MammoScreen 2.0 is an AI-based software tool designed to assist physicians by automatically analyzing standard screening mammograms including FFDM and DBT images. It marks suspicious soft tissue lesions or calcifications on breast images and provides a level of suspicion score to help radiologists improve detection and characterization of breast cancer findings. This tool acts as a concurrent reading aid to improve diagnostic accuracy but does not replace physician judgment.
MammoScreen is intended for use as a concurrent reading aid for interpreting physicians, to help identify findings on screening FFDM or DBT acquired with compatible mammography systems, and assess their level of suspicion.
MammoScreen 2.0 automatically processes four views of standard screening FFDM or DBT mammograms, detects and characterizes findings using deep learning modules trained on large datasets, and outputs a report with a MammoScreen score indicating suspicion level from 1 to 10, with detailed visual markings on the mammogram.
Clinical validation included two multi-reader multi-case studies showing improved radiologist performance when aided by MammoScreen 2.0 on FFDM and DBT mammograms, with increased average AUC scores. Standalone software performance was found to be non-inferior to unaided radiologists on FFDM and superior on DBT, supporting safety and effectiveness for concurrent reading aid use.
No predicate devices specified
Submission
5/19/2021
FDA Approval
11/26/2021
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