发表机构
Kagawa University Faculty of Medicine; Particle Beam Therapy Research Institute, Inc.（香川大学医学院; 粒子束治疗研究所有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出BNCT中粗粒化效应预测的不可行框架，证明在微观异质性下平均剂量等可观测量无法唯一确定生物响应，并给出部分识别区间与逼近界，明确信息丢失范围。
AI 中文摘要
我们确定了在硼中子俘获治疗（BNCT）中，粗粒化可观测量何时能唯一确定基于期望的生物响应。微观靶标群体由概率分布表示，而保留的可观测量是有限多个群体平均的线性描述符。对于包含所有有限支撑微观分布的容许类，精确的无分布识别成立当且仅当单靶标响应核位于常数函数与保留描述符的张成空间中。因此，在不受限制的微观异质性下，平均剂量、混合场分量均值以及有限矩集合通常并不足够。我们还推导了不可约的模糊性与逼近界、有界非增凸生存核的尖锐部分识别区间、治疗排序准则以及下尾和高暴露界。一个固定总暴露的时间模型区分了瞬态重采样与持续性靶标特异性欠暴露，而一个标记泊松模型表明，分离的频率和事件质量边际分布不一定能决定生存情况。该框架阐明了通过BNCT粗粒化丢失了哪些微观信息，同时为在独立证明合理的模型限制下进行逼近、部分识别和预测留出了空间。
英文摘要
We establish when coarse-grained observables uniquely determine an expectation-based biological response in boron neutron capture therapy (BNCT). Microscopic target populations are represented by probability distributions, while retained observables are finitely many population-averaged linear descriptors. For an admissible class containing all finitely supported microscopic distributions, exact distribution-free identification holds if and only if the single-target response kernel lies in the span of the constant function and retained descriptors. Thus mean dose, mixed-field component means, and finite moment sets are not generally sufficient under unrestricted microscopic heterogeneity. We also derive irreducible ambiguity and approximation bounds, sharp partial-identification intervals for bounded non-increasing convex survival kernels, a treatment-ranking criterion, and lower-tail and high-exposure bounds. A fixed-total-exposure temporal model distinguishes transient re-sampling from persistent target-specific underexposure, and a marked-Poisson model shows that separate frequency and event-quality marginals need not determine survival. The framework clarifies which microscopic information is lost through BNCT coarse-graining while leaving room for approximation, partial identification, and prediction under independently justified model restrictions.
Comments45 pages, 3 figures
