S2336
Physics - Quality assurance and auditing
ESTRO 2026
and delivered doses. Only one plan fell below a 95% gamma passing rate (3%/2 mm). Plan verification using a 2D array supported these findings. Computation times averaged under 4 minutes per plan, allowing efficient clinical integration. Conclusion: RadMonteCarlo demonstrated excellent agreement with both TPS calculations and physical measurements, confirming its accuracy and reliability for pre-treatment and log file–based QA on the Elekta Versa HD. By reproducing planned and measured dose distributions while reducing reliance on time- intensive measurements, RadMonteCarlo has the ability to streamline QA and supports its use as a robust, efficient tool in modern radiotherapy workflows. Keywords: Patient-Specific QA, RadMonteCarlo Estimating latencies of linac and gating system with a camera-based portable method enabling comparability across different gating platforms Catrin Rodenberg 1 , Christopher Kurz 1 , Stefanie Corradini 1,2 , Claus Belka 1,3 , Guillaume Landry 1 , Michael Reiner 1 1 Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany. 2 Now at Department of Radiation Oncology, Mini-Oral 1052 Universitätsklinikum Erlangen, Friedrich-Alexander- Universität Erlangen (FAU), Erlangen, Germany. 3 Bavarian Cancer Research Center (BZKF), Bavarian Cancer Research Center (BZKF), Munich, Germany Purpose/Objective: In surface-guided radiation therapy (SGRT), the overall gating latencies of the treatment unit arise from contributions of the linac and the gating system. The growing variety of gating systems calls for a portable method for comparative studies and QA. Existing techniques are either limited to overall latency assessment or, if addressing the gating system’s latency, rely on system-specific setups, restricting their applicability. We developed a method that quantifies both the gating system’s and overall latencies, while remaining portable across different platforms, enabling consistent QA and comparability. Material/Methods: We used a plastic scintillator (BC-412 Saint-Gobain, France) with nanosecond decay rate as an optical beam monitor. Surface motion was simulated with the vertical stage of the CIRS Dynamic Motion Phantom (Sun Nuclear, Mirion Technologies, Inc., USA), combined with a thermoplastic mask as a deformable thoracic surface surrogate. Surface motion and beam state (on/off) were recorded with a low-cost, high-
Phys., 45: e53-e83. Keywords: PSQA
Digital Poster 1011
Validation of RadMonteCarlo for Pre-treatment QA and Log File Analysis on an Elekta Versa HD Linear Accelerator Karl Jordan, Gavin Keane, Rachel Dunwoody Medical Physics, St Vincent's Private Hospital, Dublin, Ireland Purpose/Objective: Accurate dose calculation and verification are critical for radiotherapy quality assurance (QA), ensuring patient safety and treatment efficacy. As advanced linear accelerators such as the Elekta Versa HD enable increasingly complex techniques—including IMRT, VMAT, and stereotactic treatments—robust, physics- based secondary verification tools are essential. Monte Carlo (MC)–based dose calculation remains the gold standard for radiation transport simulation but has been limited in clinical use by computational and integration challenges. RadMonteCarlo, developed by Radformation, implements a high-fidelity 3D MC algorithm for pre-treatment QA and log file analysis, providing precise secondary dose verification across photon, electron, and proton modalities. This study validates RadMonteCarlo for pre-treatment QA and log file analysis on an Elekta Versa HD linear accelerator (6 MV), assessing its accuracy, consistency, and efficiency compared with the treatment planning system (TPS). Material/Methods: Beam data from the Elekta Versa HD were compared with RadMonteCarlo beam models to establish baseline agreement. Validation included point-dose measurements in solid water using a calibrated ionization chamber to confirm absolute dose accuracy. Pre-treatment QA and log-file–based RadMonteCarlo dose calculations were compared to TPS distributions using 3D gamma analysis. Point-dose verification and measurement-based QA across representative clinical treatment plans were also evaluated and compared to RadMonteCarlo. Results: Beam data comparison demonstrated excellent agreement between RadMonteCarlo and measured reference data, with percentage differences within ± 0.2% for all field sizes. Point-dose measurements confirmed absolute dose accuracy within 2.8% of RadMonteCarlo calculations. For pre-treatment QA, RadMonteCarlo dose distributions showed strong concordance with TPS results, yielding an average 3D gamma pass rate (3%/2 mm) of 98.6 ± 1.4%. Log file– based plan comparisons exhibited similar agreement (98.8 ± 0.8%), confirming consistency between planned
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