School of Medicine Publications
Document Type
Article
Publication Date
2026
Abstract
Background: The emergent treatment of acute ischemic stroke (AIS) has developed over the past four decades, and neuroimaging has always been a cornerstone of triage and decision-making prior to thrombolysis and thrombectomy interventions. Despite advances in these reperfusion therapies, AIS remains a leading cause of death and disability around the world. This review brings together the historical development of computed tomography (CT) stroke imaging and the current wave of artificial intelligence (AI) applications in a single narrative, with particular attention to non-contrast CT-based patient selection and its relevance to resource-limited settings.
Methods: This narrative review draws on peer-reviewed literature identified through keyword searches of PubMed and Google Scholar, covering the evolution of CT-based AIS imaging and recent clinical AI applications.
Results: Landmark trials relied on visual assessments of CT for risk stratification and emergent triage. Over time, these assessments have become more standardized and validated. However, in the last two decades there has been an explosion of AI applications in this space. While some models have demonstrated preliminary and promising results for large vessel occlusion detection, infarct core segmentation, and automated radiological scoring, there are crucial limitations for their immediate clinical practice implementation. These advancements will need to focus on automated, more cost-effective, and generalizable solutions to improve stroke care internationally.
Conclusion: The future of neuroimaging research for AIS management will rely on diverse and robust multicenter collaborative datasets, rigorous evaluation methods, and a relentless focus on the translation of AI technologies to demonstrated benefit on patient outcomes.
Recommended Citation
Aamir, S. R., Ganesh, A., Cherukuri, H., & Jeevarajan, J. A. (2026). CT‐Based Imaging in Acute Ischemic Stroke: Evolution, Evidence and Emerging Frontierss. Clinical Neuroimaging, 3(1), e70087. https://doi.org/10.1002/neo2.70087
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
Clinical Neuroimaging
DOI
10.1002/neo2.70087
Academic Level
medical student
Mentor/PI Department
Neurology
Comments
© 2026 The Author(s). Clinical Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging