Diffusion Tensor Metrics Research Articles

Early detection of neonatal hypoxic-ischemic white matter injury: an MR diffusion tensor imaging study.

The purpose of this study was to compare diffusion tensor metrics in normal age-matched neonates with survivors of hypoxic–ischemic encephalopathy (HIE) and extracorporeal membrane oxygenation (ECMO). Thirty-five normal, 27 HIE, and 13 ECMO infants underwent MRI at 3 T. Neurodevelopmental assessments were performed. Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) of the inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, anterior commissure, genu corpus callosum and splenium of the corpus callosum, anterior and posterior limb of the internal capsule, superior longitudinal fasciculus, and the centrum semiovale were analyzed with tract-based spatial statistics modified for use in neonates. Linear regression analysis was performed, and 95% confidence intervals were created for age effects on the tensor metrics with the control patients. Two-sample t-test was done to determine whether there was a difference in the tensor metrics between the normal and patient cohort. There was a statistically significant age effect on the FA and RD in the selected regions of the brain (F<0.05) and a group difference in the FA and RD between the normal and the HIE group (P<0.05). The group difference in the FA and RD between the normal and ECMO groups was seen in the anterior commissure, genu corpus callosum, right inferior longitudinal fasciculus, fronto-occipital fasciculus, centrum semiovale, and superior longitudinal fasciculus (P<0.05). Patients who were outside the 95% confidence intervals of the FA, AD, and RD overlapped with those with abnormalities clinically and on the conventional MRI. In conclusion, diffusion tensor imaging can play a significant role in detecting infants with early indications of hypoxic–ischemic brain injury.

Combining Diffusion Tensor Metrics and DSC Perfusion Imaging: Can It Improve the Diagnostic Accuracy in Differentiating Tumefactive Demyelination from High-Grade Glioma?

Tumefactive demyelinating lesions with atypical features can mimic high-grade gliomas on conventional imaging sequences. The aim of this study was to assess the role of conventional imaging, DTI metrics (p:q tensor decomposition), and DSC perfusion in differentiating tumefactive demyelinating lesions and high-grade gliomas. Fourteen patients with tumefactive demyelinating lesions and 21 patients with high-grade gliomas underwent brain MR imaging with conventional, DTI, and DSC perfusion imaging. Imaging sequences were assessed for differentiation of the lesions. DTI metrics in the enhancing areas and perilesional hyperintensity were obtained by ROI analysis, and the relative CBV values in enhancing areas were calculated on DSC perfusion imaging. Conventional imaging sequences had a sensitivity of 80.9% and specificity of 57.1% in differentiating high-grade gliomas (P = .049) from tumefactive demyelinating lesions. DTI metrics (p:q tensor decomposition) and DSC perfusion demonstrated a statistically significant difference in the mean values of ADC, the isotropic component of the diffusion tensor, the anisotropic component of the diffusion tensor, the total magnitude of the diffusion tensor, and rCBV among enhancing portions in tumefactive demyelinating lesions and high-grade gliomas (P ≤ .02), with the highest specificity for ADC, the anisotropic component of the diffusion tensor, and relative CBV (92.9%). Mean fractional anisotropy values showed no significant statistical difference between tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI and DSC parameters improved the diagnostic accuracy (area under the curve = 0.901). Addition of a heterogeneous enhancement pattern to DTI and DSC parameters improved it further (area under the curve = 0.966). The sensitivity increased from 71.4% to 85.7% after the addition of the enhancement pattern. DTI and DSC perfusion add profoundly to conventional imaging in differentiating tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI metrics and DSC perfusion markedly improved diagnostic accuracy.

Novel Diffusion-Kurtosis-Informed Template Reduces Distortions due to Partial Volume Effects and Improves Statistical between-Group Comparisons

Objective: Quantitative diffusion magnetic resonance imaging measures carry information about microstructural properties of the underlying tissue. Proper elucidation of their differences in healthy state and pathology, such as Alzheimer’s or Parkinson’s diseases, requires that these measures must be specific for the tissue or anatomic region of interest. However, they are often subjected to biases caused by partial volume effects and leading to erroneous analyses. The purpose of this work was to develop a novel tool allowing one to eliminate affected voxels from statistical analyses and, thus, improve accuracy of the derived measures and enhance reliability of between-group comparisons. Methods: In vivo diffusion kurtosis measurements were performed with a whole-body 3T Siemens MAGNETOM scanner for two differently aged groups of healthy volunteers. Mean values of typical diffusion tensor and kurtosis tensor metrics were estimated for 20 white matter anatomic regions. Relative differences between the group mean parameters in percentage and Cohen’s d values, as well as p-values of two-sided t-test analysis were evaluated before and after correction for partial volume effects. Results: We showed that using the tissue-specific features of diffusion kurtosis distributions allows one to reduce contamination of white matter structures by partial volume effects from neighbouring grey matter regions and cerebrospinal fluid. The performance of the developed method was demonstrated in the semi-automatic atlasbased comparison of two differently aged groups of healthy subjects showing that, after correction, the effect sizes of between-group differences in many regional diffusion indices become larger, whereas p-values of the t-tests decrease. Conclusion: Our work shows that excluding affected voxels from statistical analyses allows one to reduce confounding effects of mixing tissues and improves between-group comparisons. The proposed method is expected to be especially useful for detection of subtle between-group differences and longitudinal changes in studies of neurodegenerative pathologies and ageing associated with white matter atrophy.

Diffusion kurtosis metrics as biomarkers of microstructural development: A comparative study of a group of children and a group of adults

The most common modality of diffusion MRI used in the ageing and development studies is diffusion tensor imaging (DTI) providing two key measures, fractional anisotropy and mean diffusivity. Here, we investigated diffusional changes occurring between childhood (average age 10.3 years) and mitddle adult age (average age 54.3 years) with the help of diffusion kurtosis imaging (DKI), a recent novel extension of DTI that provides additional metrics quantifying non-Gaussianity of water diffusion in brain tissue. We performed voxelwise statistical between-group comparison of diffusion tensor and kurtosis tensor metrics using two methods, namely, the tract-based spatial statistics (TBSS) and the atlas-based regional data analysis. For the latter, fractional anisotropy, mean diffusivity, mean diffusion kurtosis, and other scalar diffusion tensor and kurtosis tensor parameters were evaluated for white matter fibres provided by the Johns-Hopkins-University Atlas in the FSL toolkit (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases). Within the same age group, all evaluated parameters varied depending on the anatomical region. TBSS analysis showed that changes in kurtosis tensor parameters beyond adolescence are more widespread along the skeleton in comparison to the changes of the diffusion tensor metrics. The regional data analysis demonstrated considerably larger between-group changes of the diffusion kurtosis metrics than of diffusion tensor metrics in all investigated regions. The effect size of the parametric changes between childhood and middle adulthood was quantified using Cohen's d. We used Cohen's d related to mean diffusion kurtosis to examine heterogeneous maturation of various fibres. The largest changes of this parameter (interpreted as reflecting the lowest level of maturation by the age of children group) were observed in the association fibres, cingulum (gyrus) and cingulum (hippocampus) followed by superior longitudinal fasciculus and inferior longitudinal fasciculus. The smallest changes were observed in the commissural fibres, forceps major and forceps minor. In conclusion, our data suggest that DKI is sensitive to developmental changes in local microstructure and environment, and is particularly powerful to unravel developmental differences in major association fibres, such as the cingulum and superior longitudinal fasciculus.

Cognitive impairment in progressive supranuclear palsy-Richardson’s syndrome is related to white matter damage

IntroductionBeside motor symptoms, patients with progressive supranuclear palsy syndrome (PSPs) commonly present cognitive and behavioral disorders. In this study we aimed to assess the structural brain correlates of cognitive impairment in PSPs. MethodsWe enrolled 23 patients with probable PSP Richardson's syndrome and 15 matched healthy controls. Patients underwent an extensive clinical and neuropsychological evaluation. Cortical thickness measures and diffusion tensor metrics of white matter tracts were obtained. Random forest analysis was used to identify the strongest MRI predictors of cognitive impairment in PSPs at an individual patient level. ResultsPSPs patients were in a moderate stage of the disease showing mild cognitive deficits with prominent executive dysfunction. Relative to controls, PSPs patients had a focal, bilateral cortical thinning mainly located in the prefrontal/precentral cortex and temporal pole. PSPs patients also showed a distributed white matter damage involving the main tracts including the superior cerebellar peduncle, corpus callosum, corticospinal tract, and extramotor tracts, such as the inferior fronto-occipital, superior longitudinal and uncinate fasciculi, and cingulum, bilaterally. Regional cortical thinning measures did not relate with cognitive features, while white matter damage showed a significant impact on cognitive impairment (r values ranging from −0.80 to 0.74). ConclusionsPSPs patients show both focal cortical thinning in dorsolateral anterior regions and a distributed white matter damage involving the main motor and extramotor tracts. White matter measures are highly associated with cognitive deficits. Diffusion tensor MRI metrics are likely to be the most sensitive markers of extramotor deficits in PSPs.

Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images

Despite its great potential in studying brain anatomy and structure, diffusion magnetic resonance imaging (dMRI) is marred by artefacts more than any other commonly used MRI technique. In this paper we present a non-parametric framework for detecting and correcting dMRI outliers (signal loss) caused by subject motion.Signal loss (dropout) affecting a whole slice, or a large connected region of a slice, is frequently observed in diffusion weighted images, leading to a set of unusable measurements. This is caused by bulk (subject or physiological) motion during the diffusion encoding part of the imaging sequence. We suggest a method to detect slices affected by signal loss and replace them by a non-parametric prediction, in order to minimise their impact on subsequent analysis. The outlier detection and replacement, as well as correction of other dMRI distortions (susceptibility-induced distortions, eddy currents (EC) and subject motion) are performed within a single framework, allowing the use of an integrated approach for distortion correction. Highly realistic simulations have been used to evaluate the method with respect to its ability to detect outliers (types 1 and 2 errors), the impact of outliers on retrospective correction of movement and distortion and the impact on estimation of commonly used diffusion tensor metrics, such as fractional anisotropy (FA) and mean diffusivity (MD). Data from a large imaging project studying older adults (the Whitehall Imaging sub-study) was used to demonstrate the utility of the method when applied to datasets with severe subject movement.The results indicate high sensitivity and specificity for detecting outliers and that their deleterious effects on FA and MD can be almost completely corrected.

Quantification of diffusion and anisotropy in intracranial epidermoids using diffusion tensor metrics and p: q tensor decomposition

To quantitatively evaluate the diffusion tensor metrics p, q, L and fractional anisotropy in intracranial epidermoids in comparison with normal white matter in the splenium of the corpus callosum. This retrospective study included 20consecutive patients referred to our institute. All patients had a magnetic resonance imaging (MRI) study on a 1.5-Tesla MR system. A spin-echo echo-planar DTI sequence with diffusion gradients along 30non-collinear directions was performed. The eigen values (λ1, λ2, λ3) were computed for each voxel and, using p: q tensor decomposition, the DTI metrics p, q and L-values and fractional anositropy (FA) were calculated. The region of interest (ROI) (6pixels each) was placed within the lesion in all the cases and in the splenium of the corpus callosum. The mean FA in the lesion and splenium were 0.50 and 0.88 respectively, with a statistically significant difference between them (P<0.01). On p: q tensor decomposition, the mean p-value in the epidermoid was 1.55±0.24 and 1.35±0.20 in the splenium; the mean q-values in the epidermoid was 0.67±0.13 and 1.27±0.17 in the splenium; the differences were statistically significant (P=0.01 and <0.01 respectively). The significant difference between p- and q-values in epidermoids compared with the splenium of callosum was probably due to structural and orientation differences in the keratin flakes in epidermoids and white matter bundles in the callosum. However, no significant statistical difference in L-values was noted (P=0.44). DTI metrics p and q have the potential to quantify the diffusion and anisotropy in various tissues thereby gaining information about their internal architecture. The results also suggest that significant differences of DTI metrics p and q between epidermoid and the splenium of the corpus callosum are due to the difference in structural organization within them.

Anomalous Diffusion in Cardiac Tissue as an Index of Myocardial Microstructure.

Diffusion in biological tissues is known to be hindered by the structural complexity of the underlying medium. In the heart, improved characterisation on how this complexity influences acquired diffusion weighted signals is key to advancing our interpretation of diffusion magnetic resonance imaging, as well as to propose novel biomarkers to further characterise myocardial microstructure. In this work, we propose stretched Mittag-Leffler signal decay models for the quantification of the anomalous decay observed in acquired diffusion weighted signals. Our results, analysed in ex vivo healthy, fixed rat ventricles, indicate that such a representation suffices to capture the anomalous signal decay observed in the myocardial syncytium. The subdiffusive order of signal decay is shown to encode independent information to that encapsulated by standard diffusion tensor metrics, and thus may provide additional information on tissue microstructure. Moreover, subdiffusion gradients are shown to be indicative of the total structural heterogeneity spanning the left ventricular wall, which includes progressive myolaminae branching and spatially varying densities of perimysial collagen, microvasculature and adipose tissue. The proposed approach may therefore have important implications for the characterisation of tissue microstructure, both in cardiac and other tissue types.

Structural brain correlates of cognitive and behavioral impairment in MND.

To assess the structural correlates of cognitive and behavioral impairment in motor neuron diseases (MND) using multimodal MRI. One hundred one patients with sporadic MND (56 classic amyotrophic lateral sclerosis, 31 upper motor neuron phenotype, and 14 lower motor neuron phenotype) and 51 controls were enrolled. Patients were classified into MND with a pure motor syndrome (MND-motor) and with cognitive/behavioral symptoms (MND-plus). Cortical thickness measures and diffusion tensor (DT) metrics of white matter (WM) tracts were assessed. A random forest approach was used to explore the independent role of cortical and WM abnormalities in explaining major cognitive and behavioral symptoms. There were 48 MND-motor and 53 MND-plus patients. Relative to controls, both patient groups showed a distributed cortical thinning of the bilateral precentral gyrus, insular and cingulate cortices, and frontotemporal regions. In all regions, there was a trend toward a more severe involvement in MND-plus cases, particularly in the temporal lobes. Both patient groups showed damage to the motor callosal fibers, which was more severe in MND-plus. MND-plus patients also showed a more severe involvement of the extra-motor WM tracts. The best predictors of executive and non-executive deficits and behavioral symptoms in MND were diffusivity abnormalities of the corpus callosum and frontotemporal tracts, including the uncinate, cingulum, and superior longitudinal fasciculi. Cortical thinning and WM degeneration are highly associated with neuropsychological and behavioral symptoms in patients with MND. DT MRI metrics seem to be the most sensitive markers of extra-motor deficits within the MND spectrum.

Increased functional connectivity common to symptomatic amyotrophic lateral sclerosis and those at genetic risk

ObjectiveTo discern presymptomatic changes in brain structure or function using advanced MRI in carriers of mutations predisposing to amyotrophic lateral sclerosis (ALS).MethodsT1-weighted, diffusion weighted and resting state functional MRI data...

Diffusion tensor metrics as biomarkers in idiopathic normal-pressure hydrocephalus

Diffusion tensor metrics as biomarkers in idiopathic normal-pressure hydrocephalus

Detecting the effects of Fabry disease in the adult human brain with diffusion tensor imaging and fast bound-pool fraction imaging.

To identify quantitative MRI parameters associated with diffusion tensor imaging (DTI) and fast bound-pool fraction imaging (FBFI) that may detect alterations in gray matter and/or white matter in adults with Fabry disease, a lysosomal storage disorder. Twelve healthy controls (mean age ± standard deviation: 48.0 ± 12.4 years) and 10 participants with Fabry disease (46.7 ± 12.9 years) were imaged at 3.0 Tesla. Whole-brain parametric maps of diffusion tensor metrics (apparent diffusion coefficient [ADC] and fractional anisotropy [FA]) and the bound-pool fraction (f) were acquired. Mean voxel values of parametric maps from regions-of-interest within gray and white matter structures were compared between cases and controls using the independent t-test. Spearman's rho was used to identify associations between parametric maps and age. Compared with controls, the left thalamus of Fabry participants had an increase in FA (0.29 ± 0.02 versus 0.33 ± 0.05, respectively; P = 0.030) and a trend toward an increase in ADC (0.73 ± 00.02 versus 0.76 ± 0.03 μm(2) /s, respectively; P = 0.082). The left posterior white matter demonstrated a reduction in f (10.45 ± 0.37 versus 9.00 ± 1.84%, respectively; P = 0.035), an increase in ADC (0.78 ± 0.04 versus 0.94 ± 0.19 μm(2) /s, respectively; P = 0.024), and a trend toward a reduction in FA (0.42 ± 0.07 versus 0.36 ± 0.08, respectively; P = 0.052). Among all parameters, only f measured in the left posterior white matter was significantly associated with age in Fabry participants (rho = -0.71; P = 0.022). Parameters derived from DTI and FBFI detect Fabry-related changes in the adult human brain, particularly in the posterior white matter where reductions in myelin density as measured by FBFI appear age related.

Motion immune diffusion imaging using augmented MUSE for high-resolution multi-shot EPI.

To develop new techniques for reducing the effects of microscopic and macroscopic patient motion in diffusion imaging acquired with high-resolution multishot echo-planar imaging. The previously reported multiplexed sensitivity encoding (MUSE) algorithm is extended to account for macroscopic pixel misregistrations, as well as motion-induced phase errors in a technique called augmented MUSE (AMUSE). Furthermore, to obtain more accurate quantitative diffusion-tensor imaging measures in the presence of subject motion, we also account for the altered diffusion encoding among shots arising from macroscopic motion. MUSE and AMUSE were evaluated on simulated and in vivo motion-corrupted multishot diffusion data. Evaluations were made both on the resulting imaging quality and estimated diffusion tensor metrics. AMUSE was found to reduce image blurring resulting from macroscopic subject motion compared to MUSE but yielded inaccurate tensor estimations when neglecting the altered diffusion encoding. Including the altered diffusion encoding in AMUSE produced better estimations of diffusion tensors. The use of AMUSE allows for improved image quality and diffusion tensor accuracy in the presence of macroscopic subject motion during multishot diffusion imaging. These techniques should facilitate future high-resolution diffusion imaging.

Diffusion tensor characteristics of gyrencephaly using high resolution diffusion MRI in vivo at 7T

Gyrification of the human cerebral cortex allows for the surface expansion that accommodates many more cortical neurons in comparison to other mammals. For neuroimaging, however, it forms a feature that complicates analysis. For example, it has long been established that cortical layers do not occupy the same depth in gyri and sulci. Recently, in vivo diffusion imaging has provided insights into the fibre architecture of the cortex, usually showing radial tensor orientations. This makes it relevant to investigate whether cortical diffusion tensor metrics depend on the gyral pattern. High-resolution (1mm isotropic) diffusion weighted MRI of the medial wall of the hemispheres was performed at 7T. Diffusion data were resampled to surfaces in the cortex and underlying white matter, where the cortical surfaces obeyed the equivolume principle for cortical laminae over the cortical curvature. Diffusion tensor metrics were averaged over bins of curvature to obtain maps of characteristic patterns in the gyrus. Diffusivity, anisotropy and radiality varied with curvature. Radiality was maximal in intermediate layers of the cortex next to the crown of the gyrus, not in white matter or on the crown. In the fundus, the deep cortical layers had tangential tensor orientations. In the white matter, tensor orientation changed from radial on the crown to tangential under the banks and fundus. White matter anisotropy gradually increased from the crown to the fundus. The characteristic pattern in the gyrus demonstrated here is in accordance with ex vivo diffusion MR microscopy and histological studies. The results indicate the necessity of taking into account the gyral pattern when cortical diffusion data is analysed. Additionally, the data suggest a confound for tractography approaches when reaching the gyrus, resulting in a possible bias towards the gyral crown. The implications for mechanisms that could drive cortical folding are discussed.

Thalamic involvement in paroxysmal kinesigenic dyskinesia: a combined structural and diffusion tensor MRI analysis.

Alteration of basal ganglia-thalamocortical circuit has been hypothesized to play a role in the pathophysiology underlying paroxysmal kinesigenic dyskinesia (PKD). We investigated macrostructural and microstructural changes in PKD patients using structural and diffusion tensor magnetic resonance imaging (MRI) analyses. Twenty-five patients with idiopathic PKD and 25 control subjects were prospectively studied on a 3T magnetic resonance (MR) scanner. Cortical thickness analysis was used to evaluate cortical gray matter (GM) changes, and automated volumetry and shape analysis were used to assess volume changes and shape deformation of the subcortical GM structures, respectively. Tract-based spatial statistics (TBSS) was used to evaluate white matter integrity changes in a whole-brain manner, and region-of-interest (ROI) analysis of diffusion tensor metrics was performed in subcortical GM structures. Compared to controls, PKD patients exhibited a reduction in volume of bilateral thalami and regional shape deformation mainly localized to the anterior and medial aspects of bilateral thalami. TBSS revealed an increase in fractional anisotropy (FA) of bilateral thalami and right anterior thalamic radiation in patients relative to controls. ROI analysis also showed an increase in FA of bilateral thalami in patients compared to controls. We have shown evidence for thalamic abnormalities of volume reduction, regional shape deformation, and increased FA in patients with PKD. Our novel findings of concomitant macrostructural and microstructural abnormalities in the thalamus lend further support to previous observations indicating causal relationship between a preferential lesion in the thalamus and development of PKD, thus providing neuroanatomical basis for the involvement of thalamus within the basal ganglia-thalamocortical pathway in PKD.

Meta-analysis of diffusion metrics for the prediction of tumor grade in gliomas.

Diffusion tensor metrics are potential in vivo quantitative neuroimaging biomarkers for the characterization of brain tumor subtype. This meta-analysis analyzes the ability of mean diffusivity and fractional anisotropy to distinguish low-grade from high-grade gliomas in the identifiable tumor core and the region of peripheral edema. A meta-analysis of articles with mean diffusivity and fractional anisotropy data for World Health Organization low-grade (I, II) and high-grade (III, IV) gliomas, between 2000 and 2013, was performed. Pooled data were analyzed by using the odds ratio and mean difference. Receiver operating characteristic analysis was performed for patient-level data. The minimum mean diffusivity of high-grade gliomas was decreased compared with low-grade gliomas. High-grade gliomas had decreased average mean diffusivity values compared with low-grade gliomas in the tumor core and increased average mean diffusivity values in the peripheral region. High-grade gliomas had increased FA values compared with low-grade gliomas in the tumor core, decreased values in the peripheral region, and a decreased fractional anisotropy difference between the tumor core and peripheral region. The minimum mean diffusivity differs significantly with respect to the World Health Organization grade of gliomas. Statistically significant effects of tumor grade on average mean diffusivity and fractional anisotropy were observed, supporting the concept that high-grade tumors are more destructive and infiltrative than low-grade tumors. Considerable heterogeneity within the literature may be due to systematic factors in addition to underlying lesion heterogeneity.

Axial diffusivity of the corona radiata correlated with ventricular size in adult hydrocephalus.

Hydrocephalus causes changes in the diffusion-tensor properties of periventricular white matter. Understanding the nature of these changes may aid in the diagnosis and treatment planning of this relatively common neurologic condition. Because ventricular size is a common measure of the severity of hydrocephalus, we hypothesized that a quantitative correlation could be made between the ventricular size and diffusion-tensor changes in the periventricular corona radiata. In this article, we investigated this relationship in adult patients with hydrocephalus and in healthy adult subjects. Diffusion-tensor imaging metrics of the corona radiata were correlated with ventricular size in 14 adult patients with acute hydrocephalus, 16 patients with long-standing hydrocephalus, and 48 consecutive healthy adult subjects. Regression analysis was performed to investigate the relationship between ventricular size and the diffusion-tensor metrics of the corona radiata. Subject age was analyzed as a covariable. There is a linear correlation between fractional anisotropy of the corona radiata and ventricular size in acute hydrocephalus (r = 0.784, p < 0.001), with positive correlation with axial diffusivity (r = 0.636, p = 0.014) and negative correlation with radial diffusivity (r = 0.668, p = 0.009). In healthy subjects, axial diffusion in the periventricular corona radiata is more strongly correlated with ventricular size than with patient age (r = 0.466, p < 0.001, compared with r = 0.058, p = 0.269). Axial diffusivity of the corona radiata is linearly correlated with ventricular size in healthy adults and in patients with hydrocephalus. Radial diffusivity of the corona radiata decreases linearly with ventricular size in acute hydrocephalus but is not significantly correlated with ventricular size in healthy subjects or in patients with long-standing hydrocephalus.

Histological correlation of diffusional kurtosis and white matter modeling metrics in cuprizone-induced corpus callosum demyelination.

The cuprizone mouse model is well established for studying the processes of both demyelination and remyelination in the corpus callosum, and it has been utilized together with diffusion tensor imaging (DTI) to investigate myelin and axonal pathology. Although some underlying morphological mechanisms contributing to the changes in diffusion tensor (DT) metrics have been identified, the understanding of specific associations between histology and diffusion measures remains limited. Diffusional kurtosis imaging (DKI) is an extension of DTI that provides metrics of diffusional non-Gaussianity, for which an associated white matter modeling (WMM) method has been developed. The main goal of the present study was to quantitatively assess the relationships between diffusion measures and histological measures in the mouse model of cuprizone-induced corpus callosum demyelination. The diffusional kurtosis (DK) and WMM metrics were found to provide additional information that enhances the sensitivity to detect the morphological heterogeneity in the chronic phase of the disease process in the rostral segment of the corpus callosum. Specifically, in the rostral segment, axonal water fraction (d = 2.6; p < 0.0001), radial kurtosis (d = 2.0; p = 0.001) and mean kurtosis (d = 1.5; p = 0.005) showed the most sensitivity between groups with respect to yielding statistically significant p values and high Cohen's d values. These results demonstrate the ability of DK and WMM metrics to detect white mater changes and inflammatory processes associated with cuprizone-induced demyelination. They also validate, in part, the application of these new WMM metrics for studying neurological diseases, as well as helping to elucidate their biophysical meaning.

Diffusional kurtosis imaging: a promising technique for detecting microstructural changes in neural development and regeneration

Diffusional kurtosis imaging: a promising technique for detecting microstructural changes in neural development and regeneration

Brain white matter diffusion tensor metrics from clinical 1.5T MRI distinguish between ALS phenotypes

Patients with amyotrophic lateral sclerosis (ALS) can present with varying degrees of upper motor neuron (UMN) and lower motor neuron dysfunction. Previous diffusion tensor imaging (DTI) studies, in which ALS patients were not separated by the degree of UMN dysfunction, have resulted in conflicting or inconclusive results. We hypothesized that (1) categorizing ALS patients by their clinical phenotype can reveal differences in DTI abnormalities along the corticospinal tract (CST), and (2) data obtained from routine clinical DTI scans can provide this type of information. Clinical DTI scans were obtained at 1.5T in 87 ALS patients (categorized into four subgroups based on clinical phenotype) and in 12 neurologic controls. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity values from the CST were compared between ALS subgroups and controls. Significantly reduced FA and elevated MD values were observed in ALS patients compared to controls at the subcortical motor cortex level. Significant differences in AD values were not only seen between control and ALS patients but also between the ALS subgroups, suggesting divergent pathologies in these ALS patients. Classifying ALS patients by phenotype reveals differences in CST abnormalities between subgroups and may provide novel insights into disease mechanisms. The close similarity of our results from routine clinical scans with published research studies suggests wider accessibility to useful DTI metrics.