Identifying Vulnerable CoronAry PLaqUes With Artificial IntElligence-assisted CT Angiography

NCT06025305 | Enrolling By Invitation DMC

• 1 other identifier: 2023DZKY-058-01
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

Brief 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. 1.Whether the AI model enables to detect and quantify coronary plaques compared with intravascular ultrasound or expert readers;
2. 2.Whether the AI model enables to identify vulnerable plaques using intravascular ultrasound or optical coherence tomography as the reference standard.
3. 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. 4.Whether the AI model enables to influnece downstream clincial decision-making.

Conditions

Coronary Artery Disease; Plaque, Atherosclerotic

Keywords

artificial intelligence; coronary CT angiography; vulnerable plaque

Outcome Measures

Primary Outcomes (1)

• Sensitivity and specificity of AI-assisted coronary CT angiography on identifying vulnerable plaques compared to intravascular imaging

  1 day

Secondary Outcomes (3)

• Overall coronary plaque detection rate using intravascular ultrasound as reference standard

  1 day

• Total plaque volume

  1 day

• Changes in medical management following the addition of the AI model compared with routine CCTA results alone.

  90 days

Study Arms (3)

Patients who underwent coronary CT angiography and intravascular ultrasound within 3 months

Diagnostic Test: Intravascular imaging test

Patients who underwent coronary CT angiography and optical coherence tomography within 3 months

Diagnostic Test: Intravascular imaging test

Patients who underwent coronary CT angiography because of suspected or known coronary artery disease

Diagnostic Test: Coronary plaque assessment

Interventions

Intravascular imaging test DIAGNOSTIC_TEST

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

Patients who underwent coronary CT angiography and intravascular ultrasound within 3 months; Patients who underwent coronary CT angiography and optical coherence tomography within 3 months

Coronary plaque assessment DIAGNOSTIC_TEST

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

Patients who underwent coronary CT angiography because of suspected or known coronary artery disease

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

consecutive patients who first underwent CCTA and then Intravascular imaging in China

You may qualify if:

• Intravascular imaging (including intravascular ultrasound or optical coherence tomography) was performed within 3 months after CCTA;
• No change in medications or clinical symptoms during CCTA and intravascular imaging examinations;
• Coronary artery diameter stenosis of 30% to 90% on invasive coronary imaging.

You may not qualify if:

• Image quality of CCTA or intravascular US was inadequate to analyze;
• Intravascular imaging was performed after percutaneous coronary intervention (PCI) or pre-dilation of the target lesions;
• Lesions could not be co-registered between CCTA and intravascular US;
• Missing CCTA or intravascular US data

Sponsors & Collaborators

• Jinling Hospital, China: lead

Study Sites (1)

Research Institute Of Medical Imaging Jinling Hospital

Nanjing, Jiangsu, 210018, China

Location

Related Publications (4)

• Follmer B, Williams MC, Dey D, Arbab-Zadeh A, Maurovich-Horvat P, Volleberg RHJA, Rueckert D, Schnabel JA, Newby DE, Dweck MR, Guagliumi G, Falk V, Vazquez Mezquita AJ, Biavati F, Isgum I, Dewey M. Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries. Nat Rev Cardiol. 2024 Jan;21(1):51-64. doi: 10.1038/s41569-023-00900-3. Epub 2023 Jul 18.

  PMID: 37464183 BACKGROUND

• Gaba P, Gersh BJ, Muller J, Narula J, Stone GW. Evolving concepts of the vulnerable atherosclerotic plaque and the vulnerable patient: implications for patient care and future research. Nat Rev Cardiol. 2023 Mar;20(3):181-196. doi: 10.1038/s41569-022-00769-8. Epub 2022 Sep 23.

  PMID: 36151312 BACKGROUND

• Zhou F, Chen Q, Luo X, Cao W, Li Z, Zhang B, Schoepf UJ, Gill CE, Guo L, Gao H, Li Q, Shi Y, Tang T, Liu X, Wu H, Wang D, Xu F, Jin D, Huang S, Li H, Pan C, Gu H, Xie L, Wang X, Ye J, Jiang J, Zhao H, Fang X, Xu Y, Xing W, Li X, Yin X, Lu GM, Zhang LJ. Prognostic Value of Coronary CT Angiography-Derived Fractional Flow Reserve in Non-obstructive Coronary Artery Disease: A Prospective Multicenter Observational Study. Front Cardiovasc Med. 2022 Jan 31;8:778010. doi: 10.3389/fcvm.2021.778010. eCollection 2021.

  PMID: 35174219 RESULT

• Chen Q, Zhou F, Xing W, Xu Y, Hu S, Pan T, Cao W, Guo L, Shi Y, Luo S, Xu L, Zhang J, Zhang S, Zheng C, Yang Z, Qiao HY, Guo B, Liu T, Xu P, Xu W, Zhong J, Xie G, Tao X, Lu G, Tang CX, Zhang JJ, Zhang LJ; China VALUE Study Group. A Fully Automated Deep Learning Model for Quantifying Coronary Plaque at Coronary CT Angiography. Radiology. 2026 Apr;319(1):e251967. doi: 10.1148/radiol.251967.

  PMID: 42012347 DERIVED

MeSH Terms

Conditions

Coronary Artery Disease; Plaque, Atherosclerotic

Condition Hierarchy (Ancestors)

Coronary Disease; Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Arteriosclerosis; Arterial Occlusive Diseases; Vascular Diseases; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms

Study Officials

• Longjiang Zhang, MD

  Jinling Hospital, Medical School of Nanjing University, Nanjing,China

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director, Head of Radiology, Principal Investigator

Study Record Dates

• First Submitted: August 30, 2023
• First Posted: September 6, 2023
• Study Start: July 1, 2023
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2027
• Last Updated: May 11, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)