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Use of molecular and functional Relative Biological Effectiveness measures to predict risk after radiotherapy - Application to high doses per fraction and to the high dose rates

Mariam Ben Kacem has defended her thesis on 19th February 2020​ at IRSN, Fontenay-aux-Roses (France)

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Authors > BEN KACEM Mariam

Publication Date > 19/02/2020


Despite the development of practices and devices which precisely deliver radiation dose to tumor with high dose rate, the biological effects on healthy tissue remain poorly studied. To predict radiation-induced biological effects, radiobiologists use the Relative Biological Effectiveness (RBE) concept to compare doses between two ionizing radiations given the same biological effect. RBE is essentially based on clonogenic assay to determine the impact of a defined ionizing radiation. Survival clonogenic curves are modelled by the linear quadratic model, and, according to several studies, this assay is insufficient to predict effects on healthy tissues after radiation exposure. Based on the various effects known after irradiation, the aim of this thesis work is therefore to acquire multiparametric biological measures to be integrated in a predictive model to foresee the biological effects of emerging radiation therapy modalities and/or protocols. First, for single dose, in vitro data show a deleterious effect at the highest dose rate on clonogenic survival, cell morphology and viability, cell cycle, senescence and gene expression signing cell dysfunction. These results were confirmed in vivo on a preclinical mice model of radiation-induced enteropathy. In contrary to ICPR statement, our results show an RBE of photon different from 1 and depending on the dose rate. On the other hand, different fractionated irradiation protocols highlight in vitro an impact of the dose rate based on a continuum of “effective biological dose” (BED). Different protocols with equivalent BED show different radio-induced response both in vitro and in vivo. This results exhibit certain limits of BED for clinical use to compare different fractionated irradiation protocols.

To conclude, this thesis work shows the interest of using multiparametric biological measures to predict more accurately the radio-induced biological effects. This methodological approach could ultimately allow a better risk prediction of emerging radiation modalities related to current and future radiotherapy practices.
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