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

ConditionPlacenta Accreta Spectrum
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexFemale
Age18-45
SponsorFANG HE

About this trial

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.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

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;

Disqualifiers

Failure to provide written informed consent;

Presence of severe complications that precluded continuation of pregnancy;

Inability to comply with study procedures for other reasons.

Trial population

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.

Trial design

Design model

Other

Time perspective

Prospective

Treatments tested in this trial

  • 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.

Treatment groups

No treatment groups listed

Trial outcomes

Primary outcomes

1

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

Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) of the model.

Time frame
At delivery (following confirmation of PAS status by surgical and/or pathological findings)

Secondary outcomes

1

Clinical Feasibility of the Standardized Ultrasound Video Recording Method

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

Time frame
At enrollment during the ultrasound examination
2

Consistency and Efficiency Between the AI Model and Physician Diagnosis

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).

Time frame
At enrollment during the ultrasound examination
3

Safety of the AI Model

False Negative Rate: Proportion of missed PAS-positive patients and the impact on patient outcomes .

Time frame
At delivery, when PAS status and maternal outcomes are assessed

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

FANG HE

Lead sponsor

The Third Affiliated Hospital of Guangzhou Medical University

Sponsor institution

Source ClinicalTrials.gov
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