This study presents a proof-of-concept for a novel Bayesian inverse method in a one-dimensional setting, aimed at proton beam therapy treatment verification. Our methodology is predicated on a hypothetical scenario wherein strategically positioned sensors detect prompt-{\gamma}'s emitted from a proton beam when it interacts with defined layers of tissue. Using this data, we employ a Bayesian framework to estimate the proton beam's energy deposition profile. We validate our Bayesian inverse estimations against a closed-form approximation of the Bragg Peak in a uniform medium and a layered lung tumour.

翻译：本研究在一维场景下提出了一种新颖的贝叶斯逆方法概念验证，旨在实现质子束治疗验证。该方法基于一个假设场景：当质子束与特定组织层相互作用时，位于策略位置的传感器可探测到其发射的瞬发-γ射线。利用这些数据，我们采用贝叶斯框架来估计质子束的能量沉积分布。我们将贝叶斯逆估计结果与均匀介质中布拉格峰的闭式近似解以及分层肺部肿瘤的实际情况进行了验证。