We propose a Bayesian hierarchical model applicable to the calibration of the linear-quadratic model of radiation dose-response. Experimental data used in model calibration were taken from a clonogenic survival assay conducted on human breast cancer cells (MDA-MB-231) across a range of radiation doses (0-6Gy). Employing Markov-chain Monte Carlo methods, we calibrated the proposed Bayesian hierarchical model, computed posterior distributions for the model parameters and survival fraction dose-response probability densities. Key contributions include the proposal of a model that incorporates multiple sources of inter- and intra-experiment variability commonly neglected in the standard frequentist approach and its subsequent application to in vitro experimental data.
|Journal||Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology|
|Early online date||01 Sep 2017|
|Publication status||Published - Sep 2017|
- Journal Article