Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.

ABSTRACT:

Purpose

To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular carcinoma (HCC) for the prediction of response to Yttrium 90 radiation segmentectomy.

Methods

This retrospective study included 154 patients (38 female; mean age 66.8 years) who underwent contrast-enhanced MRI prior to radiation segmentectomy. Radiomics features were manually extracted on volumes of interest on post-contrast T1-weighted images at the portal venous phase (PVP). Tumor-based response assessment was evaluated 6 months post-treatment using mRECIST. A logistic regression model was used to predict binary response outcome [complete response at 6 months with no-re-treatment (response group) against the rest (non-response group, including partial response, progressive di

SUBMITTER: Stocker D 

PROVIDER: S-EPMC11991973 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature