Yang Jie, Zhang Pengpeng, Tyagi Neelam, Scripes Paola Godoy, Subashi Ergys, Liang Jiayi, Lovelock Dale, Mechalakos James, Li Anyi, Lim Seng B
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, United States.
Front Oncol. 2022 Mar 11;12:747825. doi: 10.3389/fonc.2022.747825. eCollection 2022.
Commercial independent monitor unit (IMU) check systems for high-magnetic-field MR-guided radiation therapy (RT) systems are lacking. We investigated the feasibility of adopting an existing treatment planning system (TPS) as an IMU check for online adaptive radiotherapy using 1.5-Tesla MR-Linac.
The 7-MV flattening filter free (FFF) beam and multi-leaf collimator (MLC) models of a 1.5-T Elekta Unity MR-Linac within Monte Carlo-based Monaco TPS were used to generate an optimized beam model in Eclipse TPS. The MLC dosimetric leaf gap of the beam in Eclipse was determined by matching the dose distribution of Eclipse-generated intensity-modulated radiation therapy (IMRT) plans using the Analytical Anisotropic Algorithm (AAA) algorithm to Monaco plans. The plans were automatically adjusted for different source-to-axis distances (SADs) between the two systems. For IMU check, the treatment plans developed in Monaco were transferred to Eclipse to recalculate the dose using AAA. A plug-in within Eclipse was created to perform a 2D gamma analysis of the AAA and Monte Carlo dose distribution on a beam's eye view parallel plane. Monaco dose distribution was shifted laterally by 2 mm during gamma analysis to account for the impact of magnetic field on electron trajectories. Eclipse doses for posterior beams were corrected for both the Unity couch and the posterior MR coil attenuation. Thirteen patients, each with 4-5 fractions for a variety of tumor sites (pancreas, rectum, and prostate), were tested.
After thorough commissioning, the method was implemented as part of the standard clinical workflow. A total of 62 online plans, each with approximately 15 beams, were evaluated. The average per-beam gamma (3%/3 mm) pass rate for plans was 97.9% (range, 95.9% to 98.8%). The average pass rate per beam for all 932 beams used in these plans was 97.9% ± 1.9%, with the lowest per-beam gamma pass rate at 88.4%. The time for the process was within 3.2 ± 0.9 min.
The use of a second planning system provides an efficient way to perform IMU checks with clinically acceptable accuracy for online adaptive plans on Unity MR-Linac. This is essential for meeting the safety requirements for second checks as outlined in American Association of Physicists in Medicine Task Group (AAPM TG) reports 114 and 219.
用于高磁场磁共振引导放射治疗(RT)系统的商业独立监测单元(IMU)检查系统尚不存在。我们研究了采用现有的治疗计划系统(TPS)作为IMU检查的可行性,以用于使用1.5特斯拉磁共振直线加速器的在线自适应放射治疗。
基于蒙特卡洛的Monaco TPS中1.5-T Elekta Unity磁共振直线加速器的7-MV无 flattening filter(FFF)束和多叶准直器(MLC)模型,用于在Eclipse TPS中生成优化的束模型。通过使用解析各向异性算法(AAA)算法使Eclipse生成的调强放射治疗(IMRT)计划的剂量分布与Monaco计划相匹配,来确定Eclipse中束的MLC剂量学叶片间隙。针对两个系统之间不同的源轴距(SAD),对计划进行自动调整。对于IMU检查,将在Monaco中制定的治疗计划传输到Eclipse,以使用AAA重新计算剂量。在Eclipse中创建了一个插件,以在束的视场平行平面上对AAA和蒙特卡洛剂量分布进行二维伽马分析。在伽马分析期间,将Monaco剂量分布横向移动2毫米,以考虑磁场对电子轨迹的影响。对Unity治疗床和后部磁共振线圈衰减对后部束的Eclipse剂量进行校正。对13名患者进行了测试,每位患者针对多种肿瘤部位(胰腺、直肠和前列腺)接受4-5次分割照射。
经过全面调试后,该方法作为标准临床工作流程的一部分得以实施。共评估了62个在线计划,每个计划约有15束射线。计划的平均每束射线伽马(3%/3毫米)通过率为97.9%(范围为95.9%至98.8%)。这些计划中使用的所有932束射线的平均每束射线通过率为97.9%±1.9%,最低的每束射线伽马通过率为88.4%。该过程的时间在3.2±0.9分钟内。
使用第二个计划系统为在Unity磁共振直线加速器上对在线自适应计划进行IMU检查提供了一种高效的方法,且具有临床可接受的准确性。这对于满足美国医学物理学家协会任务组(AAPM TG)报告114和219中概述的二次检查安全要求至关重要。