Mathematical modelling of radiation-induced cancer risk from breast screening by mammography

Ali, R, England, A, Mercer, CE, Tootell, AK, Walton, LA ORCID: 0000-0002-8651-7443, Schaake, W and Hogg, P 2017, 'Mathematical modelling of radiation-induced cancer risk from breast screening by mammography' , European Journal of Radiology .

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Abstract

Objectives: Establish a method to determine and convey lifetime radiation risk from FFDM screening.
Methods: Radiation risk from screening mammography was quantified using effective risk (number of radiation-induced cancer cases/million). For effective risk calculations, organ doses and examined breast MGD were used. Screening mammography was simulated by exposing a breast phantom for cranio-caudal and medio-lateral oblique for each breast using 16 FFDM machines. An ATOM phantom loaded with TLD dosimeters was positioned in contact with the breast phantom to simulate the client’s body. Effective risk data were analysed using SPSS software to establish a regression model to predict the effective risk of any screening programme. Graphs were generated to extrapolate the effective risk of all screening programmes for a range of commencement ages and time intervals between screens.
Results: The most important parameters controlling clients’ total effective risk within breast screening are the screening commencement age and number of screens (correlation coefficients were -0.865 and 0.714, respectively). Since the tissue radio-sensitivity reduces with age, the end age of screening does not result in noteworthy effect on total effective risk.
Conclusions: The regression model can be used to predict the total effective risk for clients within breast screening but it cannot be used for exact assessment of total effective risk. Graphical representation of risk could be an easy way to represent risk in a fashion which might be helpful to clients and clinicians.

Item Type: Article
Schools: Schools > School of Health Sciences
Journal or Publication Title: European Journal of Radiology
Publisher: Elsevier
ISSN: 0720-048X
Related URLs:
Depositing User: P Hogg
Date Deposited: 09 Oct 2017 10:52
Last Modified: 24 Nov 2017 07:16
URI: http://usir.salford.ac.uk/id/eprint/43947

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