Comparison of translation algorithms in determining maximum allowable CTV shifts for Real-Time Gated Proton Therapy (RGPT) robustness evaluation in prostate cancers.

Introduction: 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.

Methods: Nine RGPT prostate patient plans with CTV volumes ranging from 17.1 to 96.72 cm² 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 $\pm$ 10 mm at 2 mm steps. At each step, dose metrics, which include CTV D_max, CTV D_95%, and CTV D_98%, were extracted and used as comparative metrics for CTV target coverage and hot spot evaluation.

Results: Across all axes, there were no statistically significant differences between the two algorithms for all three dose metrics: CTV D_max (P = 0.92, P = 0.91, and P = 0.47), CTV D_95% (P = 0.97, P = 0.22, and P = 0.33), and CTV D_98% (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.

Conclusion: 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.