AI can be used to ' rule-out ' breast cancer on mammography

A deep-learning algorithm can rule out the presence of breast cancer on screening mammograms, improving specificity and yielding significant workflow and downstream savings, according to research published April 10 in Radiology. A team of investigators led by first author Stefano Pedemonte, PhD, of AI software developer Whiterabbit.ai, and senior author Richard Wahl, MD, of the Mallinckrodt Institute of Radiology, trained and tested a deep-learning algorithm using over 160,000 2D full-field digital mammography exams. They found their model could sharply reduce the number of screening mammograms requiring radiologist review and lower the number of false-positive results with minimal, if any, cost to sensitivity. “The elimination of incorrect follow-up examinations and biopsies, which constitute major limitations of breast cancer screening today, benefits patients directly and is the most critical advantage of cancer rule-out technology,” the authors wrote. The researchers then retrospectively trained and tested the algorithm using datasets from two U.S. institutions and one U.K. institution. U.S. dataset 1: 143,593 mammograms interpreted by 11 breast radiologists from 2008 to 2017 U.S. dataset 2: 1,362 mammograms interpreted by 59 radiologists from 2014 to 2019 U.K. dataset 3: 18,873 mammograms interpreted by 210 readers from 2011 to 2015 Datasets 1 and 3 were used mostly for training and validating the algorithm, with 10% set aside for testing. In addition, U.S. d...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Breast Breast Imaging Source Type: news