Assessment of liver fibrosis severity using computed tomography–based liver and spleen volumetric indices in patients with chronic liver disease

• Published in: European radiology 2020-06, Vol.30 (6), p.3486-3496
• Main Authors: Son, Jung Hee, Lee, Seung Soo, Lee, Yedaun, Kang, Bo-Kyeong, Sung, Yu Sub, Jo, SoRa, Yu, Eunsil
• Format: Article
• Language: English
• Subjects: Algorithms; Autoimmune diseases; Bile; Cirrhosis; Computed tomography; Correlation coefficient; Correlation coefficients; Deep learning; Diagnostic Radiology; Etiology; Fatty liver; Fibrosis; Hepatitis; Hepatobiliary-Pancreas; Imaging; Internal Medicine; Interventional Radiology; Liver; Liver cirrhosis; Liver diseases; Machine learning; Medical imaging; Medicine; Medicine & Public Health; Neuroradiology; Radiology; Spleen; Subgroups; Ultrasound
• ISSN: 0938-7994; 1432-1084
• DOI: 10.1007/s00330-020-06665-4

Objectives To evaluate whether the liver and spleen volumetric indices, measured on portal venous phase CT images, could be used to assess liver fibrosis severity in chronic liver disease. Methods From 2007 to 2017, 558 patients (mean age 48.7 ± 13.1 years; 284 men and 274 women) with chronic liver disease ( n  = 513) or healthy liver ( n  = 45) were retrospectively enrolled. The liver volume (sVol L ) and spleen volume (sVol S ), normalized to body surface area and liver-to-spleen volume ratio (Vol L /Vol S ), were measured on CT images using a deep learning algorithm. The correlation between the volumetric indices and the pathologic liver fibrosis stages combined with the presence of decompensation (F0, F1, F2, F3, F4C [compensated cirrhosis], and F4D [decompensated cirrhosis]) were assessed using Spearman’s correlation coefficient. The performance of the volumetric indices in the diagnosis of advanced fibrosis, cirrhosis, and decompensated cirrhosis were evaluated using the area under the receiver operating characteristic curve (AUC). Results The sVol S ( ρ  = 0.47–0.73; p