OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany.
OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany.
Int J Radiat Oncol Biol Phys. 2023 Nov 1;117(3):718-729. doi: 10.1016/j.ijrobp.2023.05.002. Epub 2023 May 7.
PURPOSE: The development of online-adaptive proton therapy (PT) is essential to overcome limitations encountered by day-to-day variations of the patient's anatomy. Range verification could play an essential role in an online feedback loop for the detection of treatment deviations such as anatomical changes. Here, we present the results of the first systematic patient study regarding the detectability of anatomical changes by a prompt-gamma imaging (PGI) slit-camera system. METHODS AND MATERIALS: For 15 patients with prostate cancer, PGI measurements were performed during 105 fractions (201 fields) with in-room control computed tomography (CT)acquisitions. Field-wise doses on control CT scans were manually classified as whether showing relevant or non-relevant anatomical changes. This manual classification of the treatment fields was then used to establish an automatic field-wise ground truth based on spot-wise dosimetric range shifts, which were retrieved from integrated depth-dose (IDD) profiles. To determine the detection capability of anatomical changes with PGI, spot-wise PGI-based range shifts were initially compared with corresponding dosimetric IDD range shifts. As final endpoint, the agreement of a developed field-wise PGI classification model with the field-wise ground truth was determined. Therefore, the PGI model was optimized and tested for a subcohort of 131 and 70 treatment fields, respectively. RESULTS: The correlation between PGI and IDD range shifts was high, ρ = 0.67 (p < 0.01). Field-wise binary PGI classification resulted in an area under the curve of 0.72 and 0.80 for training and test cohorts, respectively. The model detected relevant anatomical changes in the independent test cohort, with a sensitivity and specificity of 74% and 79%, respectively. CONCLUSIONS: For the first time, evidence of the detection capability of anatomical changes in prostate-cancer PT from clinically acquired PGI data is shown. This emphasizes the benefit of PGI-based range verification and demonstrates its potential for online-adaptive PT.
目的：开发在线自适应质子治疗（PT）对于克服患者解剖结构日常变化带来的限制至关重要。在检测治疗偏差（如解剖结构变化）的在线反馈回路中，范围验证可能发挥重要作用。本文首次系统地研究了利用即时伽马成像（PGI）狭缝相机系统检测解剖变化的能力。
方法和材料：对 15 例前列腺癌患者进行了 105 次（201 野）PGI 测量，同时进行了机房控制 CT（CT）采集。手动将对照 CT 扫描上的每个射野的剂量分为是否显示相关或不相关的解剖变化。然后，基于逐点剂量范围偏移量，对治疗野的这种手动分类建立了自动逐野的真实分类，这些偏移量是从整合深度剂量（IDD）曲线中检索到的。为了确定 PGI 检测解剖变化的能力，首先比较了逐点 PGI 基于的范围偏移与相应的剂量 IDD 范围偏移。作为最终的终点，确定了一个开发的逐野 PGI 分类模型与逐野真实分类的一致性。因此，分别对 131 个和 70 个治疗野的子队列进行了 PGI 模型的优化和测试。
结果：PGI 与 IDD 范围偏移的相关性很高，ρ=0.67（p<0.01）。逐野二元 PGI 分类在训练和测试队列中得到的曲线下面积分别为 0.72 和 0.80。该模型在独立测试队列中检测到了相关的解剖变化，敏感性和特异性分别为 74%和 79%。
结论：本文首次证明了从临床获得的 PGI 数据中可以检测前列腺癌 PT 中的解剖变化。这强调了基于 PGI 的范围验证的益处，并展示了其在在线自适应 PT 中的潜力。
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