Predicting treatment response to systemic therapy in advanced gallbladder cancer using multiphase enhanced CT images.

ABSTRACT:

Background

Accurate estimation of treatment response can help clinicians identify patients who would potentially benefit from systemic therapy. This study aimed to develop and externally validate a model for predicting treatment response to systemic therapy in advanced gallbladder cancer (GBC).

Methods

We recruited 399 eligible GBC patients across four institutions. Multivariable logistic regression analysis was performed to identify independent clinical factors related to therapeutic efficacy. This deep learning (DL) radiomics signature was developed for predicting treatment response using multiphase enhanced CT images. Then, the DL radiomic-clinical (DLRSC) model was built by combining the DL signature and significant clinical factors, and its predictive performance was ev

SUBMITTER: Wu J 

PROVIDER: S-EPMC12559086 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature