Point-of-care ultrasound with AI to improve breast cancer screening

System-integrated Point-of-Care Ultrasound in Breast Cancer Screening

Not applicable Interventional Region Skane · NCT07462351

We're testing whether short-trained nurses using AI-supported handheld ultrasound together with clinical breast exams can safely and accurately triage women aged 30+ without symptoms and women 18+ with breast symptoms in community settings in Arba Minch, Ethiopia.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment4800 (estimated)
Ages18 Years and up
SexFemale
SponsorRegion Skane Academic / other
Locations1 site (Arba Minch, Gamo Zone)
Trial IDNCT07462351 on ClinicalTrials.gov

What this trial studies

After a local awareness campaign, asymptomatic and symptomatic women are invited for screening beginning with a clinical breast exam; women with positive exams or symptoms receive targeted AI-supported point-of-care ultrasound (POCUS) at the complaint site. Clinical nurses or clinical officers perform the POCUS after a short training and certification program, while breast radiologists review images as the reference standard. In the first stage an expert radiologist is on site for comparison and safety monitoring, and if safety is confirmed the second stage proceeds without an on-site expert with remote radiologist review. Women with positive ultrasound findings or predefined alarming symptoms are referred for further follow-up and diagnostic work-up.

Who should consider this trial

Good fit: Ideal candidates are women aged 30 or older without breast symptoms for screening or women aged 18 or older with breast symptoms who can understand the study information and travel to sites in Arba Minch and the Gamo Zone.

Not a fit: Individuals who cannot comprehend the study information due to language barriers or cognitive impairment are excluded and will not be able to participate or benefit.

Why it matters

Potential benefit: If successful, this approach could speed detection and referral of suspicious breast findings and expand access to effective triage in low-resource communities.

How similar studies have performed: Prior pilot projects have shown that AI-assisted handheld breast ultrasound can help non-experts identify suspicious findings in low-resource settings, but larger confirmatory trials remain limited.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Asymptomatic women from the age of 30 with no upper age limit
* Symptomatic women 18 years or older.

Exclusion Criteria:

* Individuals unable to comprehend the study information due to language barriers or cognitive impairments.

Where this trial is running

Arba Minch, Gamo Zone

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 CancerScreeningLow- and middle-income countriesGlobal healthArtificial intelligenceUltrasoundPoint-of-care ultrasoundclinical breast exam
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.