AI-fueled mammography triage software from DeepHealth wins 510(k).
Artificial intelligence (AI) developer DeepHealth, a subsidiary of RadNet, announced Monday it has secured 510(k) clearance from the U.S. Food & Drug Administration (FDA) for its mammography triage solution, Saige-Q.
This AI-driven screening worklist prioritization tool is DeepHealth’s first cleared product, and it automatically identifies screening exams that have suspicious findings that require additional evaluation, company officials said. By identifying these cases, the software helps radiologists streamline their workflow to be more efficient and effective.
“Saige-Q is built using our core artificial intelligence algorithms, described in a recent article in Nature Medicine,” said Bill Lotter, Ph.D., chief technology officer, and DeepHealth co-founder. “As the FDA-cleared mammography triage product that supports 3D mammography in addition to 2D mammography, Saige-Q demonstrates high performance that is maintained across different breast densities and lesion types.”
It is a tool that is designed to increase radiologist confidence in their ability to pinpoint suspicious findings, bolstering their ability to provide high-quality care.
For more coverage based on industry expert insights and research, subscribe to the Diagnostic Imaging e-Newsletter here.
What is the Best Use of AI in CT Lung Cancer Screening?
April 18th 2025In comparison to radiologist assessment, the use of AI to pre-screen patients with low-dose CT lung cancer screening provided a 12 percent reduction in mean interpretation time with a slight increase in specificity and a slight decrease in the recall rate, according to new research.
Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
April 16th 2025Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.
New bpMRI Study Suggests AI Offers Comparable Results to Radiologists for PCa Detection
April 15th 2025Demonstrating no significant difference with radiologist detection of clinically significant prostate cancer (csPCa), a biparametric MRI-based AI model provided an 88.4 percent sensitivity rate in a recent study.