Cette page a été traduite automatiquement et l'exactitude de la traduction n'est pas garantie. Veuillez vous référer au version anglaise pour un texte source.

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

10 septembre 2026 mis à jour par: SOIK Corporation Sarl

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.

Aperçu de l'étude

Statut

Recrutement

Les conditions

Intervention / Traitement

Description détaillée

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.

Type d'étude

Observationnel

Inscription (Estimé)

3000

Contacts et emplacements

Cette section fournit les coordonnées de ceux qui mènent l'étude et des informations sur le lieu où cette étude est menée.

Coordonnées de l'étude

  • Nom: Kuniyuki Furuta
  • Numéro de téléphone: +818099740409
  • E-mail: furuta@soik.co.jp

Lieux d'étude

Critères de participation

Les chercheurs recherchent des personnes qui correspondent à une certaine description, appelée critères d'éligibilité. Certains exemples de ces critères sont l'état de santé général d'une personne ou des traitements antérieurs.

Critère d'éligibilité

Âges éligibles pour étudier

  • Adulte
  • Adulte plus âgé

Accepte les volontaires sains

Oui

Méthode d'échantillonnage

Échantillon non probabiliste

Population étudiée

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.

La 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

Plan d'étude

Cette section fournit des détails sur le plan d'étude, y compris la façon dont l'étude est conçue et ce que l'étude mesure.

Comment l'étude est-elle conçue ?

Détails de conception

Cohortes et interventions

Groupe / Cohorte
Intervention / Traitement
Cohort A
Natural enrollment / Description: Consecutive ANC attendees (natural prevalence)
Test diagnostique: 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
Test diagnostique: 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
Test diagnostique: 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.
Test diagnostique: 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.
Test diagnostique: 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.

Que mesure l'étude ?

Principaux critères de jugement

Mesure des résultats
Description de la mesure
Délai
Gestational age mean absolute error (MAE), Trimester 2 (14-27 weeks)
Délai: Through study completion, up to 12 months
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)
Délai: Through study completion, up to 12 months
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)
Délai: At Batch 1 closure, up to 8 weeks
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
Délai: At Batch 1 closure, up to 8 weeks
Brier score of AI confidence versus reference-standard agreement; target <=0.20
At Batch 1 closure, up to 8 weeks

Mesures de résultats secondaires

Mesure des résultats
Description de la mesure
Délai
Trimester 1 gestational age MAE (CRL and GS models)
Délai: Through study completion, up to 12 months
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
Délai: Through study completion, up to 12 months
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)
Délai: During the inter-rater assessment window, up to 1 week
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
Délai: During the inter-rater assessment window, up to 1 week
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
Délai: During the inter-rater assessment window, up to 1 week
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
Délai: Through study completion, up to 12 months
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)
Délai: Through study completion, up to 12 months
Number of scans completed per device per day; target >=15
Through study completion, up to 12 months
Fidelity - protocol adherence rate (5-item checklist)
Délai: Through study completion, up to 12 months
Percentage adherence on a 5-item fidelity checklist; target >=80%
Through study completion, up to 12 months
Penetration - proportion of eligible women screened
Délai: Through study completion, up to 12 months
Percentage of eligible women in the catchment screened with AI ultrasound
Through study completion, up to 12 months
Sustainability - intention to continue use
Délai: At study completion, up to 12 months
Percentage of staff reporting intention to continue use at the end-of-study interview
At study completion, up to 12 months

Collaborateurs et enquêteurs

C'est ici que vous trouverez les personnes et les organisations impliquées dans cette étude.

Parrainer

SOIK Corporation Sarl

Les enquêteurs

  • Chercheur principal: Kuniyuki Furuta, SOIK Corporation

Dates d'enregistrement des études

Ces dates suivent la progression des dossiers d'étude et des soumissions de résultats sommaires à ClinicalTrials.gov. Les dossiers d'étude et les résultats rapportés sont examinés par la Bibliothèque nationale de médecine (NLM) pour s'assurer qu'ils répondent à des normes de contrôle de qualité spécifiques avant d'être publiés sur le site Web public.

Dates principales de l'étude

Début de l'étude (Réel)

19 juin 2026

Achèvement primaire (Estimé)

31 décembre 2026

Achèvement de l'étude (Estimé)

13 juin 2027

Dates d'inscription aux études

Première soumission

18 juin 2026

Première soumission répondant aux critères de contrôle qualité

24 juin 2026

Première publication (Réel)

1 juillet 2026

Mises à jour des dossiers d'étude

Dernière mise à jour publiée (Réel)

15 septembre 2026

Dernière mise à jour soumise répondant aux critères de contrôle qualité

10 septembre 2026

Dernière vérification

1 septembre 2026

Plus d'information

Termes liés à cette étude

Mots clés

Termes MeSH pertinents supplémentaires

Autres numéros d'identification d'étude

  • SOIK-FS2-2026

Plan pour les données individuelles des participants (IPD)

Prévoyez-vous de partager les données individuelles des participants (DPI) ?

INDÉCIS

Informations sur les médicaments et les dispositifs, documents d'étude

Étudie un produit pharmaceutique réglementé par la FDA américaine

Non

Étudie un produit d'appareil réglementé par la FDA américaine

Non

Ces informations ont été extraites directement du site Web clinicaltrials.gov sans aucune modification. Si vous avez des demandes de modification, de suppression ou de mise à jour des détails de votre étude, veuillez contacter register@clinicaltrials.gov. Dès qu'un changement est mis en œuvre sur clinicaltrials.gov, il sera également mis à jour automatiquement sur notre site Web .

S'abonner