Total risk index: a mathematical model for decision making based on clinical and radiation risk assessment in CT
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2019-12-04
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Abstract
Purpose. Radiological risk is a combination of radiation and clinical risk (likelihood of not delivering a proper diagnosis), which together may be characterized as a total risk index (TRI). While many strategies have been developed to ascertain radiation risk, there has been a paucity of studies assessing the clinical risk. This knowledge gap makes impossible to determine the total radiological procedure risk and, thus, to perform a comprehensive optimization. The purpose of this study was to develop a mathematical model to ascertain TRI and to identify the minimum TRI (mTRI) in a clinical CT population.
Materials and Methods. This IRB approved study included 21 adults abdomen exams performed on a dual-source single energy CT at two different dose levels (84 CT series). Virtual liver lesions were inserted into projection data to simulate localized stage liver cancer (LSLC). The detectability index (d') was calculated in each series and converted to percentage of correct observer answers (AUC) in a two-alternative forced-choice model. The AUC was converted into the loss of 5-year relative survival rate (SEER, NCI), considering an upper bound on patient's risk for a misdiagnosis of LSLC (false positive + false negative). Concerning radiation risk, organ doses were estimated using a Monte Carlo method and the Risk Index was calculated and converted in 5-year relative survival rate for cancer. Finally, the two risks were weighted equally into a combined TRI curve per each patient as a function of CTDIvol. The analytical minimum of each TRI curve provided the patient mTRI.
Results. The mTRI for LSLC patients that underwent an abdominal CT exhibited a rapid rise at low radiation dose due to enhanced clinical risk of under-dosed examinations. Increasing dose offered less risk with mortality per 100 patients between 2.1 and 6.5 (mean 4.5) at CTDIvol=5mGy, between 1.1 and 5.9 (mean 3.5) at CTDIvol=10mGy and between 0.5 and 5.4 (mean 3.0) at CTDIvol=20 mGy.
Conclusion. The clinical risk seems to play a more dominant factor in designing optimum CT protocols. The TRI may provide an objective and quantifiable metric of the interplay of radiation and clinical risks during the optimization of the CT technique for individual patients.
Clinical Relevance statement. CT risk-based optimization can be made possible by first quantifying both radiation and clinical risk using comparable units, then calculating an overall risk, and finally minimizing the total risk.
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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.
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.
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