RAPID Automated Patient Selection for Reperfusion Therapy: a Pooled Analysis of the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET) and the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution (DEFUSE) Study

Background And Purpose: The aim of this study was to determine if automated MRI analysis software (RAPID) can be used to identify patients with stroke in whom reperfusion is associated with an increased chance of good outcome.

Methods: Baseline diffusion- and perfusion-weighted MRI scans from the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution study (DEFUSE; n=74) and the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET; n=100) were reprocessed with RAPID. Based on RAPID-generated diffusion-weighted imaging and perfusion-weighted imaging lesion volumes, patients were categorized according to 3 prespecified MRI profiles that were hypothesized to predict benefit (Target Mismatch), harm (Malignant), and no effect (No Mismatch) from reperfusion. Favorable clinical response was defined as a National Institutes of Health Stroke Scale score of 0 to 1 or a ≥ 8-point improvement on the National Institutes of Health Stroke Scale score at Day 90.

Results: In Target Mismatch patients, reperfusion was strongly associated with a favorable clinical response (OR, 5.6; 95% CI, 2.1 to 15.3) and attenuation of infarct growth (10 ± 23 mL with reperfusion versus 40 ± 44 mL without reperfusion; P<0.001). In Malignant profile patients, reperfusion was not associated with a favorable clinical response (OR, 0.74; 95% CI, 0.1 to 5.8) or attenuation of infarct growth (85 ± 74 mL with reperfusion versus 95 ± 79 mL without reperfusion; P=0.7). Reperfusion was also not associated with a favorable clinical response (OR, 1.05; 95% CI, 0.1 to 9.4) or attenuation of lesion growth (10 ± 15 mL with reperfusion versus 17 ± 30 mL without reperfusion; P=0.9) in No Mismatch patients.

Conclusions: MRI profiles that are associated with a differential response to reperfusion can be identified with RAPID. This supports the use of automated image analysis software such as RAPID for patient selection in acute stroke trials.