Loss of function and subsequent spontaneous recovery after stroke have been associated with physiological and anatomical alterations in neuronal networks in the brain. However, the spatiotemporal pattern of such changes has been incompletely characterized. Manganese-enhanced MRI (MEMRI) provides a unique tool for in vivo investigation of neuronal connectivity. In this study, we measured manganese-induced changes in longitudinal relaxation rate, R(1), to assess the spatiotemporal pattern of manganese distribution after focal injection into the intact sensorimotor cortex in control rats (n=10), and in rats at 2 weeks after 90-min unilateral occlusion of the middle cerebral artery (n=10). MEMRI data were compared with results from conventional tract tracing with wheat-germ agglutinin horseradish peroxidase (WGA-HRP). Distinct areas of the sensorimotor pathway were clearly visualized with MEMRI. At 2 weeks after stroke, manganese-induced changes in R(1) were significantly delayed and diminished in the ipsilateral caudate putamen, thalamus and substantia nigra. Loss of connectivity between areas of the sensorimotor network was also identified from reduced WGA-HRP staining in these areas on post-mortem brain sections. This study demonstrates that MEMRI enables in vivo assessment of spatiotemporal alterations in neuronal connectivity after stroke, which may lead to improved insights in mechanisms underlying functional loss and recovery after stroke.
Recent anatomical studies have found that cortical neurons are mainly preserved during the aging process while myelin damage and even axonal loss is prominent throughout the forebrain. We used diffusion tensor imaging (DT-MRI) to evaluate the hypothesis that during the process of normal aging, white matter changes preferentially affect the integrity of long corticocortical association fiber tracts, specifically the superior longitudinal fasciculus II and the cingulum bundle. This would disrupt communication between the frontal lobes and other forebrain regions leading to cognitive impairments. We analyzed DT-MRI datasets from seven young and seven elderly behaviorally characterized rhesus monkeys, creating fractional anisotropy (FA) maps of the brain. Significant age-related reductions in mean FA values were found for the superior longitudinal fasciculus II and the cingulum bundle, as well as the anterior corpus callosum. Comparison of these FA reductions with behavioral measures demonstrated a statistically significant linear relationship between regional FA and performance on a test of executive function. These findings support the hypothesis that alterations to the integrity of these long association pathways connecting the frontal lobe with other forebrain regions contribute to cognitive impairments in normal aging. To our knowledge this is the first investigation reporting such alterations in the aging monkey.
There is increasing interest in using algorithms combining multiple magnetic resonance imaging (MRI) modalities to predict tissue infarction in acute human stroke. We developed and tested a voxel-based generalized linear model (GLM) algorithm to predict tissue infarction in an animal stroke model in order to directly compare predicted outcome with the tissue's histologic outcome, and to evaluate the potential for assessing therapeutic efficacy using these multiparametric algorithms. With acute MRI acquired after unilateral embolic stroke in rats (n=8), a GLM was developed and used to predict infarction on a voxel-wise basis for saline (n=6) and recombinant tissue plasminogen activator (rt-PA) treatment (n=7) arms of a trial of delayed thrombolytic therapy in rats. Pretreatment predicted outcome compared with post-treatment histology was highly accurate in saline-treated rats (0.92+/-0.05). Accuracy was significantly reduced (P=0.04) in rt-PA-treated animals (0.86+/-0.08), although no significant difference was detected when comparing histologic lesion volumes. Animals that reperfused had significantly lower (P<0.01) GLM-predicted infarction risk (0.73+/-0.03) than nonreperfused animals (0.81+/-0.05), possibly reflecting less severe initial ischemic injury and therefore tissue likely more amenable to therapy. Our results show that acute MRI-based algorithms can predict tissue infarction with high accuracy in animals not receiving thrombolytic therapy. Furthermore, alterations in disease progression due to treatment were more sensitively monitored with our voxel-based analysis techniques than with volumetric approaches. Our study shows that predictive algorithms are promising metrics for diagnosis, prognosis and therapeutic evaluation after acute stroke that can translate readily from preclinical to clinical settings.