Bio

Academic Appointments


Administrative Appointments


  • Executive Committee, Biomedical Informatics Training Program (2006 - Present)
  • Editor, Biomedical Computation Review (2004 - Present)
  • Vice-Chair E56.90, ASTM (2009 - Present)

Professional Education


  • B.S., Stanford University, Comp. Sci. and Elec. Eng. (1995)
  • M.S., Stanford University, Electrical Engineering (1995)
  • Ph.D., Stanford University, Biomedical Informatics (2002)

Research & Scholarship

Current Research and Scholarly Interests


My research interests lie at the intersection of radiology, molecular biology and informatics. I focus on developing and validating computational methodologies for extracting useful information content from anatomic, functional and molecular images, drawing upon image processing, computer vision, computer graphics, computational geometry, machine learning, biostatistics, modeling and simulation. I also work on integrating image-based information with non-imaging biomedical information such as genomics and proteomics.

Teaching

2013-14 Courses


Postdoctoral Advisees


Graduate and Fellowship Programs


Publications

Journal Articles


  • Impact of a Multiple Mice Holder on Quantitation of High-Throughput MicroPET Imaging With and Without Ct Attenuation Correction. Molecular imaging and biology Habte, F., Ren, G., Doyle, T. C., Liu, H., Cheng, Z., Paik, D. S. 2013; 15 (5): 569-575

    Abstract

    PURPOSE: The aim of this study is to evaluate the impact of scanning multiple mice simultaneously on image quantitation, relative to single mouse scans on both a micro-positron emission tomography/computed tomography (microPET/CT) scanner (which utilizes CT-based attenuation correction to the PET reconstruction) and a dedicated microPET scanner using an inexpensive mouse holder "hotel." METHODS: We developed a simple mouse holder made from common laboratory items that allows scanning multiple mice simultaneously. It is also compatible with different imaging modalities to allow multiple mice and multi-modality imaging. For this study, we used a radiotracer ((64)Cu-GB170) with a relatively long half-life (12.7 h), selected to allow scanning at times after tracer uptake reaches steady state. This also reduces the effect of decay between sequential imaging studies, although the standard decay corrections were performed. The imaging was also performed using a common tracer, 2-deoxy-2-[(18) F]fluoro-D-glucose (FDG), although the faster decay and faster pharmacokinetics of FDG may introduce greater biological variations due to differences in injection-to-scan timing. We first scanned cylindrical mouse phantoms (50 ml tubes) both in a groups of four at a time (multiple mice mode) and then individually (single mouse mode), using microPET/CT and microPET scanners to validate the process. Then, we imaged a first set of four mice with subcutaneous tumors (C2C12Ras) in both single- and multiple-mice imaging modes. Later, a second set of four normal mice were injected with FDG and scanned 1 h post-injection. Immediately after completion of the scans, ex vivo biodistribution studies were performed on all animals to provide a "gold-standard" to compare quantitative values obtained from PET. A semi-automatic threshold-based region of interest tool was used to minimize operator variability during image analysis. RESULTS: Phantom studies showed less than 4.5 % relative error difference between the single- and multiple-mice imaging modes of PET imaging with CT-based attenuation correction and 18.4 % without CT-based attenuation correction. In vivo animal studies (n = 4) showed <5 % (for (64)Cu, p > 0.686) and <15 % (for FDG, p > 0.4 except for brain image data p = 0.029) relative mean difference with respect to percent injected dose per gram (%ID/gram) between the single- and multiple-mice microPET imaging mode when CT-based attenuation correction is performed. Without CT-based attenuation correction, we observed relative mean differences of about 11 % for (64)Cu and 15 % for FDG. CONCLUSION: Our results confirmed the potential use of a microPET/CT scanner for multiple mice simultaneous imaging without significant sacrifice in quantitative accuracy as well as in image quality. Thus, the use of the mouse "hotel" is an aid to increasing instrument throughput on small animal scanners with minimal loss of quantitative accuracy.

    View details for DOI 10.1007/s11307-012-0602-y

    View details for PubMedID 23479323

  • Quantitative Imaging Biomarker Ontology (QIBO) for Knowledge Representation of Biomedical Imaging Biomarkers JOURNAL OF DIGITAL IMAGING Buckler, A. J., Ouellette, M., Danagoulian, J., Wernsing, G., Liu, T. T., Savig, E., Suzek, B. E., Rubin, D. L., Paik, D. 2013; 26 (4): 630-641

    Abstract

    A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

    View details for DOI 10.1007/s10278-013-9599-2

    View details for Web of Science ID 000322434700006

    View details for PubMedID 23589184

  • A Novel Knowledge Representation Framework for the Statistical Validation of Quantitative Imaging Biomarkers JOURNAL OF DIGITAL IMAGING Buckler, A. J., Paik, D., Ouellette, M., Danagoulian, J., Wernsing, G., Suzek, B. E. 2013; 26 (4): 614-629

    Abstract

    Quantitative imaging biomarkers are of particular interest in drug development for their potential to accelerate the drug development pipeline. The lack of consensus methods and carefully characterized performance hampers the widespread availability of these quantitative measures. A framework to support collaborative work on quantitative imaging biomarkers would entail advanced statistical techniques, the development of controlled vocabularies, and a service-oriented architecture for processing large image archives. Until now, this framework has not been developed. With the availability of tools for automatic ontology-based annotation of datasets, coupled with image archives, and a means for batch selection and processing of image and clinical data, imaging will go through a similar increase in capability analogous to what advanced genetic profiling techniques have brought to molecular biology. We report on our current progress on developing an informatics infrastructure to store, query, and retrieve imaging biomarker data across a wide range of resources in a semantically meaningful way that facilitates the collaborative development and validation of potential imaging biomarkers by many stakeholders. Specifically, we describe the semantic components of our system, QI-Bench, that are used to specify and support experimental activities for statistical validation in quantitative imaging.

    View details for DOI 10.1007/s10278-013-9598-3

    View details for Web of Science ID 000322434700005

    View details for PubMedID 23546775

  • ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format BMC BIOTECHNOLOGY Thomas, D. G., Gaheen, S., Harper, S. L., Fritts, M., Klaessig, F., Hahn-Dantona, E., Paik, D., Pan, S., Stafford, G. A., Freund, E. T., Klemm, J. D., Baker, N. A. 2013; 13

    Abstract

    BACKGROUND AND MOTIVATION: The high-throughput genomics communities have been successfully using standardized spreadsheet-based formats to capture and share data within labs and among public repositories. The nanomedicine community has yet to adopt similar standards to share the diverse and multi-dimensional types of data (including metadata) pertaining to the description and characterization of nanomaterials. Owing to the lack of standardization in representing and sharing nanomaterial data, most of the data currently shared via publications and data resources are incomplete, poorly-integrated, and not suitable for meaningful interpretation and re-use of the data. Specifically, in its current state, data cannot be effectively utilized for the development of predictive models that will inform the rational design of nanomaterials.We have developed a specification called ISA-TAB-Nano, which comprises four spreadsheet-based file formats for representing and integrating various types of nanomaterial data. Three file formats (Investigation, Study, and Assay files) have been adapted from the established ISA-TAB specification; while the Material file format was developed de novo to more readily describe the complexity of nanomaterials and associated small molecules. In this paper, we have discussed the main features of each file format and how to use them for sharing nanomaterial descriptions and assay metadata.The ISA-TAB-Nano file formats provide a general and flexible framework to record and integrate nanomaterial descriptions, assay data (metadata and endpoint measurements) and protocol information. Like ISA-TAB, ISA-TAB-Nano supports the use of ontology terms to promote standardized descriptions and to facilitate search and integration of the data. The ISA-TAB-Nano specification has been submitted as an ASTM work item to obtain community feedback and to provide a nanotechnology data-sharing standard for public development and adoption.

    View details for DOI 10.1186/1472-6750-13-2

    View details for Web of Science ID 000315806400001

    View details for PubMedID 23311978

  • In situ study of the impact of inter- and intra-reader variability on region of interest (ROI) analysis in preclinical molecular imaging. American journal of nuclear medicine and molecular imaging Habte, F., Budhiraja, S., Keren, S., Doyle, T. C., Levin, C. S., Paik, D. S. 2013; 3 (2): 175-181

    Abstract

    We estimated reader-dependent variability of region of interest (ROI) analysis and evaluated its impact on preclinical quantitative molecular imaging. To estimate reader variability, we used five independent image datasets acquired each using microPET and multispectral fluorescence imaging (MSFI). We also selected ten experienced researchers who utilize molecular imaging in the same environment that they typically perform their own studies. Nine investigators blinded to the data type completed the ROI analysis by drawing ROIs manually that delineate the tumor regions to the best of their knowledge and repeated the measurements three times, non-consecutively. Extracted mean intensities of voxels within each ROI are used to compute the coefficient of variation (CV) and characterize the inter- and intra-reader variability. The impact of variability was assessed through random samples iterated from normal distributions for control and experimental groups on hypothesis testing and computing statistical power by varying subject size, measured difference between groups and CV. The results indicate that inter-reader variability was 22.5% for microPET and 72.2% for MSFI. Additionally, mean intra-reader variability was 10.1% for microPET and 26.4% for MSFI. Repeated statistical testing showed that a total variability of CV < 50% may be needed to detect differences < 50% between experimental and control groups when six subjects (n = 6) or more are used and statistical power is adequate (80%). Surprisingly high variability has been observed mainly due to differences in the ROI placement and geometry drawn between readers, which may adversely affect statistical power and erroneously lead to negative study outcomes.

    View details for PubMedID 23526701

  • ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format BMC Biotechnology Thomas DG, Gaheen S, Harper SL, Fritts M, Klaessig F, Hahn-Dantona E, Paik DS, Pan S, Stafford G, Freund ET, Klemm J, Baker NA 2013; 13 (2)
  • In Vivo Imaging-Based Mathematical Modeling Techniques That Enhance the Understanding of Oncogene Addiction in relation to Tumor Growth COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE Nwabugwu, C., Rakhra, K., Felsher, D., Paik, D. 2013

    Abstract

    The dependence on the overexpression of a single oncogene constitutes an exploitable weakness for molecular targeted therapy. These drugs can produce dramatic tumor regression by targeting the driving oncogene, but relapse often follows. Understanding the complex interactions of the tumor's multifaceted response to oncogene inactivation is key to tumor regression. It has become clear that a collection of cellular responses lead to regression and that immune-mediated steps are vital to preventing relapse. Our integrative mathematical model includes a variety of cellular response mechanisms of tumors to oncogene inactivation. It allows for correct predictions of the time course of events following oncogene inactivation and their impact on tumor burden. A number of aspects of our mathematical model have proven to be necessary for recapitulating our experimental results. These include a number of heterogeneous tumor cell states since cells following different cellular programs have vastly different fates. Stochastic transitions between these states are necessary to capture the effect of escape from oncogene addiction (i.e., resistance). Finally, delay differential equations were used to accurately model the tumor growth kinetics that we have observed. We use this to model oncogene addiction in MYC-induced lymphoma, osteosarcoma, and hepatocellular carcinoma.

    View details for DOI 10.1155/2013/802512

    View details for Web of Science ID 000316905000001

    View details for PubMedID 23573174

  • Raman labeled nanoparticles: characterization of variability and improved method for unmixing JOURNAL OF RAMAN SPECTROSCOPY Kode, K., Shachaf, C., Elchuri, S., Nolan, G., Paik, D. S. 2012; 43 (7): 895-905

    View details for DOI 10.1002/jrs.3114

    View details for Web of Science ID 000306570400012

  • Mathematical Modeling of the Interactions between Cellular Programs in Response to Oncogene Inactivation IEEE 12TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS & BIOENGINEERING Nwabugwu, C., Rakhra, K., Felsher, D., Paik, D. 2012: 454-459
  • Raman labeled nanoparticles: characterization of variability and improved method for unmixing Journal of Raman Spectroscopy Kode K, Shachaf C, Elchuri S, Nolan G, Paik DS 2012; 43 (7): 895-905
  • Survival and Death Signals Can Predict Tumor Response to Therapy After Oncogene Inactivation SCIENCE TRANSLATIONAL MEDICINE Tran, P. T., Bendapudi, P. K., Lin, H. J., Choi, P., Koh, S., Chen, J., Horng, G., Hughes, N. P., Schwartz, L. H., Miller, V. A., Kawashima, T., Kitamura, T., Paik, D., Felsher, D. W. 2011; 3 (103)

    Abstract

    Cancers can exhibit marked tumor regression after oncogene inhibition through a phenomenon called "oncogene addiction." The ability to predict when a tumor will exhibit oncogene addiction would be useful in the development of targeted therapeutics. Oncogene addiction is likely the consequence of many cellular programs. However, we reasoned that many of these inputs may converge on aggregate survival and death signals. To test this, we examined conditional transgenic models of K-ras(G12D)--or MYC-induced lung tumors and lymphoma combined with quantitative imaging and an in situ analysis of biomarkers of proliferation and apoptotic signaling. We then used computational modeling based on ordinary differential equations (ODEs) to show that oncogene addiction could be modeled as differential changes in survival and death intracellular signals. Our mathematical model could be generalized to different imaging methods (computed tomography and bioluminescence imaging), different oncogenes (K-ras(G12D) and MYC), and several tumor types (lung and lymphoma). Our ODE model could predict the differential dynamics of several putative prosurvival and prodeath signaling factors [phosphorylated extracellular signal-regulated kinase 1 and 2, Akt1, Stat3/5 (signal transducer and activator of transcription 3/5), and p38] that contribute to the aggregate survival and death signals after oncogene inactivation. Furthermore, we could predict the influence of specific genetic lesions (p53?/?, Stat3-d358L, and myr-Akt1) on tumor regression after oncogene inactivation. Then, using machine learning based on support vector machine, we applied quantitative imaging methods to human patients to predict both their EGFR genotype and their progression-free survival after treatment with the targeted therapeutic erlotinib. Hence, the consequences of oncogene inactivation can be accurately modeled on the basis of a relatively small number of parameters that may predict when targeted therapeutics will elicit oncogene addiction after oncogene inactivation and hence tumor regression.

    View details for DOI 10.1126/scitranslmed.3002018

    View details for Web of Science ID 000295840000005

    View details for PubMedID 21974937

  • Informatics and standards for nanomedicine technology WILEY INTERDISCIPLINARY REVIEWS-NANOMEDICINE AND NANOBIOTECHNOLOGY Thomas, D. G., Klaessig, F., Harper, S. L., Fritts, M., Hoover, M. D., Gaheen, S., Stokes, T. H., Reznik-Zellen, R., Freund, E. T., Klemm, J. D., Paik, D. S., Baker, N. A. 2011; 3 (5): 511-532

    View details for DOI 10.1002/wnan.152

    View details for Web of Science ID 000298258800007

  • Shape "Break-and-Repair" Strategy and Its Application to Automated Medical Image Segmentation IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS Pu, J., Paik, D. S., Meng, X., Roos, J. E., Rubin, G. D. 2011; 17 (1): 115-124

    Abstract

    In three-dimensional medical imaging, segmentation of specific anatomy structure is often a preprocessing step for computer-aided detection/diagnosis (CAD) purposes, and its performance has a significant impact on diagnosis of diseases as well as objective quantitative assessment of therapeutic efficacy. However, the existence of various diseases, image noise or artifacts, and individual anatomical variety generally impose a challenge for accurate segmentation of specific structures. To address these problems, a shape analysis strategy termed "break-and-repair" is presented in this study to facilitate automated medical image segmentation. Similar to surface approximation using a limited number of control points, the basic idea is to remove problematic regions and then estimate a smooth and complete surface shape by representing the remaining regions with high fidelity as an implicit function. The innovation of this shape analysis strategy is the capability of solving challenging medical image segmentation problems in a unified framework, regardless of the variability of anatomical structures in question. In our implementation, principal curvature analysis is used to identify and remove the problematic regions and radial basis function (RBF) based implicit surface fitting is used to achieve a closed (or complete) surface boundary. The feasibility and performance of this strategy are demonstrated by applying it to automated segmentation of two completely different anatomical structures depicted on CT examinations, namely human lungs and pulmonary nodules. Our quantitative experiments on a large number of clinical CT examinations collected from different sources demonstrate the accuracy, robustness, and generality of the shape "break-and-repair" strategy in medical image segmentation.

    View details for DOI 10.1109/TVCG.2010.56

    View details for Web of Science ID 000284227100011

    View details for PubMedID 21071791

  • Informatics and standards for nanomedicine technology. Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology Thomas, D. G., Klaessig, F., Harper, S. L., Fritts, M., Hoover, M. D., Gaheen, S., Stokes, T. H., Reznik-Zellen, R., Freund, E. T., Klemm, J. D., Paik, D. S., Baker, N. A. 2011

    Abstract

    There are several issues to be addressed concerning the management and effective use of information (or data), generated from nanotechnology studies in biomedical research and medicine. These data are large in volume, diverse in content, and are beset with gaps and ambiguities in the description and characterization of nanomaterials. In this work, we have reviewed three areas of nanomedicine informatics: information resources; taxonomies, controlled vocabularies, and ontologies; and information standards. Informatics methods and standards in each of these areas are critical for enabling collaboration; data sharing; unambiguous representation and interpretation of data; semantic (meaningful) search and integration of data; and for ensuring data quality, reliability, and reproducibility. In particular, we have considered four types of information standards in this article, which are standard characterization protocols, common terminology standards, minimum information standards, and standard data communication (exchange) formats. Currently, because of gaps and ambiguities in the data, it is also difficult to apply computational methods and machine learning techniques to analyze, interpret, and recognize patterns in data that are high dimensional in nature, and also to relate variations in nanomaterial properties to variations in their chemical composition, synthesis, characterization protocols, and so on. Progress toward resolving the issues of information management in nanomedicine using informatics methods and standards discussed in this article will be essential to the rapidly growing field of nanomedicine informatics. WIREs Nanomed Nanobiotechnol 2011 DOI: 10.1002/wnan.152 This article is a U.S. Government work, and as such, is in the public domain in the United States of America. For further resources related to this article, please visit the WIREs website.

    View details for PubMedID 21721140

  • Assessing operating characteristics of CAD algorithms in the absence of a gold standard MEDICAL PHYSICS Choudhury, K. R., Paik, D. S., Yi, C. A., Napel, S., Roos, J., Rubin, G. D. 2010; 37 (4): 1788-1795

    Abstract

    The authors examine potential bias when using a reference reader panel as "gold standard" for estimating operating characteristics of CAD algorithms for detecting lesions. As an alternative, the authors propose latent class analysis (LCA), which does not require an external gold standard to evaluate diagnostic accuracy.A binomial model for multiple reader detections using different diagnostic protocols was constructed, assuming conditional independence of readings given true lesion status. Operating characteristics of all protocols were estimated by maximum likelihood LCA. Reader panel and LCA based estimates were compared using data simulated from the binomial model for a range of operating characteristics. LCA was applied to 36 thin section thoracic computed tomography data sets from the Lung Image Database Consortium (LIDC): Free search markings of four radiologists were compared to markings from four different CAD assisted radiologists. For real data, bootstrap-based resampling methods, which accommodate dependence in reader detections, are proposed to test of hypotheses of differences between detection protocols.In simulation studies, reader panel based sensitivity estimates had an average relative bias (ARB) of -23% to -27%, significantly higher (p-value < 0.0001) than LCA (ARB--2% to -6%). Specificity was well estimated by both reader panel (ARB -0.6% to -0.5%) and LCA (ARB 1.4%-0.5%). Among 1145 lesion candidates LIDC considered, LCA estimated sensitivity of reference readers (55%) was significantly lower (p-value 0.006) than CAD assisted readers' (68%). Average false positives per patient for reference readers (0.95) was not significantly lower (p-value 0.28) than CAD assisted readers' (1.27).Whereas a gold standard based on a consensus of readers may substantially bias sensitivity estimates, LCA may be a significantly more accurate and consistent means for evaluating diagnostic accuracy.

    View details for DOI 10.1118/1.3352687

    View details for Web of Science ID 000276211200044

    View details for PubMedID 20443501

  • Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistance EUROPEAN RADIOLOGY Roos, J. E., Paik, D., Olsen, D., Liu, E. G., Chow, L. C., Leung, A. N., Mindelzun, R., Choudhury, K. R., Naidich, D. P., Napel, S., Rubin, G. D. 2010; 20 (3): 549-557

    Abstract

    The diagnostic performance of radiologists using incremental CAD assistance for lung nodule detection on CT and their temporal variation in performance during CAD evaluation was assessed.CAD was applied to 20 chest multidetector-row computed tomography (MDCT) scans containing 190 non-calcified > or =3-mm nodules. After free search, three radiologists independently evaluated a maximum of up to 50 CAD detections/patient. Multiple free-response ROC curves were generated for free search and successive CAD evaluation, by incrementally adding CAD detections one at a time to the radiologists' performance.The sensitivity for free search was 53% (range, 44%-59%) at 1.15 false positives (FP)/patient and increased with CAD to 69% (range, 59-82%) at 1.45 FP/patient. CAD evaluation initially resulted in a sharp rise in sensitivity of 14% with a minimal increase in FP over a time period of 100 s, followed by flattening of the sensitivity increase to only 2%. This transition resulted from a greater prevalence of true positive (TP) versus FP detections at early CAD evaluation and not by a temporal change in readers' performance. The time spent for TP (9.5 s +/- 4.5 s) and false negative (FN) (8.4 s +/- 6.7 s) detections was similar; FP decisions took two- to three-times longer (14.4 s +/- 8.7 s) than true negative (TN) decisions (4.7 s +/- 1.3 s).When CAD output is ordered by CAD score, an initial period of rapid performance improvement slows significantly over time because of non-uniformity in the distribution of TP CAD output and not to a changing reader performance over time.

    View details for DOI 10.1007/s00330-009-1596-y

    View details for Web of Science ID 000274544800005

    View details for PubMedID 19760237

  • Noninvasive detection of therapeutic cytolytic T cells with F-18-FHBG PET in a patient with glioma NATURE CLINICAL PRACTICE ONCOLOGY Yaghoubi, S. S., Jensen, M. C., Satyamurthy, N., Budhiraja, S., Paik, D., Czernin, J., Gambhir, S. S. 2009; 6 (1): 53-58

    Abstract

    A 57-year-old man had been diagnosed with grade IV glioblastoma multiforme and was enrolled in a trial of adoptive cellular immunotherapy. The trial involved infusion of ex vivo expanded autologous cytolytic CD8+ T cells (CTLs), genetically engineered to express the interleukin 13 zetakine gene (which encodes a receptor protein that targets these T cells to tumor cells) and the herpes simplex virus 1 thymidine kinase (HSV1 tk) suicide gene, and PET imaging reporter gene.MRI, whole-body and brain PET scan with (18)F-radiolabelled 9-[4-fluoro-3-(hydroxymethyl)butyl]guanine ((18)F-FHBG) to detect CTLs that express HSV1 tk, and safety monitoring after injection of (18)F-FHBG.MRI detected grade III-IV glioblastoma multiforme plus two tumors recurrences that developed after resection of the initial tumor.Surgical resection of primary glioblastoma tumor, enrollment in CTL therapy trial, reresection of glioma recurrences, infusion of approximately 1 x 10(9) CTLs into the site of tumor reresection, and (18)F-FHBG PET scan to detect infused CTLs.

    View details for DOI 10.1038/ncponc1278

    View details for Web of Science ID 000261845300011

    View details for PubMedID 19015650

  • Adaptive border marching algorithm: Automatic lung segmentation on chest CT images COMPUTERIZED MEDICAL IMAGING AND GRAPHICS Pu, J., Roos, J., Yi, C. A., Napel, S., Rubin, G. D., Paik, D. S. 2008; 32 (6): 452-462

    Abstract

    Segmentation of the lungs in chest-computed tomography (CT) is often performed as a preprocessing step in lung imaging. This task is complicated especially in presence of disease. This paper presents a lung segmentation algorithm called adaptive border marching (ABM). Its novelty lies in the fact that it smoothes the lung border in a geometric way and can be used to reliably include juxtapleural nodules while minimizing oversegmentation of adjacent regions such as the abdomen and mediastinum. Our experiments using 20 datasets demonstrate that this computational geometry algorithm can re-include all juxtapleural nodules and achieve an average oversegmentation ratio of 0.43% and an average under-segmentation ratio of 1.63% relative to an expert determined reference standard. The segmentation time of a typical case is under 1min on a typical PC. As compared to other available methods, ABM is more robust, more efficient and more straightforward to implement, and once the chest CT images are input, there is no further interaction needed from users. The clinical impact of this method is in potentially avoiding false negative CAD findings due to juxtapleural nodules and improving volumetry and doubling time accuracy.

    View details for DOI 10.1016/j.compmedimag.2008.04.005

    View details for Web of Science ID 000258739700004

    View details for PubMedID 18515044

  • Polyp enhancing level set evolution of colon wall: Method and pilot study IEEE TRANSACTIONS ON MEDICAL IMAGING Konukoglu, E., Acar, B., Paik, D. S., Beaulieu, C. F., Rosenberg, J., Napel, S. 2007; 26 (12): 1649-1656

    Abstract

    Computer aided detection (CAD) in computed tomography colonography (CTC) aims at detecting colonic polyps that are the precursors of colon cancer. In this work, we propose a colon wall evolution algorithm polyp enhancing level sets (PELS) based on the level-set formulation that regularizes and enhances polyps as a preprocessing step to CTC CAD algorithms. The underlying idea is to evolve the polyps towards spherical protrusions on the colon wall while keeping other structures, such as haustral folds, relatively unchanged and, thereby, potentially improve the performance of CTC CAD algorithms, especially for smaller polyps. To evaluate our methods, we conducted a pilot study using an arbitrarily chosen CTC CAD method, the surface normal overlap (SNO) CAD algorithm, on a nine patient CTC data set with 47 polyps of sizes ranging from 2.0 to 17.0 mm in diameter. PELS increased the maximum sensitivity by 8.1% (from 21/37 to 24/37) for small polyps of sizes ranging from 5.0 to 9.0 mm in diameter. This is accompanied by a statistically significant separation between small polyps and false positives. PELS did not change the CTC CAD performance significantly for larger polyps.

    View details for DOI 10.1109/TMI.2007.901429

    View details for Web of Science ID 000251376500004

    View details for PubMedID 18092735

  • Registration of lung nodules using a semi-rigid model: Method and preliminary results MEDICAL PHYSICS Sun, S., Rubin, G. D., Paik, D., Steiner, R. M., Zhuge, F., Napel, S. 2007; 34 (2): 613-626

    Abstract

    The tracking of lung nodules across computed tomography (CT) scans acquired at different times for the same patient is helpful for the determination of malignancy. We are developing a nodule registration system to facilitate this process. We propose to use a semi-rigid method that considers principal structures surrounding the nodule and allows relative movements among the structures. The proposed similarity metric, which evaluates both the image correlation and the degree of elastic deformation amongst the structures, is maximized by a two-layered optimization method, employing a simulated annealing framework. We tested our method by simulating five cases that represent physiological deformation as well as different nodule shape/size changes with time. Each case is made up of a source and target scan, where the source scan consists of a nodule-free patient CT volume into which we inserted ten simulated lung nodules, and the target scan is the result of applying a known, physiologically based nonrigid transformation to the nodule-free source scan, into which we inserted modified versions of the corresponding nodules at the same, known locations. Five different modification strategies were used, one for each of the five cases: (1) nodules maintain size and shape, (2) nodules disappear, (3) nodules shrink uniformly by a factor of 2, (4) nodules grow uniformly by a factor of 2, and (5) nodules grow nonuniformly. We also matched 97 real nodules in pairs of scans (acquired at different times) from 12 patients and compared our registration to a radiologist's visual determination. In the simulation experiments, the mean absolute registration errors were 1.0+/-0.8 mm (s.d.), 1.1+/-0.7 mm (s.d.), 1.0+/-0.7 mm (s.d.), 1.0+/-0.6 mm (s.d.), and 1.1+/- 0.9 mm (s.d.) for the five cases, respectively. For the 97 nodule pairs in 12 patient scans, the mean absolute registration error was 1.4+/-0.8 mm (s.d.).

    View details for DOI 10.1118/1.2432073

    View details for Web of Science ID 000244424200027

    View details for PubMedID 17388179

  • Toward a nanobioinformatics infrastructure for nanotechnology-based prostate cancer therapeutic response tracking PROCEEDINGS OF THE 7TH IEEE INTERNATIONAL SYMPOSIUM ON BIOINFORMATICS AND BIOENGINEERING, VOLS I AND II Paik, D. S. 2007: 486-486
  • CT colonography: Influence of 3D viewing and polyp candidate features on interpretation with computer-aided detection RADIOLOGY Shi, R., Schraedley-Desmond, P., Napel, S., Olcott, E. W., Jeffrey, R. B., Yee, J., Zalis, M. E., Margolis, D., Paik, D. S., Sherbondy, A. J., Sundaram, P., Beaulieu, C. F. 2006; 239 (3): 768-776

    Abstract

    To retrospectively determine if three-dimensional (3D) viewing improves radiologists' accuracy in classifying true-positive (TP) and false-positive (FP) polyp candidates identified with computer-aided detection (CAD) and to determine candidate polyp features that are associated with classification accuracy, with known polyps serving as the reference standard.Institutional review board approval and informed consent were obtained; this study was HIPAA compliant. Forty-seven computed tomographic (CT) colonography data sets were obtained in 26 men and 10 women (age range, 42-76 years). Four radiologists classified 705 polyp candidates (53 TP candidates, 652 FP candidates) identified with CAD; initially, only two-dimensional images were used, but these were later supplemented with 3D rendering. Another radiologist unblinded to colonoscopy findings characterized the features of each candidate, assessed colon distention and preparation, and defined the true nature of FP candidates. Receiver operating characteristic curves were used to compare readers' performance, and repeated-measures analysis of variance was used to test features that affect interpretation.Use of 3D viewing improved classification accuracy for three readers and increased the area under the receiver operating characteristic curve to 0.96-0.97 (P<.001). For TP candidates, maximum polyp width (P=.038), polyp height (P=.019), and preparation (P=.004) significantly affected accuracy. For FP candidates, colonic segment (P=.007), attenuation (P<.001), surface smoothness (P<.001), distention (P=.034), preparation (P<.001), and true nature of candidate lesions (P<.001) significantly affected accuracy.Use of 3D viewing increases reader accuracy in the classification of polyp candidates identified with CAD. Polyp size and examination quality are significantly associated with accuracy.

    View details for Web of Science ID 000237738600018

    View details for PubMedID 16714460

  • Optimization of a tomosynthesis system for the detection of lung nodules MEDICAL PHYSICS Pineda, A. R., Yoon, S., Paik, D. S., Fahrig, R. 2006; 33 (5): 1372-1379

    Abstract

    Mathematical observers that track human performance can be used to reduce the number of human observer studies needed to optimize imaging systems. The performance of human observers for the detection of a 3.6 mm lung nodule in anatomical backgrounds was measured as a function of varying tomosynthetic angle and compared with mathematical observers. The human observer results showed a dramatic increase in the percent of correct responses, from 80% in the projection images to 96% in the projection images with a tomosynthetic angle of just 3 degrees. This result suggests the potential usefulness of the scanned beam digital x-ray system for this application. Given the small number of images (40) used per tomosynthetic angle and the highly nonstationary statistical nature of the backgrounds, the nonprewhitening eye observer achieved a higher performance than the channelized Hotelling observer using a Laguerre-Gauss basis. The channelized Hotelling observer with internal noise and the eye filter matched to the projection data were shown to track human performance as the tomosynthetic angle changed. The validation of these mathematical observers extends their applicability to the optimization of tomosynthesis systems.

    View details for DOI 10.1118/1.2190329

    View details for Web of Science ID 000237673600021

    View details for PubMedID 16752573

  • Pulmonary nodules on multi-detector row CT scans: Performance comparison of radiologists and computer-aided detection RADIOLOGY Rubin, G. D., Lyo, J. K., Paik, D. S., Sherbondy, A. J., Chow, L. C., Leung, A. N., Mindelzun, R., Schraedley-Desmond, P. K., Zinck, S. E., Naidich, D. P., Napel, S. 2005; 234 (1): 274-283

    Abstract

    To compare the performance of radiologists and of a computer-aided detection (CAD) algorithm for pulmonary nodule detection on thin-section thoracic computed tomographic (CT) scans.The study was approved by the institutional review board. The requirement of informed consent was waived. Twenty outpatients (age range, 15-91 years; mean, 64 years) were examined with chest CT (multi-detector row scanner, four detector rows, 1.25-mm section thickness, and 0.6-mm interval) for pulmonary nodules. Three radiologists independently analyzed CT scans, recorded the locus of each nodule candidate, and assigned each a confidence score. A CAD algorithm with parameters chosen by using cross validation was applied to the 20 scans. The reference standard was established by two experienced thoracic radiologists in consensus, with blind review of all nodule candidates and free search for additional nodules at a dedicated workstation for three-dimensional image analysis. True-positive (TP) and false-positive (FP) results and confidence levels were used to generate free-response receiver operating characteristic (ROC) plots. Double-reading performance was determined on the basis of TP detections by either reader.The 20 scans showed 195 noncalcified nodules with a diameter of 3 mm or more (reference reading). Area under the alternative free-response ROC curve was 0.54, 0.48, 0.55, and 0.36 for CAD and readers 1-3, respectively. Differences between reader 3 and CAD and between readers 2 and 3 were significant (P < .05); those between CAD and readers 1 and 2 were not significant. Mean sensitivity for individual readings was 50% (range, 41%-60%); double reading resulted in increase to 63% (range, 56%-67%). With CAD used at a threshold allowing only three FP detections per CT scan, mean sensitivity was increased to 76% (range, 73%-78%). CAD complemented individual readers by detecting additional nodules more effectively than did a second reader; CAD-reader weighted kappa values were significantly lower than reader-reader weighted kappa values (Wilcoxon rank sum test, P < .05).With CAD used at a level allowing only three FP detections per CT scan, sensitivity was substantially higher than with conventional double reading.

    View details for DOI 10.1148/radiol.2341040589

    View details for Web of Science ID 000225864800038

    View details for PubMedID 15537839

  • Registration of central paths and colonic polyps between supine and prone scans in computed tomography colonography: Pilot study MEDICAL PHYSICS Ping, L., Napel, S., Acar, B., Paik, D. S., Jeffrey, R. B., Beaulieu, C. F. 2004; 31 (10): 2912-2923

    Abstract

    Computed tomography colonography (CTC) is a minimally invasive method that allows the evaluation of the colon wall from CT sections of the abdomen/pelvis. The primary goal of CTC is to detect colonic polyps, precursors to colorectal cancer. Because imperfect cleansing and distension can cause portions of the colon wall to be collapsed, covered with water, and/or covered with retained stool, patients are scanned in both prone and supine positions. We believe that both reading efficiency and computer aided detection (CAD) of CTC images can be improved by accurate registration of data from the supine and prone positions. We developed a two-stage approach that first registers the colonic central paths using a heuristic and automated algorithm and then matches polyps or polyp candidates (CAD hits) by a statistical approach. We evaluated the registration algorithm on 24 patient cases. After path registration, the mean misalignment distance between prone and supine identical anatomic landmarks was reduced from 47.08 to 12.66 mm, a 73% improvement. The polyp registration algorithm was specifically evaluated using eight patient cases for which radiologists identified polyps separately for both supine and prone data sets, and then manually registered corresponding pairs. The algorithm correctly matched 78% of these pairs without user input. The algorithm was also applied to the 30 highest-scoring CAD hits in the prone and supine scans and showed a success rate of 50% in automatically registering corresponding polyp pairs. Finally, we computed the average number of CAD hits that need to be manually compared in order to find the correct matches among the top 30 CAD hits. With polyp registration, the average number of comparisons was 1.78 per polyp, as opposed to 4.28 comparisons without polyp registration.

    View details for DOI 10.1118/1.1796171

    View details for Web of Science ID 000224743200025

    View details for PubMedID 15543800

  • Surface normal overlap: A computer-aided detection algorithm, with application to colonic polyps and lung nodules in helical CT IEEE TRANSACTIONS ON MEDICAL IMAGING Paik, D. S., Beaulieu, C. F., Rubin, G. D., Acar, B., Jeffrey, R. B., Yee, J., Dey, J., Napel, S. 2004; 23 (6): 661-675

    Abstract

    We developed a novel computer-aided detection (CAD) algorithm called the surface normal overlap method that we applied to colonic polyp detection and lung nodule detection in helical computed tomography (CT) images. We demonstrate some of the theoretical aspects of this algorithm using a statistical shape model. The algorithm was then optimized on simulated CT data and evaluated using a per-lesion cross-validation on 8 CT colonography datasets and on 8 chest CT datasets. It is able to achieve 100% sensitivity for colonic polyps 10 mm and larger at 7.0 false positives (FPs)/dataset and 90% sensitivity for solid lung nodules 6 mm and larger at 5.6 FP/dataset.

    View details for DOI 10.1109/TMI.2004.826362

    View details for Web of Science ID 000221723600001

    View details for PubMedID 15191141

  • Computed tomography colonography - Feasibility of computer-aided polyp detection in a "First reader" paradigm JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY Mani, A., Napel, S., Paik, D. S., Jeffrey, R. B., Yee, J., Olcott, E. W., Prokesch, R., Davila, M., Schraedley-Desmond, P., Beaulieu, C. F. 2004; 28 (3): 318-326

    Abstract

    : To determine the feasibility of a computer-aided detection (CAD) algorithm as the "first reader" in computed tomography colonography (CTC).: In phase 1 of a 2-part blind trial, we measured the performance of 3 radiologists reading 41 CTC studies without CAD. In phase 2, readers interpreted the same cases using a CAD list of 30 potential polyps.: Unassisted readers detected, on average, 63% of polyps > or =10 mm in diameter. Using CAD, the sensitivity was 74% (not statistically different). Per-patient analysis showed a trend toward increased sensitivity for polyps > or =10 mm in diameter, from 73% to 90% with CAD (not significant) without decreasing specificity. Computer-aided detection significantly decreased interobserver variability (P = 0.017). Average time to detection of the first polyp decreased significantly with CAD, whereas total reading case reading time was unchanged.: Computer-aided detection as a first reader in CTC was associated with similar per-polyp and per-patient detection sensitivity to unassisted reading. Computer-aided detection decreased interobserver variability and reduced the time required to detect the first polyp.

    View details for Web of Science ID 000221234500003

    View details for PubMedID 15100534

  • CT colonography: Does improved z resolution help computer-aided polyp detection? MEDICAL PHYSICS Sundaram, P., Beaulieu, C. F., Paik, D. S., Schraedley-Desmond, P., Napel, S. 2003; 30 (10): 2663-2674

    Abstract

    Multislice helical CT offers several retrospective choices of longitudinal (z) resolution at a given detector collimation setting. We sought to determine the effect of z resolution on the performance of a computer-aided colonic polyp detector, since a human reader and a computer-aided polyp detector may have optimal performances at different z resolutions. We ran a computer-aided polyp detection algorithm on phantom data sets as well as data obtained from a single patient. All data were reconstructed at various slice thicknesses ranging from 1.25 to 10 mm. We studied the performance of the detector at various ranges of polyp sizes using free-response receiver-operating characteristic analyses. We also studied contrast-to-noise ratios (CNR) as a function of slice thickness and polyp size. For the phantom data, reducing the slice thickness from 5 to 1.25 mm improves sensitivity from 84.5% to 98.3% (all polyps), from 61.4% to 95.5% (polyps in the range [0, 5) mm) and from 97.7% to 100% (polyps in the range [5, 10) mm) at a false positive rate of 20 per data set. For polyps larger than 10 mm, there is no significant improvement in detection sensitivity when slice thickness is reduced. CNRs showed expected behavior with slice thickness and polyp size, but in all cases remained high (> 4). The results for the patient data followed similar patterns to that of the phantom case. Thus we conclude that for this detector, the optimal slice thickness is dependent upon the size of the smallest polyps to be detected. For detection of polyps 10 mm and larger, reconstruction of 5 mm sections may be sufficient. Further study is required to generalize these results to a broader population of patients scanned on different scanners.

    View details for DOI 10.1118/1.1599985

    View details for Web of Science ID 000185953700012

    View details for PubMedID 14596303

  • Edge displacement field-based classification for improved detection of polyps in CT colonography IEEE TRANSACTIONS ON MEDICAL IMAGING Acar, B., Beaulieu, C. F., Gokturk, S. B., Tomasi, C., Paik, D. S., Jeffrey, R. B., Yee, J., Napel, S. 2002; 21 (12): 1461-1467

    Abstract

    Colorectal cancer can easily be prevented provided that the precursors to tumors, small colonic polyps, are detected and removed. Currently, the only definitive examination of the colon is fiber-optic colonoscopy, which is invasive and expensive. Computed tomographic colonography (CTC) is potentially a less costly and less invasive alternative to FOC. It would be desirable to have computer-aided detection (CAD) algorithms to examine the large amount of data CTC provides. Most current CAD algorithms have high false positive rates at the required sensitivity levels. We developed and evaluated a postprocessing algorithm to decrease the false positive rate of such a CAD method without sacrificing sensitivity. Our method attempts to model the way a radiologist recognizes a polyp while scrolling a cross-sectional plane through three-dimensional computed tomography data by classification of the changes in the location of the edges in the two-dimensional plane. We performed a tenfold cross-validation study to assess its performance using sensitivity/specificity analysis on data from 48 patients. The mean specificity over all experiments increased from 0.19 (0.35) to 0.47 (0.56) for a sensitivity of 1.00 (0.95).

    View details for DOI 10.1109/TMI.2002.806405

    View details for Web of Science ID 000180871100003

    View details for PubMedID 12588030

  • Quantification of distention in CT colonography: Development and validation of three computer algorithms RADIOLOGY Hung, P. W., Paik, D. S., Napel, S., Yee, J., Jeffrey, R. B., Steinauer-Gebauer, A., Min, J., Jathavedam, A., Beaulieu, C. F. 2002; 222 (2): 543-554

    Abstract

    Three bowel distention-measuring algorithms for use at computed tomographic (CT) colonography were developed, validated in phantoms, and applied to a human CT colonographic data set. The three algorithms are the cross-sectional area method, the moving spheres method, and the segmental volume method. Each algorithm effectively quantified distention, but accuracy varied between methods. Clinical feasibility was demonstrated. Depending on the desired spatial resolution and accuracy, each algorithm can quantitatively depict colonic diameter in CT colonography.

    View details for Web of Science ID 000173502500035

    View details for PubMedID 11818626

  • Carotid disease: Automated analysis with cardiac-gated three-dimensional US - Technique and preliminary results RADIOLOGY Napel, S., Xu, H. B., Paik, D. S., Ross, B. A., Sumanaweera, T. S., Hossack, J. A., Jeffrey, R. B. 2002; 222 (2): 560-563

    Abstract

    Automatic analysis was performed of four-dimensional ultrasonographic (US) data in the carotid artery. The data, which were acquired in 31 subjects (eight healthy volunteers and 23 patients) by using a US scanner fitted with a special probe, were successfully processed. Acquisition time averaged 12 minutes. Data for all healthy volunteers (n = 8) and patients with complete occlusions (n = 3) were correctly classified. Data for two of the 12 patients with mild to severe (but not occlusive) disease were misclassified by one category.

    View details for Web of Science ID 000173502500037

    View details for PubMedID 11818628

  • A statistical 3-D pattern processing method for computer-aided detection of polyps in CT colonography IEEE TRANSACTIONS ON MEDICAL IMAGING Gokturk, S. B., Tomasi, C., Acar, B., Beaulieu, C. F., Paik, D. S., Jeffrey, R. B., Yee, J., Napel, S. 2001; 20 (12): 1251-1260

    Abstract

    Adenomatous polyps in the colon are believed to be the precursor to colorectal carcinoma, the second leading cause of cancer deaths in United States. In this paper, we propose a new method for computer-aided detection of polyps in computed tomography (CT) colonography (virtual colonoscopy), a technique in which polyps are imaged along the wall of the air-inflated, cleansed colon with X-ray CT. Initial work with computer aided detection has shown high sensitivity, but at a cost of too many false positives. We present a statistical approach that uses support vector machines to distinguish the differentiating characteristics of polyps and healthy tissue, and uses this information for the classification of the new cases. One of the main contributions of the paper is the new three-dimensional pattern processing approach, called random orthogonal shape sections method, which combines the information from many random images to generate reliable signatures of shape. The input to the proposed system is a collection of volume data from candidate polyps obtained by a high-sensitivity, low-specificity system that we developed previously. The results of our ten-fold cross-validation experiments show that, on the average, the system increases the specificity from 0.19 (0.35) to 0.69 (0.74) at a sensitivity level of 1.0 (0.95).

    View details for Web of Science ID 000173296700006

    View details for PubMedID 11811825

  • Prediction of aortoiliac stent-graft length: Comparison of measurement methods RADIOLOGY Tillich, M., Hill, B. B., Paik, D. S., Petz, K., Napel, S., Zarins, C. K., Rubin, G. D. 2001; 220 (2): 475-483

    Abstract

    To determine the accuracy of helical computed tomography (CT), projectional angiography derived from CT angiography, and intravascular ultrasonographic withdrawal (IUW) length measurements for predicting appropriate aortoiliac stent-graft length.Helical CT data from 33 patients were analyzed before and after endovascular repair of abdominal aortic aneurysm (Aneuryx graft, n = 31; Excluder graft, n = 2). The aortoiliac length of the median luminal centerline (MLC) and the shortest path (SP) that remained at least one common iliac arterial radius away from the vessel wall were calculated. Conventional angiographic measurements were simulated from CT data as the length of the three-dimensional MLC projected onto four standard viewing planes. These predeployment lengths and IUW length, available in 24 patients, were compared with the aortoiliac arterial length after stent-graft deployment.The mean error values of SP, MLC, the maximum projected MLC, and IUW were -2.1 mm +/- 4.6 (SD) (P =.013), 9.8 mm +/- 6.8 (P <.001), -5.2 mm +/- 7.8 (P <.001), and -14.1 mm +/- 9.3 (P <.001), respectively. The preprocedural prediction of the postprocedural aortoiliac length with the SP was significantly more accurate than that with the MLC (P <.001), maximum projected MLC (P <.001), and IUW (P <.001).The shortest aortoiliac path length maintaining at least one radius distance from the vessel wall most accurately enabled stent-graft length prediction for 31 AneuRx and two Excluder stent-grafts.

    View details for Web of Science ID 000169988700029

    View details for PubMedID 11477256

  • Iliac arterial injuries after endovascular repair of abdominal aortic aneurysms: Correlation with iliac curvature and diameter RADIOLOGY Tillich, M., Bell, R. E., Paik, D. S., Fleischmann, D., Sofilos, M. C., Logan, L. J., Rubin, G. D. 2001; 219 (1): 129-136

    Abstract

    To determine the relationship between iliac arterial tortuosity and cross-sectional area and the occurrence of iliac arterial injuries following transfemoral delivery of endovascular prostheses for repair of abdominal aortic aneurysms.Iliac arterial curvature values and orthogonal cross-sectional areas were determined from helical computed tomographic (CT) data acquired in 42 patients prior to transfemoral delivery of aortic stent-grafts. The curvature and luminal cross-sectional area orthogonal to the median centerline were quantified every millimeter along the median centerline of the iliac arteries. An indicator of global iliac tortuosity, the iliac tortuosity index, was defined as the sum of the curvature values for all points with a curvature of 0.3 cm(-1) or greater, and cross-sectional area (CSA) was indexed for all points as the mean cross-sectional diameter (D = 2 radical[CSA/pi]). Following stent-graft deployment, helical CT data were analyzed for the presence of iliac arterial dissections independently by two reviewers.Eighteen dissections were detected in 16 patients. The iliac tortuosity index was significantly larger in iliac arteries with dissections (35.5 +/- 20.8 [mean +/- SD]) when compared with both nondissected contralateral iliac arteries in the same patients (26.1 +/- 21.0, P =.001) and iliac arteries in patients without any iliac arterial injury (20 +/- 9, P =.009). The tortuosity index was higher ipsilateral to the primary component delivery in 10 of 11 iliac dissections that developed along the primary component delivery route.A high degree of iliac arterial tortuosity appears to impart greater risk for the development of iliac arterial injuries in patients undergoing transfemoral delivery of endovascular devices.

    View details for Web of Science ID 000167667400019

    View details for PubMedID 11274547

  • Quantitative determination of age-related geometric changes in the normal abdominal aorta JOURNAL OF VASCULAR SURGERY Fleischmann, D., Hastie, T. J., Dannegger, F. C., Paik, D. S., Tillich, M., Zarins, C. K., Rubin, G. D. 2001; 33 (1): 97-105

    Abstract

    We conducted a novel quantitative three-dimensional analysis of computed tomography (CT) angiograms to establish the relationship between aortic geometry and age, sex, and body surface area in healthy subjects.Abdominal helical CT angiograms from 77 healthy potential renal donors (33 men/44 women; mean age, 44 years; age range, 19-67 years) were selected. In each dataset, orthonormal cross-sectional area and diameter measurements were obtained at 1-mm intervals along the automatically calculated central axis of the abdominal aorta. The aorta was subdivided into six consecutive anatomic segments (supraceliac, supramesenteric, suprarenal, inter-renal, proximal infrarenal, and distal infrarenal). The interrelated effects of anatomic segment, age, sex, and body surface area on cross-sectional dimensions were analyzed with linear mixed-effects and varying-coefficient statistical models.We found that significant effects of sex and of body surface area on aortic diameters were similar at all anatomic levels. The effect of age, however, was interrelated with anatomic position, and gradually decreasing slopes of significant diameter-versus-age relationships along the aorta, which ranged from 0.14 mm/y (P <.0001) proximally to 0.03 mm/y (P =.013) distally in the abdominal aorta, were shown.The abdominal aorta undergoes considerable geometric changes when a patient is between 19 and 67 years of age, leading to an increase of aortic taper with time. The hemodynamic consequences of this geometric evolution for the development of aortic disease still need to be established.

    View details for Web of Science ID 000166576900022

    View details for PubMedID 11137929

  • A new 3-D volume processing method for polyp detection PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4 Gokturk, S. B., Tomasi, C., Acar, B., Paik, D., Beaulieu, C., Napel, S. 2001; 23: 2522-2525
  • Assessment of an optical flow field-based polyp detector for CT colonography PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4 Acar, B., Beaulieu, C. F., Paik, D. S., Gokturk, S. B., Tomasi, C., Yee, J., Napel, S. 2001; 23: 2774-2777
  • Medial axis registration of supine and prone CT colonography data PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4 Acar, B., Napel, S., Paik, D. S., Li, P., Yee, J., Jeffrey, R. B., Beaulieu, C. F. 2001; 23: 2433-2436
  • Visualization modes for CT colonography using cylindrical and planar map projections JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY Paik, D. S., Beaulieu, C. F., Jeffrey, R. B., Karadi, C. A., Napel, S. 2000; 24 (2): 179-188

    Abstract

    The purpose of this study was to demonstrate the limitations to the effectiveness of CT colonography, colloquially called virtual colonoscopy (VC), for detecting polyps in the colon and to describe a new technique, map projection CT colonography using Mercator projection and stereographic projection, that overcomes these limitations.In one experiment, data sets from nine patients undergoing CT colonography were analyzed to determine the percentage of the mucosal surface visible in various visualization modes as a function of field of view (FOV). In another experiment, 40 digitally synthesized polyps of various sizes (10, 7, 5, and 3.5 mm) were randomly inserted into four copies of one patient data set. Both Mercator and stereographic projections were used to visualize the surface of the colon of each data set. The sensitivity and positive predictive value (PPV) were calculated and compared with the results of an earlier study of visualization modes using the same CT colonography data.The percentage of mucosal surface visualized by VC increases with greater FOV but only approaches that of map projection VC (98.8%) at a distorting, very high FOV. For both readers and polyp sizes of > or =7 mm, sensitivity for Mercator projection (87.5%) and stereographic projection (82.5%) was significantly greater (p < 0.05) than for viewing axial slices (62.5%), and Mercator projection was significantly more sensitive than VC (67.5%). Mercator and stereographic projection had PPVs of 75.4 and 78.9%, respectively.The sensitivity of conventional CT colonography is limited by the percentage of the mucosal surface seen. Map projection CT colonography overcomes this problem and provides a more sensitive method with a high PPV for detecting polyps than other methods currently being investigated.

    View details for Web of Science ID 000086026800001

    View details for PubMedID 10752876

  • Automated quantification of 4D ultrasound for carotid artery disease CARS 2000: COMPUTER ASSISTED RADIOLOGY AND SURGERY Xu, H., Paik, D. S., Ross, B., Sumanaweera, T. S., Hossack, J., Jeffrey, R. B., Napel, S. 2000; 1214: 666-670
  • Display modes for CT colonography - Part II. Blinded comparison of axial CT and virtual endoscopic and panoramic endoscopic volume-rendered studies RADIOLOGY Beaulieu, C. F., Jeffrey, R. B., Karadi, C., Paik, D. S., Napel, S. 1999; 212 (1): 203-212

    Abstract

    To determine the sensitivity of radiologist observers for detecting colonic polyps by using three different data review (display) modes for computed tomographic (CT) colonography, or "virtual colonoscopy."CT colonographic data in a patient with a normal colon were used as base data for insertion of digitally synthesized polyps. Forty such polyps (3.5, 5, 7, and 10 mm in diameter) were randomly inserted in four copies of the base data. Axial CT studies, volume-rendered virtual endoscopic movies, and studies from a three-dimensional mode termed "panoramic endoscopy" were reviewed blindly and independently by two radiologists.Detection improved with increasing polyp size. Trends in sensitivity were dependent on whether all inserted lesions or only visible lesions were considered, because modes differed in how completely the colonic surface was depicted. For both reviewers and all polyps 7 mm or larger, panoramic endoscopy resulted in significantly greater sensitivity (90%) than did virtual endoscopy (68%, P = .014). For visible lesions only, the sensitivities were 85%, 81%, and 60% for one reader and 65%, 62%, and 28% for the other for virtual endoscopy, panoramic endoscopy, and axial CT, respectively. Three-dimensional displays were more sensitive than two-dimensional displays (P < .05).The sensitivity of panoramic endoscopy is higher than that of virtual endoscopy, because the former displays more of the colonic surface. Higher sensitivities for three-dimensional displays may justify the additional computation and review time.

    View details for Web of Science ID 000081086900032

    View details for PubMedID 10405743

  • Display modes for CT colonography - Part I. Synthesis and insertion of polyps into patient CT data RADIOLOGY Karadi, C., Beaulieu, C. F., Jeffrey, R. B., Paik, D. S., Napel, S. 1999; 212 (1): 195-201

    Abstract

    To develop and validate a method for the insertion of digitally synthesized polyps into computed tomographic (CT) images of the human colon for use as ground truth for evaluation of virtual colonoscopy.Spiral CT simulator software was used to generate 10 synthetic polyps in various configurations. Additional software was developed to insert these polyps into volume CT scans. Ten polyps in eight patients were selected for comparison. Three radiologists evaluated whether two-dimensional (2D) CT images and three-dimensional (3D) volume-rendered CT images showed synthetic or real polyps.Edge-response profiles and noise of simulated polyps matched those of native polyps. Frequency distributions of reviewers' responses were not significantly different for synthetic versus real polyps in either 3D or 2D images. Responses were clustered around the response of "unsure" if lesions were real or synthetic. Receiver operating characteristic curves had areas of 0.54 (95% CI = 0.39, 0.68) for 3D and 0.39 (95% CI = 0.25, 0.53) for 2D images, which were not significantly different from random guessing (P = .70 and .28 for 3D and 2D images, respectively).Synthetic polyps were indistinguishable from real polyps. This method can be used to generate ground truth experimental data for comparison of CT colonographic display and detection methods.

    View details for Web of Science ID 000081086900031

    View details for PubMedID 10405742

  • Fast 3D cardiac cine MR imaging JOURNAL OF MAGNETIC RESONANCE IMAGING Alley, M. T., Napel, S., Amano, Y., Paik, D. S., Shifrin, R. Y., Shimakawa, A., Pelc, N. J., Herfkens, R. J. 1999; 9 (5): 751-755

    Abstract

    We describe a technique for three-dimensional cine MR imaging. By using short repetition times (TR) and interleaved slice encoding, volumetric cine data can be acquired throughout the cardiac cycle with a temporal resolution of approximately 80 msec. A T1-shortening agent is used to produce contrast between blood and myocardium. A comparison between the acquisition times of this and several other two-dimensional techniques is presented.

    View details for Web of Science ID 000083418000021

    View details for PubMedID 10331775

  • New visualization techniques for virtual colonoscopy: Methods and evaluation COMPUTER-AIDED DIAGNOSIS IN MEDICAL IMAGING Napel, S., Beaulieu, C. F., Paik, D. S., Karadi, C., Jeffrey, R. B. 1999; 1182: 463-468
  • Automated flight path planning for virtual endoscopy MEDICAL PHYSICS Paik, D. S., Beaulieu, C. F., Jeffrey, R. B., Rubin, G. D., Napel, S. 1998; 25 (5): 629-637

    Abstract

    In this paper, a novel technique for rapid and automatic computation of flight paths for guiding virtual endoscopic exploration of three-dimensional medical images is described. While manually planning flight paths is a tedious and time consuming task, our algorithm is automated and fast. Our method for positioning the virtual camera is based on the medial axis transform but is much more computationally efficient. By iteratively correcting a path toward the medial axis, the necessity of evaluating simple point criteria during morphological thinning is eliminated. The virtual camera is also oriented in a stable viewing direction, avoiding sudden twists and turns. We tested our algorithm on volumetric data sets of eight colons, one aorta and one bronchial tree. The algorithm computed the flight paths in several minutes per volume on an inexpensive workstation with minimal computation time added for multiple paths through branching structures (10%-13% per extra path). The results of our algorithm are smooth, centralized paths that aid in the task of navigation in virtual endoscopic exploration of three-dimensional medical images.

    View details for Web of Science ID 000073650800004

    View details for PubMedID 9608471

  • Measurement of the aorta and its branches with helical CT RADIOLOGY Rubin, G. D., Paik, D. S., Johnston, P. C., Napel, S. 1998; 206 (3): 823-829

    Abstract

    Contiguous orthonormal arterial cross sections, segment lengths, and curvature were semiautomatically quantified from helical computed tomographic (CT) angiographic data in phantoms and two patients. Measurements of mean diameter and curvature correlated with reference values (r2 = .99), and mean fractional errors were 0.07 and 0.06 for mean diameter and curvature measurements, respectively. Volumetric measurement showed a potential to increase the accuracy, precision, and diagnostic utility of CT angiography.

    View details for Web of Science ID 000072128000042

    View details for PubMedID 9494508

  • Wide-Angle Virtual Endoscopy using Multiple-View Rendering: The Virtual Cockpit RSNA EJ Sheikh SF, Paik DS, Beaulieu CF, Rubin GD, Jeffrey RB, Napel S 1998; 2

Conference Proceedings


  • Stair-step artifacts with single versus multiple detector-row helical CT Fleischmann, D., Rubin, G. D., Paik, D. S., Yen, S. Y., Hilfiker, P. R., Beaulieu, C. F., Napel, S. RADIOLOGICAL SOC NORTH AMERICA. 2000: 185-196

    Abstract

    To compare the effects of acquisition parameters on the magnitude and appearance of artifacts between single and multiple detector-row helical computed tomography (CT).A cylindric (12.7 x 305.0-mm) acrylic rod inclined 45 degrees relative to the z axis was scanned at the isocenter and 100 mm from the isocenter with single detector-row (single-channel) helical CT (beam width, 1-10 mm; pitch, 1.0, 2.0, or 3.0) and multiple detector-row (four-channel) helical CT (detector width, 1. 25, 2.5, 3.75, and 5 mm; pitch, 0.75 or 1.5). The SD of radius measurements along the rod (SD(r)) was used to quantify artifacts in all 72 data sets and to analyze their frequency patterns. Volume-rendered images of the data sets were ranked by six independent and blinded readers; findings were correlated with acquisition parameters and SD(r) measurements.SD(r) was smaller in four- than in single-channel helical CT for any given table increment (TI). In single-channel helical CT, SD(r) increased linearly with beam width and geometrically with pitch. In four-channel helical CT, SD(r) measurements were directly proportional to the TI, regardless of the detector width and pitch combination used. Off-center object position on average increased SD(r) by a factor of 1.6 for single-channel helical CT and by a factor of 2.0 for four-channel helical CT. Subjective rankings of image quality correlated excellently with SD(r) (Spearman r = 0.94, P <.001).Artifacts are quantitatively and subjectively smaller with four- compared with single-channel helical CT for any given TI.

    View details for Web of Science ID 000087829500026

    View details for PubMedID 10887247

Stanford Medicine Resources: