DETERMINATION OF LIVER VOLUME FROM CT SCANS USING HISTOGRAM CLUSTER-ANALYSIS

The histogram cluster analysis procedure (HICAP), which was developed by NASA for processing satellite images, classifies images into discrete clusters of pixels according to one or more arbitrary imaging variables. We incorporated this nonparametric, multivariate procedure in a semiautomatic computer algorithm for calculating total liver volume from CT scans and compared its performance with that of a human observer. Total liver volumes were calculated from CT scans in adult patients by the algorithm and by an experienced radiologist using the trackball controlled cursor at the CT console. Variability in the computer calculated volumes was determined by repeating calculations three times over the course of 3-12 months. Using HICAP in the univariate mode, we calculated total liver volumes from 28 contrast enhanced CT scans in 27 patients. Liver volumes calculated by the semiautomatic and manual methods had a median absolute difference of 3.6% (V(computer) = 1.08 * V(manual) - 99.52 cc; r2 = 0.99). Median day-to-day variability of the computer calculated volumes was 1.9% (95% confidence interval: 1.3-2.7%). Using HICAP in a bivariate mode to illustrate its ability to incorporate two image features in one analysis, we studied an additional patient and compared total liver volume calculated from the univariate data set defined by the contrast enhanced CT scan with that calculated from the bivariate data set defined by nonenhanced and contrast enhanced CT scans. The HICAP errors were 4. 1% in the univariate analysis and 0.4% in the bivariate analysis. It is concluded that this statistical clustering algorithm provides a clinically accurate, repeatable, and feasible method of in vivo fiver volume determination.