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Sci—Wed PM: Delivery—08: Monte Carlo Based RapidArc QA Using LINAC Log Files
Author(s) -
Teke T,
Bergman A,
Kwa W,
Gill B,
Duzenli C,
Popescu IA
Publication year - 2009
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 - 10.1118/1.3244100
Subject(s) - monte carlo method , quality assurance , imaging phantom , ionization chamber , linear particle accelerator , nuclear medicine , radiation treatment planning , computer science , medical physics , beam (structure) , medicine , mathematics , statistics , physics , radiation therapy , ionization , optics , radiology , ion , external quality assessment , pathology , quantum mechanics
Purpose/Objective(s): To present our Monte Carlo based RapidArc quality assurance (QA) process to validate both the dose calculation and dynamic beam delivery accuracy using the planning MLC control files and the post‐delivery MLC diagnostic files. Materials/Methods: Ten clinically acceptable RapidArc treatment plans were generated with a clinical version of the planning system for various tumor sites. Monte Carlo dose calculations were performed in a water equivalent phantom for each plan using both DynaLog files and the planning control (DVA) files. Results were compared to measurements using a calibrated Farmer ionization chamber with an active volume of 0.6cm 3 . Comparison of RapidArc and Monte Carlo 3D doses was performed using a 3 dimensional Gamma‐factor analysis with a 3%/3mm DTA criteria. A thorough analysis of the DynaLog files was performed to evaluate the treatment delivery accuracy. Results: Good agreement was observed between chamber measurements and MC dose calculations and between RapidArc and MC dose distributions with Gamma values below 1 in over 90% of the points considered for all plans. The analysis of the MLC DynaLog files indicated that the leaf position errors were lower than 1 mm in more than 94% of the time with none above 2.5 mm and that few beam hold‐offs occurred Conclusions The accuracy and flexibility of our Monte Carlo based RapidArc QA system was demonstrated. Good machine performance and accurate dose distributions delivery of RapidArc plans was observed.