Patient-specific dose estimation for pediatric abdomen-pelvis CT

Proceedings of SPIE(2009)

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摘要
GE Healthcare, Waukesha, WI, USA 53188 ABSTRACT The purpose of this study is to develop a method for estimating patie nt-specific dose from abdomen-pelvis CT examinations and to invest igate dose variation across patients in the same weight group. Our study consisted of seven pediatric patients in the same weight/protocol group, for whom full-body computer models were previously created based on the patients’ CT data obtained for clinical indications. Organ and effective dose of these patients from an abdomen-pelvis sc an protocol (LightSpeed VCT scanner, 120-kVp, 85-90 mA, 0.4-s gantry rotation peri od, 1.375-pitch, 40-mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated for the same CT sy stem. The seven patients had effective dose of 2.4-2.8 mSv, corresponding to normalized effective dose of 6.6-8.3 mSv/100mAs (coefficient of variation: 7.6%). Dose variations across the patients were small for large organs in the scan coverage (mean: 6.6%; range: 4.9%-9.2%), larger for small organs in the scan coverage (mean: 10.3%; range: 1.4%-15. 6%), and the largest for organs partially or completely outside the scan coverage (mean: 14.8%; range: 5.7%-27.7%). Normalized effective dose correlated strongly with body weight (correlation coefficient: r = -0.94). Normalized dose to the kidney and the adrenal gland correlated strongly with mid-liver equivalent diameter (kidney: r = -0.97; adrenal glands: r = -0.98). Normalized dose to the small intestine correlated strongly with mid-intestine equivalent diameter ( = -0.97). rThese strong correlations suggest that patient-specific dose may be estimated for any other child in the same size group who undergoes the abdomen-pelvis scan. Keywords: computed tomography, organ dose, effective dose, pediatric, abdomen, pelvis, patient-specific, Monte Carlo
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关键词
body weight,effective dose,collimation,field of view,computer model,monte carlo,coefficient of variation
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