Faculty, Staff and Student Publications
Language
English
Publication Date
12-12-2025
Journal
npj Systems Biology and Applications
DOI
10.1038/s41540-025-00616-9
PMID
41387975
PMCID
PMC12717172
PubMedCentral® Posted Date
12-12-2025
PubMedCentral® Full Text Version
Post-print
Abstract
Escalated doses of radiotherapy associate with improved local control and overall survival (OS) in intrahepatic cholangiocarcinoma (iCCA), but personalization remains limited because conventional size-based CT criteria correlate poorly with outcomes. We hypothesized that quantitative enhancement measurements would better predict clinical outcomes and guide individualized RT optimization. In a retrospective cohort of 154 patients, we analyzed pre- and post-RT CT scans using quantitative European Association for Study of Liver (qEASL) to derive viable tumor volumes, comparing enhancement-based metrics with size-based RECIST and linking them to outcomes via survival and mathematical modeling. Change in enhancement volume was strongly associated with OS after adjustment, outperforming RECIST, and a ≥ 33% reduction optimally distinguished responders. From modeling analyses, the patient-specific tumor growth rate parameter emerged as the dominant mechanistic predictor, achieving 80.5% classification accuracy. Importantly, CT-derived mathematical parameters from this framework may inform RT planning and dose adaptation, particularly for resistant tumors, by bridging imaging with mechanistic insight.
Keywords
Humans, Cholangiocarcinoma, Male, Female, Retrospective Studies, Tomography, X-Ray Computed, Middle Aged, Bile Duct Neoplasms, Aged, Tumor Burden, Treatment Outcome, Adult, Aged, 80 and over, Cancer, Computational biology and bioinformatics, Oncology
Published Open-Access
yes
Recommended Citation
De, Brian; Dogra, Prashant; Zaid, Mohamed; et al., "Measurable Imaging-Based Changes in Enhancement of Intrahepatic Cholangiocarcinoma After Radiotherapy Reflect Physical Mechanisms of Response" (2025). Faculty, Staff and Student Publications. 5999.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/5999
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