Intended Use

MammoScreen is intended for use as a concurrent reading aid for interpreting physicians, to help identify findings on screening FFDM acquired with compatible mammography systems and assess their level of suspicion.

Technology

MammoScreen comprises a software-only system with machine learning algorithms, including deep learning modules trained on large biopsy-proven datasets to detect suspicious calcifications and soft tissue lesions. It operates as a DICOM Web compliant node, processing FFDM images from mammography systems, and provides output as marks and a suspicion score on a 1-10 scale via a user interface.

Performance

Clinical and non-clinical testing show MammoScreen is safe and effective. A clinical multi-reader multi-case study with 14 radiologists and 240 mammograms demonstrated improved radiologist performance with MammoScreen (AUC increased from 0.77 to 0.80, p=0.035), with significant improvement at breast and lesion levels. Standalone performance was comparable to radiologists. Non-clinical testing included software verification, beta validation, and hazard analysis.

Predicate Devices

No predicate devices specified

Device Timeline

  • 1

    Submission

    10/4/2019

    5 months
  • 2

    FDA Approval

    3/25/2020

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