Assessing hepatomegaly: automated volumetric analysis of the liver

Abstract

Rationale and objectives: The aims of this study were to define volumetric nomograms for identifying hepatomegaly and to retrospectively evaluate the performance of radiologists in assessing hepatomegaly.

Materials and methods: Livers were automatically segmented from 148 abdominal contrast-enhanced computed tomographic scans: 77 normal livers and 71 cases of hepatomegaly (diagnosed by visual inspection and/or linear liver height by radiologists). Quantified liver volumes were compared to manual measurements using volume overlap and error. Liver volumes were normalized to body surface area, from which hepatomegaly nomograms were defined (H scores) by analyzing the distribution of liver sizes in the healthy population. H scores were validated against consensus reports. The performance of radiologists in diagnosing hepatomegaly was retrospectively evaluated.

Results: The automated segmentation of livers was robust, with volume overlap and error of 96.2% and 2.2%, respectively. There were no significant differences (P > .10) between manual and automated segmentation for either the normal or the hepatomegaly subgroup. The average volumes of normal and enlarged livers were 1.51 ± 0.25 and 2.32 ± 0.75 L, respectively. One-way analysis of variance found that body surface area (P = .004) and gender (P = .02), but not age, significantly affected normal liver volume. No significant effects were observed for two-way and three-way interactions among the three variables (P > .18). H-score cutoffs of 0.92 and 1.08 L/m2 were used to define mild and massive hepatomegaly (95% confidence interval, ± 0.02 L/m2). Using the H score as the reference standard, the sensitivity of radiologists in detecting all, mild, and massive hepatomegaly was 84.4%, 56.7%, and 100.0% at 90.1% specificity, respectively. Radiologists disagreed on 20.9% of the diagnosed cases (n = 31). The area under the receiver-operating characteristic curve of the H-score criterion for hepatomegaly detection was 0.98.

Conclusions: Nomograms for the identification and grading of hepatomegaly from automatic volumetric liver assessment normalized to body surface area (H scores) are introduced. H scores match well with clinical interpretations for hepatomegaly and may improve hepatomegaly detection compared with height measurements or visual inspection, commonly used in current clinical practice.

Figure 1

Bland-Altman agreement plots for liver height measurements at the mid-hepatic line between a) two independent observers (n=148), b) automated method (CAD) and observer 1 (n=148), c) CAD and observer 2 (n=148), d) intra-observer supine and prone measurements (n=25, note scale change on axes). The mean error is shown in solid line and the 95% limits of agreement (+/− 1.96 SD) in dashed lines.

Figure 2

H-score (cutoff to detect hepatomegaly) variation with the number of consecutive normal samples used for its computation. The peak near the beginning of the graph is caused by an outlier with large H-score.

Figure 3

Correlations between the H-score and liver MHL heights using a linear regression model: a) normal cases, and b) hepatomegaly cases (as defined by the H-score). The vertical red lines show the cutoff for hepatomegaly as defined in literature by an MHL height of 15.5cm [7, 38].

Figure 4

The image data of a case with Riedel’s lobe with abnormal liver MHL height of 17.6 cm and normal H-score of 0.88 l/m². The automatically segmented liver is overlaid in blue over the CT image and shown in axial slices.