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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
Purpose Of Review:
Multimodal MRI provides powerful tools to study acute stroke pathophysiology and to guide stroke therapy. In particular, the perfusion-diffusion mismatch has been hypothesized as a target for treatment beyond the 3 h time window. Studies of infarct progression and of tissue oxygen metabolism suggest that infarct risk is extremely heterogeneous across the diffusion and perfusion lesion. The review describes techniques to more accurately image and model penumbral infarct risk.
Recent Findings:
Methods assessing oxygen supply by either blood oxygen level-dependent contrast MRI or models of oxygen delivery capacity may improve the detection of tissue-at-risk. Informatics approaches integrate acute multimodal and follow-up images from large patient cohorts into models of infarct progression. When applied to subsequent acute image data, these techniques may assign infarct risks to mismatch tissue. Recent studies suggest that such estimates of tissue infarct risk may detect treatment-related risk reduction in small patient cohorts.
Summary:
MRI methods may detect markers of metabolic derangement in ischemia, facilitating the detection of penumbral tissue. Predictive models extend the current perfusion-diffusion mismatch concept by estimating voxel-based risk estimates. With future developments, predictive models may support advanced prognostic support and cost-effective testing of novel stroke therapies.
Insights
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.
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.
- 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.
