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NCT Number: NCT07643090

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

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.

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Key information

Conditions

Placenta Accreta Spectrum Female Urogenital Diseases and Pregnancy Complications Obstetric Labor Complications Placenta Accreta Placenta Diseases Pregnancy Complications Urogenital Diseases

Age range

18 year–45 year

Sex eligibility

Female

Study type

Observational

Primary location

The Third Affiliated Hospital, Guangzhou Medical University

Guangzhou, Guangdong, 510150, China

Location status: Recruiting

Location contact

Fang He, MD, PhD

CONTACT

[email protected]

+86 13724831279

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Vision Transformer-Based End-to-End Ultrasound Artificial Intelligence Model

Diagnostic Test

An end-to-end ultrasound AI model based on the Vision Transformer (ViT) architecture was developed for the diagnosis of placenta accreta spectrum (PAS) using standardized ultrasound video inputs. Ultrasound Video Acquisition Protocol: With the patient in the supine position, the operator scanned the lower abdomen using a conventional grayscale probe. Video recording was performed in gray-scale mode for approximately 20-30 seconds, ensuring that the entire scanning region from the lower uterine segment to the uterine fundus was comprehensively captured.

Primary outcomes

  1. Diagnostic performance of the end-to-end Vision Transformer (ViT)-based ultrasound AI model for placenta accreta spectrum (PAS)

    Time frame: 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.

Secondary outcomes

  1. Clinical Feasibility of the Standardized Ultrasound Video Recording Method

    Time frame: At enrollment during the ultrasound examination

    Completion Rate (Proportion of patients who successfully complete the standardized recording) and time consumption (Mean recording time)

  2. Consistency and Efficiency Between the AI Model and Physician Diagnosis

    Time frame: 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).

  3. Safety of the AI Model

    Time frame: 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 .

Study contacts

Contact information is provided by the study sponsor or research team.

Fang He, M.D, PhD

CONTACT

[email protected]

+86 13724831279

Sponsors and collaborators

Lead sponsor

FANG HE

Other

Registry information

Official study title

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

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Jun 11, 2026
Registry last updated
Jun 11, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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