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

  • 0Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, USA.
Current Cardiology Reports +

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March 7, 2025

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March 7, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Vascular inflammation plays a key role in myocardial infarction with non-obstructive coronary arteries (MINOCA). Pericoronary adipose tissue (PCAT) and epicardial adipose tissue (EAT) show promise as biomarkers for predicting risk in non-obstructive coronary artery disease.

Area Of Science

  • Cardiology
  • Biomarkers
  • Inflammation

Background

  • Vascular inflammation is implicated in myocardial infarction with non-obstructive coronary arteries (MINOCA).
  • Pericoronary adipose tissue (PCAT) and epicardial adipose tissue (EAT) are emerging as potential biomarkers for risk stratification in non-obstructive coronary artery disease (CAD).

Purpose Of The Study

  • To review the role of vascular inflammation in MINOCA.
  • To explore PCAT and EAT as biomarkers for risk prediction in non-obstructive CAD.

Main Methods

  • Review of current literature on vascular inflammation, MINOCA, PCAT, and EAT.
  • Analysis of coronary computed tomography angiography (CCTA) for detecting inflammation in PCAT and EAT.
  • Integration of CCTA-derived attenuation values with artificial intelligence (AI) for risk scoring.

Main Results

  • PCAT and EAT inflammation contribute to coronary artery inflammation and plaque vulnerability.
  • CCTA can identify localized inflammation via PCAT and EAT attenuation values.
  • AI-enhanced risk scores integrating CCTA data significantly improve prognostic accuracy for MINOCA and major adverse coronary events (MACE) in non-obstructive CAD.

Conclusions

  • Assessing PCAT and EAT inflammation using CCTA and AI offers precise risk prediction for MINOCA.
  • This approach enhances prognostic accuracy for major adverse coronary events in patients with non-obstructive CAD.

Keywords:

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