AI Blind-Sweep Ultrasound for Antenatal Screening by Non-Specialist Health Workers in Rural DR Congo (FS2)

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). Planned enrollment is approximately 1,380: Batch 1 (closed, 80 enrolled) and Batch 2 (approximately 1,300), within an IRB-approved ceiling of 3,000. Early termination is 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.

Study Overview

• Status: Recruiting
• Conditions: Maternal Health; Diagnostic Imaging; Antenatal Care; Gestational Age; Placenta Praevia
• Intervention / Treatment: Diagnostic test: SPAQ E-con AI blind-sweep ultrasound

Detailed Description

Study conduct is organised in Batches. Batch 1 (Centre de Sante CBCO, Kenge health zone, Kwango province) enrolled 80 participants, of whom 78 had complete datasets, and is closed. Batch 2 is planned at approximately 1,300 participants. The confirmatory analysis cut is approximately 130 to 160 cases acquired with a model frozen before collection, comprising a core set of 80 to 100, an early-gestation enrichment of 25 to 30, and an upper-gestational-age enrichment of 25 to 30. Enrolment may stop early once the pre-specified confidence-interval criteria for the two primary gestational-age outcomes are met. The registered enrolment ceiling of 3,000 is unchanged.

Sites are facilities of the Kenge health zone, Kwango province, within the perimeter already approved in the protocol (up to 6 facilities plus 2 to 5 village outreach sites).

Eligibility follows the protocol: pregnant women aged 18 years or older. Multiple pregnancies are eligible.

Two sub-cohorts address the bounds of the gestational-age range. The early sub-cohort (crown-rump length 7 to 84 mm, approximately under 14 weeks) draws on the same source population as Cohort B-2 and is recruited through community health worker (RECO) village outreach and neighbouring health facilities; it is reported descriptively. The upper-bound sub-cohort (35 weeks or more) is a separate validation subset, recruited in parallel and analysed separately; sensitivity and specificity are reported, and positive and negative predictive values are not reported because prevalence in this subset is artificial.

The registered Trimester 3 estimation window (28 to 36 weeks) is unchanged. In Batch 2, point estimates are reported for 28 to 34 weeks, and 35 to 36 weeks is handled as "to be confirmed / refer". This is an operational reporting restriction, not a change to the registered window.

The AI model is identified and frozen before each Batch and recorded in a model and application version registry under a pre-determined change control plan. Results are reported by frozen version. AI inference is not used for clinical decision-making.

• Study Type: Observational
• Enrollment (Estimated): 3000

Contacts and Locations

• Study Contact: Name: Kuniyuki Furuta; Phone Number: +818099740409; Email: furuta@soik.co.jp

Study Locations

• Democratic Republic of the Congo
  • Kwango
    • Kenge, Kwango, Democratic Republic of the Congo
      • Recruiting
      • Centre de Sante CBCO
      • Contact: Henoch Bulu; Phone Number: +243812268392; Email: drhenochbulu@gmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Pregnant women attending routine antenatal care at participating facilities or identified through community health worker (RECO) village outreach in the Kenge health zone, Kwango province, DRC.

Description

Inclusion Criteria:

• Pregnant women aged 18 years or older
• Identified at a participating facility routine ANC visit or RECO village outreach within the Kenge health zone catchment
• Written informed consent obtained

Exclusion Criteria:

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

Study Plan

How is the study designed?

Number of groups / cohorts

5

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Cohort A; Natural enrollment / Description: Consecutive ANC attendees (natural prevalence)	Diagnostic test: SPAQ E-con AI blind-sweep ultrasound; Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training. The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
Cohort B-1 Placenta/malpresentation enriched; Enriched validation subset for placenta praevia and fetal malpresentation	Diagnostic test: SPAQ E-con AI blind-sweep ultrasound; Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training. The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
Cohort B-2 - Trimester 1 (CRL/GS) enriched; Enriched trimester 1 cases for CRL/GS gestational age models	Diagnostic test: SPAQ E-con AI blind-sweep ultrasound; Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training. The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
Cohort B-3 - Early gestation (CRL 7-84 mm) enriched; Early-gestation enrichment sub-cohort: crown-rump length 7-84 mm, approximately under 14 weeks of gestation. Drawn from the same source population as Cohort B-2 and recruited through community health worker (RECO) village outreach and neighbouring health facilities. Reported descriptively.	Diagnostic test: SPAQ E-con AI blind-sweep ultrasound; Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training. The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
Cohort B-4 - Upper gestational-age bound (>=35 weeks) validation subset; Validation subset at the upper bound of the gestational-age range (35 weeks of gestation or more), recruited in parallel with the main cohort and analysed separately. Sensitivity and specificity are reported. Positive and negative predictive values are not reported, because prevalence in this subset is artificial.	Diagnostic test: SPAQ E-con AI blind-sweep ultrasound; Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training. The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gestational age mean absolute error (MAE), Trimester 2 (14-27 weeks)	MAE in days vs reference standard, with 95% CI; target MAE ≤7 days and upper 95% CI ≤10 days	Through study completion, up to 12 months
Gestational age mean absolute error (MAE), Trimester 3 (28-36 weeks)	MAE in days vs reference standard, with 95% CI; target MAE ≤10 days and upper 95% CI ≤14 days	Through study completion, up to 12 months
AI confidence calibration - Expected Calibration Error (ECE)	Expected Calibration Error from the reliability diagram of AI confidence versus reference-standard agreement; target <=0.05	At Batch 1 closure, up to 8 weeks
AI confidence calibration - Brier score	Brier score of AI confidence versus reference-standard agreement; target <=0.20	At Batch 1 closure, up to 8 weeks

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Trimester 1 gestational age MAE (CRL and GS models)	Integrated Cohort A T1 + Cohort B-2, N=30; CRL model MAE ≤5 days or GS model MAE ≤7 days	Through study completion, up to 12 months
Placenta praevia and fetal malpresentation sensitivity and specificity	Observed sensitivity/specificity with 95% CI (Clopper-Pearson) on enriched validation subset (Cohort B-1, target N=20-25); reported as observed values	Through study completion, up to 12 months
Inter-rater reliability of gestational age - Intraclass Correlation Coefficient (ICC)	ICC(2,1) between two independent readers for gestational age in days	During the inter-rater assessment window, up to 1 week
Inter-rater reliability of placenta praevia classification - Cohen's kappa	Cohen's kappa for placenta praevia (yes/no) between two independent readers	During the inter-rater assessment window, up to 1 week
Inter-rater reliability of fetal presentation classification - weighted kappa	Linear weighted kappa for fetal presentation category between two independent readers	During the inter-rater assessment window, up to 1 week
Acceptability - Acceptability of Intervention Measure (AIM) score	Mean AIM score (4-item, 5-point Likert) among health workers	Through study completion, up to 12 months
Feasibility - ultrasound throughput (scans per device per day)	Number of scans completed per device per day; target >=15	Through study completion, up to 12 months
Fidelity - protocol adherence rate (5-item checklist)	Percentage adherence on a 5-item fidelity checklist; target >=80%	Through study completion, up to 12 months
Penetration - proportion of eligible women screened	Percentage of eligible women in the catchment screened with AI ultrasound	Through study completion, up to 12 months
Sustainability - intention to continue use	Percentage of staff reporting intention to continue use at the end-of-study interview	At study completion, up to 12 months

Collaborators and Investigators

• Sponsor: SOIK Corporation Sarl
• Investigators: Principal Investigator: Kuniyuki Furuta, SOIK Corporation

Study record dates

Study Major Dates

• Study Start (Actual): June 19, 2026
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): June 13, 2027

Study Registration Dates

• First Submitted: June 18, 2026
• First Submitted That Met QC Criteria: June 24, 2026
• First Posted (Actual): July 1, 2026

Study Record Updates

• Last Update Posted (Actual): September 15, 2026
• Last Update Submitted That Met QC Criteria: September 10, 2026
• Last Verified: September 1, 2026

More Information

Terms related to this study

• Keywords: artificial intelligence; DRC; point-of-care ultrasound; task-shifting; blind sweep ultrasound
• Additional Relevant MeSH Terms: Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Obstetric Labor Complications; Pregnancy Complications; Placenta Diseases; Placenta Previa
• Other Study ID Numbers: SOIK-FS2-2026

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No