of the gantry angle is given by a sum of the scores of all beamlets. For a given patient. the score function is evaluated for each possible beam orientation. The directions with the highest scores are then selected as the candidates for beam placement. This procedure is similar to the BEV approach used in conventional radiation therapy, except that the evaluation by a human is replaced by a score function to take into account the intensity modulation. This technique allows one to select beam orientations without the excessive computing overhead of computer optimization of beam orientation. It also provides useful insight into the problem of selection of beam orientation and is especially valuable for complicated cases where the PTV is surrounded by several sensitive structures and where it is difficult to select a set of 'good' beam orientations. Several two-dimensional (2D) model cases were used to test the proposed technique. The plans obtained using the BEVD-selected beam orientations were compared with the plans obtained using equiangular spaced beams. For all the model cases investigated, the use of BEVD-selected beam orientations improved the dose distributions significantly. These examples indicate that the technique has considerable potential for simplifying the IMRT treatment planning process and allows for better utilization of the technical capacity of IMRT.

View details for Web of Science ID 000171558300016

View details for PubMedID 11580182

Abstract

To investigate the role of beam orientation optimization in intensity-modulated radiation therapy (IMRT) and to examine the potential benefits of noncoplanar intensity-modulated beams.A beam orientation optimization algorithm was implemented. For this purpose, system variables were divided into two groups: beam position (gantry and table angles) and beam profile (beamlet weights). Simulated annealing was used for beam orientation optimization and the simultaneous iterative inverse treatment planning algorithm (SIITP) for beam intensity profile optimization. Three clinical cases were studied: a localized prostate cancer, a nasopharyngeal cancer, and a paraspinal tumor. Nine fields were used for all treatments. For each case, 3 types of treatment plan optimization were performed: (1) beam intensity profiles were optimized for 9 equiangular spaced coplanar beams; (2) orientations and intensity profiles were optimized for 9 coplanar beams; (3) orientations and intensity profiles were optimized for 9 noncoplanar beams.For the localized prostate case, all 3 types of optimization described above resulted in dose distributions of a similar quality. For the nasopharynx case, optimized noncoplanar beams provided a significant gain in the gross tumor volume coverage. For the paraspinal case, orientation optimization using noncoplanar beams resulted in better kidney sparing and improved gross tumor volume coverage.The sensitivity of an IMRT treatment plan with respect to the selection of beam orientations varies from site to site. For some cases, the choice of beam orientations is important even when the number of beams is as large as 9. Noncoplanar beams provide an additional degree of freedom for IMRT treatment optimization and may allow for notable improvement in the quality of some complicated plans.

View details for Web of Science ID 000168781000033

View details for PubMedID 11380245

Abstract

The task of treatment planning for prostate implants is to find an optimal seed configuration, comprising the target coverage and dosimetric consideration of critical structures such as the rectum and urethra. An efficient method to accomplish this is to use an inverse planning technique that derives the optimized solution from a prescribed treatment goal. The goal can be specified in the voxel domain as the desired doses to the voxels of the target and critical structures, or in the dose volume representation as the desired dose volume histograms (DVHs) of the target and critical structures. The DVH based optimization has been successfully used in plan optimization for intensity-modulated radiation therapy (IMRT) but little attention has been paid to its application in prostate implants. Clinically, it has long been known that some normal structure tolerances are more accurately assessed by volumetric information. Dose-volume histograms are also widely used for plan evaluation. When working in the DVH domain for optimization one has more control over the final DVHs. We have constructed an objective function sensitive to the DVHs of the target and critical structures. The objective function is minimized using an iterative algorithm, starting from a randomly selected initial seed configuration. At each iteration step, a trial position is given to a randomly selected source and the trial position is accepted if the objective function is decreased. To avoid being trapped in a less optimal local minimum, the optimization process is repeated. The final plan is selected from a pool of optimized plans obtained from a series of randomized initial seed configurations.

View details for Web of Science ID 000090089500011

View details for PubMedID 11099195

Abstract

The purpose of this work was to use Monte Carlo simulations to verify the accuracy of the dose distributions from a commercial treatment planning optimization system (Corvus, Nomos Corp., Sewickley, PA) for intensity-modulated radiotherapy (IMRT). A Monte Carlo treatment planning system has been implemented clinically to improve and verify the accuracy of radiotherapy dose calculations. Further modifications to the system were made to compute the dose in a patient for multiple fixed-gantry IMRT fields. The dose distributions in the experimental phantoms and in the patients were calculated and used to verify the optimized treatment plans generated by the Corvus system. The Monte Carlo calculated IMRT dose distributions agreed with the measurements to within 2% of the maximum dose for all the beam energies and field sizes for both the homogeneous and heterogeneous phantoms. The dose distributions predicted by the Corvus system, which employs a finite-size pencil beam (FSPB) algorithm, agreed with the Monte Carlo simulations and measurements to within 4% in a cylindrical water phantom with various hypothetical target shapes. Discrepancies of more than 5% (relative to the prescribed target dose) in the target region and over 20% in the critical structures were found in some IMRT patient calculations. The FSPB algorithm as implemented in the Corvus system is adequate for homogeneous phantoms (such as prostate) but may result in significant under or over-estimation of the dose in some cases involving heterogeneities such as the air-tissue, lung-tissue and tissue-bone interfaces.

View details for Web of Science ID 000089438900007

View details for PubMedID 11008950

Abstract

In a treatment planning system for intensity modulated radiation therapy (IMRT), the time sequence of multileaf collimator (MLC) settings are derived from an optimal fluence map as a postoptimization process using a software module called a "leaf sequencer." The dosimetric accuracy of the dynamic delivery depends on the functionality of the module and it is important to verify independently the correctness of the leaf sequences for each field of a patient treatment. This verification is unique to the IMRT treatment and has been done using radiographic film, electronic portal imaging device (EPID) or electronic imaging system (BIS). The measurement tests both the leaf sequencer and the dynamic multileaf collimator (MLC) delivery system, providing a reliable assurance of clinical IMRT treatment. However, this process is labor intensive and time consuming. In this paper, we propose to separate quality assurance (QA) of the leaf sequencer from the dynamic MLC delivery system. We describe a simple computer algorithm for the verification of the leaf sequences. The software reads in the leaf sequences and simulates the motion of the MLC leaves. The generated fluence map is then compared quantitatively with the reference map from the treatment planning system. A set of pre-defined QA indices is introduced to measure the "closeness" between the computed and the reference maps. The approach has been used to validate the CORVUS (NOMOS Co., Sewickley, PA) treatment plans. The results indicate that the proposed approach is robust and suitable to support the complex IMRT QA process.

View details for Web of Science ID 000089410200011

View details for PubMedID 11011737

Abstract

PURPOSE AND OBJECTIVE: The primary goal of this study was to examine systematically the dosimetric effect of small patient movements and linear accelerator angular setting misalignments in the delivery of intensity modulated radiation therapy. We will also provide a method for estimating dosimetric errors for an arbitrary combination of these uncertainties.Sites in two patients (lumbar-vertebra and nasopharynx) were studied. Optimized intensity modulated radiation therapy treatment plans were computed for each patient using a commercially available inverse planning system (CORVUS, NOMOS Corporation, Sewickley, PA). The plans used nine coplanar beams. For each patient the dose distributions and relevant dosimetric quantities were calculated, including the maximum, minimum, and average doses in targets and sensitive structures. The corresponding dose volumetric information was recalculated by purposely varying the collimator angle or gantry angle of an incident beam while keeping other beams unchanged. Similar calculations were carried out by varying the couch indices in either horizontal or vertical directions. The intensity maps of all the beams were kept the same as those in the optimized plan. The change of a dosimetric quantity, Q, for a combination of collimator and gantry angle misalignments and patient displacements was estimated using Delta=Sigma(DeltaQ/Deltax(i))Deltax(i). Here DeltaQ is the variation of Q due to Deltax(i), which is the change of the i-th variable (collimator angle, gantry angle, or couch indices), and DeltaQ/Deltax(i) is a quantity equivalent to the partial derivative of the dosimetric quantity Q with respect to x(i).While the change in dosimetric quantities was case dependent, it was found that the results were much more sensitive to small changes in the couch indices than to changes in the accelerator angular setting. For instance, in the first example in the paper, a 3-mm movement of the couch in the anterior-posterior direction can cause a 38% decrease in the minimum target dose or a 41% increase in the maximum cord dose, whereas a 5 degrees change in the θ(1)=20 degrees beam only gave rise to a 1.5% decrease in the target minimum or 5.1% in the cord maximum. The effect of systematic positioning uncertainties of the machine settings was more serious than random uncertainties, which tended to smear out the errors in dose distributions.The dose distribution of an intensity modulated radiation therapy (IMRT) plan changes with patient displacement and angular misalignment in a complex way. A method was proposed to estimate dosimetric errors for an arbitrary combination of uncertainties in these quantities. While it is important to eliminate the angular misalignment, it was found that the couch indices (or patient positioning) played a much more important role. Accurate patient set-up and patient immobilization is crucial in order to take advantage fully of the technological advances of IMRT. In practice, a sensitivity check should be useful to foresee potential IMRT treatment complications and a warning should be given if the sensitivity exceeds an empirical value. Quality assurance action levels for a given plan can be established out of the sensitivity calculation.

View details for Web of Science ID 000088159100013

View details for PubMedID 10869760

Abstract

To explore the feasibility of a multi-modality breast-conserving radiation therapy treatment technique to reduce high dose to the ipsilateral lung and the heart when compared with the conventional treatment technique using two tangential fields.An electron beam with appropriate energy was combined with four intensity modulated photon beams. The direction of the electron beam was chosen to be tilted 10-20 degrees laterally from the anteroposterior direction. Two of the intensity-modulated photon beams had the same gantry angles as the conventional tangential fields, whereas the other two beams were rotated 15-25 degrees toward the anteroposterior directions from the first two photon beams. An iterative algorithm was developed which optimizes the weight of the electron beam as well as the fluence profiles of the photon beams for a given patient. Two breast cancer patients with early-stage breast tumors were planned with the new technique and the results were compared with those from 3D planning using tangential fields as well as 9-field intensity-modulated radiotherapy (IMRT) techniques.The combined electron and IMRT plans showed better dose conformity to the target with significantly reduced dose to the ipsilateral lung and, in the case of the left-breast patient, reduced dose to the heart, than the tangential field plans. In both the right-sided and left-sided breast plans, the dose to other normal structures was similar to that from conventional plans and was much smaller than that from the 9-field IMRT plans. The optimized electron beam provided between 70 to 80% of the prescribed dose at the depth of maximum dose of the electron beam.The combined electron and IMRT technique showed improvement over the conventional treatment technique using tangential fields with reduced dose to the ipsilateral lung and the heart. The customized beam directions of the four IMRT fields also kept the dose to other critical structures to a minimum.

View details for Web of Science ID 000088159100010

View details for PubMedID 10869757

Abstract

Accurate targeting is important in intensity-modulated radiation therapy (IMRT). The positional uncertainties of structures with respect to the external beams arise in part from random organ motion and patient setup errors. While it is important to improve immobilization and reduce the influence of organ motion, the residual effects should be included in the IMRT plan design. Current inverse planning algorithms follow the conventional approach and include uncertainties by assuming population-based margins to the target and sensitive structures. Margin around a structure represents a "hard boundary" and the fact that a structure has a spatial probability distribution has been completely ignored. With increasing understanding of spatial uncertainties of structures and the technical capability of fine-tuning the dose distribution on an individual beamlet level in IMRT, it seems timely and important to fully utilize the information in the planning process. This will reduce the "effective" margins of the structures and facilitate dose escalation. Instead of specifying a "hard margin," we describe an inverse planning algorithm which takes into consideration positional uncertainty in terms of spatial probability distribution. The algorithm was demonstrated by assuming that the random organ motion can be represented by a three-dimensional Gaussian distribution function. Other probability distributions can be dealt with similarly. In particular, the commonly used "hard margin" is a special case of the current approach with a uniform probability distribution within a specified range. The algorithm was applied to plan treatment for a prostate case and a pancreatic case. The results were compared with those obtained by adding a margin to the clinical target volume. Better sparing of the sensitive structures were obtained in both cases using the proposed method for approximately the same target coverage.

View details for Web of Science ID 000088372700010

View details for PubMedID 10947260

Abstract

Beam direction optimization is an important problem in radiation therapy. In intensity modulated radiation therapy (IMRT), the difficulty for computer optimization of the beam directions arises from the fact that they are coupled with the intensity profiles of the incident beams. In order to obtain the optimal incident beam directions using iterative or stochastic methods, the beam profiles ought to be optimized after every change of beam configuration. In this paper we report an effective algorithm to optimize gantry angles for IMRT. In our calculation the gantry angles and the beam profiles (beamlet weights) were treated as two separate groups of variables. The gantry angles were sampled according to a simulated annealing algorithm. For each sampled beam configuration, beam profile calculation was done using a fast filtered backprojection (FBP) method. Simulated annealing was also used for beam profile optimization to examine the performance of the FBP for beam orientation optimization. Relative importance factors were incorporated into the objective function to control the relative importance of the target and the sensitive structures. Minimization of the objective function resulted in the best possible beam orientations and beam profiles judged by the given objective function. The algorithm was applied to several model problems and the results showed that the approach has potential for IMRT applications.

View details for Web of Science ID 000087765000005

View details for PubMedID 10902552

Abstract

An important issue in intensity modulated radiation therapy (IMRT) is the verification of the monitor unit (MU) calculation of the planning system using an independent procedure. Because of the intensity modulation and the dynamic nature of the delivery process, the problem becomes much more involved than that in conventional radiation therapy. In this work, a closed formula for MU calculation is derived. The approach is independent of the specific form of leaf sequence algorithms. It is straightforward to implement the procedure using a simple computer program. The approach is illustrated by a simplified example and is demonstrated by a few CORVUS (NOMOS Corporation, Sewickley, PA) treatment plans. The results indicate that it is robust and suitable for IMRT MU verification.

View details for Web of Science ID 000085887000017

View details for PubMedID 10730973

Abstract

To describe a wedge filter optimization technique which automatically chooses the beam weights and wedge filters and to demonstrate the implementation of the algorithm in clinical three-dimensional (3D) radiotherapy treatment planning.Given the incident directions and beam energies of J beams, the dose distribution is a function of the beam weights, wedge angles, and wedge orientations. Instead of decomposing an incident field into a superposition of an open and two nominal wedged fields and then optimizing their weights, the algorithm optimizes the objective function with respect to the beam weights, wedge angles and wedge orientations directly. A salient feature of the algorithm is that no planner intervention was required in the selection of wedge filters during the optimization process. A dose-based objective function which incorporated the relative importance of structures was adopted in this work. The objective function was minimized by the method of simulated annealing. The technique was demonstrated by using a phantom study and two clinical cases.For the phantom case, the classical wedge pair result was obtained, providing a useful test of the algorithm. Dose distributions and dose volume histograms for the target and surrounding organs were presented for the two clinical cases. It was also shown that dose homogeneity to the target could be compromised by increasing the relative importance factors to the surrounding organs.A 3D wedge filter optimization algorithm has been developed. The technique has the potential to fully automate the 3D radiotherapy treatment planning process. In addition, treatment planning time and efforts were significantly reduced.

View details for Web of Science ID 000084709600012

View details for PubMedID 10660206

Abstract

Treatment optimization is usually formulated as an inverse problem, which starts with a prescribed dose distribution and obtains an optimized solution under the guidance of an objective function. The solution is a compromise between the conflicting requirements of the target and sensitive structures. In this paper, the treatment plan optimization is formulated as an estimation problem of a discrete and possibly nonconvex system. The concept of preference function is introduced. Instead of prescribing a dose to a structure (or a set of voxels), the approach prioritizes the doses with different preference levels and reduces the problem into selecting a solution with a suitable estimator. The preference function provides a foundation for statistical analysis of the system and allows us to apply various techniques developed in statistical analysis to plan optimization. It is shown that an optimization based on a quadratic objective function is a special case of the formalism. A general two-step method for using a computer to determine the values of the model parameters is proposed. The approach provides an efficient way to include prior knowledge into the optimization process. The method is illustrated using a simplified two-pixel system as well as two clinical cases. The generality of the approach, coupled with promising demonstrations, indicates that the method has broad implications for radiotherapy treatment plan optimization.

View details for Web of Science ID 000083775800019

View details for PubMedID 10587216

Abstract

A technique was developed to reduce the size and magnitude of the hot and cold spots in the abutting regions of photon and electron fields. The photon and electron fields were set up such that the photon field extended approximately 2 cm into the electron field in the abutting region. The region of the photon beam that overlapped the electron field was modulated using a multileaf collimator, effectively broadening the photon penumbra to make it complimentary to the electron penumbra. The computer calculations were verified using film measurements for abutting a 6 MV photon beam with a 9 MeV electron beam. A uniform dose was achieved at a prespecified depth of 2 cm, and dose uniformity was improved at the specified depth and beyond compared with unmodulated photon beams. A slight increase in dose inhomogeneity was seen at shallower depths. The overall areas of the hot and cold spots were significantly reduced. The technique also reduced the sensitivity of dose homogeneity to setup errors such that the magnitudes of the hot and cold spots were about half of those produced with unmodulated photon beam when an overlap or gap of 4 mm was introduced. The technique was applied to the treatment of a head and neck cancer and a lymphoma involving the right pleura with markedly reduced dose inhomogeneity in the abutting regions.

View details for Web of Science ID 000083775800023

View details for PubMedID 10587220

Abstract

Inverse treatment planning starts with a treatment objective and obtains the solution by optimizing an objective function. The clinical objectives are usually multifaceted and potentially incompatible with one another. A set of importance factors is often incorporated in the objective function to parametrize trade-off strategies and to prioritize the dose conformality in different anatomical structures. Whereas the general formalism remains the same, different sets of importance factors characterize plans of obviously different flavour and thus critically determine the final plan. Up to now, the determination of these parameters has been a 'guessing' game based on empirical knowledge because the final dose distribution depends on the parameters in a complex and implicit way. The influence of these parameters is not known until the plan optimization is completed. In order to compromise properly the conflicting requirements of the target and sensitive structures, the parameters are usually adjusted through a trial-and-error process. In this paper, a method to estimate these parameters computationally is proposed and an iterative computer algorithm is described to determine these parameters numerically. The treatment plan selection is done in two steps. First, a set of importance factors are chosen and the corresponding beam parameters (e.g. beam profiles) are optimized under the guidance of a quadratic objective function using an iterative algorithm reported earlier. The 'optimal' plan is then evaluated by an additional scoring function. The importance factors in the objective function are accordingly adjusted to improve the ranking of the plan. For every change in the importance factors, the beam parameters need to be re-optimized. This process continues in an iterative fashion until the scoring function is saturated. The algorithm was applied to two clinical cases and the results demonstrated that it has the potential to improve significantly the existing method of inverse planning. It was noticed that near the final solution the plan became insensitive to small variations of the importance factors.

View details for Web of Science ID 000083120600011

View details for PubMedID 10533926

Abstract

Leaf motion synchronization of dynamic multileaf collimators (DMLC) for intensity-modulated radiotherapy (IMRT) is important in improving dose distribution and reducing "tongue-and-groove" effects for a prescribed intensity profile. Leaf synchronization could also be used in transforming a one-dimensional leaf-setting algorithm into a two-dimensional leaf-setting algorithm. In this work, we aim to develop a generalized leaf synchronization method for delivering IMRT with the minimized beam delivery time and the optimized subfield variations for a leaf-setting sequence.With the leaf synchronization procedure, all active MLC leaf pairs start and finish off a leaf sequence simultaneously. In this work, the MLC leaf pairs were synchronized under the condition that the resulting leaf sequence produces the desired intensity profile with the minimum beam delivery time. The parameter of the leaf synchronization function was determined through the least-square minimization of the area variations of all subfields within a leaf sequence. The leaf synchronization and optimization procedure were applied and analyzed for clinical relevant intensity profiles for treating the head-and-neck cancer patients using IMRT.The total monitor units and the optimized beam delivery time of generating a two-dimensional intensity profile was proven through this work to be the global minimum of all leaf-setting sequences including the unsynchronized leaf-setting sequences. The optimized parameter for subfield variations of the synchronized leaf trajectories was found to be dependent on individual intensity profiles. For all our studied cases, the unsynchronized leaf trajectories always have significantly larger subfield variations than the synchronized leaf trajectories.It is important and also feasible to synchronize and optimize dynamic MLC leaf motions while still keeping the total beam delivery time minimum for delivering arbitrary two-dimensional intensity-modulated fields.

View details for Web of Science ID 000081487600022

View details for PubMedID 10421549

Abstract

A commercial three-dimensional (3D) inverse treatment planning system, Corvus (Nomos Corporation, Sewickley, PA), was recently made available. This paper reports our preliminary results and experience with commissioning this system for clinical implementation. This system uses a simulated annealing inverse planning algorithm to calculate intensity-modulated fields. The intensity-modulated fields are divided into beam profiles that can be delivered by means of a sequence of leaf settings by a multileaf collimator (MLC). The treatments are delivered using a computer-controlled MLC. To test the dose calculation algorithm used by the Corvus software, the dose distributions for single rectangularly shaped fields were compared with water phantom scan data. The dose distributions predicted to be delivered by multiple fields were measured using an ion chamber that could be positioned in a rotatable cylindrical water phantom. Integrated charge collected by the ion chamber was used to check the absolute dose of single- and multifield intensity modulated treatments at various spatial points. The measured and predicted doses were found to agree to within 4% at all measurement points. Another set of measurements used a cubic polystyrene phantom with radiographic film to record the radiation dose distribution. The films were calibrated and scanned to yield two-dimensional isodose distributions. Finally, a beam imaging system (BIS) was used to measure the intensity-modulated x-ray beam patterns in the beam's-eye view. The BIS-measured images were then compared with a theoretical calculation based on the MLC leaf sequence files to verify that the treatment would be executed accurately and without machine faults. Excellent correlation (correlation coefficients > or = 0.96) was found for all cases. Treatment plans generated using intensity-modulated beams appear to be suitable for treatment of irregularly shaped tumours adjacent to critical structures. The results indicated that the system has potential for clinical radiation treatment planning and delivery and may in the future reduce treatment complexity.

View details for Web of Science ID 000078573600013

View details for PubMedID 10070795

Abstract

A treatment planning system to compute intensity modulated radiotherapy (IMRT) treatments using inverse planning was investigated. The system was designed to optimize the intensity patterns required to treat a specified target volume with specified normal structure constraints. A beam model that uses the convolution of pencil beams was used to compute the dose distributions. A multileaf collimator leaf-setting sequence intended to produce the intensity pattern was computed along with the monitor units required to deliver each of a number of fixed-gantry modulated fields. Computer calculations are commonly verified using an independent manual procedure. It is difficult to calculate treatment delivery monitor units for this variant of IMRT using manual methods. Since manual calculations are not feasible, it is important both to understand and to verify the calculation of treatment monitor units by the planning system algorithm. A formal analysis was made of the dose calculation model and the monitor unit calculation embedded in the algorithm. Experimental verification of the dose delivered by plans computed with the methodology demonstrated an agreement of better than 4% between the dose model and measurements.

View details for Web of Science ID 000078686000011

View details for PubMedID 10076972

Abstract

Three types of iterative algorithms, algebraic inverse treatment planning (AITP), simultaneous iterative inverse treatment planning (SIITP), and iterative least-square inverse treatment planning (ILSITP), differentiated according to their updating sequences, were generalized to three dimension with true beam geometry and dose model. A rapid ray-tracing approach was developed to optimize the primary beam components. Instead of recalculating the dose matrix at each iteration, the dose distribution was generated by scaling up or down the dose matrix elements of the previous iteration. This significantly increased the calculation speed. The iterative algorithms started with an initial intensity profile for each beam, specified by a two-dimensional pixel beam map of M elements. The calculation volume was divided into N voxels, and the calculation was done by repeatedly comparing the calculated and desired doses and adjusting the values of the beam map elements to minimize an objective function. In AITP, the iteration is performed voxel by voxel. For each voxel, the dose discrepancy was evaluated and the contributing pencil beams were updated. In ILSITP and SIITP, the iteration proceeded pencil beam by pencil beam instead of voxel by voxel. In all cases, the iteration procedure was repeated until the best possible dose distribution was achieved. The algorithms were applied to two examples and the results showed that the iterative techniques were able to produce superior isodose distributions.

View details for Web of Science ID 000076452500004

View details for PubMedID 9800690

Abstract

An essential step towards optimizing and automating radiation therapy treatment planning is to develop an effective algorithm to find the optimal beam weights and wedge filters for a given set of beam directions and modalities. This problem is solved by introducing a variable transformation based on the universal and omni wedge principles. Instead of directly optimizing an objective function with respect to wedge angles and orientations, each field is first decomposed into a superposition of an open field and two orthogonal wedged fields. This transforms the problem of finding J beam weights, wedge angles, and orientations to that of optimizing a system with 3J beam weights (J open beams and 2J nominal wedged beams), where J is the total number of incident beam directions. An iterative algorithm based on a method originally developed for image reconstruction is used to find the 3J beam weights. The technique is applied to a few clinical cases. Treatment plans are improved compared to those obtained through the conventional manual trial and error planning process. In addition, planning time and effort are greatly reduced.

View details for Web of Science ID 000076452500006

View details for PubMedID 9800692

Abstract

A leaf-setting algorithm is developed for generating arbitrary beam intensity profiles in discrete levels using dynamic multileaf collimators (DMLCs). The algorithm starts with the algebraic expression for the area under the beam profile. It is shown that the coefficients in this expression can be transformed into the specifications for the leaf-setting sequence. It is proven that the algorithm optimizes beam delivery time and total monitor units for the DMLC leaf setting for intensity modulated radiotherapy (IMRT). The algorithm is demonstrated to be applicable to both the 'step-and-shoot' and 'dynamic' type of beam delivery. The graphical interpretation and numerical implementation scheme of the algorithm is illustrated using a simplified example.

View details for Web of Science ID 000074257600019

View details for PubMedID 9651030

Abstract

Apoptosis and survival of diverse cell types are under hormonal control, but intracellular mechanisms regulating cell death are unclear. The Bcl-2/Ced-9 family of proteins contains conserved Bcl-2 homology regions that mediate the formation of homo- or heterodimers important for enhancing or suppressing apoptosis. Unlike most other members of the Bcl-2 family, BAD (Bcl-xL/Bcl-2 associated death promoter), a death enhancer, has no C-terminal transmembrane domain for targeting to the outer mitochondrial membrane and nuclear envelope. We hypothesized that BAD, in addition to binding Bcl-xL and Bcl-2, may interact with proteins outside the Bcl-2 family. Using the yeast two-hybrid system to search for BAD-binding proteins in an ovarian fusion cDNA library, we identified multiple cDNA clones encoding different isoforms of 14-3-3, a group of evolutionally conserved proteins essential for signal transduction and cell cycle progression. Point mutation of BAD in one (S137A), but not the other (S113A), putative binding site found in diverse 14-3-3 interacting proteins abolished the interaction between BAD and 14-3-3 without affecting interactions between BAD and Bcl-2. Because the S137A BAD mutant presumably resembles an underphosphorylated form of BAD, we used this mutant to screen for additional BAD-interacting proteins in the yeast two-hybrid system. P11, a nerve growth factor-induced neurite extension factor and member of the calcium-binding S-100 protein family, interacted strongly with the mutant BAD but less effectively with the wild type protein. In Chinese hamster ovary (CHO) cells, transient expression of wild type BAD or its mutants increased apoptotic cell death, which was blocked by cotransfection with the baculovirus-derived cysteine protease inhibitor, P35. Cotransfection with 14-3-3 suppressed apoptosis induced by wild type or the S113A mutant BAD but not by the S137A mutant incapable of binding 14-3-3. Furthermore, cotransfection with P11 attenuated the proapoptotic effect of both wild type BAD and the S137A mutant. For both 14-3-3 and P11, direct binding to BAD was also demonstrated in vitro. These results suggest that both 14-3-3 and P11 may function as BAD-binding proteins to dampen its apoptotic activity. Because the 14-3-3 family of proteins could interact with key signaling proteins including Raf-1 kinase, protein kinase C, and phosphatidyl inositol 3 kinase, whereas P11 is an early response gene induced by the neuronal survival factor, nerve growth factor, the present findings suggest that BAD plays an important role in mediating communication between different signal transduction pathways regulated by hormonal signals and the apoptotic mechanism controlled by Bcl-2 family members.

View details for Web of Science ID A1997YD56300011

View details for PubMedID 9369453

Abstract

The invariant chain (Ii) is a glycoprotein coexpressed with the major histocompatibility complex (MHC) class II antigens. Although Ii is encoded by a single gene unlinked to the MHC gene complex, Ii and MHC class II appear to have similar patterns of tissue specific expression and generally are coordinately regulated by cytokines. Here we present evidence that transcription of the murine Ii gene is controlled by multiple cis-acting elements. The 5' regulatory region of the Ii gene appears to be combined of conserved class II regulatory elements with promoter elements commonly found in other eucaryotic genes. A region containing characteristic class II promoter elements (H box, X box, and a modified Y box) serves as an upstream enhancer in the Ii gene and might contribute to the coexpression of MHC class II and Ii genes. A series of positive control elements, the kappa B element, Sp1-binding site, and CCAAT box, are present in the Ii promoter and apparently serve distinct regulatory functions. The kappa B site in the Ii gene is a cell type-specific element, contributing to expression in a B-cell line but not in a fibroblast cell line, and the Sp1 site is required by the H-X-Y' enhancer element to stimulate promoter activity. In addition, an Ii enhancer in the first intron that specifically stimulates its own promoter has been identified. Our results suggest that a sequence match between enhancers and certain promoter elements is critical.

View details for Web of Science ID A1990DP92000006

View details for PubMedID 2115116

Abstract

In an earlier report, we described a DNA helicase that is specifically induced upon infection of Vero cells with herpes simplex virus 1. We have purified this enzyme to near homogeneity and found it to consist of three polypeptides with molecular weights of 120,000, 97,000, and 70,000. Immunochemical analysis has shown these polypeptides to be the products of three of the genes UL52, UL5, and UL8 that are required for replication of a plasmid containing a herpes simplex 1 origin (oriS). In addition to helicase activity, the enzyme contains a tightly associated DNA primase. Thus, the three-subunit enzyme is a helicase-primase complex that may prime lagging-strand synthesis as it unwinds DNA at the viral replication fork.

View details for Web of Science ID A1989U042300014

View details for PubMedID 2538835

View details for Web of Science ID A1989R859800039

View details for PubMedID 2492095