Abstract
The purpose of this study was to evaluate the ability of an aperture complexity metric for volumetric‐modulated arc therapy (VMAT) plans to predict plan delivery accuracy. We developed a complexity analysis tool as a plug‐in script to Varian's Eclipse treatment planning system. This script reports the modulation of plans, arcs, and individual control points for VMAT plans using a previously developed complexity metric. The calculated complexities are compared to that of 649 VMAT plans previously treated at our institution from 2013 to mid‐2015. We used the VMAT quality assurance (QA) results from the 649 treated plans, plus 62 plans that failed pretreatment QA, to validate the ability of the complexity metric to predict plan deliverability. We used a receiver operating characteristic (ROC) analysis to determine an appropriate complexity threshold value above which a plan should be considered for reoptimization before it moves further through our planning workflow. The average complexity metric for the 649 treated plans analyzed with the script was 0.132 mm−1 with a standard deviation of 0.036 mm−1. We found that when using a threshold complexity value of 0.180 mm−1, the true positive rate for correctly identifying plans that failed QA was 44%, and the false‐positive rate was 7%. Used clinically with this threshold, the script can identify overly modulated plans and thus prevent a significant portion of QA failures. Reducing VMAT plan complexity has a number of important clinical benefits, including improving plan deliverability and reducing treatment time. Use of the complexity metric during both the planning and QA processes can reduce the number of QA failures and improve the quality of VMAT plans used for treatment.PACS number(s): 87.55.de, 87.55.Qr, 87.56.jk
Highlights
Introduction125 Younge et al.: Predicting volumetric-modulated arc therapy (VMAT) plan deliverability using aperture complexity analysis of highly modulated VMAT plans (primarily an issue with hypofractionated delivery) partially defeats one of the main advantages of VMAT over IMRT: faster delivery.[4]Several studies have focused on developing plan complexity metrics to correlate with delivery accuracy for both IMRT and VMAT.[5,6,7] A study that showed how many of these metrics are able predict individual static aperture dose calculation accuracy, including the metric developed at our institution and used in the current work, was recently performed by Götstedt et al[8] In our previous work,(9) we used this metric to add a plan’s aperture complexity as a penalty in the inverse optimization process within an in-house treatment planning system
Several studies have focused on developing plan complexity metrics to correlate with delivery accuracy for both IMRT and volumetric-modulated arc therapy (VMAT).[5,6,7] A study that showed how many of these metrics are able predict individual static aperture dose calculation accuracy, including the metric developed at our institution and used in the current work, was recently performed by Götstedt et al[8] In our previous work,(9) we used this metric to add a plan’s aperture complexity as a penalty in the inverse optimization process within an in-house treatment planning system
The primary purpose of this work is to determine whether our aperture complexity metric for VMAT plans can predict a plan’s deliverability when applied post-optimization in a commercial treatment planning system
Summary
125 Younge et al.: Predicting VMAT plan deliverability using aperture complexity analysis of highly modulated VMAT plans (primarily an issue with hypofractionated delivery) partially defeats one of the main advantages of VMAT over IMRT: faster delivery.[4]Several studies have focused on developing plan complexity metrics to correlate with delivery accuracy for both IMRT and VMAT.[5,6,7] A study that showed how many of these metrics are able predict individual static aperture dose calculation accuracy, including the metric developed at our institution and used in the current work, was recently performed by Götstedt et al[8] In our previous work,(9) we used this metric to add a plan’s aperture complexity as a penalty in the inverse optimization process within an in-house treatment planning system. The primary purpose of this work is to determine whether our aperture complexity metric for VMAT plans can predict a plan’s deliverability when applied post-optimization in a commercial treatment planning system. We developed a software tool that quantifies plan complexity using the metric to identify plans that are unnecessarily complex. Such plans may be chosen to be reoptimized prior to moving further along the plan–preparation workflow. We describe the plan complexity metric, some useful features of the software tool, and quantify the metric’s ability to successfully predict plan deliverability for a range of treatment sites
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