Quantitative imaging outperforms No-reflow in predicting functional outcomes in a translational stroke model.

Area of Science:

• Neuroscience
• Radiology
• Cardiovascular System

Background:

• Microvascular dysfunction and no-reflow are key factors in secondary brain damage after acute ischemic stroke (AIS).
• Endovascular mechanical thrombectomy (EVT) is a primary treatment for AIS, but outcomes are affected by microvascular integrity.
• Quantitative imaging is crucial for characterizing early microvascular changes post-revascularization.

Purpose of the Study:

• To utilize quantitative PET-MRI imaging to characterize early microvascular damage in a non-human primate model of AIS undergoing EVT.
• To correlate imaging findings with infarct growth and neurological outcomes one week post-EVT.
• To identify early imaging biomarkers predictive of poor outcomes and potential neuroprotection targets.

Main Methods:

• A preclinical non-human primate model of AIS underwent EVT.
• Quantitative PET-MRI imaging was performed during occlusion (perfusion, diffusion) and post-revascularization (perfusion, diffusion, blood-brain barrier permeability, oxygen metabolism).
• Neurological scores and lesion growth were assessed one week post-EVT to define poor outcomes.

Main Results:

• Early post-EVT hypoperfusion was detected by PET in 67% and by MRI Tmax in 90% of cases within the acute lesion.
• Thirty-eight percent of cases experienced a poor outcome, all of whom exhibited no-reflow phenomena on imaging.
• Diffusion ADC alterations and elevated oxygen extraction fraction (OEF) correlated with PET no-reflow; prolonged Tmax and high BBB Ktrans independently predicted poor outcomes.

Conclusions:

• Quantitative PET-MRI provides an early imaging signature of microvascular dysfunction post-EVT in AIS.
• This signature, including hypoperfusion, no-reflow, and BBB permeability, effectively predicts infarct growth and poor neurological outcomes.
• The findings highlight the potential of early quantitative imaging to guide treatment and identify targets for neuroprotection.