The AIPLAQUE Study: An Artificial Intelligence-based Prospective Study to Analyze PLAQUE Using CCTA

NCT ID: NCT05750082

Last Updated: 2023-04-19

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 100 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-04-12
• Study Completion Date: 2023-12-01

Brief Summary

This trial is a single-center, prospective, observational clinical study. All patients who have at least one coronary artery stenosis of 30%-90% in diameter ≥ 2mm confirmed by CCTA, and who are scheduled to undergo clinically indicated invasive coronary angiography (ICA) and optical coherence tomography (OCT) evaluation and/or treatment will be eligible for enrollment. We proposed a novel approach that integrates CCTA, ICA and OCT images to automatically measure plaque characterization and calculate CT-FFR using computational fluid dynamics (CFD) simulation and artificial intelligence deep learning.

Detailed Description

Acute coronary syndrome (ACS) is one of the leading causes of coronary artery disease (CAD) death worldwide. Vulnerable plaque rupture is a primary underlying cause of luminal thrombosis responsible for provoking ACS. Therefore, identifying high-risk plaques before ACS occurs has been a major research goal and requires further clinical perspectives. Coronary computed tomography angiography (CCTA) is a comprehensive, non-invasive and cost-effective imaging assessment approach, which can provide the ability to identify the characteristics and morphology of high-risk atherosclerotic plaques associated with ACS. Optical coherence tomography (OCT) is a new, light-based, intravascular imaging technique that provides high-resolution, cross-sectional images of coronary artery anatomy. Due to its superior resolution, OCT is more accurate in measuring the sites of plaque vulnerability, distinguishing the differences in its composition, informing about the anatomic severity of epicardial stenoses, and also provides input for computational models to assess functional severity.

The objectives of the study are: (1) To construct an artificial intelligence model for identifying coronary plaque components on CTA images using OCT as the reference standard. (2) To conduct fluid mechanics simulation including blood vessel wall and plaque by using geometric and physiological models of blood vessels and plaques, and to provide more accurate functional parameters (CT-FFR).

The enrollment criteria will be (1) Patients who presented with stable angina pectoris or acute coronary syndrome; (2) patients who meet the indications for coronary CT angiography, percutaneous coronary angiography and intravascular imaging; (3) Among those patients, patients who have at least one coronary artery stenosis of 30% - 90% in diameter ≥ 2mm confirmed by CCTA.

Data collected will include CCTA, full angiographic, and OCT images. Combined with CTA/ICA/OCT images of multiple modalities, this study will develop a novel images analysis technology to automatically extract vascular lumen, plaque characterization, fluid-solid mechanical properties, and myocardial ischemia conditions using computational fluid dynamics (CFD) simulation and artificial intelligence deep learning.

Conditions

Coronary Artery Disease Acute Coronary Syndrome Myocardial Ischemia Plaque Characterization

Study Design

• Observational Model Type: CASE_ONLY
• Study Time Perspective: PROSPECTIVE

Interventions

CCTA CT-FR CAG OCT

Per the protocol, patients will have a CCTA (coronary computed tomography angiography), CT-FFR (fractional flow reserve derived from CTA), ICA (invasive coronary angiography), OCT (optical coherence tomography).

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

1. Age ≥18 years and able to understand the purpose of the study and sign the informed consent;

2. Patients who presented with stable angina pectoris or acute coronary syndrome;

3. Patients who meet the indications for coronary CT angiography, percutaneous coronary angiography and intravascular imaging;

4. Among those patients, patients who have at least one coronary artery stenosis of 30% - 90% in diameter ≥ 2mm confirmed by CCTA.

Exclusion Criteria

1. Known pregnancy or breastfeeding at the time of enrollment;

2. Hemodynamic instability;

3. Allergy to contrast media or aspirin, adenosine etc.;

4. History of stroke or transient ischemic attack (TIA) within 12 months before surgery;

5. Known renal insufficiency (e.g. serum creatinine >2.0mg/dL, or creatinine clearance ≤30 mL/min), or need for dialysis, or acute kidney failure (as per physician judgment);

6. Leukopenia (WBC<4.0*10*9/L), thrombocytopenia (PLT<100*10*9/L) or thrombocytopenia (PLT>300*10*9/L);

7. Subjects who receiving oral or intravenous immunosuppressant therapy (other than inhaled steroids) or have an autoimmune disease (e.g., AIDS, SLE; except diabetes);

8. Any other factors that researchers consider not suitable for inclusion or completion of this study.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Harbin Medical University

OTHER

Sponsor Role: lead

Responsible Party

Yu Bo

Director of Department of Cardiology

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

The Second Affiliated Hospital of Harbin Medical University

Harbin, Heilongjiang, China

Site Status: RECRUITING

Countries

China

Central Contacts

Bo Yu

Role: CONTACT

yubodr@163.com

0451-86605180

Facility Contacts

Bo Yu, MD, PhD

Role: primary

yubodr@163.com

+86 451 8660 5180

MD, PhD

Role: backup

Other Identifiers

KY2021-003

Identifier Type: -

Identifier Source: org_study_id