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Open Access 07-12-2024 | Artificial Intelligence | ASO Author Reflections

ASO Author Reflections: Added Value of Pretreatment CT Radiomics for Accurate Prediction of Liver Hypertrophy Following Portal Vein Embolization

Authors: Qiang Wang, MD, PhD, Torkel B. Brismar, MD, PhD, Dennis Björk, MD, PhD, Erik Baubeta, MD, PhD, Gert Lindell, MD, PhD, Bergthor Björnsson, MD, PhD, Ernesto Sparrelid, MD, PhD

Published in: Annals of Surgical Oncology | Issue 3/2025

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Excerpt

Portal vein embolization (PVE) has been a standard procedure used preoperatively to induce growth of the future liver remnant (FLR). The goal with PVE is to ensure that a sufficient liver volume remains after resection to maintain function in patients with liver malignancies intended for extensive resections. However, predicting which patients will achieve an adequate FLR growth after PVE remains challenging. Current prediction methods are based on clinical factors such as baseline liver function, underlying liver conditions (for instance cirrhosis), and other patient factors. Despite their utility, these predictors often lack the precision required for effective individualized treatment planning. Previous studies have highlighted the need for prediction models that are accurate and accessible, without requiring invasive procedures or costly imaging alternatives.1 Our study aimed to bridge this gap by building a model that integrates clinical data with radiomic features derived from routine CT images to accurately predict insufficient liver hypertrophy following PVE.2
Literature
Metadata
Title
ASO Author Reflections: Added Value of Pretreatment CT Radiomics for Accurate Prediction of Liver Hypertrophy Following Portal Vein Embolization
Authors
Qiang Wang, MD, PhD
Torkel B. Brismar, MD, PhD
Dennis Björk, MD, PhD
Erik Baubeta, MD, PhD
Gert Lindell, MD, PhD
Bergthor Björnsson, MD, PhD
Ernesto Sparrelid, MD, PhD
Publication date
07-12-2024
Publisher
Springer International Publishing
Published in
Annals of Surgical Oncology / Issue 3/2025
Print ISSN: 1068-9265
Electronic ISSN: 1534-4681
DOI
https://doi.org/10.1245/s10434-024-16654-2
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