Clinical log data analysis for assessing the accuracy of the CyberKnife fiducial-free lung tumor tracking system.

PURPOSE

The CyberKnife Xsight Lung Tracking (XLT) and 1-View tracking systems can synchronize beam targeting to a visible lung tumor with respiratory motion during irradiation without requiring internal fiducial markers. The systems use a correlation model that relates external marker positions to tumor positions as well as a prediction model that predicts the target's future position. In this study, the correlation and prediction model uncertainties related to the CyberKnife fiducial-free tumor tracking system were evaluated using clinical log data.

METHODS AND MATERIALS

Data from 211 fractions in 42 patients with lung tumors were analyzed. Log files produced by the CyberKnife Synchrony system were acquired after each treatment; the mean correlation and prediction errors for each patient were calculated. Additionally, we examined the tracking tumor-related parameters and analyzed the relationships between the model errors and tracking tumor-related parameters.

RESULTS

The overall means ± standard deviations (SDs) of the correlation errors were 0.70 ± 0.43 mm, 0.36 ± 0.16 mm, 0.44 ± 0.22 mm, and 0.95 ± 0.43 mm for the superoinferior (SI), left-right (LR), anteroposterior (AP), and radial directions, respectively. The overall means ± SDs of the prediction errors were 0.13 ± 0.11 mm, 0.03 ± 0.02 mm, 0.03 ± 0.02 mm, and 0.14 ± 0.11 mm for the SI, LR, AP, and radial directions, respectively. There were no significant differences in these errors between the XLT and 1-View tracking methods. The tumor motion amplitude was moderately associated with the correlation error and strongly related to the prediction error in the SI and radial directions.

CONCLUSIONS

Clinical log data analysis can be used to determine the necessary margin sizes in treatment plans to compensate for correlation and prediction errors in the CyberKnife fiducial-free lung tumor tracking system. The tumor motion amplitude may facilitate margin determination.