Comparing AI-assisted and standard second readings of breast cancer screening mammograms

Évaluation de la Performance Diagnostique du dépistage du Cancer du Sein, Pour Une Seconde Lecture Des clichés de Mammographie assistée du Dispositif médical à Base d'Intelligence Artificielle MammoScreen

Not applicable Interventional Therapixel · NCT05800132

This study is testing if using AI to help read breast cancer screening mammograms is just as good as having a radiologist do it alone, to see if it can improve accuracy and save money.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment5000 (estimated)
Ages50 Years to 74 Years
SexFemale
SponsorTherapixel Industry-sponsored
Locations7 sites (Aubagne and 6 other locations)
Trial IDNCT05800132 on ClinicalTrials.gov

What this trial studies

This clinical trial aims to evaluate the diagnostic performance of an AI-assisted second reading process for breast cancer screening mammograms compared to the standard second reading by a radiologist. Participants will undergo screening mammograms, and their images will be interpreted in two ways: first by AI and then by a radiologist if the AI flags any concerns. The study will assess whether the AI-assisted approach is non-inferior to the traditional method in terms of diagnostic accuracy and whether it offers economic advantages. The final decision on mammogram results will be based on the most conservative assessment from both readings.

Who should consider this trial

Good fit: Ideal candidates are women affiliated with the French social security system who have normal or benign mammogram results and are willing to participate.

Not a fit: Patients with breast implants, clinical symptoms of breast cancer, or a history of breast surgery may not benefit from this study.

Why it matters

Potential benefit: If successful, this study could enhance the accuracy and efficiency of breast cancer screenings, potentially leading to earlier detection and better patient outcomes.

How similar studies have performed: Other studies have shown promising results with AI-assisted diagnostic processes in medical imaging, indicating potential for success in this approach.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Affiliated to the French social security system
* Whose mammograms meet the following characteristics: 4 (2 per breast, CC and MLO) meeting local regulatory standards and with correct DICOM metadata,
* Whose mammograms have been determined to be normal or to have benign lesions by the radiologist who performed the first reading of the images (L1) in the framework of the organized breast cancer screening program
* Having expressed her willingness to participate in the study, to undergo all the procedures and to make herself available for the expected duration of their participation,
* Having completed and signed the informed consent form.

Exclusion Criteria:

* Woman with breast implants,
* With clinical symptoms of breast cancer,
* With a history of breast surgery (breast reduction or surgery for benign lesion),
* Pregnant or breastfeeding,
* With medical conditions that may interfere with her ability to understand the requirements of the protocol or give informed consent,
* Deprived of liberty by judicial or administrative order,
* Participant whose mammogram images have at least one of the following defects: poor quality of the images, non-standard mammography (projection, magnification, compression), ML/LM/SIO/XCCL or XCCM view.

Where this trial is running

Aubagne and 6 other locations

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Breast Cancerartificial intelligencebreast cancer screeningsecond reading
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.