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| ID | Type | Description | Link |
|---|---|---|---|
| 2025-03460 | Other Grant/Funding Number | The Swedish Research Council |
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| Name | Class |
|---|---|
| Arba Minch University | OTHER |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| CBE follow by targeted AI-supported POCUS | Experimental | In the first stage, an expert breast radiologist will be involved on site and in the second stage, remotely. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI | Diagnostic Test | AI-supported POCUS for triage |
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| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity | 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 | Estimated 2 months (from enrollment until sufficient number of positive participants according to expert assessment) |
| Measure | Description | Time Frame |
|---|---|---|
| Specificity | Proportion of non-diseased participants correctly classified as negative | 2 months |
| Positive Predictive Value | Proportion of diseased participants of those referred for further workup |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Kristina KL Lång, MD PhD | Contact | +4640338880 | kristina.lang@med.lu.se | |
| Abayneh ATT Tunje Tanga, PhD | Contact | abaynehtun@gmail.com |
| Name | Affiliation | Role |
|---|---|---|
| Kristina KL Lån g, MD PhD | Lund University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Arba Minch University and health care facilities and markets in the Gamo Zone | Recruiting | Arba Minch | Gamo Zone | Ethiopia |
Due to data privacy. Could be considered following regulatory approvals.
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| ID | Term |
|---|---|
| D001943 | Breast Neoplasms |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
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The study will follow Simon's optimal two-stage phase II design (Simon, 1989) with type I error α = 0.05 and power 80% (β = 0.20). The primary endpoint is sensitivity, defined as the proportion of diseased participants correctly classified as positive by non-experts using AI-supported POCUS, with expert breast radiologists as the reference standard. Null hypothesis (H₀): Sensitivity ≤ 0.80, alternative hypothesis (H₁): Sensitivity ≥ 0.90. A sensitivity of 80% is considered the minimum acceptable level for clinical utility, while 90% represents the target performance based on prior pilot data and expert consensus. In stage 1, enrollment continues until 28 diseased cases are confirmed; if ≤23 are correctly classified, the study stops for futility. Otherwise, enrollment proceeds to 97 diseased cases. The null hypothesis will be rejected if ≥83 cases are correctly classified. This design yields a significance level of 0.0475 and power of 80.2%.
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The result of AI-supported POCUS performed by nurse/clinical officer will be masked for the expert radiologist in the first stage of the study
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| 2 months |
| Negative Predictive Value | Proportion of true negatives among all negative results. | 2 months |
| Cancer Detection Rate | Proportion of women with detected cancer among all screened women | 2 months |
| Recall Rate | Proportion of women triaged to further work up | 2 months |
| False Positive Rate | Proportion of participants triaged for work up with no detected cancer among all screened participants. | 2 months |
| Receiver Operating Characteristic and Area Under the Curve | Based on the AI-generated probability score (0-1), using standard ROC analysis | 2 months |
| Optimal threshold analysis | Sensitivity and specificity at the point minimizing distance to (0,1) on the ROC curve. | 2 months |
| Cancer characterstics | Distribution of cancer stage and histological type among detected cancers. | 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). | 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). | 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)). | 2 months |
| D017437 |
| Skin and Connective Tissue Diseases |