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Abstract Number: Esoc2026a2385 Hypoperfusion Intensity Ratio Is Associated With Stroke Etiology in Acute Ischemic Stroke

Year: 2026
Type: conference-abstract
Abstract: Background and aims The hypoperfusion intensity ratio (HIR) is a perfusion-derived marker associated with infarct growth and clinical outcome. However, its potential role in informing stroke etiology remains unclear. We investigated the association between HIR and TOAST stroke subtype. Methods We analyzed a consecutive cohort of patients with acute ischemic stroke who underwent baseline perfusion imaging and demonstrated a measurable perfusion deficit. HIR was analyzed as both a dichotomous (≤0.3 vs >0.3) and continuous variable. Clinical and imaging variables were compared using non-parametric tests. Multinomial logistic regression models were fitted with TOAST classification as the dependent variable, adjusting for possible confounders. Adjusted predicted probabilities of stroke etiology were estimated across increasing HIR values. Results Among 433 included patients, 234 (54.0%) had cardioembolic stroke, 86 (19.9%) large artery atherosclerosis, and 113 (26.1%) other determined or undetermined etiology. Higher HIR was associated with greater stroke severity, including higher baseline NIHSS scores and larger core, hypoperfused, and mismatch volumes (all p<0.001). In adjusted models, HIR >0.3 was associated with a higher likelihood of cardioembolic stroke compared with large artery atherosclerosis (RRR 3.07, 95% CI 1.72–5.56). Adjusted predicted probabilities demonstrated a graded increase in the likelihood of cardioembolic etiology, reaching a maximum of 0.67 (95% CI 0.59–0.75) for HIR values ≥0.7. Conclusions Higher hypoperfusion intensity is independently associated with cardioembolic stroke etiology. Perfusion patterns may contribute to early etiological stratification in AIS, reinforcing suspicion toward a cardioembolic mechanism. Conflict of interest Antonio De Mase: Nothing to disclose; Emanuele Spina: Nothing to disclose; Stefano Barbato: Nothing to disclose; Carlo Maurea: Nothing to disclose; Giovanna Servillo: Nothing to disclose; Simone Aramini: Nothing to disclose; Mario Muto: Nothing to disclose; Claudia Cuccurullo: Nothing to disclose; Vincenzo Andreone: Nothing to disclose; Paolo Candelaresi: Nothing to disclose
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $4,400
OpenAlex ID: W7160450323
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