Bertschi Stefanie, Stützer Kristin, Berthold Jonathan, Elstrøm Ulrik, Vestergaard Anne, Bernardini Giuliano Perotti, Marmitt Gabriel, Janssens Guillaume, Pietsch Julian, Both Stefan, Korreman Stine, Richter Christian
OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Phys Imaging Radiat Oncol. 2025 May 10;34:100778. doi: 10.1016/j.phro.2025.100778. eCollection 2025 Apr.
Prompt-gamma based treatment verification, such as prompt-gamma imaging (PGI), is crucial for detecting anatomical changes and serving as safety net during proton therapy treatments. This is especially important in an online-adaptive setting, when imaging will be based on cone-beam computed tomography (CBCT). This study investigated whether PGI, proven effective to detect relevant anatomical changes in clinical settings, can also verify treatment plans adapted on CBCTs, particularly the reliability of CBCT-based PGI-simulations of expected prompt-gamma distributions, a key requirement for PGI-based verification.
For a homogeneous and anthropomorphic phantom, a fan-beam computed tomography (CT) and a CBCT were acquired. Corrected CBCT and virtual CT datasets were generated. PGI simulations and independent dose calculations were performed on the different CBCT datasets and compared to the fan-beam CT, extracting PGI-based and integrated-depth-dose (IDD)-based range-shifts. For three head-and-neck cancer patients, PGI-based shifts between the fan-beam CT and a synthetic CT (from a daily CBCT) were compared to line-dose-based shifts from clinical dose calculations.
For the homogeneous phantom, all CBCT datasets enabled adequate PGI simulations, with PGI-based shifts correlating very closely with IDD-based shifts. For the anthropomorphic phantom and the three patient datasets, observed PGI-based shifts were correlated to IDD-based shifts.
For phantom and patient data, PGI simulations depended mainly on the reliability of depth-dose distributions on the planning image with negligible uncertainties from PG emission. For CBCT-based OAPT, correct depth-dose distributions are required. Hence, PGI is also a promising treatment verification tool for CBCT-based OAPT.
基于快发γ射线的治疗验证，如快发γ成像（PGI），对于在质子治疗过程中检测解剖结构变化并作为安全保障至关重要。在基于锥束计算机断层扫描（CBCT）进行成像的在线自适应治疗环境中，这一点尤为重要。本研究调查了在临床环境中已被证明能有效检测相关解剖结构变化的PGI，是否也能验证基于CBCT调整的治疗计划，特别是基于CBCT的PGI模拟预期快发γ射线分布的可靠性，这是基于PGI验证的一项关键要求。
对于一个均匀的人体模型，获取了扇束计算机断层扫描（CT）和CBCT。生成了校正后的CBCT和虚拟CT数据集。在不同的CBCT数据集上进行了PGI模拟和独立剂量计算，并与扇束CT进行比较，提取基于PGI和基于积分深度剂量（IDD） 的射程偏移。对于三名头颈癌患者，将扇束CT和合成CT（来自每日CBCT）之间基于PGI的偏移与临床剂量计算中基于线剂量的偏移进行了比较。
对于均匀人体模型，所有CBCT数据集都能进行充分的PGI模拟，基于PGI的偏移与基于IDD的偏移密切相关。对于人体模型和三个患者数据集，观察到的基于PGI的偏移与基于IDD的偏移相关。
对于人体模型和患者数据，PGI模拟主要取决于计划图像上深度剂量分布的可靠性，而PG发射产生的不确定性可忽略不计。对于基于CBCT的在线自适应质子治疗（OAPT），需要正确的深度剂量分布。因此，PGI也是基于CBCT的OAPT的一种有前景的治疗验证工具。
