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New research indicates ProFound AI may reduce interval breast cancer rates

Press releases may be edited for formatting or style | April 01, 2021 Artificial Intelligence Women's Health
NASHUA, N.H. – March 31, 2021 - iCAD, Inc. (NASDAQ: ICAD), a global medical technology leader providing innovative cancer detection and therapy solutions, today announced that ProFound® AI for 2D Mammography might notably reduce the risk of interval breast cancer, according to a retrospective analysis recently published in the Journal of Medical Screening.[1]

The aim of the study was to determine if adding AI to reading mammography as a supportive tool may help in decreasing the interval cancer rate in population-based organized mammography screening programs in Germany.

"Interval breast cancers—cancers that are diagnosed after a negative mammography screening, but before the next recommended screening exam, can be linked to a poor prognosis such as cancer that has already spread, or a more aggressive type of cancer, thus underscoring the need for iCAD's deep-learning algorithm that can analyze each mammography image and provide critical insight into individual cases," said Michael Klein, Chairman and CEO of iCAD. "The data from this retrospective analysis are very encouraging in Europe while also having an impact on screening in the US. The results further stress the importance of our ProFound AI platform as a world-class artificial intelligence (AI) solution offering benefits to radiologists and women in improving breast cancer detection rates, reducing false positives and unnecessary callbacks, and providing more personalized screening for every woman."

In the retrospective analysis, which evaluated a screening period from 2011 and 2012, a total of 37,367 women between the ages of 50-69 were screened with full-field digital mammography (FFDM). Of these, 29 cases of interval cancers with full documentation were evaluated using ProFound AI for 2D Mammography. For quality assurance, interval cancers with the prior screening mammogram were classified in four categories by the radiologists: true interval cancers, minimal sign cancers, missed cancers (false negative) based on the original screening exam deemed as normal and dismissed, and occult cancers. The objective of the study was to determine whether ProFound AI for 2D Mammography could identify interval cancers that had either minimal signs in the original normal screening or were missed in the original screening round where they had been dismissed as a normal exam.

According to the lead author of the study, Axel Gräwingholt, MD, Radiologie am Theater in Paderborn, Germany, "The results indicate that ProFound AI for 2D Mammography found 93% of these cancers—eight out of nine cancers that presented minimal signs and six out of six that were false negatives, or missed in the screening round—demonstrating that some cancers could have been detected earlier within the screening round where they were dismissed as normal and therefore wouldn´t have been detected as interval cancers."

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