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

Sponsor
Harbin Medical University (Other)
Overall Status
Recruiting
CT.gov ID
NCT05750082
Collaborator
(none)
100
1
22.6
4.4

Study Details

Study Description

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.

Condition or Disease Intervention/Treatment Phase
  • Device: CCTA CT-FR CAG OCT

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.

Study Design

Study Type:
Observational
Anticipated Enrollment :
100 participants
Observational Model:
Case-Only
Time Perspective:
Prospective
Official Title:
Automated Plaque Characterization and Functional Analysis of Coronary CTA Based on OCT Images Using Artificial Intelligence
Actual Study Start Date :
Apr 12, 2021
Anticipated Primary Completion Date :
Mar 1, 2023
Anticipated Study Completion Date :
Mar 1, 2023

Outcome Measures

Primary Outcome Measures

  1. By taking OCT results as the standard, evaluating the accuracy of automated plaque characterization and functional significance of coronary stenosis using CTA images computation. [Immediately after OCT scan]

    By taking OCT results as the standard, evaluating the accuracy of automated plaque characterization and functional significance of coronary stenosis using CTA images computation.

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years to 80 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
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<4.0109/L), thrombocytopenia (PLT<100109/L) or thrombocytopenia (PLT>300109/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.

Contacts and Locations

Locations

Site City State Country Postal Code
1 The Second Affiliated Hospital of Harbin Medical University Harbin Heilongjiang China 150086

Sponsors and Collaborators

  • Harbin Medical University

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Yu Bo, Director of Department of Cardiology, Harbin Medical University
ClinicalTrials.gov Identifier:
NCT05750082
Other Study ID Numbers:
  • KY2021-003
First Posted:
Mar 1, 2023
Last Update Posted:
Mar 1, 2023
Last Verified:
Feb 1, 2023
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Additional relevant MeSH terms:

Study Results

No Results Posted as of Mar 1, 2023