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Proceedings Paper

Prospective optimization of CT under tube current modulation: I. organ dose
Author(s): Xiaoyu Tian; Xiang Li; W. Paul Segars; Donald Frush; Ehsan Samei
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Paper Abstract

In an environment in which computed tomography (CT) has become an indispensable diagnostic tool employed with great frequency, dose concerns at the population level have become a subject of public attention. In that regard, optimizing radiation dose has become a core problem to the CT community. As a fundamental step to optimize radiation dose, it is crucial to effectively quantify radiation dose for a given CT exam. Such dose estimates need to be patient-specific to reflect individual radiation burden. It further needs to be prospective so that the scanning parameters can be dynamically adjusted before the scan is performed. The purpose of this study was to prospectively estimate organ dose in abdominopelvic CT exams under tube current modulation (TCM). CTDIvol-normalized-organ dose coefficients ( hfixed ) for fixed tube current were first estimated using a validated Monte Carlo simulation program and 58 computational phantoms. To account for the effect of TCM scheme, a weighted CTDIvol was computed for each organ based on the tube current modulation profile. The organ dose was predicted by multiplying the weighted CTDIvol with the organ dose coefficients ( hfixed ). To quantify prediction accuracy, each predicted organ dose was compared with organ dose simulated from Monte Carlo program with TCM profile explicitly modeled. The predicted organ dose showed good agreement with simulated organ dose across all organs and modulation strengths. For an average CTDIvol of a CT exam of 10 mGy, the absolute median error across all organs were 0.64 mGy (-0.21 and 0.97 for 25th and 75th percentiles, respectively). The percentage differences (normalized by CTDIvol of the exam) were within 15%. This study developed a quantitative model to predict organ dose under clinical abdominopelvic scans. Such information may aid in the optimization of CT protocols.

Paper Details

Date Published: 19 March 2014
PDF: 14 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90331Q (19 March 2014); doi: 10.1117/12.2043858
Show Author Affiliations
Xiaoyu Tian, Duke Univ. (United States)
Xiang Li, Cleveland State Univ. (United States)
W. Paul Segars, Duke Univ. (United States)
Donald Frush, Duke Univ. (United States)
Ehsan Samei, Duke Univ. (United States)

Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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