OBJECTIVE. The purposes of this study were to construct a model for estimation of splenic volume from standardized one-dimensional diameters of the spleen and to compare that model with the ellipsoid model for estimation of splenic volume. MATERIALS AND METHODS. In this retrospective study, segmentation software was used for semiautomated quantification of splenic volume by counting CT voxels in 193 consecutively registered patients. For standardization of one-dimensional measurements, the software was used to measure transaxial diameter in the slice with the largest splenic crosssectional area. By incorporation of splenic volume and the product of width, thickness, and length into the linear regression equation, a model for estimation of splenic volume was constructed, and its performance was externally assessed. Splenic volume also was calculated with the formula for a prolate ellipsoid. The ellipsoid volume and best-fit volumes were compared with segmented splenic volume by use of Bland-Altman plot and Lin concordance correlation. A value of p < 0.05 denoted statistical significance. RESULTS. Splenic width was the best one-dimensional predictor of splenic volume (r = 0.84, p < 0.05). The linear regression fitted model for estimation of splenic volume (VR) in the initial 100 patients was VR = (0.36 x W x T x L) + 28, where W is width, T is thickness, and L is length (R2 = 0.91, p < 0.05) and was externally validated by estimation of splenic volume in the other 93 patients. Compared with that observed with use of the ellipsoid formula, mean bias decreased from 22.57% to 0.93%, and the Lin coefficient increased from 0.81 to 0.96 with application of the best-fit model for calculation of splenic volume. CONCLUSION. The best-fit model VR = (0.36 x W x T x L) + 28 is more optimized than the ellipsoid formula and is associated with less bias for estimation of splenic volume.
- Splenic volume
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging