PROton Stopping power estimation in Ion Therapy (PROSIT)

带电粒子治疗(CPT)是一种有效的程序，用于照射致死剂量的肿瘤，同时避免健康组织和邻近器官处于危险之中。单束的剂量分布赋予了CPT的力量：一个明显的最大值，布拉格峰，然后是一个陡峭的下降。这一功能还使CPT对用于治疗计划的实际止血力(SP)和计算的SP之间的微小不匹配非常敏感。因此，引入了安全裕度，以防止可能的规划错误和患者形态变化的影响。然而，为了充分利用束流的物理性质，对实际剂量沉积(或至少粒子范围)的监测和核实是必要的。目前还没有一种监测方法达到临床常规，但许多技术正在研究中。其中，瞬发伽马计时(PGT)显示出很大的潜力。PGT依赖于检测到的瞬发伽马(PG)射线的时间分布，该时间分布源于沿光束路径的去激发。在我们与INFN-Turin的合作中，我们已经利用铅笔质子束的电子数据表明，不仅可以从各种探测器的PGT分布中重建PG发射顶点的粒子范围，而且还可以重建PG发射顶点的时空分布。我们的方法，SER-PGT，通过最大化泊松似然和测量过程的建模来重建PG排放的时空分布估计。在PROSIT内部，我们将首先改进和扩展我们的模型和算法，以实现更好的重建，包括对背景信号和数据截断的补偿，以及参数优化。在均匀靶的初步工作和硅内数据的支持下，我们计划超越并从重建的时空PG分布中获得阻止功率，因为后者包含了关于靶内粒子运动的信息。为此，我们利用盖革距离法则对Bortfeld提出的粒子运动学模型进行了解析逆变换。然后，将方程的参数与SER-PGT的后处理输出进行拟合。我们将把这一过程扩展到非均匀靶点，同时考虑到在铅笔束扫描中，几个不同能量和方向的光束以肿瘤体积为靶点。最后，我们设想开发一种能够跳过中间SER-PGT重建的过程，以使用PG排放模型直接从测量的PGT数据估计SP。我们的长期目标是允许体内治疗验证和根据理论和实际阻止能力的比较对治疗计划进行个性化调整，后者通过多探测器PGT系统结合我们的模型和程序进行估计。

Charged particle therapy (CPT) is an effective procedure for irradiating tumors with lethal doses while sparing healthy tissue and neighboring organs at risk. The dose profile of single beams gives CPT its strength: a pronounced maximum, the Bragg peak, followed by a steep drop. This feature also makes CPT very sensitive to small mismatches between the actual stopping power (SP) and the computed SP used for therapy planning. Safety margins are thus introduced to prevent the effects of possible planning errors and changes in patient’s morphology. However, monitoring and verification of the actual dose deposition (or at least the particle range) are necessary to take full advantage of the beam physical properties. At present no monitoring method has reached clinical routine, but many techniques are under investigation. Among them, prompt-gamma timing (PGT) shows great potential. PGT relies on the time profiles of detected prompt-gamma (PG) rays which originate from de-excitations along the beam path. In our joint work with INFN - Turin, we have shown using in-silico data of a pencil proton beam that not only the particle range but also the spatiotemporal distribution of the PG emission vertices can be reconstructed from PGT profiles from various detectors. Our method, SER-PGT, reconstructs estimates of the spatiotemporal PG emission distribution through maximization of the Poisson likelihood and the modeling of the measurement process. Within PROSIT we will first improve and extend our models and algorithms for a better reconstruction, including compensation for background signals and data truncation, as well as parameter optimization. Supported by preliminary works with homogeneous targets and in-silico data, we plan to go beyond and obtain the stopping power from the reconstructed spatiotemporal PG distribution, as the latter contains information about the particle motion within the target. To this aim, we analytically invert the equation proposed by Bortfeld to model the particle kinematics using Geiger’s range rule. Then, the parameters of the equation are fitted to the post-processed output of SER-PGT. We will extend this procedure to non-uniform targets, also taking into account that in pencil-beam scanning several beams of different energies and directions target the tumor volume. Finally, we envision developing a procedure able to skip the intermediate SER-PGT reconstruction to directly estimate the SP from measured PGT data using models of the PG emission. Our long-term goal is to allow for in-vivo treatment verification and the personalized readjustment of the treatment plan based on the comparison of the theoretical and the actual stopping power, the latter estimated through a multi-detector PGT system in combination with our models and procedures.