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Updated: Mar 6, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
Published on: September 11, 2011
Realistic phantoms to characterize dosimetry in pediatric CT
Diana E Carver1, Susan D Kost2, Nicholas D Fraser2
1Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, Nashville, TN, 37232, USA. diana.e.carver@gmail.com.
Background:
The estimation of organ doses and effective doses for children receiving CT examinations is of high interest. Newer, more realistic anthropomorphic body models can provide information on individual organ doses and improved estimates of effective dose.
Materials And Methods:
Previously developed body models representing 50th-percentile individuals at reference ages (newborn, 1, 5, 10 and 15 years) were modified to represent 10th, 25th, 75th and 90th height percentiles for both genders and an expanded range of ages (3, 8 and 13 years). We calculated doses for 80 pediatric reference phantoms from simulated chest-abdomen-pelvis exams on a model of a Philips Brilliance 64 CT scanner. Individual organ and effective doses were normalized to dose-length product (DLP) and fit as a function of body diameter.
Results:
We calculated organ and effective doses for 80 reference phantoms and plotted them against body diameter. The data were well fit with an exponential function. We found DLP-normalized organ dose to correlate strongly with body diameter (R2>0.95 for most organs). Similarly, we found a very strong correlation with body diameter for DLP-normalized effective dose (R2>0.99). Our results were compared to other studies and we found average agreement of approximately 10%.
Conclusion:
We provide organ and effective doses for a total of 80 reference phantoms representing normal-stature children ranging in age and body size. This information will be valuable in replacing the types of vendor-reported doses available. These data will also permit the recording and tracking of individual patient doses. Moreover, this comprehensive dose database will facilitate patient matching and the ability to predict patient-individualized dose prior to examination.
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