利用剂量图计算的纹理特征预测 VMAT 投递精度。
Prediction of VMAT delivery accuracy with textural features calculated from fluence maps.
机构信息
Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea.
Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.
出版信息
Radiat Oncol. 2019 Dec 23;14(1):235. doi: 10.1186/s13014-019-1441-7.
BACKGROUND
Comprehensively textural feature performance test from volumetric modulated arc therapy (VMAT) fluences to predict plan delivery accuracy.
METHODS
A total of 240 VMAT plans for various treatment sites were analyzed, with Trilogy and TrueBeam STx systems. Fluence maps superposed fluences at each control point per plan. The textural features were the angular second moment (ASM), inverse difference moment (IDM), contrast, variance, correlation, and entropy, calculated from fluence maps using three displacement distances. Correlation analysis of textural feature performance as predictors of VMAT delivery accuracy used global gamma passing rates with MapCHECK2 and ArcCHECK dosimeters, and mechanical delivery errors calculated from machine log files.
RESULTS
Spearman's rank correlation coefficients (r) of the ASM (d = 10) to the gamma passing rates with 1%/2 mm using the MapCHECK2 were 0.358 and 0.519, respectively (p < 0.001). For the ArcCHECK, they were 0.273 (p = 0.001) and 0.259 (p = 0.009), respectively. The r-values of the ASM (d = 10) to the Trilogy and TrueBeam STx MLC errors were - 0.843 and - 0.859, respectively (p < 0.001), and those to the MU delivery errors were - 0.482 and - 0.589, respectively (p < 0.001). The ASM (d = 10) showed better performance in predicting VMAT delivery accuracy.
CONCLUSIONS
The ASM (d = 10) calculated from VMAT plan fluence maps were strongly correlated with global gamma passing rates and MLC delivery errors, and can predict VMAT delivery accuracy.
背景
从容积调强弧形治疗（VMAT）射束到预测计划交付精度的全面纹理特征性能测试。
方法
分析了来自不同治疗部位的 240 个 VMAT 计划，使用 Trilogy 和 TrueBeam STx 系统。在每个计划的每个控制点上叠加通量图的通量。从通量图中计算纹理特征，包括角二阶矩（ASM）、逆差矩（IDM）、对比度、方差、相关性和熵，使用三个位移距离。使用 MapCHECK2 和 ArcCHECK 剂量仪的全局伽马通过率和机械输送误差从机器日志文件中计算，对作为 VMAT 输送精度预测因子的纹理特征性能进行相关性分析。
结果
ASM（d=10）与使用 MapCHECK2 的 1%/2mm 伽马通过率的 Spearman 秩相关系数（r）分别为 0.358 和 0.519（p<0.001）。对于 ArcCHECK，它们分别为 0.273（p=0.001）和 0.259（p=0.009）。ASM（d=10）与 Trilogy 和 TrueBeam STx MLC 误差的 r 值分别为-0.843 和-0.859（p<0.001），与 MU 输送误差的 r 值分别为-0.482 和-0.589（p<0.001）。ASM（d=10）在预测 VMAT 输送精度方面表现出更好的性能。
结论
从 VMAT 计划射束图计算的 ASM（d=10）与全局伽马通过率和 MLC 输送误差密切相关，可以预测 VMAT 输送精度。
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