Clinico-radiological features of intracranial atherosclerosis-related large vessel occlusion prior to endovascular treatment

颅内动脉粥样硬化相关大血管闭塞在血管内治疗前的临床放射学特征

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Abstract

The identification of large vessel occlusion with underlying intracranial atherosclerotic disease (ICAS-LVO) before endovascular treatment (EVT) continues to be a challenge. We aimed to analyze baseline clinical-radiological features associated with ICAS-LVO that could lead to a prompt identification. We performed a retrospective cross-sectional study of consecutive patients with stroke treated with EVT from January 2020 to April 2022. We included anterior LVO involving intracranial internal carotid artery and middle cerebral artery. We analyzed baseline clinical and radiological variables associated with ICAS-LVO and evaluated the diagnostic value of a multivariate logistic regression model to identify ICAS-LVO before EVT. ICAS-LVO was defined as presence of angiographic residual stenosis or a trend to re-occlusion during EVT procedure. A total of 338 patients were included in the study. Of them, 28 patients (8.3%) presented with ICAS-LVO. After adjusting for confounders, absence of atrial fibrillation (OR 9.33, 95% CI 1.11-78.42; p = 0.040), lower hypoperfusion intensity ratio (HIR [Tmax > 10 s/Tmax > 6 s ratio], (OR 0.69, 95% CI 0.50-0.95; p = 0.025), symptomatic intracranial artery calcification (IAC, OR .15, 95% CI 1.64-26.42, p = 0.006), a more proximal occlusion (ICA, MCA-M1: OR 4.00, 95% CI 1.23-13.03; p = 0.021), and smoking (OR 2.91, 95% CI 1.08-7.90; p = 0.035) were associated with ICAS-LVO. The clinico-radiological model showed an overall well capability to identify ICAS-LVO (AUC = 0.88, 95% CI 0.83-0.94; p < 0.001). In conclusion, a combination of clinical and radiological features available before EVT can help to identify an ICAS-LVO. This approach could be useful to perform a rapid assessment of underlying etiology and suggest specific pathophysiology-based measures. Prospective studies are needed to validate these findings in other populations.

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