Risk Evaluation by COronary Imaging and Artificial intelliGence Based fuNctIonal analyZing tEchniques - III

Recruiting

• Conditions: Coronary Artery Disease; Coronary Atheroscleroses; Acute Coronary Syndromes (ACS)

• Registration Number: NCT06793774
• Lead Sponsor: Ruijin Hospital

Brief Summary

This is a single-center, prospective cohort study. This study is designed to accurately analyze coronary artery plaque characteristics and local hemodynamic parameters in patients diagnosed with chronic coronary syndrome (CCS) or non-ST-segment elevation acute coronary syndrome (NSTE-ACS), with marginal lesions or obstructive lesions in major coronary arteries by multimodality imaging including noninvasive coronary CT angiography (CCTA) and intracoronary imaging techniques, such as intravascular ultrasound (IVUS), optical coherence tomography (OCT), and near infrared spectroscopy (NIRS). The purpose of this study is to improve the accuracy and depth of plaque analysis by CCTA under the guidance of intracoronary imaging, therefore constructing a new CCTA-based high-risk plaque model.

Detailed Description

This is a single-center, prospective cohort study. This study is designed to accurately analyze coronary artery plaque characteristics and local hemodynamic parameters in patients diagnosed with chronic coronary syndrome (CCS) or non-ST-segment elevation acute coronary syndrome (NSTE-ACS), with marginal lesions (diameter stenosis \[DS\] between 40%-69%) or obstructive lesions (DS ≥70% or CT-FFR \<0.8) in major coronary arteries by multimodality imaging including noninvasive coronary CT angiography (CCTA) and intracoronary imaging techniques, such as intravascular ultrasound (IVUS), optical coherence tomography (OCT), and near infrared spectroscopy (NIRS). The congruity and incongruity between different imaging modalities will be evaluated.

The purpose of this study is to improve the accuracy and depth of plaque analysis by CCTA under the guidance of intracoronary imaging by co-registration, feature extraction, radiomic analysis and machine learning. Afterwards, a new CCTA-based high-risk plaque model will be constructed through the training process guided by intracoronary imaging and hemodynamic evaluation.

The cohort will be followed-up every 3 months for 2 years. Cross-validation will be performed to compare the new model with traditional CTA models in detecting high-risk plaques and predicting the occurrence of major adverse cardiovascular events (MACEs). All the patients with CCS or NSTE-ACS, who undergo CCTA to confirm the presence of marginal or obstructive coronary lesions, and the subsequent invasive coronary angiography and intracoronary imaging examination within 1 month after CCTA will be enrolled.

Study Timeline

• Study Start: 2024-07-01
• Status Verified: 2025-01
• Study First Submitted: 2025-01-21
• Study First Submitted QC: 2025-01-21
• Last Update Submitted: 2025-01-21
• Study First Posted: 2025-01-27
• Last Update Posted: 2025-01-27
• Primary Completion: 2025-12-31
• Study Completion: 2027-12-31

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 300

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

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Prediction performance of high-risk plaques by CCTA	2 Years	By using intracoronary imaging as the 'gold standard', the new CCTA model generated by machine learning will be compared with traditional CCTA models in the prediction performance of high-risk plaques (area under receiver operating characteristics curve, etc.)

Secondary Outcome Measures

Name	Time	Method
Major cardiovascular events (MACEs)	2 years	A composite endpoint of cardiovascular death, non-fatal myocardial infarction, and unplanned revascularization during follow-up. The prediction performance of MACEs by the new model and traditional CCTA models will be compared
Cardiovascular death	2 years	The occurrence of cardiovascular death during follow-up. The prediction performance of cardiovascular death by the new model and traditional CCTA models will be compared.
Myocardial infarction	2 years	The occurrence of myocardial infarction during follow-up. The prediction performance of myocardial infarction by the new model and traditional CCTA models will be compared.
Unplanned revascularization	2 years	The occurrence of unplanned revascularization during follow-up. The prediction performance of unplanned revascularization by the new model and traditional CCTA models will be compared.

Trial Locations

Locations (1)

Ruijin Hospital, Shanghai Jiaotong University School of Medicine; 🇨🇳 Shanghai, Shanghai, China