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Program Information

Commissioning Varian Portal Dosimetry for EPID-Based Patient Specific QA in a Non-Aria Environment

M Schmidt

M Schmidt1,2,4*, N Knutson1,2,4 , J Herrington2 , M Price1,2,3 , (1) Rhode Island Hospital, Providence , RI, (2) University of Rhode Island, Kingston, RI, (3) Alpert Medical School of Brown University, Providence, RI, (4) University of Massachusetts Lowell, Lowell, MA


SU-F-T-262 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: Development of an in-house program facilitates a workflow that allows Electronic Portal Imaging Device (EPID) patient specific quality assurance (QA) measurements to be acquired and analyzed in the Portal Dosimetry Application (Varian Medical Systems, Palo Alto, CA) using a non-Aria Record and Verify (R&V) system (MOSAIQ, Elekta, Crawley, UK) to deliver beams in standard clinical treatment mode.

Methods: Initial calibration of an in-house software tool includes characterization of EPID dosimetry parameters by importing DICOM images of varying delivered MUs to determine linear mapping factors in order to convert image pixel values to Varian-defined Calibrated Units (CU). Using this information, the Portal Dose Image Prediction (PDIP) algorithm was commissioned by converting images of various field sizes to output factors using the Eclipse Scripting Application Programming Interface (ESAPI) and converting a delivered configuration fluence to absolute dose units. To verify the algorithm configuration, an integrated image was acquired, exported directly from the R&V client, automatically converted to a compatible, calibrated dosimetric image, and compared to a PDIP calculated image using Varian’s Portal Dosimetry Application.

Results: For two C-Series and one TrueBeam Varian linear accelerators, gamma comparisons (global 3% / 3mm) of PDIP algorithm predicted dosimetric images and images converted via the in-house system demonstrated agreement for ≥99% of all pixels, exceeding vendor-recommended commissioning guidelines.

Conclusion: Combinations of a programmatic image conversion tool and ESAPI allow for an efficient and accurate method of patient IMRT QA incorporating a 3rd party R&V system.

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