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. 2024 Apr;33(4):107584.
doi: 10.1016/j.jstrokecerebrovasdis.2024.107584. Epub 2024 Jan 19.

Automated evaluation of collateral circulation for outcome prediction in acute ischemic stroke

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Automated evaluation of collateral circulation for outcome prediction in acute ischemic stroke

Valéria Cristina Scavasine et al. J Stroke Cerebrovasc Dis. 2024 Apr.

Abstract

Introduction: The assessment of collateral circulation in acute ischemic stroke management is essential. Modern tools, such as Brainomix's e-CTA, powered by artificial intelligence, provide detailed insights into collateral assessment. This retrospective study aims to identify factors contributing to favorable collateral status and compare outcomes between patients with good collaterals (grade 3) and fair collaterals (grade 0-2).

Method: This retrospective study included 97 patients admitted to the Stroke Unit at the Hospital de Clínicas of the Federal University of Paraná, Brazil, from September 2021 to January 2023. Comparative analyses involved demographic factors, cardiovascular risk factors, and the combined outcome of mortality and moderate to severe disability at discharge, 30-day, and 90-day follow-ups.

Results: Among the 97 cases, 58.8 % showed 'good collaterals' with a grade 3 status. Variables affecting collateral status included age (p = 0.042), neutrophil-lymphocyte ratio (p = 0.005), and initial NIHSS scores (p<0.001). The presence of good collaterals according to e-CTA reduced the odds of death and moderate-severe disability at discharge (p = 0.003; OR 0.27) and at 30 days (p = 0.015; OR 0.33), although this effect diminished at the 90-day mark after multivariate analysis.

Discussion: Automated collateral assessment through e-CTA is a valuable tool in acute ischemic stroke evaluation. Good e-CTA collateral score serve as a promising imaging biomarker, guiding informed clinical decisions during Stroke Unit hospitalizations. This study highlights the relationship between collaterals and stroke outcomes and underscores the potential for AI-driven tools to enhance stroke care management.

Keywords: Artificial intelligence; Collateral circulation; Computed tomography angiography; Ischemic stroke.

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Conflict of interest statement

Declaration of competing interest All the authors report no disclosures. There is no conflict of interest to declare and no sponsorship or funding in this study.

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