Clinical Validation of an Artificial Intelligence Algorithm to Help Interpret Mammograms

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05640011

Acronym

ALGO-MAMMO

Enrollment

1000

Registered

2022-12-07

Start date

2021-04-20

Completion date

2023-05-20

Last updated

2023-11-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Breast Cancer

Keywords

Breast Cancer, Mammography, Artificial intelligence, Tumor detection on mammograms

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.

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

FEMALE

Age

40 Years to 75 Years

Healthy volunteers

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

Design outcomes

Primary

Measure	Time frame	Description
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.	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.

Countries

France

Outcome results