Utilizing radiomics and dosiomics with AI for precision prediction of radiation dermatitis in breast cancer patients.

ABSTRACT:

Purpose

This study explores integrating clinical features with radiomic and dosiomic characteristics into AI models to enhance the prediction accuracy of radiation dermatitis (RD) in breast cancer patients undergoing volumetric modulated arc therapy (VMAT).

Materials and methods

This study involved a retrospective analysis of 120 breast cancer patients treated with VMAT at Kaohsiung Veterans General Hospital from 2018 to 2023. Patient data included CT images, radiation doses, Dose-Volume Histogram (DVH) data, and clinical information. Using a Treatment Planning System (TPS), we segmented CT images into Regions of Interest (ROIs) to extract radiomic and dosiomic features, focusing on intensity, shape, texture, and dose distribution characteristics. Features significantly asso

SUBMITTER: Lee TF 

PROVIDER: S-EPMC11304569 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature