Bouts MJRJ, Westmoreland SV, de Crespigny AJ, Liu Y, Vangel M, Dijkhuizen RM, Wu O, D'Arceuil HE. Magnetic resonance imaging-based cerebral tissue classification reveals distinct spatiotemporal patterns of changes after stroke in non-human primates. BMC Neurosci 2015;16:91.Abstract
    BACKGROUND: Spatial and temporal changes in brain tissue after acute ischemic stroke are still poorly understood. Aims of this study were three-fold: (1) to determine unique temporal magnetic resonance imaging (MRI) patterns at the acute, subacute and chronic stages after stroke in macaques by combining quantitative T2 and diffusion MRI indices into MRI 'tissue signatures', (2) to evaluate temporal differences in these signatures between transient (n = 2) and permanent (n = 2) middle cerebral artery occlusion, and (3) to correlate histopathology findings in the chronic stroke period to the acute and subacute MRI derived tissue signatures. RESULTS: An improved iterative self-organizing data analysis algorithm was used to combine T2, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) maps across seven successive timepoints (1, 2, 3, 24, 72, 144, 240 h) which revealed five temporal MRI signatures, that were different from the normal tissue pattern (P < 0.001). The distribution of signatures between brains with permanent and transient occlusions varied significantly between groups (P < 0.001). Qualitative comparisons with histopathology revealed that these signatures represented regions with different histopathology. Two signatures identified areas of progressive injury marked by severe necrosis and the presence of gitter cells. Another signature identified less severe but pronounced neuronal and axonal degeneration, while the other signatures depicted tissue remodeling with vascular proliferation and astrogliosis. CONCLUSION: These exploratory results demonstrate the potential of temporally and spatially combined voxel-based methods to generate tissue signatures that may correlate with distinct histopathological features. The identification of distinct ischemic MRI signatures associated with specific tissue fates may further aid in assessing and monitoring the efficacy of novel pharmaceutical treatments for stroke in a pre-clinical and clinical setting.
    Bouts MJRJ, Tiebosch IA, van der Toorn A, Viergever MA, Wu O, Dijkhuizen RM. Early identification of potentially salvageable tissue with MRI-based predictive algorithms after experimental ischemic stroke. J Cereb Blood Flow Metab 2013;33(7):1075-82.Abstract
    Individualized stroke treatment decisions can be improved by accurate identification of the extent of salvageable tissue. Magnetic resonance imaging (MRI)-based approaches, including measurement of a 'perfusion-diffusion mismatch' and calculation of infarction probability, allow assessment of tissue-at-risk; however, the ability to explicitly depict potentially salvageable tissue remains uncertain. In this study, five predictive algorithms (generalized linear model (GLM), generalized additive model, support vector machine, adaptive boosting, and random forest) were tested in their potency to depict acute cerebral ischemic tissue that can recover after reperfusion. Acute T2-, diffusion-, and perfusion-weighted MRI, and follow-up T2 maps were collected from rats subjected to right-sided middle cerebral artery occlusion without subsequent reperfusion, for training of algorithms (Group I), and with spontaneous (Group II) or thrombolysis-induced reperfusion (Group III), to determine infarction probability-based viability thresholds and prediction accuracies. The infarction probability difference between irreversible-i.e., infarcted after reperfusion-and salvageable tissue injury-i.e., noninfarcted after reperfusion-was largest for GLM (20±7%) with highest accuracy of risk-based identification of acutely ischemic tissue that could recover on subsequent reperfusion (Dice's similarity index=0.79±0.14). Our study shows that assessment of the heterogeneity of infarction probability with MRI-based algorithms enables estimation of the extent of potentially salvageable tissue after acute ischemic stroke.
    Wu O, Sumii T, Asahi M, Sasamata M, Ostergaard L, Rosen BR, Lo EH, Dijkhuizen RM. Infarct prediction and treatment assessment with MRI-based algorithms in experimental stroke models. J Cereb Blood Flow Metab 2007;27(1):196-204.Abstract
    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.
    van Eijsden P, Notenboom RGE, Wu O, de Graan PNE, van Nieuwenhuizen O, Nicolay K, Braun KPJ. In vivo 1H magnetic resonance spectroscopy, T2-weighted and diffusion-weighted MRI during lithium-pilocarpine-induced status epilepticus in the rat. Brain Res 2004;1030(1):11-8.Abstract
    Temporal lobe epilepsy (TLE) is associated with febrile convulsions and childhood status epilepticus (SE). Since the initial precipitating injury, triggering epileptogenesis, occurs during this SE, we aimed to examine the metabolic and morphological cerebral changes during the acute phase of experimental SE noninvasively. In the rat lithium-pilocarpine model of SE, we performed quantified T(2)- and isotropic-diffusion-weighted (DW) magnetic resonance imaging (MRI) at 3 and 5 h of SE and acquired single-voxel (1)H MR spectra at 2, 4 and 6 h of SE. T(2) was globally decreased, most pronounced in the amygdala (Am) and piriformic cortex (Pi), in which also a significant decrease in apparent diffusion coefficient (ADC) was found. In contrast, ADC values increased transiently in the hippocampus (HC) and thalamus (Th). MR spectra showed a decrease in N-acetylaspartate (NAA) and choline (Cho) and an increase of lactate in a hippocampal voxel. The T(2) decrease, attributed to raised deoxyhemoglobin, and the presence of lactate both indicate a mismatch between oxygen demand and delivery. The ADC decrease, indicative of excitotoxicity, confirms that the amygdala and piriformic cortex are particularly vulnerable to lithium-pilocarpine-induced seizures. The transient ADC increase in the thalamus may reflect the breakdown of the blood-brain barrier (BBB), which is shown to occur in this region at these time points. Neuronal damage and failure of energy-dependent formation of NAA are likely causes of an observed decrease in NAA, while the decrease in Cho is possibly due to depletion of the cholinergic system. This study illustrates that relative hypoxia, excitotoxicity and concomitant neuronal damage associated with SE can be probed noninvasively with MR. These pathological phenomena are the first to contribute to the pathophysiology of spontaneous recurrent seizures in a later stage in this animal model.