Spatiotemporal microstructural white matter changes in diffusion tensor imaging after transient focal ischemic stroke in rats

Structural reorganization in white matter (WM) after stroke is a potential contributor to substitute or to newly establish the functional field on the injured brain in nature. Diffusion tensor imaging (DTI) is an imaging modality that can be used to evaluate damage and recovery within the brain. This method of imaging allows for in vivo assessment of the restricted movements of water molecules in WM and provides a detailed look at structural connectivity in the brain. For longitudinal DTI studies after a stroke, the conventional region of interest method and voxel‐based analysis are highly dependent on the user‐hypothesis and parameter settings for implementation. In contrast, tract‐based spatial statistics (TBSS) allows for reliable voxel‐wise analysis via the projection of diffusion‐derived parameters onto an alignment‐invariant WM skeleton. In this study, spatiotemporal WM changes were examined with DTI‐derived parameters (fractional anisotropy, FA; mean diffusivity, MD; axial diffusivity, DA; radial diffusivity, RD) using TBSS 2 h to 6 weeks after experimental focal ischemic stroke in rats (N = 6). FA values remained unchanged 2–4 h after the stroke, followed by a continuous decrease in the ipsilesional hemisphere from 24 h to 2 weeks post‐stroke and gradual recovery from the ipsilesional corpus callosum to the external capsule until 6 weeks post‐stroke. In particular, the fibers in these areas were extended toward the striatum of the ischemic boundary region at 6 weeks on tractography. The alterations of the other parameters in the ipsilesional hemisphere showed patterns of a decrease at the early stage, a subsequent pseudo‐normalization of MD and DA, a rapid reduction of RD, and a progressive increase in MD, DA and RD with a decreased extent in the injured area at later stages. The findings of this study may reflect the ongoing processes on tissue damage and spontaneous recovery after stroke.     

Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping

Background and purposeThe ability to predict high-grade meningioma preoperatively is important for clinical surgical planning. The purpose of this study is to evaluate the performance of comprehensive multiparametric MRI, including susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) in predicting high-grade meningioma both qualitatively and quantitatively.MethodsNinety-two low-grade and 37 higher grade meningiomas in 129 patients were included in this study. Morphological characteristics, quantitative histogram analysis of QSM and ADC images, and tumor size were evaluated to predict high-grade meningioma using univariate and multivariate analyses. Receiver operating characteristic (ROC) analyses were performed on the morphological characteristics. Associations between Ki-67 proliferative index (PI) and quantitative parameters were calculated using Pearson correlation analyses.ResultsFor predicting high-grade meningiomas, the best predictive model in multivariate logistic regression analyses included calcification (β = 0.874, P = 0.110), peritumoral edema (β = 0.554, P = 0.042), tumor border (β = 0.862, P = 0.024), tumor location (β = 0.545, P = 0.039) for morphological characteristics, and tumor size (β = 4 × 10⁻⁵, P = 0.004), QSM kurtosis (β = − 5 × 10⁻³, P = 0.058), QSM entropy (β = − 0.067, P = 0.054), maximum ADC (β = − 1.6 × 10⁻³, P = 0.003), ADC kurtosis (β = − 0.013, P = 0.014) for quantitative characteristics. ROC analyses on morphological characteristics resulted in an area under the curve (AUC) of 0.71 (0.61–0.81) for a combination of them. There were significant correlations between Ki-67 PI and mean ADC (r = − 0.277, P = 0.031), 25^th percentile of ADC (r = − 0.275, P = 0.032), and 50^th percentile of ADC (r = − 0.268, P = 0.037).ConclusionsAlthough SWI and QSM did not improve differentiation between low and high-grade meningiomas, combining morphological characteristics and quantitative metrics can help predict high-grade meningioma.     

Cerebellar swelling after surgery for medulloblastoma with leptomeningeal dissemination in children. A case based-update

ObjectDespite the improvement in the overall management of medulloblastomas in recent years, certain phenomena and in particular postoperative cerebellar swelling remain an enigma. This rare complication, little described in the literature, is nonetheless life threatening for the patients.Case reportsWe report our experience about two children who developed severe cerebellar swelling with hydrocephalus and upward herniation soon after a gross total resection of a fourth ventricle medulloblastoma by a telo-velar approach. Despite rapid management of ventricular dilation and optimal medical intensive treatment of intracranial hypertension, both children died quickly after the surgery. Pathological examination analyses were in favour of anaplastic/large cell medulloblastoma.DiscussionDiffuse cerebellar swelling with upward herniation may occur postoperatively in young children with anaplastic/large cell medulloblastoma with leptomeningeal spread. In the literature, only 4 cases have been so far described with delayed onset of symptoms. Two children survived with an aggressive management (decompressive surgery and early radio-chemotherapy).ConclusionCerebellar swelling is an unrecognised and sudden complication of posterior fossa surgery for metastatic anaplastic medulloblastoma with leptomeningeal dissemination in young children. An initial less invasive surgical approach could be considered in such cases, in order to prevent this complication with potentially tragic issue, and which cannot be managed with a CSF shunt alone.     

Double‐pulsed diffusional kurtosis imaging

Diffusional kurtosis imaging (DKI) is extended to double‐pulsed‐field‐gradient (d‐PFG) diffusion MRI sequences. This gives a practical approach for acquiring and analyzing d‐PFG data. In particular, the leading d‐PFG effects, beyond what conventional single‐pulsed field gradient (s‐PFG) provides, are interpreted in terms of the kurtosis for a diffusion displacement probability density function (dPDF) in a six‐dimensional (6D) space. The 6D diffusional kurtosis encodes the unique information provided by d‐PFG sequences up to second order in the b‐value. This observation leads to a compact expression for the signal magnitude, and it suggests novel data acquisition and analysis methods. Double‐pulsed DKI (DP‐DKI) is demonstrated for in vivo mouse brain with d‐PFG data obtained at 7 T. Copyright © 2014 John Wiley & Sons, Ltd.     

Oscillating gradient diffusion kurtosis imaging of normal and injured mouse brains

Recent advances in diffusion MRI employ multiple diffusion encoding schemes with varying diffusion direction, weighting, and diffusion time to investigate specific microstructural properties in biological tissues. In this study, we examined time‐dependent diffusion kurtosis contrast in adult mouse brains and in neonatal mouse brains after hypoxic–ischemic (HI) injury. In vivo diffusion kurtosis maps were acquired with a short diffusion time using an oscillating gradient spin echo (OGSE) sequence at 100 Hz and with a relatively long diffusion time (20 ms) using a pulsed gradient spin echo (PGSE) sequence. In the adult mouse brain, we found that the cortex and hippocampus showed larger differences between OGSE kurtosis and PGSE kurtosis than major white matter tracts. In neonatal mouse brains with unilateral HI injury, the OGSE kurtosis map overall provided stronger edema contrast than the PGSE kurtosis map, and the differences between OGSE and PGSE kurtosis measurements in the edema region reflected heterogeneity of injury. This is the first in vivo study that has demonstrated multi‐direction OGSE kurtosis contrasts in the mouse brain. Comparing PGSE and OGSE kurtosis measures may provide additional information on microstructural changes after ischemic stroke.     

Methods for identifying subject‐specific abnormalities in neuroimaging data

Algorithms that are capable of capturing subject‐specific abnormalities (SSA) in neuroimaging data have long been an area of focus for diverse neuropsychiatric conditions such as multiple sclerosis, schizophrenia, and traumatic brain injury. Several algorithms have been proposed that define SSA in patients (i.e., comparison group) relative to image intensity levels derived from healthy controls (HC) (i.e., reference group) based on extreme values. However, the assumptions underlying these approaches have not always been fully validated, and may be dependent on the statistical distributions of the transformed data. The current study evaluated variations of two commonly used techniques (“pothole” method and standardization with an independent reference group) for identifying SSA using simulated data (derived from normal, t and chi‐square distributions) and fractional anisotropy maps derived from 50 HC. Results indicated substantial group‐wise bias in the estimation of extreme data points using the pothole method, with the degree of bias being inversely related to sample size. Statistical theory was utilized to develop a distribution‐corrected z‐score (DisCo‐Z) threshold, with additional simulations demonstrating elimination of the bias and a more consistent estimation of extremes based on expected distributional properties. Data from previously published studies examining SSA in mild traumatic brain injury were then re‐analyzed using the DisCo‐Z method, with results confirming the evidence of group‐wise bias. We conclude that the benefits of identifying SSA in neuropsychiatric research are substantial, but that proposed SSA approaches require careful implementation under the different distributional properties that characterize neuroimaging data. Hum Brain Mapp 35:5457–5470, 2014. © 2014 Wiley Periodicals, Inc.     

Large animal models of human cauda equina injury and repair: evaluation of a novel goat model

Previous animal studies of cauda equina injury have primarily used rat models, which display significant differences from humans. Furthermore, most studies have focused on electrophysiological examination. To better mimic the outcome after surgical repair of cauda equina injury, a novel animal model was established in the goat. Electrophysiological, histological and magnetic resonance imaging methods were used to evaluate the morphological and functional outcome after cauda equina injury and end-to-end suture. Our results demonstrate successful establishment of the goat experimental model of cauda equina injury. This novel model can provide detailed information on the nerve regenerative process following surgical repair of cauda equina injury.     

Multiparametric classification of sub‐acute ischemic stroke recovery with ultrafast diffusion, 23Na,and MPIO‐labeled stem cell MRI at 21.1 T

MRI leverages multiple modes of contrast to characterize stroke. High‐magnetic‐field systems enhance the performance of these MRI measurements. Previously, we have demonstrated that individually sodium and stem cell tracking metrics are enhanced at ultrahigh field in a rat model of stroke, and we have developed robust single‐scan diffusion‐weighted imaging approaches that utilize spatiotemporal encoding (SPEN) of the apparent diffusion coefficient (ADC) for these challenging field strengths. Here, we performed a multiparametric study of middle cerebral artery occlusion (MCAO) biomarker evolution focusing on comparison of these MRI biomarkers for stroke assessment during sub‐acute recovery in rat MCAO models at 21.1 T. T₂‐weighted MRI was used as the benchmark for identification of the ischemic lesion over the course of the study. The number of MPIO‐induced voids measured by gradient‐recalled echo, the SPEN measurement of ADC, and ²³Na MRI values were determined in the ischemic area and contralateral hemisphere, and relative performances for stroke classification were compared by receiver operator characteristic analysis. These measurements were associated with unique time‐dependent trajectories during stroke recovery that changed the sensitivity and specificity for stroke monitoring during its evolution. Advantages and limitations of these contrasts, and the use of ultrahigh field for multiparametric stroke assessment, are discussed.     

Diffusion MRI detects early brain microstructure abnormalities in 2‐month‐old 3×Tg‐AD mice

The 3×Tg‐AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg‐AD mice, with inconsistent results. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2‐month‐old 3×Tg‐AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K_┴) were found to be significantly lower in 3×Tg‐AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D_┴) were found to be elevated. In the fornix, K_┴ was lower for 3×Tg‐AD mice; in the dorsal hippocampus MD and D_┴ were elevated, as were FA, MD, and D_┴ in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg‐AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg‐AD mice compared with the age‐matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2‐month‐old 3×Tg‐AD mice.