Open AccessValidation of a secondary dose check tool against Monte Carlo and analytical clinical dose calculation algorithms in VMAT
Author(s) -
Piffer Stefano,
Casati Marta,
Marrazzo Livia,
Arilli Chiara,
Calusi Silvia,
Desideri Isacco,
Fusi Franco,
Pallotta Stefania,
Talamonti Cinzia
Publication year - 2021
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 - 10.1002/acm2.13209
Subject(s) - monte carlo method , algorithm , computer science , nuclear medicine , medical physics , mathematics , statistics , medicine
Purpose Patient‐specific quality assurance (QA) is very important in radiotherapy, especially for patients with highly conformed treatment plans like VMAT plans. Traditional QA protocols for these plans are time‐consuming reducing considerably the time available for patient treatments. In this work, a new MC‐based secondary dose check software (SciMoCa) is evaluated and benchmarked against well‐established TPS (Monaco and Pinnacle 3 ) by means of treatment plans and dose measurements. Methods Fifty VMAT plans have been computed using same calculation parameters with SciMoCa and the two primary TPSs. Plans were validated with measurements performed with a 3D diode detector (ArcCHECK) by translating patient plans to phantom geometry. Calculation accuracy was assessed by measuring point dose differences and gamma passing rates (GPR) from a 3D gamma analysis with 3%–2 mm criteria. Comparison between SciMoCa and primary TPS calculations was made using the same estimators and using both patient and phantom geometry plans. Results TPS and SciMoCa calculations were found to be in very good agreement with validation measurements with average point dose differences of 0.7 ± 1.7% and −0.2 ± 1.6% for SciMoCa and two TPSs, respectively. Comparison between SciMoCa calculations and the two primary TPS plans did not show any statistically significant difference with average point dose differences compatible with zero within error for both patient and phantom geometry plans and GPR (98.0 ± 3.0% and 99.0 ± 3.0% respectively) well in excess of the typical 95 % clinical tolerance threshold. Conclusion This work presents results obtained with a significantly larger sample than other similar analyses and, to the authors' knowledge, compares SciMoCa with a MC‐based TPS for the first time. Results show that a MC‐based secondary patient‐specific QA is a clinically viable, reliable, and promising technique, that potentially allows significant time saving that can be used for patient treatment and a per‐plan basis QA that effectively complements traditional commissioning and calibration protocols.