Clinical Validation of an Artificial Intelligence Algorithm to Help Interpret Mammograms
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Breast Cancer
- Sponsor
- University Hospital, Strasbourg, France
- Enrollment
- 1000
- Locations
- 1
- Primary Endpoint
- Evaluate the diagnostic performance (sensitivity, specificity) for operator tumor detection assisted by mammographic diagnostic aid software, and compare it to the diagnostic performance of an unassisted operator.
- Status
- Completed
- Last Updated
- 2 years ago
Overview
Brief Summary
This aims to clinically validate, on a large population, a tumor detection aid software which has already been trained on a representative French population (from several hospital centers and liberals from several departments in the west and east of France).
This population consists of 1000 patients who have been treated for breast cancer (histologically proven by breast biopsy) and whose investigators have mammograms performed at the time of diagnosis. The control population consists of the unaffected breast of each patient (with the exception of the rare cases of bilateral cancers).
This innovative software has the main feature of recognizing healthy breast tissue, allowing the radiologist to focus on breast tissue at risk, improving the management of medical time and the management of "difficult" files.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Adult woman (40 to 75 years old)
- •Treatment at the University Hospitals of Strasbourg between 2010 and 2020 for breast cancer
- •including mammography and histological evidence available
- •Patient who has already given her consent for the reuse of her anonymous data for research purposes
Exclusion Criteria
- •Woman who expressed her opposition to participating in the study
Outcomes
Primary Outcomes
Evaluate the diagnostic performance (sensitivity, specificity) for operator tumor detection assisted by mammographic diagnostic aid software, and compare it to the diagnostic performance of an unassisted operator.
Time Frame: Files analysed retrospectively from January 01, 2010 to January 01, 2020 will be examined
This assessment is based on contouring the tumor area on mammograms.