Synchrony Respiratory Tracking system adapted from CyberKnife has been introduced in Radixact to compensate the tumor motion caused by respiration. This study aims to compare the modeling accuracy of the Synchrony system between Radixact and CyberKnife. Two Synchrony plans based on fiducial phantoms were created for CyberKnife and Radixact, respectively. Different respiratory motion traces were used to drive a motion platform to move along the superoinferior and left-right direction. The cycle time and the amplitude of target/surrogate motion of one selected motion trace were scaled to investigate the dependence of modeling accuracy on the motion characteristic. The predicted target position, the correlation error, potential difference (Radixact only) and standard error (CyberKnife only) were extracted from raw data or log files of the two systems. The modeling accuracy was evaluated by calculating the root-mean-square (RMS) error between the predicted target positions and the input motion trace. A threshold T95 within which 95% of the potential difference or the standard error lay was defined and evaluated. Except for the motion trace with a small amplitude and a good (linear) correlation between target and surrogate motion, Radixact showed smaller RMS errors than CyberKnife. The RMS error of both systems increased with the motion amplitude and showed a decreasing trend with the increasing cycle time. No correlation was found between the RMS error and the amplitude of surrogate motion. T95 could be a good estimator of modeling accuracy for CyberKnife rather than Radixact. The correlation error defined in Radixact were largely affected by the number of fiducial markers and the setup error. In general, the modeling accuracy of the Radixact Synchrony system is better than that of the CyberKnife Synchrony system under unfavorable conditions.

Radixact引入了改编自Cyber​​Knife的同步呼吸跟踪系统，以补偿呼吸引起的肿瘤运动。本研究旨在比较 Radixact 和 Cyber​​Knife 之间 Synchrony 系统的建模精度。分别为 Cyber​​Knife 和 Radixact 创建了两个基于基准模型的同步计划。采用不同的呼吸运动轨迹驱动运动平台沿上下左右方向移动。对一个选定运动轨迹的循环时间和目标/替代运动的幅度进行缩放，以研究建模精度对运动特性的依赖性。从两个系统的原始数据或日志文件中提取预测的目标位置、相关误差、电位差（仅限 Radixact）和标准误差（仅限 Cyber​​Knife）。通过计算预测目标位置和输入运动轨迹之间的均方根 (RMS) 误差来评估建模精度。定义和评估 95% 的电位差或标准误差的阈值 T95。除了具有小幅度的运动轨迹以及目标和替代运动之间的良好（线性）相关性之外，Radixact 显示出比 Cyber​​Knife 更小的 RMS 误差。两个系统的均方根误差随着运动幅度的增加而增加，并随着循环时间的增加呈减小趋势。在 RMS 误差和替代运动幅度之间没有发现相关性。T95 可能是 Cyber​​Knife 而不是 Radixact 建模精度的一个很好的估计器。Radixact 中定义的相关误差很大程度上受基准标记数量和设置误差的影响。