S2335
Physics - Quality assurance and auditing
ESTRO 2026
Results:
not yet in the commissioning dataset, highlighting the need to update it. Conclusion: A continuous QA framework for DLS was successfully clinically implemented, using SPC and adapted Nelson rules to automatically report outliers and trend shifts,
leading to detection of such deviations. Keywords: continuous, monitoring, alarms
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Table 1. Description of each simulated machine- delibery error plan and its clinical acceptability in terms of impact on target coverage and OAR doses.
Evaluation of SRS MapCHECK Sensitivity to Treatment Delivery Errors Using the SEAFARER Approach Víctor Riu Molinero 1 , Cristina Ansón Marcos 1 , Sergi Serrano-Rueda 2 , Helena Vivancos Bargalló 1 , Natalia Tejedor Aguilar 1 , Pedro Gallego Franco 1 , Jaime Pérez- Alija Fernández 1 , Agustin Ruiz Martinez 1 , Marta Barceló Pagès 1 , Alejandro Domínguez Perea 1 , Eva Maria Ambroa Rey 1 , Pol Martínez Ramos 1 , Javier Roda Garcia 1 , Núria Jornet Sala 1 , Pablo Carrasco de Fez 1 1 Medical Physics and Radiation Protection, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. 2 Radiation Oncology, Hospital Clínic, Barcelona, Spain Purpose/Objective: This study aims to evaluate the sensitivity of the SRS MapCHECK detector array from Sun Nuclear (SN), used for patient-specific quality assurance (PSQA), in detecting machine delivery errors in stereotactic treatments. Material/Methods: Three clinical treatment plans were selected: a cranial SRS and a lung SBRT plan delivered with VMAT, and a head-and-neck SBRT plan delivered with IMRT, all using 6X FFF beams. Dose calculation was performed using AcurosXB in Eclipse v15.6. The treatment plans were recalculated on a CT scan set from SRS Mapcheck inserted in the SteroPHAN phantom (SN).To evaluate the sensitivity of the PSQA detector array, intentional machine-delivery errors were introduced in line with the SEAFARER approach [1]. These error - simulated plans (n = 11) were generated using a Python script and then recalculated in the treatment planning system on the patient CT scan set to determine their dosimetric and clinical relevance (Table 1). All plans were delivered on a TrueBeam linac. Measurements were performed field-by-field with the SRS MapCHECK array mounted within the StereoPHAN phantom and analysed in SNC Patient software (SN) to assess error - detection performance.A comparison of the 2D dose distribution at the array plane was performed between the measured and calculated clinical plans for each field separately, using global gamma analysis (3%/2 mm, 10% threshold) [2] (Table 2).
Table 2. Gamma passing rate (%) for each plan compared with TPS-calculated dose distributions. Passing rates >95% are highlighted in green, 95–90% in orange, and <90% in red.All original plans showed good agreement between measured and calculated dose distributions, with gamma passing rates exceeding 95%. Most of the simulated error plans resulted in a consistent reduction of gamma passing rates below clinical tolerance levels (90%). Errors ≤ 1 mm in MLC bank positions were only partially detected. Collimator angle (±1°) variations alone had minor effects. However, these are the only error- simulated plans showing clinical acceptability (Table 1).Comparing techniques, the IMRT plan showed slightly higher sensitivity to submillimetre MLC geometric deviations than VMAT. Conclusion: The SRS MapCHECK proved highly sensitive to clinically relevant delivery errorsunder the tested conditions, particularly MLC deviations ≥ 1 mm. By applying the SEAFARER approach, this work demonstrates a practical and clinically driven method to benchmark PSQA system performance. References: [1] Lehmann J, Hussein M, Barry MA, Siva S, Moore A, Chu M, Díez P, Eaton DJ, Harwood J, Lonski P, Claridge Mackonis E, Meehan C, Patel R, Ray X, Shaw M, Shepherd J, Smyth G, Standen TS, Subramanian B, Greer PB, Clark CH. SEAFARER - A new concept for validating radiotherapy patient specific QA for clinical trials and clinical practice. Radiother Oncol. 2022 Jun;171:121-128.[2] Miften, M., Olch, A., Mihailidis, D., Moran, J., Pawlicki, T., Molineu, A., Li, H., Wijesooriya, K., Shi, J., Xia, P., Papanikolaou, N. and Low, D.A. (2018), Tolerance limits and methodologies for IMRT measurement-based verification QA: Recommendations of AAPM Task Group No. 218. Med.
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