Raed M K M Ali1, Andrew England2, Claire Mercer3, Andrew Tootell4, Lucy Walton5, Wouter Schaake6, Peter Hogg7. 1. Faculty of Medicine, University of Kufa, Iraq; University of Salford, UK. Electronic address: raedm.kadhim@uokufa.edu.iq. 2. University of Salford, UK. Electronic address: A.England@salford.ac.uk. 3. University of Salford, UK. Electronic address: C.E.Mercer@salford.ac.uk. 4. University of Salford, UK. Electronic address: A.K.Tootell@salford.ac.uk. 5. University of Salford, UK. Electronic address: L.A.Walton@salford.ac.uk. 6. Department of Medical Imaging and Radiation Therapy, Hanze University of Applied Sciences, Eyssoniusplein 18, 9714 CE Groningen, The Netherlands. Electronic address: w.schaake@pl.hanze.nl. 7. University of Salford, UK; Karolinska Institute, Sweden. Electronic address: P.Hogg@salford.ac.uk.
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.
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.
Authors: Bruno Barufaldi; Samantha P Zuckerman; Regina B Medeiros; Andrew D Maidment; Homero Schiabel Journal: Phys Med Date: 2020-03-03 Impact factor: 2.685