Organ Doses from CT Localizer Radiographs: Development, Validation, and Application of a Monte Carlo Estimation Technique.
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PURPOSE:The purpose of this study was to simulate and validate organ doses from different CT localizer radiograph geometries using Monte Carlo methods for a population of patients. METHODS:A Monte Carlo method was developed to estimate organ doses from CT localizer radiographs using PENELOPE. The method was validated by comparing dosimetry estimates with measurements using an anthropomorphic phantom imbedded with thermoluminescent dosimeters (TLDs) scanned on a commercial CT system (Siemens SOMATOM Flash). The Monte Carlo simulation platform was then applied to conduct a population study with fifty-seven adult computational phantoms (XCAT). In the population study, clinically relevant chest localizer protocols were simulated with the x-ray tube in anterior-posterior (AP), right lateral, and PA positions. Mean organ doses and associated standard deviations (in mGy) were then estimated for all simulations. The obtained organ doses were studied as a function of patient chest diameter. Organ doses for breast and lung were compared across different views and represented as a percentage of organ doses from rotational CT scans. RESULTS:The validation study showed an agreement between the Monte Carlo and physical TLD measurements with a maximum percent difference of 15.5% and a mean difference of 3.5% across all organs. The XCAT population study showed that breast dose from AP localizers was the highest with a mean value of 0.24 mGy across patients, while the lung dose was relatively consistent across different localizer geometries. The organ dose estimates were found to vary across the patient population, partially explained by the changes in the patient chest diameter. The average effective dose was 0.18 mGy for AP, 0.09 mGy for lateral, and 0.08 mGy for PA localizer. CONCLUSION:A platform to estimate organ doses in CT localizer scans using Monte Carlo methods was implemented and validated based on comparison with physical dose measurements. The simulation platform was applied to a virtual patient population, where the localizer organ doses were found to range within 0.4-8.6% of corresponding organ doses for a typical CT scan, 0.2-3.3% of organ doses for a CT pulmonary angiography scan, and 1.1-20.8% of organ doses for a low dose lung cancer screening scan.
Published Version (Please cite this version)10.1002/mp.13781
Publication InfoHoye, Jocelyn; Sharma, Shobhit; Zhang, Yakun; Fu, Wanyi; Ria, Francesco; Kapadia, Anuj; ... Samei, Ehsan (2019). Organ Doses from CT Localizer Radiographs: Development, Validation, and Application of a Monte Carlo Estimation Technique. Medical physics. 10.1002/mp.13781. Retrieved from https://hdl.handle.net/10161/19242.
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Anuj J Kapadia
Adjunct Associate Professor in the Department of Radiology
My research focuses on developing an innovative imaging modality - Neutron Stimulated Emission Computed Tomography (NSECT), that uses inelastic scattering through fast neutrons to generate tomographic images of the body's element composition. Such information is vital in diagnosing a variety of disorders ranging from iron and copper overload in the liver to several cancers. Specifically, there are two ongoing projects: 1) Experimental Implementation of NSECT Neutron sp
Reed and Martha Rice Distinguished Professor of Radiology
Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE, FIOMP, FACR 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, where he also serves as the Chief Imaging Physicist for Duke University Health System, the director of the Carl E Ravin Advanced Imaging Laboratories, and the director of Center for Virtual Imaging Trials. He is certi
William Paul Segars
Associate Professor in Radiology
Our current research involves the use of computer-generated phantoms and simulation techniques to investigate and optimize medical imaging systems and methods. Medical imaging simulation involves virtual experiments carried out entirely on the computer using computational models for the patients as well as the imaging devices. Simulation is a powerful tool for characterizing, evaluating, and optimizing medical imaging systems. A vital aspect of simulation is to have realistic models of the
Joshua M Wilson
Assistant Professor of Radiology
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