ArticleAbdominal radiology (New York)2026
Exploring radiomics as a predictor of hypertrophy of future liver remnant after portal vein embolization in biliary malignancies: a retrospective cohort study.
Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivePortal vein embolization (PVE) is an established procedure to induce hypertrophy of the future liver remnant (FLR) in cases requiring major hepatectomies. However, prediction of FLR hypertrophy prior to PVE is challenging. The study aims to evaluate the utility of CT derived radiomics of the liver and clinical and laboratory parameters in predicting the hypertrophy of FLR.
methodsThis retrospective cohort study included 43 patients (mean age 46.8 years; males - 25; females - 18) who underwent PVE for biliary malignancies at our institution. Clinical, biochemical, and imaging data were collected, and texture analysis was performed on pre-PVE CT scans. Patients were stratified into two groups based on post-PVE FLR volume as a percentage of total liver volume (Group A < 25% hypertrophy, Group B ≥ 25% hypertrophy), and comparisons were made between biochemical parameters and texture analysis findings.
resultsThere were 18 patients (mean age: 47.3 years; 12 males) in group A and 25 patients (mean age: 47.9 years; 13 males) in group B. Significant differences were seen in serum alkaline phosphatase (p = 0.014) and serum aspartate transaminase (p = 0.021) levels between the two groups. Significant differences (p < 0.05) were observed in the kurtosis values of liver segments 1 and 3 between the two groups at multiple spatial scale filters (SSF). Additionally, segment 6 showed a significant difference in skewness at SSF 5. ROC curve analysis revealed area under the curves ranging from 0.66 to 0.76 for the above mentioned parameters.
conclusionPre-procedure CT radiomics of the liver has the ability to predict FLR hypertrophy after PVE in biliary malignancies and could be a promising tool in patient stratification.
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