Introduction: This study aimed to evaluate the accuracy of radiographers' screen-reading mammograms. Currently, radiologist workforce shortages may be compromising the BreastScreen Australia screening program goal to detect early breast cancer. The solution to a similar problem in the United Kingdom has successfully encouraged radiographers to take on the role as one of two screen-readers. Prior to consideration of this strategy in Australia, educational and experiential differences between radiographers in the United Kingdom and Australia emphasise the need for an investigation of Australian radiographers' screen-reading accuracy.
Methods: Ten radiographers employed by the Westmead Breast Cancer Institute with a range of radiographic (median = 28 years), mammographic (median = 13 years) and BreastScreen (median = 8 years) experience were recruited to blindly and independently screen-read an image test set of 500 mammograms, without formal training. The radiographers indicated the presence of an abnormality using BI-RADS®. Accuracy was determined by comparison with the gold standard of known outcomes of pathology results, interval matching and client 6-year follow-up.
Results: Individual sensitivity and specificity levels ranged between 76.0% and 92.0%, and 74.8% and 96.2% respectively. Pooled screen-reader accuracy across the radiographers estimated sensitivity as 82.2% and specificity as 89.5%. Areas under the reading operating characteristic curve ranged between 0.842 and 0.923.
Conclusions: This sample of radiographers in an Australian setting have adequate accuracy levels when screen-reading mammograms. It is expected that with formal screen-reading training, accuracy levels will improve, and with support, radiographers have the potential to be one of the two screen-readers in the BreastScreen Australia program, contributing to timeliness and improved program outcomes.
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http://dx.doi.org/10.1002/jmrs.59 | DOI Listing |
Lancet Oncol
August 2023
Division of Diagnostic Radiology, Department of Translational Medicine, Lund University, Malmö, Sweden.
Background: Retrospective studies have shown promising results using artificial intelligence (AI) to improve mammography screening accuracy and reduce screen-reading workload; however, to our knowledge, a randomised trial has not yet been conducted. We aimed to assess the clinical safety of an AI-supported screen-reading protocol compared with standard screen reading by radiologists following mammography.
Methods: In this randomised, controlled, population-based trial, women aged 40-80 years eligible for mammography screening (including general screening with 1·5-2-year intervals and annual screening for those with moderate hereditary risk of breast cancer or a history of breast cancer) at four screening sites in Sweden were informed about the study as part of the screening invitation.
J Med Radiat Sci
March 2022
School of Dentistry and Health Sciences, Charles Sturt University, Wagga Wagga, NSW, Australia.
Introduction: A high demand has been placed on radiologists to perform screen reads due to higher number of women undergoing mammography. This study aims to examine radiographer performance in reporting low compared with high-mammographic density (MD) images; and to assess the influence of key demographics of Jordanian radiographers on their performance.
Methods: Thirty mammograms with varied MD were reported by 12 radiographers using the Breast Imaging-Reporting and Data System (BI-RADS).
Eur Radiol
March 2021
Diagnostic Radiology, Department of Translational Medicine, Lund University, Inga Maria Nilssons gata 47, SE-20502, Malmö, Sweden.
Objectives: To evaluate the potential of artificial intelligence (AI) to identify normal mammograms in a screening population.
Methods: In this retrospective study, 9581 double-read mammography screening exams including 68 screen-detected cancers and 187 false positives, a subcohort of the prospective population-based Malmö Breast Tomosynthesis Screening Trial, were analysed with a deep learning-based AI system. The AI system categorises mammograms with a cancer risk score increasing from 1 to 10.
Lancet Oncol
November 2018
Department of Translational Medicine, Diagnostic Radiology, Lund University, Skåne University Hospital Malmö, Malmö, Sweden.
Background: Digital breast tomosynthesis is an advancement of the mammographic technique, with the potential to increase detection of lesions during breast cancer screening. The main aim of the Malmö Breast Tomosynthesis Screening Trial (MBTST) was to investigate the accuracy of one-view digital breast tomosynthesis in population screening compared with standard two-view digital mammography.
Methods: In this prospective, population-based screening study, of women aged 40-74 years invited to attend national breast cancer screening at Skåne University Hospital, Malmö, Sweden, a random sample was asked to participate in the trial (every third woman who was invited to attend regular screening was invited to participate).
Eur J Radiol
September 2018
Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, Australia. Electronic address:
Background: We previously reported the Screening with tomosynthesis or standard mammography-2 (STORM-2) trial, showing that tomosynthesis (3D-mammography) screening detected more cancers than 2D-mammography in double-reading practice. In this study, we report reader-specific detection measures for radiologists who performed the screen-reading in this trial.
Methods: This is a sub-study of the STORM-2 trial which prospectively integrated 3D-mammography with acquired or synthetized 2D-mammograms in parallel double-reading arms.
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