Oleg N Vassiliev1, Christine B Peterson2, David R Grosshans3, Radhe Mohan1. 1. Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 2. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 3. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Abstract
OBJECTIVES: The relative biological effectiveness (RBE) of X-rays and γ radiation increases substantially with decreasing beam energy. This trend affects the efficacy of medical applications of this type of radiation. This study was designed to develop a model based on a survey of experimental data that can reliably predict this trend. METHODS: In our model, parameters α and β of a cell survival curve are simple functions of the frequency-average linear energy transfer (LF) of delta electrons. The choice of these functions was guided by a microdosimetry-based model. We calculated LF by using an innovative algorithm in which LF is associated with only those electrons that reach a sensitive-to-radiation volume (SV) within the cell. We determined model parameters by fitting the model to 139 measured (α,β) pairs. RESULTS: We tested nine versions of the model. The best agreement was achieved with [Formula: see text] and β being linear functions of [Formula: see text] .The estimated SV diameter was 0.1-1 µm. We also found that α, β, and the α/β ratio increased with increasing [Formula: see text] . CONCLUSIONS: By combining an innovative method for calculating [Formula: see text] with a microdosimetric model, we developed a model that is consistent with extensive experimental data involving photon energies from 0.27 keV to 1.25 MeV. ADVANCES IN KNOWLEDGE: We have developed a photon RBE model applicable to an energy range from ultra-soft X-rays to megaelectron volt γ radiation, including high-dose levels where the RBE cannot be calculated as the ratio of α values. In this model, the ionization density represented by [Formula: see text] determines the RBE for a given photon spectrum.
OBJECTIVES: The relative biological effectiveness (RBE) of X-rays and γ radiation increases substantially with decreasing beam energy. This trend affects the efficacy of medical applications of this type of radiation. This study was designed to develop a model based on a survey of experimental data that can reliably predict this trend. METHODS: In our model, parameters α and β of a cell survival curve are simple functions of the frequency-average linear energy transfer (LF) of delta electrons. The choice of these functions was guided by a microdosimetry-based model. We calculated LF by using an innovative algorithm in which LF is associated with only those electrons that reach a sensitive-to-radiation volume (SV) within the cell. We determined model parameters by fitting the model to 139 measured (α,β) pairs. RESULTS: We tested nine versions of the model. The best agreement was achieved with [Formula: see text] and β being linear functions of [Formula: see text] .The estimated SV diameter was 0.1-1 µm. We also found that α, β, and the α/β ratio increased with increasing [Formula: see text] . CONCLUSIONS: By combining an innovative method for calculating [Formula: see text] with a microdosimetric model, we developed a model that is consistent with extensive experimental data involving photon energies from 0.27 keV to 1.25 MeV. ADVANCES IN KNOWLEDGE: We have developed a photon RBE model applicable to an energy range from ultra-soft X-rays to megaelectron volt γ radiation, including high-dose levels where the RBE cannot be calculated as the ratio of α values. In this model, the ionization density represented by [Formula: see text] determines the RBE for a given photon spectrum.
Authors: Alejandro Carabe; Maryam Moteabbed; Nicolas Depauw; Jan Schuemann; Harald Paganetti Journal: Phys Med Biol Date: 2012-02-14 Impact factor: 3.609