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Modelling cell death for cancer hadrontherapy

1 Department of Physics, University of Pavia, via Bassi 6, I-27100 Pavia, Italy
2 INFN-National Institute of Nuclear Physics, Section of Pavia, via Bassi 6, I-27100 Pavia, Italy

Many cancer types are treated more and more frequently with protons or Carbon ions, which allow obtaining a high dose conformation to the tumor and, in the case of Carbon, a high biological effectiveness, which makes heavy ions particularly suitable to treat tumors that are resistant to conventional photon therapy. For Carbon ions it is therefore mandatory an evaluation of the beam biological effectiveness, which depends not only on the particle energy, and thus the depth in tissue, but also on many other parameters including dose, cell type and considered biological effect. In specific cases, typically for single-field irradiation of tumors located immediately before an organ at risk, this kind of evaluation may be useful also for protons, for which the constant biological effectiveness currently assumed in clinics may be sub-optimal. In principle such evaluation can be based both on experimental data and on biophysical models; of course, both methods have advantages and drawbacks. In this framework, the two main approaches adopted for Carbon therapy, that is the Local Effect Model (LEM) used in Germany and Italy and the empirical approach used in Japan, will presented and discussed, as well as an alternative model called Microdosimetric-Kinetic Model (MKM). Some recent phenomenological models specific for protons, which share as a common basis the so-called Linear-Quadratic formulation, will also be reviewed. Finally, a biophysical model of cell death and chromosome aberrations called BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations), developed in Pavia (Italy), will be presented.
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Keywords hadrontherapy; cell death; chromosome aberrations; biophysical models; Monte Carlo simulations

Citation: Mario P. Carante, Francesca Ballarini. Modelling cell death for cancer hadrontherapy. AIMS Biophysics, 2017, 4(3): 465-490. doi: 10.3934/biophy.2017.3.465

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