Giulia Murgia
Carotid Stenosis and Cryptogenic Stroke: The Evidence from the Imaging-based Studies Carotid stenosis and Cryptogenic Stroke
Saba, Luca;Cau, RiccardoSecond
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2024-01-01
Abstract
Objectives: Cryptogenic stroke represents a type of ischemic stroke with an unknown origin, presenting a significant challenge in both stroke management and prevention. According to the Trial of Org 10172 in Acute Stroke Treatment (TOAST) criteria, a stroke is categorized as being caused by large artery atherosclerosis only when there is more than 50% luminal narrowing of the ipsilateral internal carotid artery. However, non-stenosing carotid artery plaques can be an underlying cause of ischemic stroke. Indeed, emerging evidence documents that some features of plaque vulnerability may act as an independent risk factor, regardless of the degree of stenosis, in precipitating cerebrovascular events. This review, drawing from an array of imaging-based studies, explores the predictive values of carotid imaging modalities in the detection of non-stenosing carotid plaque (<50%), that could be the cause of a cerebrovascular event when some features of vulnerability are present. Methods: Google Scholar, Scopus, and PubMed were searched for manuscripts on cryptogenic stroke and those reporting the association between cryptogenic stroke and imaging features of carotid plaque vulnerability. Results: Despite extensive diagnostic evaluations, the etiology of a considerable proportion of strokes remains undetermined, contributing to the recurrence rate and persistent morbidity in affected individuals. Advances in imaging modalities, such as including Magnetic Resonance (MR), Computed Tomography (CT) and Ultrasound (US), facilitate more accurate detection of non-stenosing carotid artery plaque, allow to better stratify stroke risk leading to more tailored treatment strategy. Conclusion: Early detection of non-stenosing carotid plaque with features of vulnerability through carotid imaging techniques impacts the clinical management of cryptogenic stroke, resulting in refined stroke subtype classification and improved patient management. Additional research is required to validate these findings and recommend the integration of these state-of-the-art imaging methodologies into standard diagnostic protocols to improve stroke management and prevention.File | Size | Format | |
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PIIS0741521424000193.pdf open access
Type: versione pre-print
Size 2.63 MB
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2.63 MB | Adobe PDF | View/Open |
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