ArticleAnnals of surgical oncology2023
Multi-organ Radiomics-Based Prediction of Future Remnant Liver Hypertrophy Following Portal Vein Embolization.
Article in Annals of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 9 citations in OpenAlex.
- CT Radiomics to Predict Regenerative Biomarker Expression after Liver Venous Embolization: Proof-of-Concept in a Porcine Model.Journal of vascular and interventional radiology : JVIR · 2026Article
- A Multiphase CT-Based Radiomics-Clinical Model to Identify Inadequate Future Liver Remnant Hypertrophy After Portal Vein Embolization Before Major Hepatectomy.Cancer management and research · 2026Article
- Deep learning-based volumetry of the future liver remnants and prediction of candidates for major hepatectomy.BMC medical imaging · 2025Article
- Development and External Validation of a Combined Clinical-Radiomic Model for Predicting Insufficient Hypertrophy of the Future Liver Remnant following Portal Vein Embolization.Annals of surgical oncology · 2025Article
- Utilization of Multiorgan Radiomics to Predict Future Liver Remnant Hypertrophy After Portal Vein Embolization: Another Tool for the Toolbox?Annals of surgical oncology · 2024Article
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12 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPortal vein embolization (PVE) is used to induce remnant liver hypertrophy prior to major hepatectomy. The purpose of this study was to evaluate the predictive value of baseline computed tomography (CT) data for future remnant liver (FRL) hypertrophy after PVE.
methodsIn this retrospective study, all consecutive patients undergoing right-sided PVE with or without hepatic vein embolization between 2018 and 2021 were included. CT volumetry was performed before and after PVE to assess standardized FRL volume (sFRLV). Radiomic features were extracted from baseline CT after segmenting liver (without tumor), spleen and bone marrow. For selecting features that allow classification of response (hypertrophy ≥ 1.33), a stepwise dimension reduction was performed. Logistic regression models were fitted and selected features were tested for their predictive value. Decision curve analysis was performed on the test dataset.
resultsA total of 53 patients with liver tumor were included in this study. sFRLV increased significantly after PVE, with a mean hypertrophy of FRL of 1.5 ± 0.3-fold. sFRLV hypertrophy ≥ 1.33 was reached in 35 (66%) patients. Three independent radiomic features, i.e. liver-, spleen- and bone marrow-associated, differentiated well between responders and non-responders. A logistic regression model revealed the highest accuracy (area under the curve 0.875) for the prediction of response, with sensitivity of 1.0 and specificity of 0.5. Decision curve analysis revealed a positive net benefit when applying the model.
conclusionsThis proof-of-concept study provides first evidence of a potential predictive value of baseline multi-organ radiomics CT data for FRL hypertrophy after PVE.
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