New methods to image unstable atherosclerotic plaques

Jack P M Andrews1, Zahi A Fayad2, Marc R Dweck1

  • 1Centre for Cardiovascular Science, University of Edinburgh, Chancellor's Building, Royal Infirmary of Edinburgh, Edinburgh EH16 4SB, UK.

Atherosclerosis
|March 31, 2018
PubMed

Insights

Advanced imaging techniques like PET-CT and PET-MR offer new ways to assess atherosclerotic plaque, improving prediction of heart attack and stroke risk. This helps differentiate active versus inactive disease for better patient management.

Area of Science:

  • Cardiovascular Imaging
  • Biomedical Engineering
  • Radiology

Background:

  • Atherosclerotic plaque rupture causes myocardial infarction and stroke, leading global mortality.
  • Accurate prediction of these events is challenging due to the rarity of individual occurrences despite widespread atherosclerosis.
  • Current imaging methods assess plaque morphology, but integrating functional data is crucial.

Purpose of the Study:

  • To review advanced imaging techniques for assessing atherosclerotic plaque characteristics.
  • To explore the potential of hybrid PET-CT and PET-MR in evaluating plaque biology.
  • To discuss how these methods can redefine risk prediction and therapy allocation for coronary artery disease.

Main Methods:

  • Computed Tomography (CT) and Magnetic Resonance (MR) imaging for plaque morphology and characteristics.
  • Positron Emission Tomography (PET) imaging for measuring pathological processes and disease activity.
  • Hybrid integration of PET with CT or MR for comprehensive plaque assessment.

Main Results:

  • CT and MR can identify unstable plaque features linked to rupture risk.
  • PET imaging differentiates active from inactive atherosclerotic disease states.
  • Hybrid PET-CT/MR enables assessment of plaque burden, morphology, and biology.

Conclusions:

  • Advanced imaging, particularly hybrid PET-CT/MR, promises to enhance understanding of coronary artery disease.
  • These techniques may refine patient risk stratification beyond traditional symptomatic evaluation.
  • Improved risk prediction can guide the allocation of novel, expensive therapies more effectively.

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