Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 541-546 |
| Journal | Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology |
| Volume | 124 |
| Issue number | 3 |
| Early online date | 01 Sep 2017 |
| DOIs | |
| Publication status | Published - Sep 2017 |
Keywords
- Journal Article
Access to Document
- A hierarchical Bayesian approach to calibrating the linear-quadratic model from clonogenic survival assay data
Copyright 2017 Elsevier. This manuscript is distributed under a Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits distribution and reproduction for non-commercial purposes, provided the author and source are cited.
