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Identifying Vulnerable CoronAry PLaqUes With Artificial IntElligence-assisted CT Angiography

NCT06025305 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2026-05-11

No results posted yet for this study

Summary

The goal of this observational study is to develop an automatic whole-process AI model to detect, quantify, and characterize plaques using coronary CT angiography in coronary artery disease patients. The main questions it aims to answer are:

1. Whether the AI model enables to detect and quantify coronary plaques compared with intravascular ultrasound or expert readers;
2. Whether the AI model enables to identify vulnerable plaques using intravascular ultrasound or optical coherence tomography as the reference standard.
3. Whether the AI model enables to predict future adverse cardiac events in a large cohort of 10,000 patients with non-obstructive CAD.
4. Whether the AI model enables to influnece downstream clincial decision-making.

Conditions

Interventions

DIAGNOSTIC_TEST

Intravascular imaging test

Coronary artery disease patients first underwent CCTA and then intravascular imaging test within 3 months.

DIAGNOSTIC_TEST

Coronary plaque assessment

Plaques on coronary CT angiography (CCTA) were quantified and characterized using the developed AI model.

Sponsors & Collaborators

  • Jinling Hospital, China

    lead OTHER

Principal Investigators

  • Longjiang Zhang, MD · Jinling Hospital, Medical School of Nanjing University, Nanjing,China

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-07-01
Primary Completion
2026-12-31
Completion
2027-12-31

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06025305 on ClinicalTrials.gov