Purpose: To test the hypothesis that patient size can be accurately calculated from axial computed tomographic (CT) images, including correction for the effects of anatomy truncation that occur in routine clinical CT image reconstruction.
Materials and methods: Institutional review board approval was obtained for this HIPAA-compliant study, with waiver of informed consent. Water-equivalent diameter (D(W)) was computed from the attenuation-area product of each image within 50 adult CT scans of the thorax and of the abdomen and pelvis and was also measured for maximal field of view (FOV) reconstructions. Linear regression models were created to compare D(W) with the effective diameter (D(eff)) used to select size-specific volume CT dose index (CTDI(vol)) conversion factors as defined in report 204 of the American Association of Physicists in Medicine. Linear regression models relating reductions in measured D(W) to a metric of anatomy truncation were used to compensate for the effects of clinical image truncation.
Results: In the thorax, D(W)versus D(eff) had an R(2) of 0.51 (n = 200, 50 patients at four anatomic locations); in the abdomen and pelvis, R(2) was 0.90 (n = 150, 50 patients at three anatomic locations). By correcting for image truncation, the proportion of clinically reconstructed images with an extracted D(W) within ±5% of the maximal FOV D(W) increased from 54% to 90% in the thorax (n = 3602 images) and from 95% to 100% in the abdomen and pelvis (6181 images).
Conclusion: The D(W) extracted from axial CT images is a reliable measure of patient size, and varying degrees of clinical image truncation can be readily corrected. Automated measurement of patient size combined with CT radiation exposure metrics may enable patient-specific dose estimation on a large scale.
© RSNA, 2013.