An effective and optimized patient-specific QA workload reduction for VMAT plans after MLC-modelling optimization. (March 2023)

• Record Type: Journal Article
• Authors: Marsac, Thomas; Camejo, Arianna Batista; Chiavassa, Sophie; Jan, Simon; Lorand, Hugo; Moignier, Alexandra
• Is Part Of: Physica medica. Volume 107(2023)
• Publication Date: 2023-03
• Subjects: Radiotherapy -- Patient-specific quality assurance -- Complexity metrics -- MLC modelling -- Workload reduction; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2023.102548
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: Optimal complexity metric for predicting plan deliverability with our equipment. Effective PSQA workload reduction using complexity metric. Further PSQA workload reduction after optimization of the MLC modelling. Abstract: Introduction: Many complexity metrics characterize modulated plans. First, this study aimed at identify the optimal complexity metrics to reduce workload associated to patient-specific quality assurance (PSQA) for our equipment and processes. Second, it intended to optimize our MLC modelling to improve measurement and calculation agreement with expectation of further reducing PSQA workload. Methods: Correlation and sensitivity at specificity equals to 1 were evaluated for PSQA results and different complexity metrics. Thresholds to stop PSQA were determined. After validation of the optimal complexity metric and threshold for our equipment and process, the MLC modelling was reviewed with a recently published methodology. This method is based on measurements with a Farmer-type ionization chamber of synchronous and asynchronous sweeping gap plans. Effect on the PSQA results and the identified threshold was investigated. Results: In our center, the most appropriate complexity metric for reducing our PSQA workload was the Modulation Complexity Score for VMAT (MCSv). The optimization of the MLC modelling significantly reduced the number of controlled plans, specifically for one of our two Varian Clinac. Any plan with a MCSv >= 0.34 is treated without PSQA. Conclusion: This study rationalized and reduced our PSQA workload by approximately 30%. It is a continuing work with new TPS, machine or PSQA equipment. It encourages centers to re-evaluate their MLC modelling as well as assess the benefit of complexity metrics to streamline their PSQA workflow. An easier access, at least for reporting, at best for optimizing plans, into the TPS would be beneficial for the community.