Assessing hepatomegaly: automated volumetric analysis of the liver.

Academic Radiology
Marius George LinguraruRonald M Summers

Abstract

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

References

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Citations

Feb 26, 2016·Abdominal Radiology·A M RoloffJ P Kühn
Apr 22, 2016·AJR. American Journal of Roentgenology·Ronald M Summers
Mar 5, 2017·Academic Radiology·Puskar PattanayakRonald M Summers
Dec 9, 2016·Journal of Applied Clinical Medical Physics·Wei CaiFucang Jia
Mar 1, 2019·Radiology. Artificial Intelligence·Kang WangUNKNOWN members of the NASH Clinical Research Network

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