PT - JOURNAL ARTICLE AU - Eilaghi, A. AU - d'Esterre, C.D. AU - Lee, T.Y. AU - Jakubovic, R. AU - Brooks, J. AU - Liu, R.T.-K. AU - Zhang, L. AU - Swartz, R.H. AU - Aviv, R.I. TI - Toward Patient-Tailored Perfusion Thresholds for Prediction of Stroke Outcome AID - 10.3174/ajnr.A3740 DP - 2014 Mar 01 TA - American Journal of Neuroradiology PG - 472--477 VI - 35 IP - 3 4099 - http://www.ajnr.org/content/35/3/472.short 4100 - http://www.ajnr.org/content/35/3/472.full SO - Am. J. Neuroradiol.2014 Mar 01; 35 AB - BACKGROUND AND PURPOSE: Multiple patient-specific clinical and radiologic parameters impact traditional perfusion thresholds used to classify/determine tissue outcome. We sought to determine whether modified baseline perfusion thresholds calculated by integrating baseline perfusion and clinical factors better predict tissue fate and clinical outcome. MATERIALS AND METHODS: CTP within 4.5 hours of acute anterior circulation stroke onset and 5- to 7-day MR imaging were performed for 203 patients with stroke, divided into derivation (n = 114) and validation (n = 89) data bases. Affected regions were operationally classified as infarct and noninfarct according to baseline CTP and follow-up FLAIR imaging. Perfusion thresholds were derived for each of the infarct and noninfarct regions, without and with transformation by baseline clinical and radiologic variables by using a general linear mixed model. Performance of transformed and nontransformed perfusion thresholds for tissue fate and 90-day clinical outcome prediction was then tested in the derivation data base. Reproducibility of models was verified by using bootstrapping and validated in an independent cohort. RESULTS: Perfusion threshold transformation by clinical and radiologic baseline parameters significantly improved tissue fate prediction for both gray matter and white matter (P < .001). Transformed thresholds improved the 90-day outcome prediction for CBF and time-to-maximum (P < .001). Transformed relative CBF and absolute time-to-maximum values demonstrated maximal GM and WM accuracies in the derivation and validation cohorts (relative CBF GM: 91%, 86%; WM: 86%, 83%; absolute time-to-maximum 88%, 79%, and 80%, 76% respectively). CONCLUSIONS: Transformation of baseline perfusion parameters by patient-specific clinical and radiologic parameters significantly improves the accuracy of tissue fate and clinical outcome prediction. Tmaxtime-to-maximum