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Related Experiment Videos

Predicting tissue outcome in stroke: new approaches.

Leif Ostergaard1, Kristjana Yr Jónsdóttir, Kim Mouridsen

  • 1Center of Functionally Integrative Neuroscience, Department of Neuroradiology, University of Aarhus, Aarhus University Hospital, Aarhus, Denmark. leif@cfin.dk

Current Opinion in Neurology
|January 22, 2009
PubMed
Summary

Advanced MRI techniques can identify tissue at risk for stroke, improving treatment targeting beyond the standard time window. These methods estimate individual infarct risk, aiding in the development of new stroke therapies.

Related Concept Videos

Ischemic Stroke ll: Pathophysiology01:15

Ischemic Stroke ll: Pathophysiology

An ischemic stroke occurs when a cerebral blood vessel becomes obstructed, most often by a thrombus or embolus, interrupting the delivery of oxygen and glucose to brain tissue. Because neurons rely on continuous aerobic metabolism, energy failure begins within minutes of reduced perfusion. The region receiving the least blood flow becomes the infarct core, an area of irreversible cellular death. Surrounding this core lies the penumbra, a zone of hypoperfused but still viable tissue that is...

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Area of Science:

  • Neuroimaging
  • Stroke Research
  • Medical Informatics

Background:

  • Multimodal MRI is crucial for understanding acute stroke and guiding therapy.
  • The perfusion-diffusion mismatch is a key target for extended stroke treatment windows.
  • Infarct risk is highly variable within the diffusion and perfusion lesion.

Purpose of the Study:

  • To review techniques for accurately imaging and modeling penumbral infarct risk.
  • To explore advanced MRI methods for assessing tissue at risk in acute stroke.
  • To discuss the role of predictive models in stroke therapy.

Main Methods:

  • Utilizing blood oxygen level-dependent contrast MRI to assess oxygen supply.
  • Employing models of oxygen delivery capacity to detect tissue-at-risk.

Related Experiment Videos

  • Integrating multimodal and follow-up MRI data using informatics approaches for infarct progression modeling.

    • Main Results:

    • Oxygen supply assessment methods improve the detection of tissue-at-risk.
    • Informatics approaches applied to acute imaging data can assign infarct risks to mismatch tissue.
    • Estimates of tissue infarct risk have shown potential in detecting treatment-related risk reduction.

    Conclusions:

    • MRI methods can detect metabolic derangements in ischemia, identifying penumbral tissue.
    • Predictive models enhance the perfusion-diffusion mismatch concept with voxel-based risk estimates.
    • Future predictive models may offer advanced prognostic support and facilitate cost-effective stroke therapy testing.