Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Department of Radiation Oncology, Michigan Medicine, Ann Arbor, Michigan, USA.
J Appl Clin Med Phys. 2023 Dec;24(12):e14133. doi: 10.1002/acm2.14133. Epub 2023 Aug 29.
With the clinical implementation of kV-CBCT-based daily online-adaptive radiotherapy, the ability to monitor, quantify, and correct patient movement during adaptive sessions is paramount. With sessions lasting between 20-45 min, the ability to detect and correct for small movements without restarting the entire session is critical to the adaptive workflow and dosimetric outcome. The purpose of this study was to quantify and evaluate the correlation of observed patient movement with machine logs and a surface imaging (SI) system during adaptive radiation therapy.
Treatment machine logs and SGRT registration data log files for 1972 individual sessions were exported and analyzed. For each session, the calculated shifts from a pre-delivery position verification CBCT were extracted from the machine logs and compared to the SGRT registration data log files captured during motion monitoring. The SGRT calculated shifts were compared to the reported shifts of the machine logs for comparison for all patients and eight disease site categories.
The average (±STD) net displacement of the SGRT shifts were 2.6 ± 3.4 mm, 2.6 ± 3.5 mm, and 3.0 ± 3.2 in the lateral, longitudinal, and vertical directions, respectively. For the treatment machine logs, the average net displacements in the lateral, longitudinal, and vertical directions were 2.7 ± 3.7 mm, 2.6 ± 3.7 mm, and 3.2 ± 3.6 mm. The average difference (Machine-SGRT) was -0.1 ± 1.8 mm, 0.2 ± 2.1 mm, and -0.5 ± 2.5 mm for the lateral, longitudinal, and vertical directions. On average, a movement of 5.8 ± 5.6 mm and 5.3 ± 4.9 mm was calculated prior to delivery for the CBCT and SGRT systems, respectively. The Pearson correlation coefficient between CBCT and SGRT shifts was r = 0.88. The mean and median difference between the treatment machine logs and SGRT log files was less than 1 mm for all sites.
Surface imaging should be used to monitor and quantify patient movement during adaptive radiotherapy.
随着基于千伏锥形束 CT(kV-CBCT)的每日在线自适应放疗的临床实施,能够在自适应治疗过程中监测、量化和纠正患者运动至关重要。由于治疗时间通常在 20-45 分钟之间,因此无需重新开始整个治疗过程即可检测和纠正小的运动,这对于自适应工作流程和剂量学结果至关重要。本研究的目的是量化和评估在自适应放疗过程中观察到的患者运动与治疗机日志和表面成像(SI)系统之间的相关性。
导出并分析了 1972 个治疗单元的治疗机日志和 SGRT 注册数据日志文件。对于每个治疗单元,从预配准位置验证 CBCT 中提取计算得到的移位值,并将其与运动监测期间捕获的 SGRT 注册数据日志文件进行比较。将 SGRT 计算得到的移位值与机器日志中报告的移位值进行比较,以比较所有患者和八个疾病部位类别的数据。
SGRT 移位的平均(±标准差)净位移分别为 2.6 ± 3.4mm、2.6 ± 3.5mm 和 3.0 ± 3.2mm,在横向、纵向和垂直方向上。对于治疗机日志,横向、纵向和垂直方向上的平均净位移分别为 2.7 ± 3.7mm、2.6 ± 3.7mm 和 3.2 ± 3.6mm。横向、纵向和垂直方向上的平均差值(机器-SGRT)分别为-0.1 ± 1.8mm、0.2 ± 2.1mm 和-0.5 ± 2.5mm。平均而言,在进行 CBCT 和 SGRT 系统配准时,分别计算出 5.8 ± 5.6mm 和 5.3 ± 4.9mm 的运动。CBCT 和 SGRT 移位之间的 Pearson 相关系数为 r = 0.88。所有部位的治疗机日志和 SGRT 日志文件之间的平均和中位数差值均小于 1mm。
在自适应放疗过程中,应使用表面成像来监测和量化患者运动。