Abstract Number: Esoc2026a1312 Association Between Antegrade-collateral Flow Balance Patterns and Cerebral Blood Flow in Acute Ischemic Stroke
Year: 2026
Type: conference-abstract
Abstract: Background and aims Adequate antegrade and collateral flow distal to occluded vessels is critical for maintaining cerebral perfusion in acute ischemic stroke (AIS) patients. This study aimed to investigate the correlation between distinct antegrade-collateral (AnCo) flow balance patterns and perfusion status in ischemic brain tissue. Methods This multicenter cohort study recruited AIS or transient ischemic attack (TIA) patients with symptomatic intracranial atherosclerotic stenosis (sICAS). Eligible patients presented within 7 days of symptom onset and had middle cerebral artery (MCA) M1 segment occlusion. All patients underwent multimodal CT; antegrade flow and leptomeningeal collaterals (LMCs) were graded on dynamic CT angiography, and cerebral perfusion parameters were derived from CT perfusion (CTP) maps. Three balance patterns were defined: AnCo(+) (preserved antegrade flow with favorable LMCs), AnCo(-) (absent antegrade flow with poor LMCs), and AnCo(mix) (intermediate patterns). The primary outcome was the volume of tissue with relative cerebral blood flow (rCBF) < 30%. Results A total of 146 patients were enrolled (mean age 58.3 years, 76.7% male, median NIHSS 5): 53 in AnCo(+), 70 in AnCo(mix), 23 in AnCo(-). Linear regression analyses demonstrated that AnCo(-) was independently associated with a larger rCBF < 30% volume compared with AnCo(+) (adjusted β = -8.9, 95% CI -15.2 to -2.6; p = 0.006) and AnCo(mix) (adjusted β = -7.9, 95% CI -13.8 to -1.9; p = 0.01). Conclusions Antegrade-collateral flow balance patterns are valid predictors of tissue perfusion in sICAS patients with large-vessel occlusion. Conflict of interest All authors: nothing to disclose
Source: European Stroke Journal
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,400
OpenAlex ID: W7160417783
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