Clinical validation of an artificial intelligence system to improve the quality, efficiency and experience of breast cancer screening

Imperial College London0 sites68,000 target enrollmentJune 6, 2022

Overview

No summary available.

Registry

who.int

Start Date

June 6, 2022

End Date

May 21, 2024

Last Updated

3 years ago

Study Type

Observational

Sex

Female

Sponsor

•1\. Women undergoing routine breast cancer screening (age 50\-70 years) as part of the national breast screening programme from January 2016 onwards
•2\. Mammography images acquired using Hologic/Lorad, Siemens, or GE devices

•1\. Women attending an assessment clinic or symptomatic clinic (i.e. not routine screening)
•2\. Women undergoing annual screening due to:
•2\.1\. High risk (lifetime risk \>30% \- e.g. faulty BRCA1, BRCA2, TP53\)
•2\.2\. Moderate risk (lifetime risk 17\-30%)
•2\.3\. Personal stratified follow up (e.g. indeterminate B3 lesions)
•3\. Presence of breast implants
•4\. Screens with incomplete (\<4 standard screening views \- e.g. due to abandoned screen)
•5\. Poor diagnostic quality imaging (which would be repeated)
•6\. Non\-standard acquisitions beyond the routine 4 screening views
•7\. For negative or benign cases, women without a negative follow up screen approximately 3 years later (at least 31 months after initial screen), as this would preclude determination of a robust ground truth