Neuroimaging diagnosis and the collateral circulation in moyamoya disease

Wenhua Liu1, Gelin Xu1, Xinfeng Liu1

  • 1Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.

Interventional Neurology
|September 5, 2014
PubMed

Insights

Moyamoya disease (MMD) involves brain artery narrowing and fragile collateral vessels. Neuroimaging, especially MRI, helps diagnose MMD and assess its associated risks like stroke.

Area of Science:

  • Neurology
  • Radiology
  • Vascular Medicine

Background:

  • Moyamoya disease (MMD) is a rare cerebrovascular disorder.
  • It is defined by progressive stenosis of the internal carotid artery's terminal portion and its branches.
  • This condition leads to the formation of fragile collateral vessels at the brain's base.

Purpose of the Study:

  • To review neuroimaging modalities for diagnosing MMD.
  • To highlight the significance of hyperintense vessels on fluid-attenuated inversion recovery (FLAIR) MRI in evaluating MMD collateral patterns.
  • To summarize common angiographic collateral patterns in MMD and their association with cerebrovascular lesions.

Main Methods:

  • Review of neuroimaging techniques for MMD diagnosis.
  • Analysis of fluid-attenuated inversion recovery (FLAIR) MRI findings, specifically hyperintense vessels.
  • Summary of conventional cerebral angiography findings and collateral patterns.
  • Correlation of angiographic patterns with ischemic and hemorrhagic lesions.

Main Results:

  • Neuroimaging plays a crucial role in MMD diagnosis.
  • Hyperintense vessels on FLAIR MRI are valuable indicators for assessing collateral circulation in MMD.
  • Specific angiographic collateral patterns are associated with increased risk of ischemia and hemorrhage in MMD patients.

Conclusions:

  • Comprehensive neuroimaging, including advanced MRI techniques, is essential for MMD diagnosis and management.
  • Understanding collateral patterns is key to predicting MMD-related cerebrovascular events.
  • This review provides a framework for evaluating MMD using various imaging modalities.