Predictive dosimetric parameters for adaptive replanning in proton beam therapy for thoracic cancer.

Authors

Nrusingh C Biswal, Hua-Ren Cherng, Abdul K Parchur, Baoshe Zhang, David Alicia, Elizabeth Manuel, Kai Sun, ByongYong Yi, Matthew J Ferris, Zaker Rana

Published in

Medical dosimetry : official journal of the American Association of Medical Dosimetrists. Jul 04, 2026. Epub Jul 04, 2026.

Abstract

Proton beam therapy (PBT) offers the advantage of delivering high doses of localized radiation therapy while sparing surrounding normal tissue, making it highly suitable for thoracic malignancies. However, the precision of PBT also makes it susceptible to treatment-related changes in the tumor or target volume, patient anatomy, and surrounding tissues, necessitating adaptive replanning. This study retrospectively analyzed the treatment plans of 180 thoracic cancer patients treated at an academic proton therapy center between 2020 and 2023. We investigated whether treatment planning dosimetric parameters, such as robustness, dose maximum, and doses to organs at risk in initial plans, can predict the need for adaptive replanning. Significant predictors identified include clinical target volume (CTV), heart volume, plan Dmax, mean lung dose, lung V20, lung V5, mean heart dose, heart V50, and spinal cord Dmax. Among those parameters, CTV and heart volume independently predict the need for replanning, and the cutoff values are 191 cc and 888 cc, respectively. Per 100-cc increase, odds of replanning increased by 15% for CTV volume (OR 1.15; 95% CI, 1.02 to 1.31) and 26% for heart volume (OR 1.26; 95% CI, 1.03 to 1.55). Our results suggest that monitoring these parameters can help identify plans that require closer scrutiny and more frequent scanning during the course of treatment to evaluate and adjust initial plans. This study contributes to optimizing the scheduling of quality assurance CT (QACT) scans, enhancing patient care by predicting which patients are likely to benefit from adaptive replanning.

PMID:
42401519
Bibliographic data and abstract were imported from PubMed on 05 Jul 2026.

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