Can AI be a second reader in breast cancer screening? By Erik L. Ridley, AuntMinnie staff writer
An artificial intelligence (AI) algorithm could obviate the need for a second radiologist to review a screening mammogram in more than four out of five exams performed for a national breast cancer screening program, according to a presentation on Monday morning at the virtual RSNA 2020 meeting. A team of researchers led by Dr. Nisha Sharma of Leeds Teaching Hospitals NHS Trust in the U.K. simulated the use of AI as a second reader by retrospectively applying an AI algorithm to over 40,000 screening mammograms and then comparing the software’s results with that of the initial radiologist interpretation. They found that over 80% of the exams could have been accurately categorized as either normal or abnormal without requiring any additional interpretation. “Our study shows that an AI algorithm is a viable option to replace the second human reader in the double reading of screening mammograms,” Sharma said. Standard of care Although the practice isn’t common in the U.S., double reading of screening mammography studies is the standard of care in many countries around the world. In the U.K., women ages 50 to 70 are eligible to receive breast screening under the National Health System (NHS) National Breast Screening program every three years. Screening mammograms are
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interpreted independently by two radiologists. If the readers agree on the findings, this consensus result is used to categorize a mammogram as normal and the woman is then invited back for routine screening in three years. Women will be recalled for second-stage screening if their screening mammogram is considered to be abnormal by both readers. If the two readers have discordant findings, then a third reader or readers will review the study to determine the diagnosis. This model is labor-intensive, however, and difficult to achieve due to the ongoing workforce crisis in the U.K., according
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