ArticleNPJ systems biology and applications2025
Measurable imaging-based changes in enhancement of intrahepatic cholangiocarcinoma after radiotherapy reflect physical mechanisms of response.
Article in NPJ systems biology and applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Rational design of immunogenic nanoparticles as a platform to reduce ovarian tumor burden in mice.International journal of pharmaceutics · 2025Article
- The use of minor response, volumetric assessment, and growth rate kinetics as endpoints in grade 1-3 glioma clinical trials: a RANO perspective.Neuro-oncology · 2025Review
- New Insights into Personalized Surgical Oncology.Journal of personalized medicine · 2025Article
- Rational Design of Immunogenic Nanoparticles as a Platform for Enhanced Ovarian Cancer Immunotherapy in Mice.bioRxiv : the preprint server for biology · 2025Article
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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.
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