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Department of Mathematical Sciences

Seminar Archives

On this page you can find information about seminars in this and previous academic years, where available on the database.

Statistics Seminars: Count data models for cytogenetic dose estimation

Presented by Manuel Higueras, Newcastle University

23 January 2017 14:00 in CM221

Ionising radiation overexposures are one of the major current concerns of our society. Consequently, biological retrospective dosimetry relies on quantifying the amount of damage induced by radiation at a cellular level, e.g. by counting dicentrics observed in metaphases from a sample of peripheral blood lymphocytes. This quantification is essential for predicting the derived health consequences in overexposed individuals. Moreover, biological dosimetry provides an accurate, personal and individual dosimeter.
In biological dosimetry it is typically assumed that the number of chromosomal aberrations produced in a blood cell is Poisson distributed, whose intensity is a quadratic function of the absorbed dose. Dose-response curves are calculated from cytogenetic laboratory experiments where blood samples are exposed to different doses, simulating whole body homogeneous irradiations. This classical Poisson assumption is not supported in a lot of irradiation scenarios, for instance for high linear energy transfer, partial body or gradient irradiations. These situations lead to compound Poisson, zero-inflated Poisson and Poisson finite mixture models, among others.
The cytogenetic dose estimation implies inverse regression models, because the doses of the dose-responses curves are not random variables. New Bayesian count data inverse regression methods [1, 2, 3] have been developed aiming a more accurate dose estimation uncertainty than the classical established methods, IAEA Manual 2011 [4].
1. Higueras M, Puig P, Ainsbury EA, Vinnikov VA, Rothkamm K. A new Bayesian model applied to cytogenetic partial body irradiation estimation. Radiat Prot Dosim, 168(3), 330-6 (2016).
2. Higueras M, Puig P, Ainsbury EA, Rothkamm K. A new inverse regression model applied to radiation biodosimetry. Proc. R. Soc. A, DOI: 10.1098/rspa.2014.0588 (2015).
3. Higueras M, Puig P, Ainsbury EA. On the cytogenetic dose estimation in gradient exposure scenarios. SEIO2016. Toledo (Spain). 5 September 2016. Lecture.
4. IAEA. Cytogenetic dosimetry: applications in preparedness for and response to radiation emergencies. International Atomic Energy Agency: Vienna (2011).

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