Modeling Patient-Informed Liver Contrast Perfusion in Contrast-enhanced Computed Tomography.
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OBJECTIVE: To determine the correlation between patient attributes and contrast enhancement in liver parenchyma and demonstrate the potential for patient-informed prediction and optimization of contrast enhancement in liver imaging. METHODS: The study included 418 chest/abdomen/pelvis computed tomography scans, with 75% to 25% training-testing split. Two regression models were built to predict liver parenchyma contrast enhancement over time: first model (model A) utilized patient attributes (height, weight, sex, age, bolus volume, injection rate, scan times, body mass index, lean body mass) and bolus-tracking data. A second model (model B) only used the patient attributes. Pearson coefficient was used to assess predictive accuracy. RESULTS: Weight- and height-related features were found to be statistically significant predictors (P < 0.05), weight being the strongest. Of the 2 models, model A (r = 0.75) showed greater accuracy than model B (r = 0.42). CONCLUSIONS: Patient attributes can be used to build prediction model for liver parenchyma contrast enhancement. The model can have utility in optimization and improved consistency in contrast-enhanced liver imaging.
Published Version (Please cite this version)10.1097/RCT.0000000000001095
Publication InfoSetiawan, Hananiel; Ria, Francesco; Abadi, Ehsan; Fu, Wanyi; Smith, Taylor B; & Samei, Ehsan (2020). Modeling Patient-Informed Liver Contrast Perfusion in Contrast-enhanced Computed Tomography. J Comput Assist Tomogr, 44(6). pp. 882-886. 10.1097/RCT.0000000000001095. Retrieved from https://hdl.handle.net/10161/21707.
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Assistant Professor in Radiology
Visiting Research Scholar in the Department of Radiology
Professor of Radiology
Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE is a Persian-American medical physicist. He is a tenured Professor of Radiology, Medical Physics, Biomedical Engineering, Physics, and Electrical and Computer Engineering at Duke University. He serves as the Director of the Duke Medical Physics Graduate Program and the Director of the Clinical Imaging Physics Group. He is certified by the American Board of Radiology, and is a Fellow o
Doctor of Philosophy (PhD) Student in Medical Physics, 2017-PresentAs an early Medical Physics PhD student in the "Imaging" track, I currently study contrast-enhanced Computed Tomography (CT) imaging, with the goal of quantifying, managing, mitigating, monitoring, and optimizing variability of the protocol. I am looking forward to be applying physics knowledge and technique to the field of medicine.<!--[if gte mso 9
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