Open AccessPredicting deliverability of volumetric‐modulated arc therapy (VMAT) plans using aperture complexity analysis
Author(s) -
Younge Kelly C.,
Roberts Don,
Janes Lindsay A.,
Anderson Carlos,
Moran Jean M.,
Matuszak Martha M.
Publication year - 2016
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1120/jacmp.v17i4.6241
Subject(s) - metric (unit) , computer science , workflow , quality assurance , plan (archaeology) , radiation treatment planning , aperture (computer memory) , medical physics , medicine , operations management , database , radiation therapy , surgery , physics , engineering , external quality assessment , archaeology , history , acoustics
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 − 1with 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