Biophysical models in ion beam radiotherapy

Abstract One major rationale for the application of heavy ion beams in tumor therapy is their increased relative biological effectiveness (RBE) in the Bragg peak region. For dose prescription, the increased effectiveness has to be taken into account in treatment planning. Hence, the complex dependencies of RBE on the dose level, biological endpoint, position in the field etc. require biophysical models, which have to fulfill two important criteria: simplicity and quantitative precision. Simplicity means that the number of free parameters should be kept at a minimum. Due to the lack of precise quantitative data, at least at present, this requirement is incompatible with approaches aiming at the molecular modeling of the whole chain of production, processing and repair of biological damages. Quantitative precision is required since steep gradients in the dose response curves are observed for most tumor and normal tissues; thus, even small uncertainties in the estimation of the biologically effective dose can transform into large uncertainties in the clinical outcome. The paper will give a general introduction into the field, followed by a description of a specific model, the so called ‘Local Effect Model’ (LEM). This model has been successfully applied within treatment planning in the GSI pilot project for carbon ion tumor therapy over almost 10 years now. The model is based on the knowledge of charged particle track structure in combination with the response of the cells or tissues under consideration to conventional photon radiation. The model is compared to other approaches developed for the calculation of the biological effects of high-LET radiation. Furthermore, recent improvements of the model are described. Due to the quantitative precision, besides applications in tumor therapy the LEM seems to be adequate for the calculation of stochastic radiation effects, i.e. in the framework of radiation protection. Examples for the calculation of cell transformation are presented.

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