CT Permeability Imaging Predicts Clinical Outcomes in Acute Ischemic Stroke Patients Treated with Intra-arterial Thrombolytic Therapy

In this study, we determined whether a prediction of final infarct volume (FIV) and clinical outcomes in patients with an acute stroke is improved by using a contrast transfer coefficient (K^trans) as a biomarker for blood–brain barrier (BBB) dysfunction. Here, consecutive patients admitted with signs and symptoms suggesting acute hemispheric stroke were included in this study. Ninety-eight participants with intra-arterial therapy were assessed (46 female). Definition of predicted FIV was performed using conventional perfusion CT (PCT-PIV) parameters alone and in combination with K^trans (K^trans-PIV). Multiple logistic regression analyses and linear regression modeling were conducted to determine independent predictors of the 90-day modified Rankin score (mRS) and FIV, respectively. We found that patients with favorable outcomes were younger and had lower National Institutes of Health Stroke Scale (NIHSS) score, smaller PCT-PIV, K^trans-PIV, and smaller FIV (P < 0.001). K^trans-PIV showed good correlation with FIV (P < 00.001, R² = 0.6997). In the regression analyses, K^trans-PIV was the best predictor of clinical outcomes (P = 0.009, odds ratio (OR) = 1.960) and also the best predictor for FIV (F = 75.590, P < 0.0001). In conclusion, combining PCT and K^trans maps derived from first-pass PCT can identify at-risk cerebral ischemic tissue more precisely than perfusion parameters alone. This provides improved accuracy in predicting FIV and clinical outcomes.