A mechanistic relative biological effectiveness model-based biological dose optimization for charged particle radiobiology studies.

In charged particle therapy, the objective is to exploit both the physical and radiobiological advantages of charged particles to improve the therapeutic index. Use of the beam scanning technique provides the flexibility to implement biological dose optimized intensity-modulated ion therapy (IMIT). An easy-to-implement algorithm was developed in the current study to rapidly generate a uniform biological dose distribution, namely the product of physical dose and the relative biological effectiveness (RBE), within the target volume using scanned ion beams for charged particle radiobiological studies.

RBE Model-Based Biological Dose Optimization for Proton Radiobiology Studies.

Purpose: The purpose of the current study was (1) to develop a straightforward and rapid method to incorporate a dose-averaged linear energy transfer (LET )-based biological effect model into a dose optimization algorithm for scanned protons; and (2) to apply a novel beam delivery strategy with increased LET within the target, thereby enhancing the biological effect predicted using the selected relative biological effectiveness (RBE) model.

Materials And Methods: We first generated pristine dose Bragg curves in water and their corresponding LET distributions for 94 groups of proton beams, using experimentally validated Geant4 Monte Carlo simulations. Next, we developed 1-dimensional dose optimization algorithms by using the Python programming language.

Physical parameter optimization scheme for radiobiological studies of charged particle therapy.

We have developed an easy-to-implement method to optimize the spatial distribution of a desired physical quantity for charged particle therapy. The basic methodology requires finding the optimal solutions for the weights of the constituent particle beams that together form the desired spatial distribution of the specified physical quantity, e.g.