Dose-Response Mapping of Bladder and Rectum in Prostate Cancer Patients Undergoing Radiotherapy with and Without Baseline Toxicity Correction

Abstract

Background and Purpose: Radiotherapy dose-response maps (DRM) combine dose-surface maps (DSM) and toxicity outcomes to identify high-risk sub-regions in organ-at-risk (OAR). This study compares two methods of incorporating late toxicities—baseline correction and no baseline correction—in dose-response modelling to evaluate their impact on high-risk bladder/rectum sub-regions in prostate cancer patients undergoing radiotherapy. Materials and Methods: The analysis included 1808 datasets, with 589 exclusions before toxicity-specific data removal. Bladder/rectum were automatically segmented on planning computed tomography scans, DSMs unwrapped into 91x90 grids, and converted to equivalent doses in 2 Gy fractions (EQD2; α/β=1 Gy). Seventeen late toxicities were assessed with two methods: (i) baseline toxicity subtracted from the maximum of 12- and 24-months toxicity scores, dichotomized at grade 1, and (ii) maximum of 12- and 24-months toxicity scores dichotomized at grade 1. DSMs were split accordingly, and voxel-wise t-values computed using Welch’s t-equation. Statistically significant voxels were identified via the 95th percentile of Tmax distribution. Results: Event counts with baseline correction were 82, 82, 286, and 226 for urinary tract obstruction, retention, urgency, and incontinence, respectively; without baseline correction, they were 93, 104, 465, and 361. For bladder DSMs, incontinence, obstruction, retention, and urgency had 1143/186, 1768/1848, 516/0, and 33/0 significant voxels without/with baseline correction. For rectum DSMs, incontinence and obstruction had 604/0 and 1980/889 significant voxels without/with baseline correction. Conclusions: DRM without baseline correction appears more sensitive to high-risk regions due to higher event counts. Non-linear toxicity grading and multivariable analysis may enhance DRM reliability.

Note:
Funding declaration: This work was funded by Movember, Prostate Cancer UK (RIA15-ST2-031), and Christie NHS Foundation Trust. Marcel van Herk and Ananya Choudhury were supported by the National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre (NIHR203308). Catharine West would like to acknowledge BRC/RADNET. This research was made possible through funding from the European Union - Seventh Framework Programme for Research, Technological Development, and Demonstration, under Grant ID: 601826. Ana Vega: supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (PI22/00589, PI19/01424; INT24/00023); the ERAPerMed JTC2018 funding (AC18/00117); the Autonomous Government of Galicia (Consolidation and structuring program: IN607B), and by the AECC (PRYES211091VEGA).

Conflict of Interests: Dirk de Ruysscher obtained grants and/or contracts from (i) AstraZeneca/BMS/Beigene/Philips/Olink: Research grant/support/Advisory Board: Institutional financial interests (no personal financial interests), and (ii) Eli-Lilly: Advisory Board: Institutional financial interests (no personal financial interests). All other authors declare no competing interests.

Ethical Approval: All procedures complied with relevant regulations and received ethics approval (UK: North West - GM East REC, ref: 14/NW/0035).

Keywords: prostate cancer, Radiotherapy, Toxicity, Prediction modeling, Voxel-based dose-response analysis (VBA), Organs-at-risk (OAR)