ABSTRACT
Cerebral collateral circulation is a critical determinant of infarct evolution, therapeutic response, and clinical outcomes in patients with acute ischemic stroke. While the concept of “time is brain” has traditionally guided reperfusion therapy, recent evidence—particularly from trials like DAWN and DEFUSE 3—suggests that collateral status more accurately determines the rate of infarct progression and the extent of salvageable tissue. This comprehensive review synthesizes advances in neuroimaging modalities for evaluating cerebral collaterals, emphasizing their role in refining stroke diagnosis, guiding patient selection, and informing personalized treatment strategies. Structural approaches such as multiphase and dynamic CT angiography, alongside perfusion-based parameters (e.g., cerebral blood volume, hypoperfusion intensity ratio, and Tmax delay maps), are examined. Cortical venous outflow, assessed via the cortical vein opacification score, emerges as an independent predictor of outcome, complementing arterial grading. Susceptibility-weighted imaging, arterial spin labeling, and metabolic and molecular techniques (e.g., PET imaging of inflammation and vascular remodeling) offer functional insights beyond traditional angiography. Biomarkers such as matrix metalloproteinase-9, integrin αvβ3, and translocator protein–targeted PET ligands are discussed in relation to collateral vessel dynamics. Finally, we explore the integration of genetically informed brain atlases, spatial transcriptomics, and imaging–genomic platforms for high-resolution collateral phenotyping. Although promising, these modalities face challenges related to heterogeneity, limited validation, and the lack of standardization. A biologically informed, multimodal, and automated imaging paradigm may herald a new era of precision stroke medicine.
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This post is Copyright: Ritwick Mondal,
Shramana Deb,
Nirmalya Ray,
Ananya Sengupta,
Vramanti Sarkar,
Subhadeep Banerjee,
Avik Mukherjee,
Jayanta Roy,
Julián Benito‐León | August 18, 2025
Wiley: Journal of Neuroimaging: Table of Contents