Advanced statistical methods for cytogenetic radiation biodosimetry

Abstract

The original aim of this thesis, entitled `Advanced Statistical Methods for Cytogenetic Radiation Biodosimetry¿ was to `develop novel solutions for statistical analysis of cytogenetic data¿ and the question that was to be addressed by this project was `how best to correctly quantify cytogenetic damage that is induced by radiation in complex scenarios of radiation exposure, where it is recognised that the current techniques are insufficient.¿ The project was created with the aim of providing increased statistical accuracy of cytogenetic dose estimates carried out both for the Public Health England's biological dosimetry service and for research purposes, which will correspondingly further inform health risk assessment for radiation protection. The specific objectives were: 1. Identification of further limitations in the existing cytogenetic methodologies (in addition to those that had been previously identified); 2. Identification of scenarios that pose particular difficulties for practical cytogenetic biodosimetry, for which advancement of statistical methods may offer solutions; 3. Identification and comparison of solutions that have been previously developed/proposed in the literature and their further development/application (as appropriate) for the scenarios found in 2; 4. Development and testing of further novel solutions, in the Bayesian and classical frameworks, and implementation of these for use in practical cytogenetic biodosimetry (e.g. in Java); 5. Publication of the results. This project has addressed the original aim and above objectives through original research into statistical methods for biological dosimetry resulting in six peer-reviewed publications. The main results from each of these publications are as follows: A review of the literature to identify radiation exposure scenarios requiring further work which outlines the rationale behind a Bayesian approach and gives a practical example; Development of techniques to address the identified gaps, in particular new models for inverse regression and partial body irradiation; Demonstration of application of these novel methodologies to existing and new cytogenetic data in a number of different scenarios and Development of two R-project packages, one to support biological dose estimation using the novel methodology and another to manage the family of Generalized Hermite Distributions.