Incorporating ADC temporal profiles in acute stroke to predict ischemic tissue fate

INTRODUCTION The mismatch between the perfusion and diffusion abnormality – widely considered to approximate the ischemic penumbra – indicates tissue at risk for infarction but potentially salvageable [1]. The perfusion-diffusion mismatch has been utilized to guide thrombolytic therapy and offers predictive value of ischemic tissue fate. Predictive models have employed multiple acute MRI parameters [2]. These predictive models, however, have been limited to using data from only a single time point. In principle, understanding the temporal evolution of apparent diffusion coefficient (ADC) should help to improve prediction accuracy. For example, tissue with mild ADC reduction followed by further ADC reduction will be more likely to infarct than not, whereas tissue with mild ADC reduction followed by ADC returning toward a normal value at a subsequent time point will likely recover. In this study, we propose a novel approach to incorporate quantitative temporal profiles of acute ADC changes to characterize tissue fate on a pixel-by-pixel basis. Analysis was performed on stroke rats subjected to permanent and 60-min middle cerebral artery occlusion (MCAO).