S2383
Physics - Quality assurance and auditing
ESTRO 2026
References: [1] Miften M, et al. Tolerance limits and methodologies for IMRT measurement-based verification QA: Recommendations of AAPM Task Group No. 218. Med Phys 2018;45:53- 83. https://doi.org/10.1002/mp.12810[2] Mehrens H, et al Survey results of 3D - CRT and IMRT quality assurance practice. J Appl Clin Med Phys. 2020;21:70- 6. https://doi.org/10.1002/acm2.12885[3] Chan GH, et al. Survey of patient - specific quality assurance practice for IMRT and VMAT. J Appl Clin Med Phys. 2021;22:155- 64. https://doi.org/10.1002/acm2.13294. [4] Lehmann J, et al. SEAFARER – A new concept for validating radiotherapy patient specific QA for clinical trials and clinical
deviations, making mechanical metrics the most relevant predictors for selecting plans that require measurement.Our goal is to identify which aspects of these mechanical features most strongly predict delivery deviations, enabling a selective, evidence- based QA process that preserves accuracy while optimising resources and clinical workflow efficiency. Material/Methods: A retrospective dataset of previously treated patients with available PSQA measurements was analysed. Absolute dose verification was performed using an ionization chamber, and three-dimensional relative dose verification used the PTW Octavius system. Gamma analysis applied a 2%/2mm criterion, whereas absolute dose measurements were within tolerance when differing less than 2% at representative points in the PTV and critical organs. Plans exceeding these thresholds were considered out of tolerance.Mechanical descriptors included mean absolute MLC speed and acceleration, number of leaf motion inversions, and aperture metrics such as the number of MLC islands and open area per unit time. Gantry motion characteristics was also evaluated. Correlation analyses was made to determine the relationship between these mechanical delivery variables and PSQA performance. Results: Approximately 7% of plans exceeded PSQA tolerance limits. To maintain high sensitivity in detecting potential delivery deviations while preserving acceptable specificity, the algorithm is designed to select about 20% of all plans for measurement-based QA. This proportion represents a conservative balance between sensitivity and resource efficiency, hopefully covering all out-of-tolerance cases while substantially reducing the overall QA workload. Conclusion: Integrating mechanical complexity metrics into QA decision-making offers a practical approach to streamlining radiotherapy verification. Selecting plans based on actual delivery behaviour supports efficient allocation of QA resources while maintaining rigorous standards of treatment safety and accuracy. References: Hernandez V, Saez J, Pasler M, Jurado-Bruggeman D, Jornet N. Comparison of complexity metrics for multi- institutional evaluations of treatment plans in radiotherapy. Physics and Imaging in Radiation Oncology. 2018Claessens M, De Kerf G, Vanreusel V, Mollaert I, Hernandez V, Saez J, Jornet N, Verellen D et al. Multi-institutional generalizability of a plan complexity machine learning model for predicting pre- treatment quality assurance results in radiotherapy. Physics and Imaging in Radiation Oncology. 2024Kaplan LP, Placidi L, Bäck A, Canters R, Hussein M, Vaniqui A. Results of the 2020 ESTRO survey on plan complexity and robustness. Radiotherapy and
practice. Radiother Oncol 2022;171:121–8. https://doi.org/10.1016/j.radonc.2022.04.019. Keywords: delivery errors, SEAFARER, PSQA
Digital Poster 3537
Development of an algorithm based on mechanical complexity for automatic selection of radiotherapy plans that require PSQA Miguel Pontes 1 , Claudio Batista 2 , Ana Campos 1 , Inês Gil 3 , Leonel Lourenço 4 , Sandra Brás 3 , Raquel Mota 5 , Mauro Trindade 6 1 Physics-RT, Joaquim Chaves Saúde, Carnaxide, Portugal. 2 Physics-RT, Joaquim Chaves Saúde, Santarém, Portugal. 3 Physics-RT, Joaquim Chaves Saúde, Faro, Portugal. 4 Physics-RT, Joaquim Chaves Saúde, Funchal, Portugal. 5 Physics-RT, Joaquim Chaves Saúde, Évora, Portugal. 6 Physics-RT, Joaquim Chaves Saúde, Lisboa, Portugal Purpose/Objective: In modern radiotherapy, Patient-Specific Quality Assurance (PSQA) remains crucial, ensuring that the delivered dose matches the planned distribution. The growing complexity of treatment techniques has substantially increased QA workload. To address this, the aim of our study was to develope an algorithm capable of automatically identifying which treatment plans truly require measurement-based verification, reducing unnecessary QA without compromising patient safety.Instead of relying on broad modulation indices, as many existing metrics do, the approach centres on the detailed mechanical behaviour of the delivery system. The study examines individual MLC leaf motion — average speed and acceleration, number of reversals, and the size, number, and temporal evolution of aperture gaps (MLC islands) — together with gantry motion. PSQA outcomes are influenced by both calculation uncertainties and delivery factors, yet machine-related delivery issues generally dominate in-phantom measurment
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