A model for relative biological effectiveness of therapeutic proton beams based on a global fit of cell survival data

TL;DR

This paper presents a new global fitting method for cell survival data in proton therapy, incorporating LET effects and microdosimetric models to better predict biological effectiveness.

Contribution

It introduces a novel fitting approach that accounts for correlations between dose, LET, and cell survival, improving RBE modeling for proton therapy.

Findings

The method reveals a smooth transition of LQ parameters across LETs.

It provides insights into microscopic mechanisms of radiobiological responses.

The approach may resolve discrepancies in current RBE models.

Abstract

We introduce an approach for global fitting of the recently published high-throughput and high accuracy clonogenic cell-survival data for therapeutic scanned proton beams. Our fitting procedure accounts for the correlation between the cell-survival, the absorbed (physical) dose and the proton linear energy transfer (LET). The fitting polynomials and constraints have been constructed upon generalization of the microdosimetric kinetic model (gMKM) adapted to account for the low energy and high lineal-energy spectrum of the beam where the current radiobiological models may underestimate the reported relative biological effectiveness (RBE). The parameters ({\alpha},\b{eta}) of the linear-quadratic (LQ) model calculated by the presented method reveal a smooth transition from low to high LETs which is an advantage of the current method over methods previously employed to fit the same clonogenic data. Finally, the presented approach provides insight into underlying microscopic mechanisms which, with future study, may help to elucidate radiobiological responses along the Bragg curve and resolve discrepancies between experimental data and current RBE models.