To assess the feasibility, safety, and clinical performance of community-based breast cancer screening incorporating clinical breast exam and short-termed trained examiners performing AI-supported breast POCUS for triage in limited-resource settings.
Following awareness campaign, asymptomatic and symptomatic women are invited to breast cancer screening. The screening intervention consists initially of clinical breast exam (CBE). Those that are positive at CBE or that present with symptoms are further examined with targeted artificial intelligence (AI)-supported breast point-of-care ultrasound (POCUS) on the complaint site. The AI-supported POCUS is performed by clinical nurses or clinical officers that have undergone a short training program and certification process in POCUS examination. In the first stage of the study, the same women will also be examined by an expert on site (breast radiologist). If clinical safety can be determined, the second stage of the study will start in which expert radiologist will not be on site. Ultrasound images will be assessed by breast radiologists that will serve as reference standard (on site in stage 1 and remotely in stage 2). Women positive at POCUS triage (positive ultrasound finding or with predefined alarming clinical symptoms) will be referred to further follow up.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SCREENING
Masking
NONE
Enrollment
4,800
AI-supported POCUS for triage
Arba Minch University and health care facilities and markets in the Gamo Zone
Arba Minch, Gamo Zone, Ethiopia
RECRUITINGSensitivity
The primary endpoint is sensitivity, defined as the proportion of diseased women correctly classified as positive by non-experts using AI-supported POCUS. Expert breast radiologists will be used as reference standard
Time frame: Estimated 2 months (from enrollment until sufficient number of positive participants according to expert assessment)
Specificity
Proportion of non-diseased participants correctly classified as negative
Time frame: 2 months
Positive Predictive Value
Proportion of diseased participants of those referred for further workup
Time frame: 2 months
Negative Predictive Value
Proportion of true negatives among all negative results.
Time frame: 2 months
Cancer Detection Rate
Proportion of women with detected cancer among all screened women
Time frame: 2 months
Recall Rate
Proportion of women triaged to further work up
Time frame: 2 months
False Positive Rate
Proportion of participants triaged for work up with no detected cancer among all screened participants.
Time frame: 2 months
Receiver Operating Characteristic and Area Under the Curve
Based on the AI-generated probability score (0-1), using standard ROC analysis
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Time frame: 2 months
Optimal threshold analysis
Sensitivity and specificity at the point minimizing distance to (0,1) on the ROC curve.
Time frame: 2 months
Cancer characterstics
Distribution of cancer stage and histological type among detected cancers.
Time frame: 6 months
Breast cancer in stage I-II
Proportion of breast cancer in stage I-II compared to historical standard-of-care data (2021-2025).
Time frame: 12 months
WHO Global Breast Cancer Initiative key performance indicators
Proportion of participants with cancer in relation to the WHO Global Breast Cancer Initiative key performance indicators ( ≥60% of breast cancers diagnosed at stage I-II, ≤60 days from first presentation to diagnosis ≥80% completion of recommended treatment).
Time frame: 12 months
Usability and Acceptability
Reported usability and acceptability of the AI-supported POCUS system: qualitative measure based on questionnaires (standard usability scale 1-5 and proportion of technical issues (y/n)).
Time frame: 2 months