PET-Guided Modeling of Mucosal Boron Heterogeneity Improves Dose-Toxicity Prediction in BNCT

To evaluate whether mucosal boron heterogeneity measured using fluoro-boronophenylalanine positron emission tomography (¹⁸F-BPA PET) improves the prediction of oral mucositis in boron neutron capture therapy (BNCT), and to establish an imaging-guided framework for normal tissue complication probability (NTCP) modeling.

This retrospective study analyzed 45 BNCT treatment sessions for head and neck cancer. Pre-treatment ¹⁸F-BPA PET was used to quantify PET-derived mucosal uptake and to derive an uptake-defined mucosal region using a tissue-to-blood ratio (TBR) threshold of 1.8. Four mucosal dose-calculation workflows were compared: (1) the Finnish workflow and (2) the Japanese workflow-both delineating mucosa anatomically and assuming uniform boron concentration implemented via a fixed TBR; (3) anatomical mucosa and (4) uptake-defined mucosa with heterogeneous boron distribution derived from PET-derived uptake heterogeneity. Biological (Gy-equivalent) and physical (Gy) subvolume dose metrics, including dose to the hottest 0.05 cubic centimeters (D_0.05cc), were evaluated for correlation with mucositis severity, discrimination of grade ≥ 2 toxicity, and suitability for NTCP modeling.

¹⁸F-BPA PET demonstrated pronounced functional heterogeneity across the mucosa. Among all evaluated metrics, uptake-defined biological D_0.05cc showed the strongest and most consistent association with toxicity, fulfilling all NTCP validity criteria yielding the highest discriminative performance (repeated cross-validated area under the curve, 0.738 ± 0.025) and physiologically plausible TD₁₀-TD₉₀ thresholds (4.85-12.84 Gy-equivalent). In contrast, Finnish and Japanese anatomical maximum-dose metrics, based on uniform-boron assumptions, showed no meaningful correlation with clinical outcomes.

Functional PET imaging reveals clinically important mucosal heterogeneity that influences BNCT toxicity. The uptake-defined biological D_0.05cc demonstrated superior prediction of oral mucositis and may provide a promising hypothesis-generating framework for developing patient-specific mucosal dose constraints, pending prospective validation.