Clinical Validation of an Artificial Intelligence Algorithm to Help Interpret Mammograms (ALGO-MAMMO)

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.

Study Overview

• Status: Completed
• Conditions: Breast Cancer

• Study Type: Observational
• Enrollment (Actual): 1000

Contacts and Locations

Study Locations

• France
  • Strasbourg, France, 67091
    • Service de Radiologie 1 - CHU de Strasbourg - France

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 40 years to 75 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Adult woman (40 to 75 years old) treated at the University Hospitals of Strasbourg between 2010 and 2020 for breast cancer

Description

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

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Only
• Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	This assessment is based on contouring the tumor area on mammograms.	Files analysed retrospectively from January 01, 2010 to January 01, 2020 will be examined

Collaborators and Investigators

• Sponsor: University Hospital, Strasbourg, France

Study record dates

Study Major Dates

• Study Start (Actual): April 20, 2021
• Primary Completion (Actual): March 20, 2023
• Study Completion (Actual): May 20, 2023

Study Registration Dates

• First Submitted: November 25, 2022
• First Submitted That Met QC Criteria: November 25, 2022
• First Posted (Actual): December 7, 2022

Study Record Updates

• Last Update Posted (Actual): November 8, 2023
• Last Update Submitted That Met QC Criteria: November 7, 2023
• Last Verified: November 1, 2022

More Information

Terms related to this study

• Keywords: Breast Cancer; Mammography; Artificial intelligence; Tumor detection on mammograms
• Additional Relevant MeSH Terms: Skin Diseases; Neoplasms; Neoplasms by Site; Breast Diseases; Breast Neoplasms
• Other Study ID Numbers: 7964

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No