Ruptured versus stable plaques in human coronary arteries

Demosthenes G Katritsis1, Efstathios P Efstathopoulos, Ioannis Pantos

  • 1Department of Cardiology, Athens Euroclinic, Athens, Greece. dkatritsis@euroclinic.gr

Insights

A new model identifies high-risk left anterior descending (LAD) coronary artery stenoses prone to plaque rupture. This tool aids in predicting thrombosis and stratifying risk for ST-elevation myocardial infarction (STEMI) patients.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Biomedical Engineering

Background:

  • ST-elevation myocardial infarction (STEMI) is often caused by plaque rupture in the left anterior descending (LAD) coronary artery.
  • Identifying stenoses prone to rupture and thrombosis is crucial for effective risk stratification and treatment.

Purpose of the Study:

  • To develop and validate a predictive model for identifying LAD coronary artery stenoses with a high probability of plaque rupture and thrombosis.
  • To establish specific anatomical characteristics on coronary angiograms that differentiate culprit lesions from stable stenoses.

Main Methods:

  • Three-dimensional reconstruction of coronary angiograms from 186 patients with anterior STEMI and 293 patients with stable LAD stenoses.
  • Comparison of anatomical features including lesion location, length, bifurcation involvement, angulation, and symmetry.
  • Development and validation of a predictive model using multiple regression analysis.

Main Results:

  • Culprit lesions associated with STEMI were predominantly located 20-40 mm from the LAD ostium, were longer, and more frequently involved bifurcations compared to stable lesions.
  • Culprit lesions exhibited sharper angulation and symmetrical morphology, while stable lesions were located on the inner vessel wall.
  • The derived model demonstrated high discriminating ability in both original (AUC: 0.88) and validation (AUC: 0.69) samples.

Conclusions:

  • Specific anatomical features of LAD stenoses identified via coronary angiography can effectively predict plaque rupture and thrombosis.
  • The developed model aids in the risk stratification of coronary stenoses, particularly in patients presenting with STEMI.
Abstract

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