Lee James Kuan Huei, Lew Kah Seng, Koh Calvin Wei Yang, Lee James Cheow Lei, Bettiol Andrew A, Park Sung Yong, Tan Hong Qi
Department of Physics, National University Singapore, Singapore, Singapore.
Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore.
J Appl Clin Med Phys. 2025 Jan;26(1):e14543. doi: 10.1002/acm2.14543. Epub 2024 Oct 3.
Real-Time Gated Proton Therapy (RGPT) is an active motion management technique that utilizes treatment gating and tumor tracking via fiducial markers. When performing RGPT treatment for prostate cancer, it is essential to account for the CTV displacement relative to the body in the clinical workflow. The workflow at the National Cancer Centre Singapore (NCCS) includes bone matching via CT-CBCT images, followed by fiducial matching via pulsed fluoroscopy (soft tissue matching), and finally, a robustness evaluation procedure to determine if the difference is within an allowable tolerance. In this study, we compare two CTV translation methods for robustness evaluation: (1) an in-house translation algorithm and (2) the RayStation "simulate organ motion" Deformable image registration (DIR) algorithm.
Nine RGPT prostate patient plans with CTV volumes ranging from 17.1 to 96.72 cm were included in this study. An in-house translation algorithm and "simulate organ motion" DIR RayStation algorithm were used to generate CTV shifts along R-L, I-S, and P-A axes between 10 mm at 2 mm steps. At each step, dose metrics, which include CTV D, CTV D, and CTV D, were extracted and used as comparative metrics for CTV target coverage and hot spot evaluation.
Across all axes, there were no statistically significant differences between the two algorithms for all three dose metrics: CTV D (P = 0.92, P = 0.91, and P = 0.47), CTV D (P = 0.97, P = 0.22, and P = 0.33), and CTV D (P = 0.85, P = 0.33, and P = 0.36). Further, the in-house translation algorithm evaluation time was less than 10 s, two orders of magnitude faster than the DIR algorithm.
Our results demonstrate that the simpler in-house algorithm performs equivalently to the realistic DIR algorithm when simulating CTV motion in prostate cancers. Furthermore, the in-house algorithm completes the robustness evaluation two orders of magnitude faster than the DIR algorithm. This significant reduction in evaluation time is crucial especially when preparatory time efficiency is of paramount importance in a busy clinic.
实时门控质子治疗（RGPT）是一种主动运动管理技术，它通过基准标记物利用治疗门控和肿瘤追踪。在对前列腺癌进行RGPT治疗时，在临床工作流程中考虑CTV相对于身体的位移至关重要。新加坡国立癌症中心（NCCS）的工作流程包括通过CT - CBCT图像进行骨匹配，随后通过脉冲荧光透视（软组织匹配）进行基准匹配，最后进行稳健性评估程序以确定差异是否在允许的公差范围内。在本研究中，我们比较了两种用于稳健性评估的CTV平移方法：（1）一种内部平移算法和（2）RayStation的“模拟器官运动”可变形图像配准（DIR）算法。
本研究纳入了9例RGPT前列腺患者计划，CTV体积范围为17.1至96.72 cm。使用内部平移算法和“模拟器官运动”DIR RayStation算法在R - L、I - S和P - A轴上以2 mm步长生成10 mm的CTV位移。在每个步骤中，提取包括CTV D、CTV D和CTV D在内的剂量指标，并将其用作CTV靶区覆盖和热点评估的比较指标。
在所有轴向上，两种算法在所有三个剂量指标上均无统计学显著差异：CTV D（P = 0.92，P = 0.91，P = 0.47）、CTV D（P = 0.97，P = 0.22，P = 0.33）和CTV D（P = 0.85，P = 0.33，P = 0.36）。此外，内部平移算法的评估时间少于10秒，比DIR算法快两个数量级。
我们的结果表明，在模拟前列腺癌的CTV运动时，更简单的内部算法与逼真的DIR算法表现相当。此外，内部算法完成稳健性评估的速度比DIR算法快两个数量级。评估时间的显著减少至关重要，特别是在繁忙的诊所中准备时间效率至关重要的情况下。
