S1877
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
daily dose calculation is crucial in a direct to unit workflow for online adaptive MR-guided radiotherapy (MRIgRT). This relies on acquiring a simulation CT (CT_sim) and deformably registering it to the daily planning MRI (pMRI). In alternative to synthetic CT (sCT) generation from MRI, this study evaluates a new approach that removes the need for CT_sim by deformably registering a benchmark CT (bCT) directly to the pMRI. Material/Methods: Seven prostate cancer patients treated at 0.35T MR- Linac system with SIB-SBRT MRIgRT (36.25Gy @Dmean prostate PTV-LD, 40Gy @80% isodose to the dominant intraprostatic lesion PTV-DIL, in 5 fractions) were retrospectively selected. For each patient, the same bCT, selected from our patients’ cohort, was deformably registered to the pMRI, followed by EDM generation and treatment plan optimization (MRIdian- TPS MonteCarlo algorithm 1x1mm2 dose grid and 1% uncertainty). The plan was recalculated on the CT_sim EDM, gamma analysis (1%-1mm and 2%-1mm) and DVH parameters for PTV and Organs-of-Interest Dose Guidance (OoI-DG) were evaluated. The same analysis on the same patients was also realized on a new MRIgRT treatment plan with a Conventional Fractionation (CF) treatment scheme (70Gy @Dmean in 35 fractions). For both cases results were compared with the same workflow realized with sCT1 instead of bCT Results: bCT and sCT results were compared with CT_sim on the two dose prescriptions, 10 and 14 DVH metrics were analyzed respectively for SIB-SBRT MRIgRT and CF. Paired comparisons (Wilcoxon) showed no significant differences between bCT and sCT. Equivalence testing (TOST, ±1% or ±0.1cc) revealed mixed outcomes: for SBRT (Fig.1), 5 DVH metrics met equivalence criteria, while 5 did not. The mean gamma passing rate (1%-1mm, 2%-1mm) were 92.7% and 99.0% for bCT, 93.8% and 98.8% for sCT. For CF (Fig.2) 8 DVH metrics were equivalent and 6 were not. The mean gamma passing rate (1%-1mm, 2%-1mm) were 93.2% and 99.1% for bCT, 93.4% and 99.0% for sCT.
Conclusion: The new GPU-accelerated beam model eliminates the need for user-specific tuning and reduces variability between institutions, while maintaining comparable dosimetric accuracy to the clinically optimized VSM1.6. However, introducing a single tunable parameter for leaf position offset may further enhance accuracy. Overall, VSM2.0 offers a robust and efficient solution for accurate dose calculation in Elekta TPS, supporting improved standardization and ultimately safety in radiotherapy planning across radiotherapy centers. Keywords: TPS, Beam modeling, MLC modeling Digital Poster 2155 Direct to unit: dosimetric feasibility of an alternative approach for synthetic CT generation for Online Adaptive MRIgRT Matteo Galetto 1 , Matteo Nardini 1 , Simone Raggio 1 , Davide Cusumano 2 , Luisa Altabella 3 , Luca Boldrini 1,4 , Giuditta Chiloiro 1 , Randa El Gawhary 5 , Marco Fusella 6 , Gianluca Gragnaniello 1 , Ina Isufi 1 , Parvin Mohammadyari 7 , Giulia Panza 1 , Angela Romano 1 , Luca Russo 1 , Elena Huong Tran 1 , Claudio Votta 1 , Konstantinos Zormpas-Petridis 8,9 , Evis Sala 1,4 , Maria Antonietta Gambacorta 1,4 , Marco De Spirito 1,9 , Lorenzo Placidi 1 1 Diagnostic Imaging and Oncological Radiotherapy Department, Fondazione Policlinico Universitario A. Gemelli, Roma, Italy. 2 UO Fisica Medica e Radioprotezione, Mater Olbia Hospital, Olbia, Italy. 3 Medical Physics Unit, Azienda Ospedaliera Universitaria Integrata, Verona, Italy. 4 Dipartimento di Scienze radiologiche ed ematologiche, Università Cattolica del Sacro Cuore, Roma, Italy. 5 Radiotherapy Department, San Pietro Fatebenefratelli Hospital, Roma, Italy. 6 Department of Radiation Oncology, Abano Terme Hospital, Abano Terme, Italy. 7 Facoltà di Medicina e Chirurgia, Università Cattolica del Sacro Cuore, Roma, Italy. 8 Computational Pathology and Spatially-Integrated Omics GSTeP facility, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italy. 9 Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, Roma, Italy Purpose/Objective: Generating accurate electron density maps (EDM) for
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