A standardized measurement-based approach to estimate modelled relative biological effectiveness for auditing carbon ion beams

Why clinicians should know about it

• Picked for Medical Physics (paper of the day, 14 September 2026): Measurement‑based RBE estimation for carbon ion beams

Abstract

BACKGROUND AND PURPOSE: Differences in dose delivered during carbon radiotherapy are due largely to variations in relative biological effectiveness (RBE), which can be calculated by several models. While RBE can theoretically be calculated using Microdosimetric Kinetic Model (MKM) and measured microdosimetric quantities, clinical implementation relies on lookup tables. There exist no means of measuring RBE by MKM or other common models, including Repair Misrepair Fixation (RMF) and Local Effect Model-I (LEM). This study investigated estimating RBE using a single microdosimetric measurement for each model, allowing measurement-based validation and inter-model comparison. MATERIALS AND METHODS: Monte Carlo simulations were performed at 260 positions across nine carbon beams, from which microdosimetric quantities ( y ∗ ) and linear ( α ) and quadratic ( β ) RBE parameters were derived using each model definition. To estimate RBE from microdosimetric input, α and β were fit as functions of y ∗ for two test beams. The fits were applied to microdosimetric data from the remaining simulated beams and experimental measurements to validate resulting RBE predictions against full Monte Carlo-calculated RBE. RESULTS: Modelled RBE calculated using simulated input parameters versus estimated with the measurement-based fit were compared and found to be within ±10% accuracy in 96% (MKM), 100% (LEM), and 98% (RMF) of points. Average estimation uncertainty was 2.6% (MKM), 1.7% (LEM), and 4.3% (RMF). CONCLUSIONS: While modelled RBE has extensive associated uncertainty, this study demonstrated that it could be estimated with reasonable accuracy using a standardized measurement-based framework. Results suggested that microdosimetry can be used as a quality assurance tool to characterize carbon fields and verify correct implementation of RBE models.

Abstract as published, via PubMed.