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Using an EPID for patient‐specific VMAT quality assurance
Author(s) -
Bakhtiari M.,
Kumaraswamy L.,
Bailey D. W.,
de Boer S.,
Malhotra H. K.,
Podgorsak M. B.
Publication year - 2011
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3552925
Subject(s) - multileaf collimator , dicom , quality assurance , computer science , software , image guided radiation therapy , computer vision , artificial intelligence , radiation treatment planning , medical imaging , collimator , aperture (computer memory) , nuclear medicine , optics , medicine , radiation therapy , engineering , physics , radiology , external quality assessment , pathology , programming language , mechanical engineering
Purpose: A patient‐specific quality assurance (QA) method was developed to verify gantry‐specific individual multileaf collimator (MLC) apertures (control points) in volumetric modulated arc therapy (VMAT) plans using an electronic portal imaging device (EPID). Methods: VMAT treatment plans were generated in an Eclipse treatment planning system (TPS). DICOM images from a Varian EPID (aS1000) acquired in continuous acquisition mode were used for pretreatment QA. Each cine image file contains the grayscale image of the MLC aperture related to its specific control point and the corresponding gantry angle information. The TPS MLC file of this RapidArc plan contains the leaf positions for all 177 control points (gantry angles). In‐house software was developed that interpolates the measured images based on the gantry angle and overlays them with the MLC pattern for all control points. The 38% isointensity line was used to define the edge of the MLC leaves on the portal images. The software generates graphs and tables that provide analysis for the number of mismatched leaf positions for a chosen distance to agreement at each control point and the frequency in which each particular leaf mismatches for the entire arc. Results: Seven patients plans were analyzed using this method. The leaves with the highest mismatched rate were found to be treatment plan dependent. Conclusions: This in‐house software can be used to automatically verify the MLC leaf positions for all control points of VMAT plans using cine images acquired by an EPID.