NanOx model: how to predict RBE for hadrontherapy
Résumé
Hadrontherapyis becoming an attractive modality for cancer treatment, as the exponential increase in the number of dedicated facilities built over the past decades shows. The favorable depth-dose profile of protons is mostly exploited to eradicate localized tumors situated close to organs at risk, while the high biological effectiveness makes carbon ion beams more adequate than the conventional radiotherapy modalities to treat radioresistant cancers. Such an efficiency in cell killing is quantified through the RBE (relative biological effectiveness), which is a complex function of multiple parameters related to the incident particles, the irradiation conditions and the intrinsic properties of the biological system. Determining the value of RBE for every scenario is a challenging task that requires modeling to comply with the demands of a clinical environment. NanOx addresses some of the flaws in the models currently implemented in the treatment planning systems, and presents many innovative features.This model [1, 2] integrates the fully-stochastic nature of ionizing radiation by taking into account the fluctuations in the deposited energyboth at nanometric and micrometric scales. Moreover, it considers the accumulation of oxidative stress and sublethal damage via theproduction and diffusion of reactive chemical species. The prediction of cell survival probability for a wide LET range requires the determination of only 5 parameters issued from experimental measurements specific to the cell line. The results obtained forV79, CHO-K1 and HSG cells in response to monoenergetic beams of photons, protons and carbon ions are in good agreement with the experimental data. NanOxis able to describe the effectiveness of ions, including the overkill effect at high LET values. Moreover, the typical shoulder in cell survival curves is reproduced owing to the introduction of the chemical specific energy which varies with LET. These promising results incited us to perform further studies to test the model predictions in conditions that are closer to the clinical context, i.e., for spread-out Bragg peak irradiations. We are currently working on the production of tables of linear-quadratic parameters (α,β), which constitute the input for estimating cell survival to mixed fields in hadrontherapy facilities thanks to Kanai approximation [3].Finally, NanOx field of application may be extended to other innovative radiotherapy treatments, e.g photoactivation of nanoparticles or neutron capture therapy. [1] Cunha, M.; Monini, C.; Testa, E.; Beuve, M. “NanOx, a new model to predict cell survival in the context of particle therapy.” Phys. Med. Biol. 2017, 62, 1248–1268.[2] Monini, C.; Cunha, M.; Testa, E.; Beuve, M. “Study of the Influence of NanOxParameters” Cancers (Basel), vol. 10, no. 4, doi: 10.3390/cancers10040087, 2018.[3] Kanai, T. et al. “Irradiation of Mixed Beam and Design of Spread-Out Bragg Peak for Heavy-Ion Radiotherapy.” Radiat. Res.1997, 1, 147 Supported by ITMO Cancer (Project Nos. PC201312, PC201606) and by LABEX PRIMES (ANR-11-LABX-063)