AI Blind-Sweep Ultrasound for Antenatal Screening by Non-Specialist Health Workers in Rural DR Congo

Diagnostic Accuracy and Implementation Feasibility of AI-Assisted Blind Ultrasound Sweep (SPAQ E-con AI) for Antenatal Screening by Non-Specialist Health Workers in Rural Democratic Republic of the Congo

FS2 evaluates the diagnostic accuracy and implementation feasibility of an AI-assisted blind-sweep obstetric ultrasound (SPAQ E-con AI), operated by trained non-specialist health workers, for antenatal screening in rural Democratic Republic of the Congo. Primary outcomes are gestational age mean absolute error (Trimester 2 and Trimester 3) with 95% confidence intervals and AI confidence calibration. The reference standard is manual measurement by a reference reader (early ultrasound first; manual BPD if unavailable; last menstrual period is not used). Target enrollment is approximately 1,430 (IRB-approved ceiling 3,000), with early termination permitted upon achievement of pre-specified analysis-plan thresholds. The study is a multi-center prospective Hybrid Type 1 Effectiveness-Implementation design and includes a pre-specified adaptive model-update (Batch 2 cut) plan following FDA PCCP and STARD-AI guidance.

Inclusion Criteria:

• Pregnant women
• Identified at a participating facility routine ANC visit or RECO village outreach within the Kenge health zone catchment
• Informed consent obtained (16-17 years with parent/guardian consent)

Exclusion Criteria:

• Emergency presentation
• Multiple pregnancy
• Duplicate re-registration of an already-enrolled woman
• Lacking capacity to consent
• Planned relocation outside Kwango province during the study period
• Refusal of consent