A novel neuroimaging model to predict early neurological deterioration after acute ischemic stroke

Objective: In acute ischemic stroke, early neurological deterioration (END) may occur in up to one-third of patients. However, there is still no satisfying or comprehensive predictive model for all the stroke subtypes. We propose a practical model to predict END using magnetic resonance imaging (MRI). Method: Patients with anterior circulation infarct were recruited and they underwent an MRI within 24 hours of stroke onset. END was defined as an elevation of ≥2 points on the National Institute of Health Stroke Scale (NIHSS) within 72 hours of stroke onset. We examined the relationships of END to individual END models, including: A, infarct swelling; B, small subcortical infarct; C, mismatch; and D, recurrence. Results: There were 163 patients recruited and 43 (26.4%) of them had END. The END models A, B and C significantly predicted END respectively after adjusting for confounding factors (p=0.022, p=0.007 and p<0.001 respectively). In END model D, we examined all imaging predictors of Recurrence Risk Estimator (RRE) individually and only the “multiple acute infarcts” pattern was significantly associated with END (p=0.032). When applying END models A, B, C and D, they successfully predicted END (p<0.001; odds ratio: 17.5[95% confidence interval: 5.1– 60.8]), with 93.0% sensitivity, 60.0% specificity, 45.5% positive predictive value and 96.0% negative predictive value. Conclusion: The results demonstrate that the proposed model could predict END in all stroke subtypes of anterior circulation infarction. It provides a practical model for clinical physicians to select high-risk patients for more aggressive treatment to prevent END.