Saige-Dx by DeepHealth, Inc is an AI-powered software that assists radiologists by automatically analyzing DBT mammograms and associated 2D images to detect potential soft tissue lesions and calcifications that might indicate breast cancer. It provides suspicion levels for findings and the entire case to support physicians during screening mammogram interpretation, improving diagnostic accuracy and efficiency.
Saige-Dx analyzes digital breast tomosynthesis (DBT) mammograms to identify the presence or absence of soft tissue lesions and calcifications that may be indicative of cancer. It assigns Suspicion Levels for each detected finding and for the entire case and is used as a concurrent reading aid for interpreting physicians on screening mammograms with compatible DBT hardware.
Saige-Dx is a software-only AI device that processes DICOM files from DBT mammography exams, analyzing both 3D image stacks and 2D images. It applies machine learning algorithms to detect suspicious findings, generating bounding boxes and suspicion levels at the finding and case level, outputting results in DICOM Structured Report and Secondary Capture formats for integration with PACS and workstation displays.
Performance testing included standalone validation on an independent dataset of 1,804 screening DBT exams from multiple clinical sites and diverse populations. The study demonstrated non-inferior and comparable accuracy to the predicate device across multiple vendors and imaging conditions, with a case-level AUC of 0.910. Additional testing confirmed safety and effectiveness on exams with Hologic HD images, unilateral breasts, and breast implants. Software verification testing showed compliance with requirements and no unintended differences from predicate.
No predicate devices specified
Submission
6/18/2024
FDA Approval
11/18/2024
Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.
We respect your privacy. Unsubscribe at any time.