AI-POCUS for Maternal and Neonatal Health in Ethiopia

Sponsor
Tsinghua University
Study ID
NCT07171086
Phase
PHASE4
Status
Not Yet Recruiting

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Conditions

  • Fetal Growth Restriction
  • Pregnancy
  • Pregnancy Abnormal
  • Pregnancy Complications
  • Preterm Birth
  • Stillbirth and Fetal Death

Eligibility Criteria

Sex
FEMALE
Age
15 Years - 49 Years
Healthy Volunteers
Accepted

Interventions

  • AI-POCUS (BabyChecker, Delft Imaging) — DEVICE
    A portable AI-driven ultrasound system developed by Delft Imaging (Netherlands). The device integrates fetal position, amniotic fluid volume, and biparietal diameter measurements, with built-in diagnostic suggestions and risk alerts. Primary healthcare workers, after brief training, use it for antenatal screening, complication detection, and referral decision-making.
  • AI-POCUS (Edan, China) — DEVICE
    An AI-POCUS device developed by Edan (China), capable of analyzing blind ultrasound sweeps to extract fetal diagnostic parameters and assist in early risk identification. It supports clinical decision-making for antenatal care.

Study Details

Maternal and neonatal health remains one of the most pressing global health challenges, particularly in low- and middle-income countries (LMICs). Ethiopia continues to face a high burden, with maternal mortality estimated at 195 per 100,000 live births, neonatal mortality at 27 per 1,000 live births, and perinatal mortality rates ranging from 37‰ to 124‰ depending on the level of care. These outcomes remain substantially higher than the targets set under the United Nations Sustainable Development Goals (SDGs) for 2030. The World Health Organization (WHO) recommends that all pregnant women receive at least one ultrasound scan before 24 weeks of gestation, yet nearly two-thirds of women worldwide-especially in LMICs-lack access to this service. Barriers include high costs of ultrasound machines, limited technical expertise, and shortages of skilled sonographers in rural primary care. Artificial Intelligence-driven Point-of-Care Ultrasound (AI-POCUS) represents a promising innovation to expand prenatal imaging in resource-constrained settings by equipping frontline health workers with AI-supported diagnostic capabilities. This study, conducted under the Tsinghua University BRIGHT (Bringing Research to Impact for Global Health at Tsinghua) program, will evaluate the clinical effectiveness, feasibility, cost, and scalability of AI-POCUS in rural Ethiopia. A three-arm cluster randomized controlled trial will compare two AI-enabled ultrasound technologies-BabyChecker (Netherlands) and a China-developed AI-POCUS device-against standard antenatal care without ultrasound. Findings will generate robust clinical and policy-relevant evidence to guide the sustainable implementation of AI-enabled maternal health interventions in sub-Saharan Africa.

Key Dates

First listed
Sep 12, 2025
Start date
Sep 30, 2025
Status verified
Sep 2025
Primary completion
Mar 31, 2026
Completion
Aug 31, 2026

Study Design

Enrollment
1,059 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SCREENING

Arms

  • No Intervention: Standard Care Control
    Participants in this arm will receive routine antenatal care (ANC) according to Ethiopian national guidelines, without the use of AI-POCUS devices. All examinations, screenings, and referrals will be conducted through standard clinical practice. This group serves as the baseline comparator for evaluating the added impact of AI-POCUS technology.
  • Experimental: BabyChecker (Delft Imaging, Netherlands)
    Health centers in this arm will be equipped with the BabyChecker system developed by Delft Imaging (Netherlands). The portable device integrates fetal position, amniotic fluid volume, and biparietal diameter measurements, and provides diagnostic suggestions and risk alerts. After brief training, primary healthcare workers will independently perform antenatal examinations, screen for obstetric complications, and make referral decisions.
  • Experimental: AI-POCUS (Edan, China)
    This arm will use the AI-POCUS device developed by Edan (China), designed to analyze blind ultrasound sweeps and automatically extract fetal diagnostic parameters. The system supports the early detection of maternal and fetal risks and assists in clinical decision-making.

Primary Outcome Measure

Maternal Mortality Ratio [ Time Frame: Baseline through 42 days postpartum ]

Central Contacts

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