Description and evaluation of a new volumetric-modulated arc therapy plan complexity metric

This study describes a new plan complexity metric for volumetric-modulated arc therapy (VMAT) and evaluates the relationship of this metric with the VMAT dosimetric accuracy. The new modulation complexity score for VMAT (NMCSv) that is based on the aperture shape and multi-leaf collimator (MLC) leaf travel is described. Its performance is evaluated through correlation and receiver operating characteristic (ROC) analyses with patient-specific gamma passing rates using 2 3-dimensional diode arrays. For comparison, the following metrics are evaluated using the same correlation analyses: average field width, average leaf travel, modulation complexity score, and leaf travel modulation complexity score. Spearman's rank correlation analysis is performed to examine any relationships between the complexity metrics and the patient-specific gamma passing rates. ROC curves are used to assess the performance of the plan metrics using a gamma passing rate of 3%/3 mm criterion with a 95% tolerance level. In both the diode arrays, the gamma passing rates (3%/3 mm and 2%/2 mm) for patient-specific dosimetric verification of VMAT plans are moderately or weakly correlated to all the complexity metrics. NMCSv demonstrates the highest correlation with the passing rates (r = 0.652, p < 0.001 for Delta4 and r = 0.499, p < 0.001 for ArcCheck) and the highest area under the curve value (0.809, p < 0.01 for Delta4 and 0.734, p < 0.01 for ArcCheck). While using the Delta4 system, NMCSv exhibits an excellent classification performance with area under the curves of 0.926 (sensitivity: 0.913; specificity: 0.860; p < 0.01) and 0.918 (sensitivity: 0.943; specificity: 0.720; p < 0.01) for rectal and cervical cancer plans, respectively. NMCSv as a novel potential clinical plan complexity metric is moderately correlated with the gamma passing rate. It demonstrates the best performance with respect to distinguishing the dosimetric accuracy of VMAT plans among the evaluated metrics. The classification performance of complexity metrics can be affected by various dosimetry verification devices and treatment sites.