A Computational Model of Cellular Response to Modulated Radiation Fields
- Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, Northern Ireland (United Kingdom)
Purpose: To develop a model to describe the response of cell populations to spatially modulated radiation exposures of relevance to advanced radiotherapies. Materials and Methods: A Monte Carlo model of cellular radiation response was developed. This model incorporated damage from both direct radiation and intercellular communication including bystander signaling. The predictions of this model were compared to previously measured survival curves for a normal human fibroblast line (AGO1522) and prostate tumor cells (DU145) exposed to spatially modulated fields. Results: The model was found to be able to accurately reproduce cell survival both in populations which were directly exposed to radiation and those which were outside the primary treatment field. The model predicts that the bystander effect makes a significant contribution to cell killing even in uniformly irradiated cells. The bystander effect contribution varies strongly with dose, falling from a high of 80% at low doses to 25% and 50% at 4 Gy for AGO1522 and DU145 cells, respectively. This was verified using the inducible nitric oxide synthase inhibitor aminoguanidine to inhibit the bystander effect in cells exposed to different doses, which showed significantly larger reductions in cell killing at lower doses. Conclusions: The model presented in this work accurately reproduces cell survival following modulated radiation exposures, both in and out of the primary treatment field, by incorporating a bystander component. In addition, the model suggests that the bystander effect is responsible for a significant portion of cell killing in uniformly irradiated cells, 50% and 70% at doses of 2 Gy in AGO1522 and DU145 cells, respectively. This description is a significant departure from accepted radiobiological models and may have a significant impact on optimization of treatment planning approaches if proven to be applicable in vivo.
- OSTI ID:
- 22149480
- Journal Information:
- International Journal of Radiation Oncology, Biology and Physics, Vol. 84, Issue 1; Other Information: Copyright (c) 2012 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0360-3016
- Country of Publication:
- United States
- Language:
- English
Similar Records
Studies of Bystander Effects in 3-D Tissue Systems Using a Low-LET Microbeam
Use of a State-Vector Model of Radiation Carcinogenesis to Integrate Information from in vitro, in vivo, Epidemiological and Physiological Studies