The study was conducted to evaluate the thresholds at which the ProFound AI system could be used for triaging DBT exams to reach a minimum rate of false negatives per 1,000 screened in an enriched dataset of 506 biopsy-proven cancer cases and 1,293 non-cancer cases with 320 days of negative follow-up. A consecutive series of cases were collected from 18 sites in the United States and three sites in France.

In addition, new data presented by Dr. Mark Traill at the NCoBC Interdisciplinary Breast Center Conference highlights the comparison of ProFound AI Case Scores to BI-RADS assessment categories determined by a single radiologist without using AI in a retrospective analysis. Researchers used ProFound AI on 890 consecutive DBT studies and 50 consecutive cases with biopsy-proven breast cancer detected with DBT. Results showed a strong positive correlation between a ProFound AI Case Score of less than 60 percent and patients assessed as likely to be normal (BI-RADS 1 or 2), while most of the biopsy-proven cancers had a Case Score of greater than 60 percent.


"We wanted to describe the Case Score distribution in a screening population to better understand the significance of score value as a clinical decision tool," said Dr. Traill. "We found a very strong correlation between a Case Score of less than 60 percent and a BI-RADS score assessment of 1 or 2. Also, only 15 percent of the Case Scores were greater than 60 percent, but this group contained most of the detected cancers. As a clinical decision tool, a Case Score above 60 percent is an independent indicator of higher chance of underlying malignancy. This is very helpful in guiding the intensity of the cancer search, while improving workflow functionality and reducing stress for the reading radiologist."

ProFound AI for DBT is a high-performance, deep-learning workflow solution trained to detect malignant soft-tissue densities and calcifications. It became the first 3D tomosynthesis software using artificial intelligence (AI) to be FDA cleared in December 2018. Built with the latest in deep-learning technology, ProFound AI for DBT rapidly analyzes each tomosynthesis image, detecting malignant soft tissue densities. Certainty of Finding and Case Scores are relative scores computed by the ProFound AI algorithm and represent its confidence that a detection or case is malignant. The Certainty of Finding scores help radiologists by aiding in clinical decision making. Case Scores, which are assigned to each case by the algorithm, help clinicians to gain a sense of case complexity, which may be useful for prioritizing the reading worklist. In a reader study published in Radiology: Artificial Intelligence, ProFound AI for DBT Version 2.0 was clinically proven to reduce reading time for radiologists by 52.7 percent, improve radiologists' sensitivity by 8 percent, and reduce the rate of false positives and unnecessary patient recalls by 7.2 percent.[1]

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