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AI from ScreenPoint Medical and Volpara Health demonstrates ability to predict long-term breast cancer risk

Press releases may be edited for formatting or style | May 24, 2023 Artificial Intelligence Women's Health
NIJMEGEN, Netherlands and WELLINGTON, New Zealand, May 23, 2023 /PRNewswire/ -- Researchers from the Mayo Clinic (Rochester, MN) and University of California, San Francisco confirmed that pairing artificial intelligence (AI) imaging and volumetric breast density algorithms can assist in predicting long-term risk of breast cancer, in particular invasive disease. The study, "Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer," was recently published in the Journal of Clinical Oncology.

The study was designed to determine if an AI algorithm could contribute to long-term risk prediction for advanced and interval cancers. Researchers used images from 2,412 women with invasive breast cancer and 4,995 matched controls who had digital mammograms performed 2-5.5 years before cancer diagnosis. The performance of conventional assessment measures (traditional radiologist interpretation and BI-RADS® density categories) were compared to the ability of newer AI-powered techniques (precise volumetric density measures and image-based malignancy risk scores) for long-term risk prediction of advanced and interval cancers.

Research findings:
Transpara AI score improves long-term risk prediction when combined with clinical risk factors including breast density for overall invasive cancers, screen-detected, advanced, and nonadvanced cancers. For interval cancers, the TruDensity measures remained of greatest importance for discrimination, even years before the cancer.

AI software used in this study

The Transpara Exam Score is an image-based risk tool that categorizes exams using a 10-point scale and is used for concurrent reading of mammograms. The higher the score, the higher the risk of cancer in the mammogram. Clinical research conducted with Transpara shows that scores between 1 - 7 (Low Risk) have a 99.97% negative predictive value. The Volpara TruDensity AI algorithm uses a combination of x-ray physics and machine learning to generate an accurate volumetric measure of breast composition to eliminate variability that can arise from human interpretation.

"While we have known for decades that density and breast cancer risk are correlated, recent research has really pushed forward our ability to better understand the effects of density combined with image-based risk to drive personalized medicine for women," said Professor Nico Karssemeijer, PhD, Chief Scientific Officer at Screenpoint Medical, and faculty member at Radboud University.

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