A retrospective multi‐center feasibility study of a new PTV margin estimation approach for moving targets using CyberKnife log files

Abstract

AbstractPurposeThis study investigates a new approach for estimating the planning target volume (PTV) margin for moving tumors treated with robotic stereotactic body radiotherapy (SBRT).MethodsIn this new approach, the covariance of modeling and prediction errors was estimated using error propagation and implemented in the Van Herk formula to form a Modified Van Herk formula (MVHF). To perform a retrospective multi‐center analysis, the MVHF was studied using 163 patients treated with different system versions of robotic SBRT (G3 version 6.2.3, VSI version 8.5, and VSI version 9.5) and compared with two established PTV margins estimation methods: The original Van Herk Formula (VHF) and the Uncertainty Estimation Method (UEM).ResultsOverall, the PTV margins provided by the three formalisms are similar with 4–5 mm in the lung region and 4 mm in abdomen region to the PTV margins used in clinical. Furthermore, when analyzing individual patients, a difference of up to 1 mm was found between the PTV margin estimations using MVHF and VHF. The corresponding average discrepancies for the superior‐inferior (SI) direction ranged between −0.19 mm to 0.38 mm in CK G3 version 6.2.3, −0.36 mm to 0.33 mm in CK VSI version 8.5, and −0.34 mm to 0.40 mm in CK VSI version 9.5.ConclusionsIt was found that for the lower left lung, upper left lung, lower right lung, upper right lung, central liver, and upper liver, the effect of covariance between model and prediction errors in SI direction was around 20%, 30%, 25%, 25%, 25%, and 30%, respectively. Notable covariance effects between model and prediction errors can be considered in PTV margin estimation using a modified VHF, which allowed for more precise target localization in robotic SBRT for moving tumors. Overall, in each of the three directions, the difference between MVHF and utilized clinical margins is 0.65 mm in the lung and abdominal region. Therefore, to improve the clinical PTV margins with the new approach, it is suggested to use the adaptive PTV margins in the next fractions.