Vessel wall MR imaging of intracranial atherosclerosis

Jae W Song1, Bruce A Wasserman2

  • 1Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.

Insights

Intracranial atherosclerotic disease (ICAD) is a leading cause of ischemic stroke. High-resolution vessel wall MRI advances ICAD diagnosis and plaque characterization, improving stroke prognosis and treatment personalization.

Area of Science:

  • Neurology
  • Radiology
  • Cardiovascular Imaging

Background:

  • Intracranial atherosclerotic disease (ICAD) is a major cause of ischemic stroke globally, associated with high recurrence rates, cognitive decline, and significant economic burden.
  • Atherosclerotic lesions in intracranial arteries vary from subtle, angiographically occult changes to severe stenosis.
  • Traditional imaging focuses on lumen diameter, often missing critical vessel wall pathology.

Purpose of the Study:

  • To review the advantages of intracranial high-resolution vessel wall MRI (VW-MR) for characterizing ICAD.
  • To explore the potential of VW-MR in identifying vulnerable intracranial plaques and assessing disease burden.
  • To discuss the role of VW-MR in evaluating treatment response and future applications of AI in ICAD assessment.

Main Methods:

  • Review of recent advancements in intracranial high-resolution vessel wall MR (VW-MR) imaging techniques.
  • Discussion of how VW-MR enables characterization of vessel wall pathology beyond lumen imaging.
  • Exploration of bioimaging markers and artificial intelligence in plaque assessment.

Main Results:

  • Intracranial VW-MR allows detailed imaging of the vessel wall, revealing atherosclerotic changes.
  • This technique can identify angiographically occult lesions and assess plaque vulnerability.
  • VW-MR aids in evaluating treatment responses, such as to statin therapy, and understanding arterial remodeling.

Conclusions:

  • Intracranial VW-MR imaging significantly enhances the understanding and diagnosis of ICAD.
  • It offers potential for identifying vulnerable plaques and personalizing stroke treatment through lesion-based risk models.
  • Future integration of AI with VW-MR promises improved lesion scoring and assessment for better patient outcomes.

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