Linking Microdosimetric Measurements to Biological Effectiveness in Ion Beam Therapy: A Review of Theoretical Aspects of MKM and Other Models

Abstract

Different qualities of radiation are known to cause different biological effects at the same absorbed dose. Enhancements of the biological effectiveness are a direct consequence of the energy deposition clustering at the scales of DNA molecule and cell nucleus whilst absorbed dose is a macroscopic averaged quantity which does not take into account heterogeneities at the nanometer and micrometer scales. Microdosimetry aims to measure radiation quality at cellular or sub-cellular levels trying to increase the understanding of radiation damage mechanisms and effects. Existing microdosimeters rely on the well-established gas-based detectors or the more recent solid-state devices. They provide specific energy z spectra and other derived quantities as lineal energy (y) spectra assessed at the micrometer level. The interpretation of the radio-biological experimental data in the framework of different models has raised interest and various investigations have been performed to link in vitro and in vivo radiobiological outcomes with the observed microdosimetric data. A review of the major models based on experimental microdosimetry, with a particular focus on ion beam therapy applications and an emphasis on the microdosimetric kinetic model (MKM), will be presented in this work, enlightening the advantages of each one in terms of accuracy, initial assumptions, and agreement with experimental data. The MKM has been used to predict different kinds of radiobiological quantities such as the relative biological effects for cell inactivation or the oxygen enhancement ratio. Recent developments of the MKM will be also presented, including new non-Poissonian correction approaches for high linear energy transfer radiation, the inclusion of partial repair effects for fractionation studies, and the extension of the model to account for non-targeted effects. We will also explore developments for improving the models by including track structure and the spatial damage correlation information, by using the full fluence spectrum and by better accounting for the energy-deposition fluctuations at the intra- and inter-cellular level.