Evaluating coronary artery plaque using advanced imaging techniques
Official title: Risk Evaluation by Coronary Imaging and Artificial Intelligence-Based Functional Analyzing Techniques: Integrated Plaque Analysis by Coronary CT Angiography and Intracoronary Imaging.
Run by Ruijin Hospital · NCT06793774 · Data updated 2026-11-12
This study is testing new imaging techniques to better understand coronary artery plaque in patients with heart conditions and see if these methods can help predict serious heart problems in the future.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 300 (estimated) |
| Sponsor | Ruijin Hospital Academic / other |
| Locations | 1 site (Shanghai, Shanghai Municipality) |
| Status | Recruiting |
| Started | July 1, 2024 |
| Main results expected | December 31, 2025 |
| Study ends | December 31, 2027 |
| Registry record updated | January 27, 2025 |
| Trial ID | NCT06793774 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include adults aged 18 and older diagnosed with chronic coronary syndrome or non-ST-segment elevation acute coronary syndrome who have specific coronary artery lesions.
✕Probably not a fit
Patients who have undergone recent coronary interventions or have severe comorbidities may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to analyze coronary artery plaque characteristics and local hemodynamic parameters in patients with chronic coronary syndrome or non-ST-segment elevation acute coronary syndrome. It utilizes multimodality imaging, including noninvasive coronary CT angiography and intracoronary imaging techniques like intravascular ultrasound and optical coherence tomography. The study seeks to enhance plaque analysis accuracy by integrating these imaging modalities and developing a new high-risk plaque model based on the findings. Patients will be followed for two years to assess the model's effectiveness in predicting major adverse cardiovascular events.
Why it matters
Potential benefit: If successful, this study could lead to improved risk stratification and management of patients with coronary artery disease.
How similar studies have gone: While multimodality imaging approaches have been explored, this specific integration of techniques for high-risk plaque modeling is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥ 18 years * Patients with CCS or NSTE-ACS * Receive CCTA scan, with marginal lesions (DS between 40%-69%) or obstructive lesions (DS ≥70% or CT-FFR \<0.8) in major coronary arteries * Receive invasive coronary angiography and intracoronary imaging examination, including IVUS, OCT, NIRS, within 1 month after CCTA Exclusion Criteria: * Unsuitable for CCTA (such as severe renal impairment, uncontrolled thyroid condition, allergic to iodine, etc.) * Receive percutaneous coronary intervention (PCI) within 6 months * Prior history of myocardial infarction or heart failure * Prior history of coronary artery bypass graft (CABG) * Abnormal liver function (serum alanine aminotransferase \[ALT\] level exceeding 3 times the upper limit of normal) or abnormal kidney function (eGFR ≤30%) * Familial hypercholesterolemia * Estimated survival ≤ 1 year * Malignant tumor * Pregnant or lactation, or have the intention to give birth within one year * Poor compliance, unable to follow-up
Where it's running
-
Ruijin Hospital, Shanghai Jiaotong University School of Medicine
Shanghai, Shanghai Municipality, China Recruiting
Study contacts
- Study coordinator: Xiaoqun Wang, M.D., Ph.D.
- Email: xiaoqun_wang@hotmail.com
- Phone: +86 21 64370045
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.