Standardizing MRI-only radiotherapy commissioning: Benchmark dataset and acceptance levels from the MESCAL initiative

Abstract

BACKGROUND: Magnetic Resonance Imaging (MRI)-only, radiotherapy (RT) is increasingly adopted, but still lacks standardized commissioning procedures. This variability limits consistent clinical implementation: the Multicenter Evaluation of commercial Synthetic-Computed tomography ALgorithms (MESCAL) project aims to establish a benchmark dataset, provide commissioning guidelines, and define tolerance levels to support safe and reproducible MRI-only photon-beam RT adoption. METHODS: Data from 32 patients (16 brain, 16 pelvis) were retrospectively collected from two centers. Four sCT solutions licensed for clinical use were evaluated: MRI Planner (Spectronic), SyngoAI (Siemens), MR Box (Therapanacea), and MRCAT (Philips). For each patient, multiple sCTs were generated and compared with the planning CT. Image quality was assessed using mean absolute error (MAE) and three additional indicators. Dose accuracy was evaluated by recalculating treatment plans on sCTs and performing dose-volume histogram (DVH) analysis. Position-verification accuracy was quantified by comparing CBCT-to-sCT versus CBCT-to-CT registrations. Plans meeting acceptability criteria (DVH differences < 2%, gamma-passing rate 95% at 2%/2 mm) were used to derive tolerance intervals. RESULTS: Three to four sCTs were generated per case. Brain cases showed higher inter-software variability than pelvic cases, particularly in MAE within body (pelvis: 30-70 HU; brain: 40-130 HU). DVH differences remained within 3% (pelvis) and 4% (brain). Position-verification accuracy was higher in the brain (89% within 1 mm/1°) than in the pelvis (74%). Acceptability criteria were met by 37/43 pelvic and 30/39 brain plans: tolerance values were derived from these cases. CONCLUSION: MESCAL provides a commissioning framework, benchmark dataset, and tolerance levels to guide local sCT commissioning and promote standardized MRI-only photon-beam RT implementation.