BACKGROUND Whether brain imaging can identify patients who are most likely to benefit from therapies for acute ischemic stroke and whether endovascular thrombectomy improves clinical outcomes in such patients remains unclear. METHODS In this study, we randomly assigned patients within 8 hours after the onset of large-vessel, anterior-circulation strokes to undergo mechanical embolectomy (Merci Retriever or Penumbra System) or receive standard care. All patients underwent pretreatment computed tomography or magnetic resonance imaging of the brain. Randomization was stratified according to whether the patient had a favorable penumbral pattern (substantial salvageable tissue and small infarct core) or a non-penumbral pattern (large core or small or absent penumbra). We assessed outcomes using the 90-day modified Rankin scale, ranging from 0 (no symptoms) to 6 (dead). RESULTS Among 118 eligible patients, the mean age was 65.5 years, the mean time to enrollment was 5.5 hours, and 58% had a favorable penumbral pattern. Revascularization in the embolectomy group was achieved in 67% of the patients. Ninety-day mortality was 21%, and the rate of symptomatic intracranial hemorrhage was 4%; neither rate differed across groups. Among all patients, mean scores on the modified Rankin scale did not differ between embolectomy and standard care (3.9 vs. 3.9, P = 0.99). Embolectomy was not superior to standard care in patients with either a favorable penumbral pattern (mean score, 3.9 vs. 3.4; P = 0.23) or a nonpenumbral pattern (mean score, 4.0 vs. 4.4; P = 0.32). In the primary analysis of scores on the 90-day modified Rankin scale, there was no interaction between the pretreatment imaging pattern and treatment assignment (P = 0.14). CONCLUSIONS A favorable penumbral pattern on neuroimaging did not identify patients who would differentially benefit from endovascular therapy for acute ischemic stroke, nor was embolectomy shown to be superior to standard care. (Funded by the National Institute of Neurological Disorders and Stroke; MR RESCUE ClinicalTrials.gov number, NCT00389467.)

Background. Motor recovery after stroke is predicted only moderately by clinical variables, implying that there is still a substantial amount of unexplained, biologically meaningful variability in recovery. Regression diagnostics can indicate whether this is associated simply with Gaussian error or instead with multiple subpopulations that vary in their relationships to the clinical variables. Objective. To perform regression diagnostics on a linear model for recovery versus clinical predictors. Methods. Forty-one patients with ischemic stroke were studied. Impairment was assessed using the upper extremity Fugl-Meyer Motor Score. Motor recovery was defined as the change in the upper extremity Fugl-Meyer Motor Score from 24 to 72 hours after stroke to 3 or 6 months later. The clinical predictors in the model were age, gender, infarct location (subcortical vs cortical), diffusion weighted imaging infarct volume, time to reassessment, and acute upper extremity Fugl-Meyer Motor Score. Regression diagnostics included a Kolmogorov-Smirnov test for Gaussian errors and a test for outliers using Studentized deleted residuals. Results. In the random sample, clinical variables explained only 47% of the variance in recovery. Among the patients with the most severe initial impairment, there was a set of regression outliers who recovered very poorly. With the outliers removed, explained variance in recovery increased to 89%, and recovery was well approximated by a proportional relationship with initial impairment (recovery ≅ 0.70 × initial impairment). Conclusions. Clinical variables only moderately predict motor recovery. Regression diagnostics demonstrated the existence of a subpopulation of outliers with severe initial impairment who show little recovery. When these outliers were removed, clinical variables were good predictors of recovery among the remaining patients, showing a tight proportional relationship to initial impairment.

Background and Purpose-Recovery from hemiparesis due to corticospinal tract infarction is well documented, but the mechanism of recovery is unknown. Functional MRI (fMRI) provides a means of identifying focal brain activity related to movement of a paretic hand. Although prior studies have suggested that supplementary motor regions in the ipsilesional and contralesional hemisphere play a role in recovery, little is known about the time course of cortical activation in these regions as recovery proceeds. Methods-Eight patients with first-ever corticospinal tract lacunes causing hemiparesis had serial fMRIs within the first few days after stroke and at 3 to 6 months. Six healthy subjects were used as controls. Statistically significant voxels during a finger-thumb opposition task were identified with an automated image processing program. An index of ipsilateral versus contralateral activity was used to compare relative contributions of the 2 hemispheres to motor function in the acute and chronic phases after stroke. Results-Controls showed expected activation in the contralateral sensorimotor cortex (SMC), premotor, and supplementary motor areas. Stroke patients differed from control patients in showing greater activation in the ipsilateral SMC, ipsilateral posterior parietal, and bilateral prefrontal regions. Compared with the nonparetic hand, the ratio of contralateral to ipsilateral SMC activity during movement of the paretic hand increased significantly over time as the paretic hand regained function. Conclusions-The evolution of activation in the SMC from early contralesional activity to late ipsilesional activity suggests that a dynamic bihemispheric reorganization of motor networks occurs during recovery from hemiparesis.