Development of a fast and feasible spectrum modeling technique for flattening filter free beams
2013; 40 (4)
Penile metastases originating from a pancreatic primary tumor: a case report
J Radiat Oncol
2012; 2 (1): 107-112
Understanding the impact of RapidArc therapy delivery errors for prostate cancer.
Journal of applied clinical medical physics
2011; 12 (3): 3409-?
To develop a fast and robust technique for the determination of optimized photon spectra for flattening filter free (FFF) beams to be applied in convolution/superposition dose calculations.A two-step optimization method was developed to derive optimal photon spectra for FFF beams. In the first step, a simple functional form of the photon spectra proposed by Ali ["Functional forms for photon spectra of clinical linacs," Phys. Med. Biol. 57, 31-50 (2011)] is used to determine generalized shapes of the photon spectra. In this method, the photon spectra were defined for the ranges of field sizes to consider the variations of the contributions of scattered photons with field size. Percent depth doses (PDDs) for each field size were measured and calculated to define a cost function, and a collapsed cone convolution (CCC) algorithm was used to calculate the PDDs. In the second step, the generalized functional form of the photon spectra was fine-tuned in a process whereby the weights of photon fluence became the optimizing free parameters. A line search method was used for the optimization and first order derivatives with respect to the optimizing parameters were derived from the CCC algorithm to enhance the speed of the optimization. The derived photon spectra were evaluated, and the dose distributions using the optimized spectra were validated.The optimal spectra demonstrate small variations with field size for the 6 MV FFF beam and relatively large variations for the 10 MV FFF beam. The mean energies of the optimized 6 MV FFF spectra were decreased from 1.31 MeV for a 3 × 3 cm(2) field to 1.21 MeV for a 40 × 40 cm(2) field, and from 2.33 MeV at 3 × 3 cm(2) to 2.18 MeV at 40 × 40 cm(2) for the 10 MV FFF beam. The developed method could significantly improve the agreement between the calculated and measured PDDs. Root mean square differences on the optimized PDDs were observed to be 0.41% (3 × 3 cm(2)) down to 0.21% (40 × 40 cm(2)) for the 6 MV FFF beam, and 0.35% (3 × 3 cm(2)) down to 0.29% (40 × 40 cm(2)) for the 10 MV FFF beam. The first order derivatives from the functional form were found to improve the speed of computational time up to 20 times compared to the other techniques.The derived photon spectra resulted in good agreements with measured PDDs over the range of field sizes investigated. The suggested method is easily applicable to commercial radiation treatment planning systems since it only requires measured PDDs as input.
View details for DOI 10.1118/1.4797469
View details for Web of Science ID 000317945900027
View details for PubMedID 23556891
IEC accelerator beam coordinate transformations for clinical Monte Carlo simulation from a phase space or full BEAMnrc particle source
AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE
2010; 33 (4): 351-355
The purpose of this study is to simulate random and systematic RapidArc delivery errors for external beam prostate radiotherapy plans in order to determine the dose sensitivity for each error type. Ten prostate plans were created with a single 360° arc. The DICOM files for these treatment plans were then imported into an in-house computer program that introduced delivery errors. Random and systematic gantry position (0.25°, 0.5°, 1°), monitor unit (MU) (1.25%, 2.5%, 5%), and multileaf collimator (MLC) position (0.5, 1, 2 mm) errors were introduced. The MLC errors were either random or one of three types of systematic errors, where the MLC banks moved in the same (MLC gaps remain unchanged) or opposing directions (increasing or decreasing the MLC gaps). The generalized equivalent uniform dose (gEUD) was calculated for the original plan and all treatment plans with errors introduced. The dose sensitivity for the cohort was calculated using linear regression for the gantry position, MU, and MLC position errors. Because there was a large amount of variability for systematic MLC position errors, the dose sensitivity of each plan was calculated and correlated with plan MU, mean MLC gap, and the percentage of MLC leaf gaps less than 1 and 2 cm for each individual plan. We found that random and systematic gantry position errors were relatively insignificant (< 0.1% gEUD change) for gantry errors up to 1°. Random MU errors were also insignificant, and systematic MU increases caused a systematic increase in gEUD. For MLC position errors, random MLC errors were relatively insignificant up to 2 mm as had been determined in previous IMRT studies. Systematic MLC shift errors caused a decrease of approximately -1% in the gEUD per mm. For systematic MLC gap open errors, the dose sensitivity was 8.2%/mm and for MLC gap close errors the dose sensitivity was -7.2%/mm. There was a large variability for MLC gap open/close errors for the ten RapidArc plans which correlated strongly with MU, mean gap width, and percentage of MLC gaps less than 1 or 2cm. This study evaluates the magnitude of various simulated RapidArc delivery errors by calculating gEUED on various prostate plans.
View details for PubMedID 21844850
Clinical significance of multi-leaf collimator positional errors for volumetric modulated arc therapy
RADIOTHERAPY AND ONCOLOGY
2010; 97 (3): 554-560
Monte Carlo simulation of clinical treatment plans require, in general, a coordinate transformation to describe the incident radiation field orientation on a patient phantom coordinate system. The International Electrotechnical Commission (IEC) has defined an accelerator coordinate system along with positive directions for gantry, couch and collimator rotations. In order to describe the incident beam's orientation with respect to the patient's coordinate system, DOSXYZnrc simulations often require transformation of the accelerator's gantry, couch and collimator angles to describe the incident beam. Similarly, versions of the voxelized Monte Carlo code (VMC(++)) require non-trivial transformation of the accelerator's gantry, couch and collimator angles to standard Euler angles α, β, γ, to describe an incident phase space source orientation with respect to the patient's coordinate system. The transformations, required by each of these Monte Carlo codes to transport phase spaces through a phantom, have been derived with a rotation operator approach. The transformations have been tested and verified against the Eclipse treatment planning system.
View details for DOI 10.1007/s13246-010-0037-1
View details for Web of Science ID 000288432000008
View details for PubMedID 21053115
Monte Carlo evaluation of RapidArc oropharynx treatment planning strategies for sparing of midline structures
Phys Med Biol
2010; 55 (16)
Inference of the optimal pretarget electron beam parameters in a Monte Carlo virtual linac model through simulated annealing
2009; 36 (6): 2309-2319
Multi-leaf collimator (MLC) positional errors occur during intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) deliveries. The impact of such errors has been evaluated for IMRT but not VMAT. The purpose of this work is to understand how random and systematic VMAT MLC positional errors affect the patient dose distribution.Eight head and neck single arc (360°) VMAT treatment plans were created. Random and two types of systematic MLC errors were simulated for error magnitudes of 0.25, 0.5, 1, 2 and 5mm. The two types of systematic MLC errors were: (1) MLC banks are shifted in the same direction (left or right) and (2) MLC banks are shifted in opposing directions resulting in smaller or larger field shapes. The MLC errors were simulated, for all control points, on both banks of active MLC leaves only.There is a linear correlation of MLC errors with gEUD for all error types. The gEUD dose sensitivities with MLC error for the PTV70 were -0.2, -0.9, -2.8 and 1.9 Gy/mm for random, systematic shift, systematic close and systematic open MLC errors, respectively. The sensitivity of VMAT plans to MLC positional errors was similar to those of IMRT plans with less than 50 segments but much less than those created for a step and shoot with more than 50 segments or sliding-window delivery technique. To maintain the PTV70 to within 2% would require that MLC open/close errors be within 0.6mm.Radiation therapy centers should have adequate quality assurance programs in place to assess open/close MLC errors (i.e. leaf gap errors) as they tend to be more impactful than random or systematic MLC shift errors.
View details for DOI 10.1016/j.radonc.2010.06.013
View details for Web of Science ID 000285222200035
View details for PubMedID 20817291
Monte Carlo simulation of RapidArc radiotherapy delivery
PHYSICS IN MEDICINE AND BIOLOGY
2008; 53 (19): N359-N370
The purpose of this study was to develop an efficient method to determine the optimal intensity distribution of the pretarget electron beam in a Monte Carlo (MC) accelerator model able to most accurately reproduce a set of measured photon field profiles for a given accelerator geometry and nominal photon beam energy. The method has the ability to reduce the number of simulations required to commission a MC accelerator model and has achieved better agreement with measurement than other methods described in literature. The method begins from a cylindrically symmetric pretarget electron beam (radius of 0.5 cm) of uniform intensity. This beam is subdivided into annular regions of fluence for which each region is individually transported through the accelerator head and into a water phantom. A simulated annealing search is then performed to determine the optimal combination of weights of the annular fluences that provide a best match between the measured dose distributions and the weighted sum of annular dose distributions for particular pretarget electron energy. When restricted to Gaussian intensity distributions, the optimization determined an optimal FWHM=1.34 mm for 18.0 MeV electrons, with a RMSE=0.49% on 40 x 40 cm2 lateral profiles. When allowed to deviate from Gaussian intensities a further reduction in RMSE was achieved. For our Clinac 21 EX accelerator MC model (based on the 1996 Varian Oncology Systems, Monte Carlo Project package), the optimal unrestricted intensity distribution was found to be a Gaussian-like solution (18.0 MeV, FWHM= 1.10 mm, 40 x 40 cm2 profile, and RMSE=0.15%) with the presence of an extra focal halo contribution on the order of 10% of the maximum Gaussian intensity. Using the optimally derived intensity, 10 x 10 and 4 x 4 cm2 profiles were found to be in agreement with measurement with a maximum RMSE=0.49%. The optimized Gaussian and unrestricted values of the electron beam FWHM were both within the range of those inferred by focal spot image measurements performed by Jaffray et al. ["X-ray sources of medical linear accelerators: Focal and extra-focal radiation," Med. Phys. 20, 1417-1427 (1993)]. The inference of an extra focal pretarget electron component may be an indicator of a deficiency in the MC model and needs further investigation.
View details for DOI 10.1118/1.3130102
View details for Web of Science ID 000266442000039
View details for PubMedID 19610319
A technique for generating phase-space-based Monte Carlo beamlets in radiotherapy applications
PHYSICS IN MEDICINE AND BIOLOGY
2008; 53 (18): N337-N347
RapidArc radiotherapy technology from Varian Medical Systems is one of the most complex delivery systems currently available, and achieves an entire intensity-modulated radiation therapy (IMRT) treatment in a single gantry rotation about the patient. Three dynamic parameters can be continuously varied to create IMRT dose distributions-the speed of rotation, beam shaping aperture and delivery dose rate. Modeling of RapidArc technology was incorporated within the existing Vancouver Island Monte Carlo (VIMC) system (Zavgorodni et al 2007 Radiother. Oncol. 84 S49, 2008 Proc. 16th Int. Conf. on Medical Physics). This process was named VIMC-Arc and has become an efficient framework for the verification of RapidArc treatment plans. VIMC-Arc is a fully automated system that constructs the Monte Carlo (MC) beam and patient models from a standard RapidArc DICOM dataset, simulates radiation transport, collects the resulting dose and converts the dose into DICOM format for import back into the treatment planning system (TPS). VIMC-Arc accommodates multiple arc IMRT deliveries and models gantry rotation as a series of segments with dynamic MLC motion within each segment. Several verification RapidArc plans were generated by the Eclipse TPS on a water-equivalent cylindrical phantom and re-calculated using VIMC-Arc. This includes one 'typical' RapidArc plan, one plan for dual arc treatment and one plan with 'avoidance' sectors. One RapidArc plan was also calculated on a DICOM patient CT dataset. Statistical uncertainty of MC simulations was kept within 1%. VIMC-Arc produced dose distributions that matched very closely to those calculated by the anisotropic analytical algorithm (AAA) that is used in Eclipse. All plans also demonstrated better than 1% agreement of the dose at the isocenter. This demonstrates the capabilities of our new MC system to model all dosimetric features required for RapidArc dose calculations.
View details for DOI 10.1088/0031-9155/53/19/N01
View details for Web of Science ID 000259116100022
View details for PubMedID 18758001
Azimuthal particle redistribution for the reduction of latent phase-space variance in Monte Carlo simulations
PHYSICS IN MEDICINE AND BIOLOGY
2007; 52 (14): 4345-4360
As radiotherapy treatment planning moves toward Monte Carlo (MC) based dose calculation methods, the MC beamlet is becoming an increasingly common optimization entity. At present, methods used to produce MC beamlets have utilized a particle source model (PSM) approach. In this work we outline the implementation of a phase-space-based approach to MC beamlet generation that is expected to provide greater accuracy in beamlet dose distributions. In this approach a standard BEAMnrc phase space is sorted and divided into beamlets with particles labeled using the inheritable particle history variable. This is achieved with the use of an efficient sorting algorithm, capable of sorting a phase space of any size into the required number of beamlets in only two passes. Sorting a phase space of five million particles can be achieved in less than 8 s on a single-core 2.2 GHz CPU. The beamlets can then be transported separately into a patient CT dataset, producing separate dose distributions (doselets). Methods for doselet normalization and conversion of dose to absolute units of Gy for use in intensity modulated radiation therapy (IMRT) plan optimization are also described.
View details for DOI 10.1088/0031-9155/53/18/N01
View details for Web of Science ID 000258728800027
View details for PubMedID 18711246
Direct aperture optimization for IMRT using Monte Carlo generated beamlets
2006; 33 (10): 3666-3679
It is well known that the use of a phase space in Monte Carlo simulation introduces a baseline level of variance that cannot be suppressed through the use of standard particle recycling techniques. This variance (termed latent phase-space variance by Sempau et al) can be a significant limiting factor in achieving accurate, low-uncertainty dose scoring results, especially near the surface of a phantom. A BEAMnrc component module (MCTWIST) has been developed to reduce the presence of latent variance in phase-space-based Monte Carlo simulations by implementing azimuthal particle redistribution (APR). For each recycled use of a phase-space particle a random rotation about the beam's central axis is applied, effectively utilizing cylindrical symmetry of the particle fluence and therefore providing a more accurate representation of the source. The MCTWIST module is unique in that no physical component is actually added to the accelerator geometry. Beam modifications are made by directly transforming particle characteristics outside of BEAMnrc/EGSnrc particle transport. Using MCTWIST, we have demonstrated a reduction in latent phase-space variance by more than a factor of 20, for a 10 x 10 cm(2) field, when compared to standard phase-space particle recycling techniques. The reduction in latent variance has enabled the achievement of dramatically smoother in-water dose profiles. This paper outlines the use of MCTWIST in Monte Carlo simulation and quantifies for the first time the latent variance reduction resulting from exploiting cylindrical phase-space symmetry.
View details for DOI 10.1088/0031-9155/52/14/021
View details for Web of Science ID 000247400000021
View details for PubMedID 17664612
Monte Carlo direct aperture optimization (MC-DAO) for IMRT
2006; 33 (6): 2198-2199
This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods.
View details for DOI 10.1118/1.2336509
View details for Web of Science ID 000241424100009
View details for PubMedID 17089832