The Rapid Occluded Vessel Etiology Score: A Novel Algorithm to Identify Acute Atherosclerotic Large Vessel Occlusions of the Middle Cerebral Artery
Recommended Citation
Fana M, Choudhury O, Bou Chebl A, Latack K, Schultz L, Albanna A, Reardon T, Iqbal Z, Kole M, Marin H. The Rapid Occluded Vessel Etiology Score: A Novel Algorithm to Identify Acute Atherosclerotic Large Vessel Occlusions of the Middle Cerebral Artery. Stroke 2025; 56.
Document Type
Conference Proceeding
Publication Date
1-30-2025
Publication Title
Stroke
Abstract
Introduction: Mechanical thrombectomy (MT) devices were fundamentally designed for the treatment of cardioembolic (CE) strokes despite that 10-20% of large vessel occlusions (LVO) are caused by large artery atherosclerosis (LAA), which may not respond comparably. Therefore, the differentiation between LAA and non-LAA LVO may be critical for selecting the ideal MT technique. Here, we construct an algorithm for use in the emergent setting pre-operatively to differentiate between LAA and non-LAA LVO using clinical and radiographic features. Methods: Using our prospectively collected stroke database we identified all middle cerebral artery (MCA) occlusions treated with MT with confirmed etiology as either LAA or non-LAA (CE, cryptogenic) according to TOAST criteria. Stroke risk factors and CT angiography (CTA) of the head and neck features were compared between LAA and non-LAA etiologies in a univariate analysis. An algorithm was then constructed using these variables in a multivariable logistic regression with corresponding score estimates for each variable to assess how well the model distinguished between LAA and non-LAA groups. The sensitivity and specificity were computed for each sum score to identify the ideal cut-off point for differentiating LAA from non-LAA LVOs. Results: Final analysis included 33 LAA, 207 CE, and 120 cryptogenic strokes. Patients presenting with LAA LVOs were significantly less likely to have atrial fibrillation (9.1% vs 53.8%; p<0.0001), EF<35% (9.1% vs 27.8%; p=0.0208) and more likely to present with progressive or fluctuating symptoms (21.2% vs 4.6%; p=0.0018), intracranial multi-vessel atherosclerotic disease on CTA (84.8% vs 37%; p<0.0001), tapered appearance of occlusion with associated collaterals (60.6% vs 0.9%; p<0.0001), and ICA bulb plaque with high-risk features (87.9% vs 37.6%; p<0.0001) (Table 1). The AUC was 0.9650 (95% CI=0.9332, 0.9968) and the highest combination of sensitivity and specificity (97% and 88%, respectively) was associated with a cut-off score of 9 (Tables 2 and 3). Conclusion: Our scoring system reliably differentiates between non-LAA and LAA LVO with high sensitivity and specificity based on 6 clinical and radiographic features. This will need to be validated with an external patient dataset and then in a prospective study. .
Volume
56
