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An AI Fusion Model for Vulnerable Plaque Driven by Multimodal Ultrasound: A Prospective Radiomics Clinical Study

An AI Fusion Model for Vulnerable Plaque Driven by Multimodal Ultrasound: A Prospective Radiomics Clinical Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600125820
Enrollment
Unknown
Registered
2026-06-01
Start date
2026-06-01
Completion date
Unknown
Last updated
2026-06-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Vulnerable plaque (VP) rupture

Interventions

Gold Standard:1. Postoperative histopathological diagnosis of carotid endarterectomy (preferred), classifying the target plaques according to the modified AHA criteria into VP and non-VP
2. For those who cannot undergo surgery, the HRMRI interpretation results are used as the reference standard.
Index test:An AI fusion diagnostic model constructed by combining multimodal ultrasound (gray-scale ultrasound, ultrasound viscoelasticity technology, high-frame-rate ultrasound contrast imaging) with

Sponsors

The First Affiliated Hospital of Fujian Medical University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Using the First Affiliated Hospital of Fujian Medical University (Chating/Binhai/Aoti Campus) as the research center, prospectively include patients scheduled for carotid endarterectomy (CEA) or undergoing HRMRI examination.

Exclusion criteria

Exclusion criteria: 1. Age <18 years; 2. Carotid occlusion or stenosis caused by other conditions (e.g., arterial dissection, arteritis); 3. Severe plaque calcification with acoustic shadowing precluding ultrasound assessment; 4. Severe multiple organ failure; 5. Emergency surgery or incomplete imaging/pathological data.

Design outcomes

Primary

MeasureTime frame
The area under the curve;

Secondary

MeasureTime frame
Sensitivity;Specificity;Decision analysis curve;

Countries

China

Contacts

Public ContactLei Yan

The First Affiliated Hospital of Fujian Medical University

yanlei20082336@163.com+86 137 0591 0071

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026