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Energy deposition clustering as a functional radiation quality descriptor for modeling relative biological effectiveness
Author(s) -
Villegas Fernanda,
Bäckström Gloria,
Tilly Nina,
Ahnesjö Anders
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4966033
Subject(s) - relative biological effectiveness , weighting , cluster analysis , monte carlo method , residual , cluster (spacecraft) , dosimetry , algorithm , statistics , physics , mathematics , radiation , computer science , nuclear medicine , optics , acoustics , medicine , programming language
Purpose: To explore the use of the frequency of the energy deposition (ED) clusters of different sizes (cluster order, CO) as a surrogate (instead of, e.g., LET) classification of the physical characteristics of ionizing radiation at a nanometer scale, to construct a framework for the calculation of relative biological effectiveness (RBE) with cell survival as endpoint. Methods: The frequency of cluster order f CO is calculated by sorting the ED sites generated with the Monte Carlo track structure code LIonTrack into clusters based on a single parameter called the cluster distance d C being the maximum allowed distance between two neighboring EDs belonging to a cluster. Published cell survival data parameterized with the linear‐quadratic (LQ) model for V79 cells exposed to 15 different radiation qualities (including brachytherapy sources, proton, and carbon ions) were used as input to a fitting procedure, designed to determine a weighting function w CO that describes the capacity of a cluster of a certain CO to damage the cell's sensitive volume. The proposed framework uses both f CO and w CO to construct surrogate based functions for the LQ parameters α and β from which RBE values can be derived. Results: The results demonstrate that radiation quality independent weights w CO exist for both the α and β parameters. This enables the calculation of α values that correlate to their experimental counterparts within experimental uncertainties (relative residual of 15% for d C = 2.5 nm). The combination of both α and β surrogate based functions, despite the higher relative residuals for β values, yielded an RBE function that correlated to experimentally derived RBE values (relative residual of 16.5% for d C = 2.5 nm) for all radiation qualities included in this work. Conclusions: The f CO cluster characterization of ionizing radiation at a nanometer scale can effectively be used to calculate particle and energy dependent α and β values to predict RBE values with potential applications to, e.g., treatment planning systems in radiotherapy.