Overview of Imaging Modalities in Stroke.

Area of Science:

• Neurology
• Radiology
• Medical Imaging

Background:

• Acute stroke diagnosis relies heavily on timely and accurate imaging.
• Neuroimaging advancements offer precise assessment of brain tissue viability and fate.
• Machine learning integration enhances the interpretability of complex imaging data.

Purpose of the Study:

• To review common imaging modalities for acute stroke diagnosis and management.
• To demonstrate the application of these modalities in clinical decision-making.
• To highlight the role of multimodal imaging in understanding cerebrovascular pathologies.

Main Methods:

• Review of noncontrast head computed tomography (CT) for initial stroke evaluation.
• Discussion of CT angiography (CTA) for identifying large vessel occlusions and cervical artery disease.
• Exploration of CT perfusion, magnetic resonance imaging (MRI), and other advanced techniques like optical coherence tomography (OCT), positron emission tomography (PET), and single-photon emission computerized tomography (SPECT).

Main Results:

• Noncontrast head CT is the primary tool due to its speed and sensitivity to hemorrhage.
• CTA is crucial for detecting large vessel occlusions and guiding endovascular therapy selection.
• Advanced MRI and perfusion techniques provide insights into stroke prognosis and etiology.
• Multimodal imaging approaches offer tailored mechanistic insights for diverse cerebrovascular conditions.

Conclusions:

• Advanced neuroimaging, including CT and MRI, is essential for accurate acute stroke diagnosis and management.
• Machine learning tools are increasingly important for interpreting imaging studies and supporting clinical decisions.
• Tailored multimodal imaging strategies are key to understanding and treating various cerebrovascular pathologies effectively.