Predicting the sensitivity to ion therapy based on the response to photon irradiation - experimental evidence and mathematical modelling
Number of Authors: 7
2014 (English)In: Anticancer Research, ISSN 0250-7005, E-ISSN 1791-7530, Vol. 34, no 6, 2801-2806 p.Article in journal (Refereed) Published
Background/Aim: The use of ion radiation therapy is growing due to the continuously increasing positive clinical experience obtained. Therefore, there is a high interest in radio-biological experiments comparing the relative efficiency in cell killing of ions and photons as the photons are currently the main radiation modality used for cancer treatment. This comparison is particularly important since the treatment planning systems (TPSs) used at the main ion therapy centres make use of parameters describing the cellular response to photons, respectively ions, determined in vitro. It was therefore the aim of this paper to compare the effects of high LET ion radiation with low LET photons and determine whether the cellular response to low LET could predict the response to high LET irradiation. Materials and Methods: Clonogenic cell survival data of five tumor cell lines irradiated with different ion beams of similar, clinically-relevant, LET were studied in relation to the response to low LET photons. Two mathematical models were used to fit the data, the repairable-conditionally repairable damage (RCR) model and the linear quadratic (LQ) model. Results: The results indicate that the relative biological efficiency of the high LET radiation assessed with the RCR model could be predicted based only on the response to the low LET irradiation. Conclusion: The particular features of the RCR model indicate thus that tumor cells showing a large capacity for repairing the damage will have the larger benefit from radiation therapy with ions beams.
Place, publisher, year, edition, pages
2014. Vol. 34, no 6, 2801-2806 p.
Clonogenic cell survival, linear energy transfer, high LET, low LET, relative biological effectiveness
Cancer and Oncology
IdentifiersURN: urn:nbn:se:su:diva-103172ISI: 000336875200014OAI: oai:DiVA.org:su-103172DiVA: diva2:716060