Coronary Imaging and Metabolic Indicators-Based Risk Prediction Model for Coronary Artery Disease(CMI-RiskCAD) (CMI-RiskCAD)

Coronary Imaging and Metabolic Indicators-Based Risk Prediction Model for Coronary Artery Disease:A Retrospective and Prospective Cohort Study

The primary design of this study is an ambispective cohort study. We plan to integrate coronary imaging features (including parameters derived from Coronary Computed Tomography Angiography(CCTA) and coronary angiography(CAG)), coronary functional indices (e.g., FFR, QFR), and metabolic biomarkers (e.g., LDL-C, Lp(a), hs-CRP). First, we will develop a multimodal risk prediction model for coronary artery disease using a retrospective cohort; subsequently, we will validate the model in a prospective cohort to assess its performance in discriminating high- versus low-risk individuals and to explore its potential clinical utility for risk stratification and decision-making.

Study Overview

• Status: Not yet recruiting
• Conditions: Coronary Artery Disease (CAD) (E.G., Angina, Myocardial Infarction, and Atherosclerotic Heart Disease (ASHD))

Detailed Description

Coronary Computed Tomography Angiography (CCTA), currently the preferred non-invasive imaging modality for clinical diagnosis of coronary artery disease (CAD), not only enables intuitive assessment of coronary stenosis severity but also allows quantitative and qualitative analysis of coronary atherosclerotic plaque burden and phenotype. Quantitative CCTA integrated with artificial intelligence, particularly convolutional neural network algorithms, has achieved rapid and accurate quantitative diagnosis of atherosclerotic plaques. A large body of research has demonstrated that high-risk plaque features identified by CCTA (such as low-attenuation plaques, positive remodeling, spotty calcification, and the napkin-ring sign) are closely associated with the occurrence of acute coronary syndrome and can be used to predict major adverse cardiovascular events (MACEs). With advancements in image post-processing techniques, CCTA can also compute CT Fractional Flow Reserve (CT-FFR) via dedicated software, enabling non-invasive assessment of whether a lesion causes hemodynamic abnormalities and myocardial ischemia, thereby partially overcoming the limitations of purely anatomical evaluation. Notably, CCTA not only focuses on intravascular and vascular wall changes but also allows quantitative characterization of phenotypic changes in Perivascular Adipose Tissue (PVAT). By calculating the Perivascular Fat Attenuation Index (pFAI), it can reflect alterations in PVAT density and composition, indirectly indicating the inflammatory activity status of the local coronary artery wall, thus providing a novel imaging perspective for understanding CAD from the "inflammation and metabolism" viewpoint. Furthermore, CCTA can characterize the lesion patterns of coronary atherosclerosis based on physiological and geometric distribution characteristics of the vasculature. For instance, the Pullback Pressure Gradient (PPG) derived from CCTA allows comprehensive quantitative assessment of the longitudinal distribution of CAD vasculature, enabling the classification of CAD phenotypes as predominantly focal or diffuse. The CT-FFR gradient, defined as the peak instantaneous CT-FFR gradient per unit length of the vessel, has also been recently confirmed to possess incremental predictive ability for future coronary events, thereby more comprehensively describing coronary atherosclerosis in terms of both "lesion distribution pattern" and "local functional severity".

Coronary Angiography (CAG), the gold standard for diagnosing CAD, has traditionally relied on stenosis severity and SYNTAX score to assess the anatomical complexity of lesions and the difficulty of interventional treatment. However, anatomical information alone remains limited for predicting plaque stability and event risk. In recent years, emerging parameters such as Radial Wall Strain (RWS) extracted from single or multiple angiographic views have provided new tools for identifying high-risk plaques from a vascular mechanics perspective. Studies have shown that RWS can reflect the radial deformation characteristics of the arterial wall during the cardiac cycle and exhibits good correlation with vulnerable plaques and the risk of plaque rupture, holding promise as a supplementary indicator for risk stratification beyond traditional angiographic parameters.

Meanwhile, intravascular imaging techniques such as Intravascular Ultrasound (IVUS) and Optical Coherence Tomography (OCT) can visualize plaque composition, burden, and fibrous cap morphology with high resolution, more closely approximating the pathological "vulnerable plaque" phenotype. Coronary functional assessments, such as FFR, Quantitative Flow Ratio (QFR), Murray Law-Based QFR (μFR), and Coronary Angiography-derived FFR (caFFR), evaluate from a hemodynamic perspective whether a stenosis causes functional myocardial ischemia. The continuous development of these technologies has addressed the limitation of traditional CAG, which only assesses anatomical stenosis and cannot accurately distinguish between "ischemia-causing" and "non-ischemia-causing" lesions, thereby reducing the risks of overtreatment and missed lesions. Beyond epicardial large vessel disease, Coronary Microvascular Dysfunction (CMVD) is also a significant mechanism underlying clinically common myocardial ischemia. For assessing microcirculatory function, various non-invasive or minimally invasive functional indices have emerged in recent years, such as the Coronary Angiography-derived Index of Microcirculatory Resistance (caIMR), which comprehensively reflects myocardial ischemic burden from the perspectives of microcirculatory resistance and perfusion efficiency. This provides a novel solution to the clinical conundrum of "presence of ischemia and symptoms without significant angiographic stenosis".

In addition to imaging and functional information, routine clinical metabolic and inflammatory markers also play a crucial role in the development, progression, and prognostic evaluation of CAD. Examples include low-density lipoprotein cholesterol, triglyceride-glucose index, lipoprotein(a), glycated hemoglobin, high-sensitivity C-reactive protein, homocysteine, fasting blood glucose, and N-terminal pro-B-type natriuretic peptide. These indices reflect the body's overall metabolic status and cardiovascular risk from different dimensions, including lipid metabolism, glycolipid metabolic disorders, chronic inflammation, endothelial function, myocardial stress, and cardiac function. Studies have suggested that the combined application of metabolic and inflammatory markers with coronary imaging features facilitates more refined individualized risk stratification and prognostic prediction.

In summary, the current assessment of CAD is gradually shifting from a single focus on "anatomical stenosis" to a multidimensional comprehensive characterization encompassing "anatomical structure + functional evaluation + plaque phenotype + perivascular environment + systemic metabolic status". However, there remains a lack of systematic research on how to integrate the aforementioned multi-source information (such as CCTA plaque and functional parameters, CAG and intravascular imaging information, microcirculatory function parameters, and clinical metabolic indicators) into a unified risk prediction model, construct the model through retrospective analysis, and subsequently validate its predictive value and clinical feasibility in a prospective cohort. Therefore, this project aims to integrate coronary imaging features (including CCTA and CAG-related parameters), functional indices, and metabolic markers to construct a multimodal CAD risk prediction model. The model will be developed using a retrospective cohort and its performance validated using a prospective cohort, exploring its application value in clinical risk stratification and decision-making.

This study is led by the National Clinical Research Center for Cardiovascular Diseases and invited to be carried out by several Chinese centers including Beijing Anzhen Hospital.

• Study Type: Observational
• Enrollment (Estimated): 10960

Contacts and Locations

• Study Contact: Name: Chenchen Tu; Phone Number: +8615201648899; Email: tcc2033@mail.ccmu.edu.cn

Study Locations

• China
  • Beijing, China
    • Beijing Anzhen Hospital, Capital Medical University
    • Contact: Chenchen Tu; Phone Number: +8615201648899; Email: tcc2033@mail.ccmu.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Suspected CAD patients underwent CCTA

Description

Inclusion Criteria:

(1)Completion of CCTA examination. (2)Age ≥ 18 years. (3)Signed written informed consent, and willing and able to comply with baseline assessment and long-term follow-up.

Exclusion Criteria:

1. Acute ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation myocardial infarction (NSTEMI) occurring within 72 hours; history of coronary artery bypass grafting (CABG); severe valvular heart disease; dilated or hypertrophic cardiomyopathy; congenital heart disease; or heart failure (NYHA functional class III-IV).
2. Severe hepatic insufficiency (Child-Pugh class C) or renal failure (estimated glomerular filtration rate [eGFR] < 30 mL/min/1.73m²).
3. Pregnancy or lactation.
4. Life expectancy of less than 1 year, or any other condition that, in the opinion of the investigator, renders the patient unsuitable for participation in the study.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
retrospective cohort; patients with suspected CAD who underwent CCTA between 2020 and 2025
prospective cohort; patients with suspected CAD who underwent CCTA between 2026 and 2030

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The composite endpoint of major adverse cardiovascular events (MACE)	including cardiac death, non-fatal myocardial infarction, and rehospitalization for unstable angina or heart failure.	At 12, 24, 36, 48, and 60 months after discharge
Frequency of occurrence of high-risk plaques	Frequency (%) of occurrence of high-risk plaque morphologic features (ow-attenuation plaques, positive remodeling, spotty calcification, and the napkin-ring sign, minimal lumen area[MLA]<4mm2)	baseline, pre-intervention
CT Fractional Flow Reserve gradient	The CT-FFR gradient is defined as the peak instantaneous CT-FFR gradient per unit vessel length, serving as an indicator of local lesion severity. The calculation of the CT-FFR gradient was performed only for lesions with diameter stenosis > 30%.	baseline, pre-intervention
Perivascular Fat Attenuation Index	The Fat Attenuation Index (FAI) was defined as the mean attenuation of perivascular adipose tissue (PVAT). The density range of adipose tissue included in the analysis was restricted to -190 HU to -30 HU, and the FAI surrounding the target vessel was automatically calculated by the software.	baseline, pre-intervention
PPG derived by follow up CCTA	pullback pressure gradient (PPG) derived by follow up CCTA, the values derived from CT-FFR were calculated using the formula	baseline, pre-intervention
SYNTAX score	In patients undergoing coronary angiography, each lesion (diameter stenosis ≥ 50%) within the coronary artery tree was quantified based on the angiographic findings	immediately after the intervention
Coronary Angiography-derived FFR and Coronary Angiography-derived Index of Microcirculatory Resistance	In patients undergoing coronary angiography, clear angiographic images of the left anterior descending (LAD), left circumflex (LCX), and right coronary arteries (RCA) were acquired from at least two different projections, ensuring no overlap or foreshortening. Three-dimensional (3D) reconstruction and hemodynamic calculations were performed using dedicated software (AccuIMR version 1.0).	baseline, pre-intervention
Radial Wall Strain	For patients undergoing coronary angiography, image frames corresponding to four key cardiac phases-late systole, early systole, late systole, and mid-diastole-were selected for a specific vessel. After segmentation and registration of the lumen contours	immediately after the intervention
IVUS-related parameters	Minimal Lumen Area, Minimal Lumen Diameter	immediately after the intervention
OCT-related parameters	Minimal Lumen Area, Lipid Core Burden Index, Fibrous Cap Thickness	immediately after the intervention

Collaborators and Investigators

• Sponsor: Beijing Anzhen Hospital

Publications and helpful links

General Publications

• Nurmohamed NS, Min JK, Anthopolos R, Reynolds HR, Earls JP, Crabtree T, Mancini GBJ, Leipsic J, Budoff MJ, Hague CJ, O'Brien SM, Stone GW, Berger JS, Donnino R, Sidhu MS, Newman JD, Boden WE, Chaitman BR, Stone PH, Bangalore S, Spertus JA, Mark DB, Shaw LJ, Hochman JS, Maron DJ. Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial. Eur Heart J. 2024 Sep 29;45(36):3735-3747. doi: 10.1093/eurheartj/ehae471.

Study record dates

Study Major Dates

• Study Start (Estimated): January 1, 2026
• Primary Completion (Estimated): December 31, 2035
• Study Completion (Estimated): December 31, 2035

Study Registration Dates

• First Submitted: December 28, 2025
• First Submitted That Met QC Criteria: January 18, 2026
• First Posted (Actual): January 20, 2026

Study Record Updates

• Last Update Posted (Actual): January 20, 2026
• Last Update Submitted That Met QC Criteria: January 18, 2026
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Coronary Computed Tomography Angiography; Perivascular Fat Attenuation Index; Coronary Angiography-derived FFR
• Additional Relevant MeSH Terms: Pain; Neurologic Manifestations; Vascular Diseases; Cardiovascular Diseases; Pathologic Processes; Heart Diseases; Infarction; Necrosis; Arteriosclerosis; Arterial Occlusive Diseases; Coronary Disease; Myocardial Ischemia; Ischemia; Chest Pain; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Coronary Artery Disease; Myocardial Infarction; Angina Pectoris
• Other Study ID Numbers: BeijingAnzhen_2

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Due to patient privacy and ethical restrictions.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No