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22 March 2016 An automated technique for estimating patient-specific regional imparted energy and dose in TCM CT exams
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Currently computed tomography (CT) dosimetry relies on CT dose index (CTDI) and size specific dose estimates (SSDE). Organ dose is a better metric of radiation burden. However, organ dose estimation requires precise knowledge of organ locations. Regional imparted energy and dose can also be used to quantify radiation burden. Estimating the imparted energy from CT exams is beneficial in that it does not require precise estimates of the organ size or location. This work investigated an automated technique for retrospectively estimating the imparted energy from chest and abdominopelvic tube current modulated (TCM) CT exams. Monte Carlo simulations of chest and abdominopelvic TCM CT examinations across various tube potentials and TCM strengths were performed on 58 adult computational extended cardiac-torso (XCAT) phantoms to develop relationships between scanned mass and imparted energy normalized by dose length product (DLP). An automated algorithm for calculating the scanned patient volume was further developed using an open source mesh generation toolbox. The scanned patient volume was then used to estimate the scanned mass accounting for diverse density within the scan region. The scanned mass and DLP from the exam were used to estimate the imparted energy to the patient using the knowledgebase developed from the Monte Carlo simulations. Patientspecific imparted energy estimates were made from 20 chest and 20 abdominopelvic clinical CT exams. The average imparted energy was 274 ± 141 mJ and 681 ± 376 mJ for the chest and abdominopelvic exams, respectively. This method can be used to estimate the regional imparted energy and/or regional dose in chest and abdominopelvic TCM CT exams across clinical operations.
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Jeremiah W. Sanders, Xiaoyu Tian, W. Paul Segars, John Boone, and Ehsan Samei "An automated technique for estimating patient-specific regional imparted energy and dose in TCM CT exams", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97833I (22 March 2016);

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