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Current Cardiology Reports

Coronary Inflammation and Cardiovascular Events in Patients Without Obstructive Coronary Artery Disease

  • Open Access
  • 01-12-2025
  • Arterial Diseases
  • Ischemic Heart Disease (D Mukherjee, Section Editor)
Published in:
Authors
Jia Ling Diau
Richard A. Lange
Published in
Current Cardiology Reports | Issue 1/2025

Abstract

Purpose of Review

This review evaluates the role of vascular inflammation in patients who develop myocardial infarction with non-obstructive coronary arteries (MINOCA). It also introduces pericoronary adipose tissue (PCAT) and epicardial adipose tissue (EAT) as possible biomarkers for risk prediction in patients with non-obstructive coronary artery disease (CAD).

Recent Findings

PCAT and EAT contribute to the development and progression of coronary artery inflammation and plaque vulnerability. Coronary computed tomography angiography (CCTA) can detect localized areas of inflammation through changes in the attenuation values of PCAT and EAT. Attenuation values can be further integrated with traditional risk factors using artificial intelligence to generate risk scores that significantly enhance prognostic accuracy in patients with and without obstructive coronary artery disease.

Summary

Assessing PCAT and EAT inflammation via CCTA and AI-driven risk algorithms enable precise risk prediction of MINOCA and major adverse coronary events (MACE) in patients with non-obstructive CAD.
Title
Coronary Inflammation and Cardiovascular Events in Patients Without Obstructive Coronary Artery Disease
Authors
Jia Ling Diau
Richard A. Lange
Publication date
01-12-2025
Publisher
Springer US
Published in
Current Cardiology Reports / Issue 1/2025
Print ISSN: 1523-3782
Electronic ISSN: 1534-3170
DOI
https://doi.org/10.1007/s11886-025-02221-y
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This content is intended for healthcare professionals outside of the UK.

Independent Medical Education Grant:
  • Bayer HealthCare Pharmaceuticals Inc.
Learn more Link opens in a new window
Image Credits
Abstract graphic of layered, concentric circular shapes in bright green, pink, blue, and purple on a dark blue background. The rings and segments form a complex radial pattern without text/© Springer Health+ IME