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From Tissue Injury to Network Failure: The Emerging Role of Brain Mapping in Early Ischemic Stroke Detection
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Brain Mapping Applications in Epilepsy – Across Pediatric and Adult Populations
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Presenter Author:
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Nayer Seyfizadeh
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Author:
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| Name 1:
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Nayer Seyfizadeh - Corresponding - Presenter
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| Affiliation 1:
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Neurosciences Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
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Mehdi Farhoudi
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Abstract
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Original Research
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introduction :
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Early diagnosis of acute ischemic stroke is critical for timely therapeutic intervention and improved neurological outcomes. Despite advances in conventional neuroimaging, early ischemic changes may remain undetected, particularly during the hyperacute phase or in diffusion-weighted imaging–negative cases. In recent years, brain mapping has emerged as an integrative framework capable of capturing early structural, hemodynamic, functional, and electrophysiological alterations associated with cerebral ischemia, enabling detection beyond focal tissue injury.
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Methods:
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This narrative review summarizes peer-reviewed studies published between 2020 and 2025 and indexed in PubMed, Web of Science, and Scopus. Included studies investigated brain mapping approaches for early ischemic stroke detection, including diffusion-weighted MRI, CT and MR perfusion mapping, resting-state functional MRI, functional connectivity analysis, EEG-based brain mapping, and multimodal artificial intelligence–driven methods.
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Results:
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Diffusion-weighted MRI remained the most sensitive modality for identifying acute ischemic injury; however, its diagnostic performance improved significantly when combined with perfusion-based brain mapping, allowing early delineation of ischemic penumbra. Functional brain mapping consistently demonstrated early disruption of large-scale neural networks preceding definitive structural damage, supporting the concept of ischemic stroke as a network-level disorder. EEG-based brain mapping identified characteristic spatiotemporal patterns related to reduce cerebral perfusion and large-vessel occlusion. Multimodal machine-learning models integrating these data enhanced early diagnostic accuracy and clinical decision-making.
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Conclusion:
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Overall, recent evidence indicates that brain mapping reframes ischemic stroke as a dynamic network dysfunction rather than a purely focal lesion, enabling ultra-early diagnosis and improved therapeutic targeting. Integration of multimodal brain mapping with explainable artificial intelligence represents a promising direction for advancing acute stroke diagnostics, although further multicenter validation and protocol standardization are required.
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| Attachment:
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| Keywords:
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Brain Mapping; Ischemic Stroke; Early Diagnosis; Functional Connectivity; Multimodal Neuroimaging
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| Key message:
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