Benefit of endovascular recanalization beyond established treatment time windows likely exists in select stroke patients. However, there is currently no imaging model that predicts infarction adjusting for elapsed time between the pathologic snapshot of admission imaging until endovascular recanalization. We trained and cross validated a multivariate generalized linear model (GLM) that uses computer tomography perfusion and clinical data to quantify patient-specific dynamic change of tissue infarction depending on degree and time of recanalization. Multicenter data of 161 patients with proximal anterior circulation occlusion undergoing endovascular therapy were included. Multivariate voxelwise infarct probability was calculated within the GLM. The effect of increasing time to treatment and degree of recanalization on voxelwise infarction was calculated in each patient. Tissue benefit of successful relative to unsuccessful recanalization was shown up to 15 hours after onset in individual patients and decreased nonlinearly with time. On average, the relative reduction of infarct volume at the treatment interval of 5 hours was 53% and this salvage effect decreased by 5% units per hour to o 5% after 10 additional hours to treatment. Treatment time-adjusted multivariate prediction of infarction by perfusion and clinical status may identify patients who benefit from extended time to recanalization therapy.
Kemmling et al. REF use a multivariate computed tomography perfusion (CTP)-based model to calculate the probability of voxelwise infarcts.
Multivariate Dynamic Prediction of Ischemic Infarction and Tissue Salvage as a Function of Time and Degree of Recanalization
Journal of Cerebral Blood Flow & Metabolism
Medicine