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Diagnostic Trial of a Vision Transformer-Based Ultrasound AI Model for Placenta Accreta Spectrum

8. juni 2026 oppdatert av: FANG HE

Diagnostic Trial of Vision Transformer-Based End-to-End Ultrasound Artificial Intelligence Model for Assisting in the Diagnosis of Placenta Accreta Spectrum Disorders: An Investigator-Initiated Prospective Clinical Study

This study develops an end-to-end Vision Transformer (ViT)-based artificial intelligence system for ultrasound-based diagnosis of placenta accreta spectrum (PAS), aiming to improve the accuracy and efficiency of prenatal screening using standardized ultrasound video inputs.

Studieoversikt

Status

Rekruttering

Forhold

Placenta Accreta Spectrum

Intervensjon / Behandling

Diagnostisk test: Vision Transformer-Based End-to-End Ultrasound Artificial Intelligence Model

Detaljert beskrivelse

Placenta accreta spectrum (PAS) is a life-threatening obstetric disorder involving abnormal placental invasion into the uterine wall, which is associated with severe maternal and neonatal complications. Despite advances in imaging, prenatal diagnosis remains challenging due to variability in ultrasound interpretation and reliance on operator expertise.

This study will establish a standardized ultrasound video acquisition protocol and develop a deep learning-based model using Vision Transformer (ViT) architecture to process dynamic ultrasound sequences. The model will be trained using clinically confirmed postpartum outcomes as reference labels.

The diagnostic performance of the system will be systematically evaluated, with the goal of improving consistency in interpretation and supporting more efficient clinical decision-making in prenatal PAS screening.

Studietype

Observasjonsmessig

Registrering (Antatt)

561

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

Navn: Fang He, M.D, PhD
Telefonnummer: +86 13724831279
E-post: Gzhefang@gzhmu.edu.cn

Studiesteder

Kina
- Guangdong
  - Guangzhou, Guangdong, Kina, 510150
    - Rekruttering
    - The Third Affiliated Hospital, Guangzhou Medical University
    - Ta kontakt med:
      
      Fang He, MD, PhD
      
      Telefonnummer: +86 13724831279
      
      E-post: Gzhefang@gzhmu.edu.cn

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

Voksen

Tar imot friske frivillige

Nei

Prøvetakingsmetode

Ikke-sannsynlighetsprøve

Studiepopulasjon

Pregnant women aged 18-45 years; Gestational age between 24 and 34 weeks; Pregnant women with a history of placenta previa or with an anterior placenta.

Beskrivelse

Inclusion criteria:

Pregnant women aged between 18 and 45 years;
Gestational age between 24 and 34 weeks;
Pregnant women with a history of placenta previa;
Pregnant women with an anterior placenta;
Willingness to participate in the study and provision of written informed consent.

Exclusion criteria:

Failure to provide written informed consent;
Presence of severe complications that precluded continuation of pregnancy;
Inability to comply with study procedures for other reasons.

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

Hva måler studien?

Primære resultatmål

Resultatmål	Tiltaksbeskrivelse	Tidsramme
Diagnostic performance of the end-to-end Vision Transformer (ViT)-based ultrasound AI model for placenta accreta spectrum (PAS) Tidsramme: At delivery (following confirmation of PAS status by surgical and/or pathological findings)	Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) of the model.	At delivery (following confirmation of PAS status by surgical and/or pathological findings)

Sekundære resultatmål

Resultatmål	Tiltaksbeskrivelse	Tidsramme
Clinical Feasibility of the Standardized Ultrasound Video Recording Method Tidsramme: At enrollment during the ultrasound examination	Completion Rate (Proportion of patients who successfully complete the standardized recording) and time consumption (Mean recording time)	At enrollment during the ultrasound examination
Consistency and Efficiency Between the AI Model and Physician Diagnosis Tidsramme: At enrollment during the ultrasound examination	Diagnostic Consistency: Kappa coefficient used to evaluate the consistency between the AI model's diagnoses and those of experienced ultrasound physicians (Kappa > 0.75 indicates good agreement).	At enrollment during the ultrasound examination
Safety of the AI Model Tidsramme: At delivery, when PAS status and maternal outcomes are assessed	False Negative Rate: Proportion of missed PAS-positive patients and the impact on patient outcomes .	At delivery, when PAS status and maternal outcomes are assessed

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

FANG HE

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Faktiske)

1. september 2025

Primær fullføring (Antatt)

1. september 2027

Studiet fullført (Antatt)

31. desember 2027

Datoer for studieregistrering

Først innsendt

2. juni 2026

Først innsendt som oppfylte QC-kriteriene

8. juni 2026

Først lagt ut (Faktiske)

11. juni 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)