A database of 40 patient-based computational models for benchmarking organ dose estimates in CT.
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2020-07-06
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Abstract
PURPOSE:Patient radiation burden in CT can best be characterized through risk estimates derived from organ doses. Organ doses can be estimated by Monte Carlo simulations of the CT procedures on computational phantoms assumed to emulate the patients. However, the results are subject to uncertainties related to how accurately the patient and CT procedure are modeled. Different methods can lead to different results. This paper, based on decades of organ dosimetry research, offers a database of CT scans, scan specifics, and organ doses computed using a validated Monte Carlo simulation of each patient and acquisition. It is aimed that the database can serve as means to benchmark different organ dose estimation methods against a benchmark dataset. ACQUISITION AND VALIDATION METHODS:Organ doses were estimated for 40 adult patients (22 female, 18 female) who underwent Chest and Abdominopelvic CT examinations. Patient-based computational models were created for each patient including 26 organs for female and 25 organs for male cases. A Monte Carlo code, previously validated experimentally, was applied to calculate organ doses under constant and two modulated tube current conditions. DATA FORMAT AND USAGE NOTES:The generated database reports organ dose values for Chest and Abdominopelvic examinations per patient and imaging condition. Patient information and images and scan specifications (energy spectrum, bowtie filter specification, and tube current profiles) are provided. The database is available at publicly accessible digital repositories. POTENTIAL APPLICATIONS:Consistency in patient risk estimation, and associated justification and optimization requires accuracy and consistency in organ dose estimation. The database provided in this paper is a helpful tool to benchmark different organ dose estimation methodologies to facilitate comparisons, assess uncertainties, and improve assessment of risk of CT scans based on organ dose.
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Samei, Ehsan, Francesco Ria, Xiaoyu Tian and Paul W Segars (2020). A database of 40 patient-based computational models for benchmarking organ dose estimates in CT. Medical physics. 10.1002/mp.14373 Retrieved from https://hdl.handle.net/10161/21176.
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Ehsan Samei
Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE, FIOMP, FACR is a Persian-American medical physicist. He is the Reed and Martha Rice Distinguished Professor of Radiology, and Professor of Medical Physics, Biomedical Engineering, Physics, and Electrical and Computer Engineering at Duke University. He serves as the Chief Imaging Physicist for Duke University Health System, the Director of the Carl E Ravin Advanced Imaging Laboratories and the Center for Virtual Imaging Trials (CVIT), and Co-Director of the Triangle Centers of Excellence in Regulatory Science and Innovation (Triangle CERSI). Certified by the American Board of Radiology, he is recognized as a Distinguished Investigator by the Academy of Radiology Research, awarded Fellow by five professional organizations, and has been the recipient of the Jimmy O. Fenn Lifetime Achievement Award of SEAAPM and the Marie Sklodowska-Curie Award by IOMP. He founded/co-founded the Duke Medical Physics Program, the Duke Imaging Physics Residency Program, the Duke Clinical Imaging Physics Group, the Center for Virtual Imaging Trials, and the Society of Directors of Academic Medical Physics Programs (SDAMPP). He has held senior leadership positions in the AAPM, SPIE, SDAMPP, and RSNA, including serving as president of the SEAAPM (2010-2011), SDAMPP (2011), and AAPM (2023). He is ranked 8th among over 56,000 medical physicists worldwide for his lifetime contribution to medical physics.
Dr. Samei has mentored over 160 trainees (graduate and postgraduate). He has over 1500 scientific publications, including 4 books, over 430 refereed journal papers, over 260 full-length conference articles, over 350 conference presentations, and over 340 invited talks. Citations to his work are reflected in an h-index of 82 and a Weighted Relative Citation Ratio of 759. His laboratory has been supported continuously for over two decades by 50 extramural grants totaling $47 million. Those include a Program Project grant from the NIH in 2021 to establish the National Center for Virtual Imaging Trials (CVIT), and a multi-institutional grant in 2023 from the FDA to establish the Triangle Center of Excellence in Regulatory Science and Innovation (Triangle CERSI), both joining highly selective biomedical research and regulatory science centers nationwide.
On the personal side, Ehsan Samei is a semi-professional musician, leads a chamber ensemble, and has an active interest in common traits and interactions between science, art, and faith. He has led workshops on leadership and leadership development. He has run five marathons (3:17 PR), including the 2013 Boston Marathon, is married to Dr. Maija Samei, a scholar of medieval Chinese literature, and is blessed with four gifted children.
Francesco Ria
Dr. Francesco Ria is a medical physicist and he serves as an Assistant Professor in the Department of Radiology. Francesco has an extensive expertise in the assessment of procedure performances in radiology. In particular, his research activities focus on the simultaneous evaluation of radiation dose and image quality in vivo in computed tomography providing a comprehensive evaluation of radiological exams. Moreover, Francesco is developing and investigating novel mathematical models that, uniquely in the radiology field, can incorporate a comprehensive and quantitative risk-to-benefit assessment of the procedures; he is continuing to apply his expertise towards the definition of new patient specific risk metrics, and in the assessment of image quality in vivo also using state-of-the-art imaging technology, such as photon counting computed tomography scanners, and machine learning reconstruction algorithms.
Dr. Ria is a member of the American Association of Physicists in Medicine (AAPM) task group 392 (Investigation and Quality Control of Automatic Exposure Control System in CT), of the AAPM task group 430 (Comprehensive quantification and dissemination of patient-model-based organ and effective dose estimations and their associated uncertainties for CT examinations), of the AAPM Medicine Public Education working group (WGATE), and of the Italian Association of Medical Physics task group Dose Monitoring in Diagnostic Imaging.
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