The Abridged Microdosimetric Distribution Methodology for flexible and efficient relative biological effectiveness calculations in ion radiotherapy.

Objective. Current clinical approaches for calculating the relative biological effectiveness (RBE) in ion beam therapy rely on pre-computed lookup tables tied to a specific RBE model and cell line. While practical, this framework limits flexibility, as a subsequent RBE recalculation with a different biological model or cell line requires re-running the radiation transport simulations. This work systematically benchmarks a computationally efficient method that allows accurate and flexible RBE calculations in ion beam therapy.Approach.The Abridged Microdosimetric Distribution Methodology (AMDM) was introduced to summarize the microdosimetric distributions using only 20 values per voxel (named AMDM quantities). Using the Monte Carlo code particle and heavy ion transport code system, lineal energy distributions were simulated at a total of 2780 in-field and 1200 out-of-field locations along pristine and spread-out Bragg peaks of1H,4He,12C,16O, and20Ne ions. The RBE was computed using the AMDM quantities and compared to corresponding reference values (obtained by processing the entire microdosimetric distributions) for 27 combinations of RBE models (modified microdosimetric kinetic model and Mayo Clinic Florida microdosimetric kinetic model) and cell lines.Main results. The average relative deviation between AMDM-based and reference low-dose RBE values (worst case scenario) was 0.2% and 0.3% for in-field and out-of-field calculations, respectively. The maximum relative deviation between AMDM-based and reference low-dose RBE values was 0.9% (1H), 0.8% (4He), 0.9% (12C), 1.1% (16O), and 1.5% (20Ne) for in-field calculations and 0.9% (1H), 0.8% (4He), 0.8% (12C), 1.2% (16O), and 1.9% (20Ne) for out-of-field calculations.Significance. The AMDM enables accurate multi model/cell line RBE calculations and subsequent RBE recalculations without the need for new radiation transport simulations, offering unprecedented flexibility in RBE modeling and retrospective studies. Moreover, a validated approach for implementing the AMDM in any Monte Carlo code or treatment planning system is described, thus facilitating its practical integration in clinical and research applications.