Leukoaraiosis Predicts Short-term Cognitive But not Motor Recovery in Ischemic Stroke Patients During Rehabilitation.

BACKGROUND: Leukoaraiosis has been shown to impact functional outcomes after acute ischemic stroke. However, its association with domain specific recovery after ischemic stroke is uncertain. We sought to determine whether pre-existing leukoaraiosis is associated with short-term motor and cognitive recovery after stroke. METHODS: We retrospectively studied ischemic stroke patients admitted to acute inpatient rehabilitation (AIR) between January 2013 and September 2015. Patient baseline characteristics, infarct volume, prestroke modified Rankin Scale, stroke cause, rehabilitation length of stay, and Functional Independence Measure (FIM) scores were recorded. Leukoaraiosis severity was graded on brain magnetic resonance imaging using the Fazekas scale. Multiple linear regression was used to determine factors independently associated with the total, cognitive, and motor FIM scores at AIR discharge, respectively. RESULTS: Of 1600 ischemic stroke patients screened, 109 patients were included in the final analysis. After adjustment, the initial National Institute of Health Stroke Scale (ß -0.541, confidence interval [CI] -0.993 to -0.888; P = 0.020) and pre-existing leukoaraiosis severity (ß -1.448, CI -2.861 to -0.034; P = 0.045) independently predicted the total FIM score. Domain specific analysis showed that infarct volume (ß -0.012, CI -0.019 to -0.005; P = 0.002) and leukoaraiosis severity (ß -0.822, CI -1.223 to -0.410; P = 0.0001) independently predicted FIM cognitive scores at discharge from AIR. Leukoaraiosis did not predict FIM motor score (P = 0.17). CONCLUSIONS: Leukoaraiosis severity is an independent predictor of total and cognitive, but not motor FIM scores after AIR for acute ischemic stroke. This highlights that leukoaraiosis affects poststroke recovery in a domain specific fashion, information that may aid counseling of patients and families as well as tailor rehabilitative efforts.

Brain region and epilepsy-associated differences in inflammatory mediator levels in medically refractory mesial temporal lobe epilepsy.

BACKGROUND: Epilepsy patients have distinct immune/inflammatory cell profiles and inflammatory mediator levels in the blood. Although the neural origin of inflammatory cells and mediators has been implied, few studies have measured these inflammatory components in the human brain itself. This study examines the brain levels of chemokines (8), cytokines (14), and vascular injury mediators (3) suspected of being altered in epilepsy. METHODS: Soluble protein extracts of fresh frozen resected hippocampus, entorhinal cortex, and temporal cortex from 58 medically refractory mesial temporal lobe epilepsy subjects and 4 nonepileptic neurosurgical subjects were assayed for 25 inflammation-related mediators using ultrasensitive low-density arrays. RESULTS: Brain mediator levels were compared between regions and between epileptic and nonepileptic cases, showing a number of regional and possible epilepsy-associated differences. Eotaxin, interferon-γ, interleukin (IL)-2, IL-4, IL-12 p70, IL-17A, tumor necrosis factor-α, and intercellular adhesion molecule (ICAM)-1 levels were highest in the hippocampus, the presumptive site of epileptogenesis. Surprisingly, IL-1ß and IL-1α were lowest in the hippocampus, compared to cortical regions. In the temporal cortex, IL-1ß, IL-8, and MIP-1α levels were highest, compared to the entorhinal cortex and the hippocampus. The most pronounced epilepsy-associated differences were decreased levels of eotaxin, IL-1ß, C-reactive protein, and vascular cell adhesion molecule (VCAM)-1 and increased IL-12 p70 levels. Caution must be used in interpreting these results, however, because nonepileptic subjects were emergent neurosurgical cases, not a control group. Correlation analyses of each mediator in each brain region yielded valuable insights into the regulation of these mediator levels in the brain. Over 70 % of the associations identified were between different mediators in a single brain region, providing support for local control of mediator levels. Correlations of different mediators in different brain regions suggested more distributed control mechanisms, particularly in the hippocampus. Interestingly, only four mediators showed robust correlations between the brain regions, yet levels in three of these were significantly different between regions, indicating both global and local controls for these mediators. CONCLUSIONS: Both brain region-specific and epilepsy-associated changes in inflammation-related mediators were detected. Correlations in mediator levels within and between brain regions indicated local and global regulation, respectively. The hippocampus showed the majority of interregional associations, suggesting a focus of inflammatory control between these regions.

TLE lateralization using whole brain structural connectivity.

A prerequisite of temporal lobe epilepsy (TLE) surgery is to lateralize the disease. Recent studies have shown the capability of diffusion weighted MRI (DWMRI) in lateralizing TLE patients. This has been achieved by analyzing diffusion parameters of specific white matter tracts or regions known to be involved in the disease; however, other brain regions and connections have not been investigated for TLE lateralization. Whole brain structural connectivity using DWMRI provides a wealth of information regarding the structural connections in the brain. This information can be explored to find the most effective connections for TLE lateralization. In this work, we investigate the connectivity matrices calculated from DWMRI of 10 left and 10 right TLE patients to find the most effective connections for lateralizing the disease. Linear support vector machine (LSVM) classifier and leave-one-out cross validation scheme are used to estimate classification performance of the connectivity feature subsets. A subset of three connections with 100% classification accuracy is found. The corresponding LSVM classifier may be used to lateralize prospective TLE patients.

Application of MEG coherence in lateralization of mTLE.

Magnetoencephalography (MEG) is a noninvasive imaging method for localization of focal epileptiform activity in patients with epilepsy. This study investigates the cerebral functional abnormalities quantified by MEG coherence laterality in mesial temporal lobe epilepsy (mTLE). Resting state MEG data was analyzed using MEG coherence source imaging (MEG-CSI) method to determine the coherence in 54 anatomical sites in 12 adult mTLE patients and 12 age- and gender-matched controls. MEG coherence laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in insular cortex and both lateral orbitofrontal and superior temporal gyri (p<;0.025). None of these anatomical sites showed statistically significant differences in coherence laterality between right and left sides of controls. Coherence laterality was in agreement with the declared side of epileptogenicity in insular cortex (in 75% of patients) and both lateral orbitofrontal (83%) and superior temporal gyri (84%). Combining all significant laterality indices improved the lateralization accuracy to 92%. The proposed methodology for using MEG to investigate the abnormalities related to focal epileptogenicity and propagation can provide a further means of noninvasive lateralization.

Application of DTI connectivity in lateralization of mTLE.

Diffusion tensor imaging (DTI) is a noninvasive imaging method for measuring the diffusion properties of the underlying white matter tracts through which epileptiform activity is propagated. This study investigates the structural abnormalities quantified by DTI in mesial temporal lobe epilepsy (mTLE). Fiber tracts passing through 54 anatomical sites in 12 adult mTLE patients and 12 age- and gender-matched controls were identified using DTI tractography. DTI nodal degree (ND) and laterality index were then calculated. ND laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in gyrus rectus, insular cortex, precuneus and superior temporal gyrus (p<;0.025). None of these anatomical sites showed statistically significant differences in ND laterality between right and left sides of the controls. Laterality models determined by logistic regression on the ND laterality data agreed with the side of epileptogenicity as it pertained to the gyrus rectus, insular cortex, precuneus and superior temporal gyrus for 89%, 72%, 83% and 92% of the patients, respectively. Combining the laterality measures in these four anatomical sites improved the results further with correct lateralization of 100% for all patients. The proposed methodology for using DTI connectivity to investigate diffusion abnormalities related to focal epileptogenicity and propagation can provide a further means of noninvasive lateralization.

Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models.

PURPOSE: Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. METHODS AND MATERIALS: The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. RESULTS: A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. CONCLUSION: The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment.

Lateralization of temporal lobe epilepsy using a novel uncertainty analysis of MR diffusion in hippocampus, cingulum, and fornix, and hippocampal volume and FLAIR intensity.

PURPOSE: To analyze the utility of a quantitative uncertainty analysis approach for evaluation and comparison of various MRI findings for the lateralization of epileptogenicity in mesial temporal lobe epilepsy (mTLE), including novel diffusion-based analyses. METHODS: We estimated the hemispheric variation uncertainty (HVU) of hippocampal T1 volumetry and FLAIR (Fluid Attenuated Inversion Recovery) intensity. Using diffusion tensor images of 23 nonepileptic subjects, we estimated the HVU levels of mean diffusivity (MD) in the hippocampus, and fractional anisotropy (FA) in the posteroinferior cingulum and crus of fornix. Imaging from a retrospective cohort of 20 TLE patients who had undergone surgical resection with Engel class I outcomes was analyzed to determine whether asymmetry of preoperative volumetrics, FLAIR intensities, and MD values in hippocampi, as well as FA values in posteroinferior cingula and fornix crura correctly predicted laterality of seizure onset. Ten of the cohort had pathologically proven mesial temporal sclerosis (MTS). Seven of these patients had undergone extraoperative electrocorticography (ECoG) for lateralization or to rule out extra-temporal foci. RESULTS: HVU was estimated to be 3.1×10(-5) for hippocampal MD, 0.027 for FA in posteroinferior cingulum, 0.018 for FA in crus of fornix, 0.069 for hippocampal normalized volume, and 0.099 for hippocampal normalized FLAIR intensity. Using HVU analysis, a higher hippocampal MD value, lower FA within the posteroinferior cingulum and crus of fornix, shrinkage in hippocampal volume, and higher hippocampal FLAIR intensity were observed beyond uncertainty on the side ipsilateral to seizure onset for 10, 10, 9, 9, and 10 out of 10 pathology-proven MTS patients, respectively. Considering all 20 TLE patients, these numbers were 18, 15, 14, 13, and 16, respectively. However, consolidating the lateralization results of HVU analysis on these quantities by majority voting has detected the epileptogenic side for 19 out of 20 cases with no wrong lateralization. CONCLUSION: The presence of MTS in TLE patients is associated with an elevated MD value in the ipsilateral hippocampus and a reduced FA value in the posteroinferior subregion of the ipsilateral cingulum and crus of ipsilateral fornix. When considering all TLE patients, among the mentioned biomarkers the hippocampal MD had the best performance with true detection rate of 90% without any wrong lateralization. The proposed uncertainty based analyses hold promise for improving decision-making for surgical resection.

Lateralization of temporal lobe epilepsy by imaging-based response-driven multinomial multivariate models.

We have developed response-driven multinomial models, based on multivariate imaging features, to lateralize the epileptogenicity in temporal lobe epilepsy (TLE) patients. To this end, volumetrics and statistical quantities of FLAIR intensity and normalized ictal-interictal SPECT intensity on left and right hippocampi were extracted from preoperative images of forty-five retrospective TLE patients with surgical outcome of Engel class l. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Among univariate response models, the response model with SPECT attributes and response model with mean FLAIR attributes achieved the lowest fit deviance (65.1±0.2 and 65.5±0.3, respectively). They resulted in the highest probability of detection (0.82) and lowest probability of false alarm (0.02) for the epileptogenic side. The multivariate response model with incorporating all volumetrics, mean and standard deviation FLAIR, and SPECT attributes achieved a significantly lower fit deviance than other response models (11.9±0.1, p <; 0.001). It reached probability of detection of 1 with no false alarms. We were able to correctly lateralize the fifteen TLE patients who had undergone phase II intracranial monitoring. Therefore, the phase II intracranial monitoring might have been avoided for this set of patients. Based on this lateralization response model, the side of epileptogenicity was also detected for all thirty patients who had preceded to resection with only phase I of EEG monitoring. In conclusion, the proposed multinomial multivariate response-driven model for lateralization of epileptogenicity in TLE patients can help in decision-making prior to surgical resection and may reduce the need for implantation of intracranial monitoring electrodes.

Tract based spatial statistical analysis and voxel based morphometry of diffusion indices in temporal lobe epilepsy.

White matter (WM) microstructure can be evaluated by diffusion tensor imaging (DTI). Tract-based spatial statistical (TBSS) analysis provides a means of assessing alterations in WM tracts. In this paper, both voxel-based morphometry (VBM) and TBSS are examined using DTI data of temporal lobe epilepsy (TLE) patients and nonepileptic subjects. In addition to fractional anisotropy (FA), ellipsoidal area ratio (EAR) is used in this study. Significant reductions of FA and EAR are identified by TBSS in the parahippocampal white matter. Because of methodological differences, TBSS detects more localized abnormalities than VBM, while the EAR is more sensitive to WM alteration than FA.

Dataset of magnetic resonance images of nonepileptic subjects and temporal lobe epilepsy patients for validation of hippocampal segmentation techniques.

The hippocampus has become the focus of research in several neurodegenerative disorders. Automatic segmentation of this structure from magnetic resonance (MR) imaging scans of the brain facilitates this work. Segmentation techniques must be evaluated using a dataset of MR images with accurate hippocampal outlines generated manually. Manual segmentation is not a trivial task. Lack of a unique segmentation protocol and poor image quality are only two factors that have confounded the consistency required for comparative study. We have developed a publicly available dataset of T1-weighted (T1W) MR images of epileptic and nonepileptic subjects along with their hippocampal outlines to provide a means of evaluation of segmentation techniques. This dataset contains 50 T1W MR images, 40 epileptic and ten nonepileptic. All images were manually segmented by a widely used protocol. Twenty five images were selected for training and were provided with hippocampal labels. Twenty five other images were provided without labels for testing algorithms. The users are allowed to evaluate their generated labels for the test images using 11 segmentation similarity metrics. Using this dataset, we evaluated two segmentation algorithms, Brain Parser and Classifier Fusion and Labeling (CFL), trained by the training set. For Brain Parser, an average Dice coefficient of 0.64 was obtained with the testing set. For CFL, this value was 0.75. Such findings indicate a need for further improvement of segmentation algorithms in order to enhance reliability.

Knowledge-based localization of hippocampus in human brain MRI.

We present a novel and efficient method for localization of human brain structures such as hippocampus. Landmark localization is important for segmentation and registration. This method follows a statistical roadmap, consisting of anatomical landmarks, to reach the desired structures. Using a set of desired and undesired landmarks, identified on a training set, we estimate Gaussian models and determine optimal search areas for desired landmarks. The statistical models form a set of rules to evaluate the extracted landmarks during the search procedure. When applied on 900 MR images of 10 epileptic patients, this method demonstrated an overall success rate of 83%.

Influence of ionizing radiation on the course of kindled epileptogenesis.

Several clinical and experimental reports suggest that low-dose irradiation of an established epileptic focus can reduce the occurrence of spontaneous seizures. Conversely, some recent reports suggest that under some conditions low-dose irradiation may have disinhibitory effects on seizure expression. Here, we have investigated mechanistic aspects of this phenomenon in the kindling model of epilepsy by applying focal irradiation at various points during kindling development. Rats were kindled to stage 5 by afterdischarge-threshold electrostimulation of the left amygdala. Treatment groups were irradiated using a collimated X-ray beam (18 MV) either prior to kindling, at kindling stage 3, or at kindling stage 5, by exposure of the left amygdala to a single-fraction central-axis dose of 25 Gy. Generalized seizure thresholds (GSTs) were subsequently assayed at weekly intervals for 10 weeks and at monthly intervals for an additional 3 months, along with the severity of the evoked seizures. Irradiation produced no significant effects on seizure threshold, but did produce persistent changes in seizure severity which varied as a function of the timing of irradiation. Relative to sham irradiated controls, the occurrence of stage 6 seizures was significantly increased by irradiation prior to kindling, but was unaffected by irradiation at kindling stage 3, and significantly reduced by irradiation at kindling stage 5. Quantitative immunohistochemical assays for neuron and astrocyte densities within the amygdala and hippocampus revealed only subtle changes in neuronal density within the dentate granule cell layer. These results are discussed in relation to mechanisms of seizure- and radiation-induced plasticity.

Effects of kindling and irradiation on neuronal density in the rat dentate gyrus.

Low-dose radiosurgery is presently in use as a treatment modality for focal epilepsy, but the mechanisms underlying the associated changes in seizure expression are poorly understood. We investigated whether total and parvalbumin expressing (PV+) neuronal densities within the hippocampus and amygdala are affected by analogous focal irradiation in amygdala-kindled rats. Adult rats were kindled by electrical stimulation through 10 stage 5 seizures. The kindled amygdala was then focally irradiated at 18 or 25 Gy, and generalized seizure thresholds were subsequently monitored for approximately 6 months. Histological and immunohistochemical assays of total and PV+ neuronal densities were performed bilaterally throughout the hippocampus and within the basolateral amygdala. PV+ neuronal densities were unaffected by kindling or irradiation in these regions. Kindling selectively reduced neuronal densities in the dentate granule cell layer, and medial CA3 pyramidal cell layer. Irradiation at 25 Gy, but not at 18 Gy, prevented or reversed this kindling-associated reduction in density.