¹⁸F-FDG PET/CT-based intratumoral and peritumoral radiomics combining ensemble learning for prognosis prediction in hepatocellular carcinoma: a multi-center study.

ABSTRACT:

Background

Radiomic models combining intratumoral with peritumoral features are potentially beneficial to enhance the predictive performance. This study aimed to identify the optimal ¹⁸F-FDG PET/CT-derived radiomic models for prediction of prognosis in hepatocellular carcinoma (HCC).

Methods

A total of 135 HCC patients from two institutions were retrospectively included. Four peritumoral regions were defined by dilating tumor region with thicknesses of 2 mm, 4 mm, 6 mm, and 8 mm, respectively. Based on segmentation of intratumoral, peritumoral and integrated volume of interest (VOI), corresponding radiomic features were extracted respectively. After feature selection, a total of 15 intratumoral radiomic models were constructed based on five ensemble learning algor

SUBMITTER: Sui C 

PROVIDER: S-EPMC11841186 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature