Health AI Central
Peer-Reviewed Publication
Phys Med Biol2025;70(21)October 22, 2025Clinical Trial, Phase II

Exploring radiomic and topological features to evaluate treatment response in rectal cancer.

Haozhao Zhang1,2, Jiaqi Liu1,2, Naveen Rajamohan3, Nina N Sanford1, Gaurav Khatri3, Arely Perez Rodriguez1, Satwik Rajaram1, Steve Jiang1,2, Robert Timmerman1, Todd Aguilera1, Hao Peng1,2
1Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States of America.
2Medical Artificial Intelligence and Automation Laboratory, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States of America.
3Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States of America.
PubMed DOI

Abstract

Objective.This study investigates the potential of topological data analysis (TDA) in conjunction with conventional radiomics applied to longitudinal T2-weighted magnetic resonance imaging (MRI) to evaluate treatment response following neoadjuvant therapy, with or without anti-CD40 immunotherapy, in patients with locally advanced rectal cancer.Approach.Paired pre- and post-treatment MRIs from 21 p…

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