Diffusion Tensor Imaging of Auditory Pathway in Patients With Crigler-Najjar Syndrome Type I: Correlation With Auditory Brainstem Response.

AIM: To evaluate the role of diffusion tensor imaging of the auditory pathway in patients with Crigler Najjar syndrome type I and its relation to auditory brainstem response. METHODS: Prospective study was done including 12 patients with Crigler Najjar syndrome type I and 10 age- and sex-matched controls that underwent diffusion tensor imaging of brain. Mean diffusivity and fractional anisotropy at 4 regions of the brain and brainstem on each side were measured and correlated with the results of auditory brainstem response for patients. RESULTS: There was significantly higher mean diffusivity of cochlear nucleus, superior olivary nucleus, inferior colliculus, and auditory cortex of patients versus controls on both sides for all regions (P = .001). The fractional anisotropy of cochlear nucleus, superior olivary nucleus, inferior colliculus, and auditory cortex of patients versus controls was significantly lower, with P values of, respectively, .001, .001, .003, and .001 on the right side and .001, .001, .003, and .001 on left side, respectively. Also, a negative correlation was found between the maximum bilirubin level and fractional anisotropy of the left superior olivary nucleus and inferior colliculus of both sides. A positive correlation was found between the mean diffusivity and auditory brainstem response wave latency of the right inferior colliculus and left cochlear nucleus. The fractional anisotropy and auditory brainstem response wave latency of the right superior olivary nucleus, left cochlear nucleus, and inferior colliculus of both sides were negatively correlated. CONCLUSION: Diffusion tensor imaging can detect microstructural changes in the auditory pathway in Crigler Najjar syndrome type I that can be correlated with auditory brainstem response.

Multidimensional analysis and detection of informative features in human brain white matter.

The white matter contains long-range connections between different brain regions and the organization of these connections holds important implications for brain function in health and disease. Tractometry uses diffusion-weighted magnetic resonance imaging (dMRI) to quantify tissue properties along the trajectories of these connections. Statistical inference from tractometry usually either averages these quantities along the length of each fiber bundle or computes regression models separately for each point along every one of the bundles. These approaches are limited in their sensitivity, in the former case, or in their statistical power, in the latter. We developed a method based on the sparse group lasso (SGL) that takes into account tissue properties along all of the bundles and selects informative features by enforcing both global and bundle-level sparsity. We demonstrate the performance of the method in two settings: i) in a classification setting, patients with amyotrophic lateral sclerosis (ALS) are accurately distinguished from matched controls. Furthermore, SGL identifies the corticospinal tract as important for this classification, correctly finding the parts of the white matter known to be affected by the disease. ii) In a regression setting, SGL accurately predicts "brain age." In this case, the weights are distributed throughout the white matter indicating that many different regions of the white matter change over the lifespan. Thus, SGL leverages the multivariate relationships between diffusion properties in multiple bundles to make accurate phenotypic predictions while simultaneously discovering the most relevant features of the white matter.

Multimodal principal component analysis to identify major features of white matter structure and links to reading.

The role of white matter in reading has been established by diffusion tensor imaging (DTI), but DTI cannot identify specific microstructural features driving these relationships. Neurite orientation dispersion and density imaging (NODDI), inhomogeneous magnetization transfer (ihMT) and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT) can be used to link more specific aspects of white matter microstructure and reading due to their sensitivity to axonal packing and fiber coherence (NODDI) and myelin (ihMT and mcDESPOT). We applied principal component analysis (PCA) to combine DTI, NODDI, ihMT and mcDESPOT measures (10 in total), identify major features of white matter structure, and link these features to both reading and age. Analysis was performed for nine reading-related tracts in 46 neurotypical 6-16 year olds. We identified three principal components (PCs) which explained 79.5% of variance in our dataset. PC1 probed tissue complexity, PC2 described myelin and axonal packing, while PC3 was related to axonal diameter. Mixed effects regression models did not identify any significant relationships between principal components and reading skill. Bayes factor analysis revealed that the absence of relationships was not due to low power. Increasing PC1 in the left arcuate fasciculus with age suggest increases in tissue complexity, while increases of PC2 in the bilateral arcuate, inferior longitudinal, inferior fronto-occipital fasciculi, and splenium suggest increases in myelin and axonal packing with age. Multimodal white matter imaging and PCA provide microstructurally informative, powerful principal components which can be used by future studies of development and cognition. Our findings suggest major features of white matter undergo development during childhood and adolescence, but changes are not linked to reading during this period in our typically-developing sample.

Non-right-handedness in children born extremely preterm: Relation to early neuroimaging and long-term neurodevelopment.

OBJECTIVE: This study aimed to define the prevalence and predictors of non-right-handedness and its link to long-term neurodevelopmental outcome and early neuroimaging in a cohort of children born extremely preterm (<28 weeks gestation). METHODS: 179 children born extremely preterm admitted to the Neonatal Intensive Care Unit of our tertiary centre from 2006-2013 were included in a prospective longitudinal cohort study. Collected data included perinatal data, demographic characteristics, neurodevelopmental outcome measured by the Bayley Scales of Infant and Toddler Development at 2 years and the Movement Assessment Battery for Children at 5 years, and handedness measured at school age (4-8 years). Magnetic resonance imaging performed at term-equivalent age was used to study overt brain injury. Diffusion tensor imaging scans were analysed using tract-based spatial statistics to assess white matter microstructure in relation to handedness and neurodevelopmental outcome. RESULTS: The prevalence of non-right-handedness in our cohort was 22.9%, compared to 12% in the general population. Weaker fine motor skills at 2 years and paternal non-right-handedness were significantly associated with non-right-handedness. Both overt brain injury and fractional anisotropy of white matter structures on diffusion tensor images were not related to handedness. Fractional anisotropy measurements showed significant associations with neurodevelopmental outcome. CONCLUSIONS: Our data show that non-right-handedness in children born extremely preterm occurs almost twice as frequently as in the general population. In the studied population, non-right-handedness is associated with weaker fine motor skills and paternal non-right-handedness, but not with overt brain injury or microstructural brain development on early magnetic resonance imaging.

Distance-based analysis of variance for brain connectivity.

The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures, including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that might mask the salient features of high-dimensional distributions. In this work, we consider a general framework for two-sample testing of complex structures by studying generalized within-group and between-group variances based on distances between complex and potentially high-dimensional observations. We derive an asymptotic approximation to the null distribution of the ANOVA test statistic, and conduct simulation studies with scalar and graph outcomes to study finite sample properties of the test. Finally, we apply our test to our motivating study of structural connectivity in autism spectrum disorder.

The prospective relationship between prehypertension, race, and whole-brain white matter microstructure.

Compared with whites, blacks develop hypertension earlier in life, progress from prehypertension to hypertension at an accelerated rate, and exhibit greater hypertension-mediated organ damage (e.g., kidney disease, stroke). In this paper, we tested whether the longitudinal associations between elevated systolic blood pressure and disruption of brain white matter structural integrity differ as a function of race. A community sample of 100 middle-aged adults with prehypertension underwent diffusion imaging to quantify indirect metrics of white matter structural integrity, including fractional anisotropy. Blood pressure and diffusion imaging measurements were collected at baseline and at a 2-year follow-up. Regression analyses showed that higher systolic blood pressure at baseline was associated with a decrease in fractional anisotropy over 2 years in blacks only (ß = -0.51 [95% CI = -0.85, -0.16], t = -2.93, p = 0.004, ΔR2 = 0.09). These findings suggest that blacks are more susceptible to the impact of systolic prehypertension on white matter structural integrity.

Measuring graphical strength within the connectome: A neuroanatomic, parcellation-based study.

INTRODUCTION: Graph theory is a promising mathematical tool to study the connectome. However, little research has been undertaken to correlate graph metrics to functional properties of the brain. In this study, we report a unique association between the strength of cortical regions and their function. METHODS: Eight structural graphs were constructed within DSI Studio using publicly available imaging data derived from the Human Connectome Project. Whole-brain fiber tractography was performed to quantify the strength of each cortical region comprising our atlas. RESULTS: Rank-order analysis revealed 27 distinct areas with high average strength, several of which are associated with eloquent cortical functions. Area 4 localizes to the primary motor cortex and is important for fine motor control. Areas 2, 3a and 3b localize to the primary sensory cortex and are involved in primary sensory processing. Areas V1-V4 in the occipital pole are involved in primary visual processing. Several language areas, including area 44, were also found to have high average strength. CONCLUSIONS: Regions of average high strength tend to localize to eloquent areas of the brain, such as the primary sensorimotor cortex, primary visual cortex, and Broca's area. Future studies will examine the dynamic effects of neurologic disease on this metric.

Comparison of Fractional Anisotropy from Tract-Based Spatial Statistics with and without Lesion Masking in Patients with Intracerebral Hemorrhage: A Technical Note.

BACKGROUND: Diffusion-tensor fractional anisotropy (FA) is an index of neural-fiber damage in patients following stroke. To better characterize FA, tract-based spatial statistics (TBSS) is frequently used, which involves spatial transformation into the standard brain space. Despite its utility, this technique is susceptible to space-occupying hematoma in patients with intracerebral hemorrhage. To correct this, "lesion making" has been proposed. Here, FA values from TBSS without lesion masking and TBSS with lesion masking were compared, and the clinical utility was evaluated. METHODS: Forty patients from our previously published work were entered into the study. Diffusion-tensor imagings were acquired 14-21 days after onset and FA maps were generated. Lesion masks were produced in reference with nondiffusion (b = 0) brain images. Two types (with or without lesion masking) of TBSS were then performed. For both types, using individual data we extracted mean FA values within for the corticospinal tract (CST) and the superior longitudinal fasciculus (SLF). FA ratio (rFA) between the lesioned hemisphere and the unaffected hemisphere was then calculated. The two sets of the data were then compared by assessing residuals of mean root sum square error (RMSE). RESULTS: Although rFA obtained from TBSS with lesion masking tended to be slightly smaller, the estimated RMSE was .025 for both the CST and the SLF. CONCLUSIONS: The estimated FA differences between the two sets of TBSS were very small. Considering the time for manual labor for producing lesion masks, regular TBSS without lesion masking may be sufficient in terms of clinical utility.

Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging.

This study presents a modelling framework in which information on muscle fiber direction and orientation during contraction is derived from diffusion tensor imaging (DTI) and incorporated in a computational model of the surface electromyographic (EMG) signal. The proposed model makes use of the principle of reciprocity to simultaneously calculate the electric potentials produced at the recording electrode by charges distributed along an arbitrary number of muscle fibers within the muscle, allowing for a computationally efficient evaluation of extracellular motor unit action potentials. The approach is applied to the complex architecture of the first dorsal interosseous (FDI) muscle of the hand to simulate EMG during index finger flexion and abduction. Using diffusion tensor imaging methods, the results show how muscle fiber orientation and curvature in this intrinsic hand muscle change during flexion and abduction. Incorporation of anatomically accurate muscle architecture and other hand tissue morphologies enables the model to capture variations in extracellular action potential waveform shape across the motor unit population and to predict experimentally observed differences in EMG signal features when switching from index finger abduction to flexion. The simulation results illustrate how structural and electrical properties of the tissues comprising the volume conductor, in combination with fiber direction and curvature, shape the detected action potentials. Using the model, the relative contribution of motor units of different sizes located throughout the muscle under both conditions is examined, yielding a prediction of the detection profile of the surface EMG electrode array over the muscle cross-section.

Predictive role of subcomponents of the left arcuate fasciculus in prognosis of aphasia after stroke: A retrospective observational study.

The relationship between the left arcuate fasciculus (AF) and stroke-related aphasia is unclear. In this retrospective study, we aimed to investigate the role of subcomponents of the left AF in predicting prognosis of aphasia after stroke. Twenty stroke patients with aphasia were recruited and received language assessment as well as diffusion tensor tractography scanning at admission. According to injury of the left AF, the participants were classified into four groups: group A (4 cases), the AF preserved intactly; group B (6 cases), the anterior segment injured; group C (4 cases), the posterior segment injured; and group D (6 cases), completely injured. After a consecutive speech therapy, language assessment was performed again. Changes of language functions among the groups were compared and the relation between these changes with segments injury of the AF was analyzed. After therapy, relatively high increase score percentage changes in terms of all the subcategories of language assessment were observed both in group A and C; by contrast, only naming in group B, and spontaneous speech in group D. Although no statistical difference was demonstrated among the four groups. In addition, there was no significant correlation between improvement of language function with segments injury of the AF. The predictive role of subcomponents of the left AF in prognosis of aphasia is obscure in our study. Nevertheless, it indicates the importance of integrity of the left AF for recovery of aphasia, namely that preservation of the left AF on diffusion tensor tractography could mean recovery potential of aphasia after stroke.

Elastic Statistical Shape Analysis of Biological Structures with Case Studies: A Tutorial.

We describe a recent framework for statistical shape analysis of curves and show its applicability to various biological datasets. The presented methods are based on a functional representation of shape called the square-root velocity function and a closely related elastic metric. The main benefit of this approach is its invariance to reparameterization (in addition to the standard shape-preserving transformations of translation, rotation and scale), and ability to compute optimal registrations (point correspondences) across objects. Building upon the defined distance between shapes, we additionally describe tools for computing sample statistics including the mean and covariance. Based on the covariance structure, one can also explore variability in shape samples via principal component analysis. Finally, the estimated mean and covariance can be used to define Wrapped Gaussian models on the shape space, which are easy to sample from. We present multiple case studies on various biological datasets including (1) leaf outlines, (2) internal carotid arteries, (3) Diffusion Tensor Magnetic Resonance Imaging fiber tracts, (4) Glioblastoma Multiforme tumors, and (5) vertebrae in mice. We additionally provide a MATLAB package that can be used to produce the results given in this manuscript.

Spin echo based cardiac diffusion imaging at 7T: An ex vivo study of the porcine heart at 7T and 3T.

Purpose of this work was to assess feasibility of cardiac diffusion tensor imaging (cDTI) at 7 T in a set of healthy, unfixed, porcine hearts using various parallel imaging acceleration factors and to compare SNR and derived cDTI metrics to a reference measured at 3 T. Magnetic resonance imaging was performed on 7T and 3T whole body systems using a spin echo diffusion encoding sequence with echo planar imaging readout. Five reference (b = 0 s/mm2) images and 30 diffusion directions (b = 700 s/mm2) were acquired at both 7 T and 3 T using a GRAPPA acceleration factor R = 1. Scans at 7 T were repeated using R = 2, R = 3, and R = 4. SNR evaluation was based on 30 reference (b = 0 s/mm2) images of 30 slices of the left ventricle and cardiac DTI metrics were compared within AHA segmentation. The number of hearts scanned at 7 T and 3 T was n = 11. No statistically significant differences were found for evaluated helix angle, secondary eigenvector angle, fractional anisotropy and apparent diffusion coefficient at the different field strengths, given sufficiently high SNR and geometrically undistorted images. R≥3 was needed to reduce susceptibility induced geometric distortions to an acceptable amount. On average SNR in myocardium of the left ventricle was increased from 29±3 to 44±6 in the reference image (b = 0 s/mm2) when switching from 3 T to 7 T. Our study demonstrates that high resolution, ex vivo cDTI is feasible at 7 T using commercial hardware.

Habenular connectivity may predict treatment response in depressed psychiatric inpatients.

INTRODUCTION: The habenula (Hb) is a small midbrain structure that signals negative events and may play a major role in the etiology of psychiatric disorders including depression. The lateral Hb has three major efferent connections: serotonergic raphe nuclei, noradrenergic locus coeruleus, and dopaminergic ventral tegmental area/substantia nigra compacta. We wanted to test whether Hb connectivity may be important to predict treatment outcomes in depression patients. METHODS: We studied whether habenular connectivity at admission into a psychiatric clinic can predict treatment response. We used an inpatient sample (N = 175) to assess habenular connectivity (diffusion tensor imaging and resting state functional connectivity (RSFC) between the Hb and its targets) close to admission. In addition, we obtained the Patient Health Questionnaire-depression module (PHQ-9) close to admission and at discharge. Inpatients in the study entered the clinic with at least moderately severe depression (score 15 and up). Inpatients considered treatment resistant had scores of 9 or more at discharge. RESULTS: Compared to responders, treatment non-responders had lower fractional anisotropy in the right Hb afferent fibers and lower RSFC between right Hb and median raphe, but higher RSFC between left Hb and locus coeruleus. A logistic regression model was significantly different from chance, and explained 27.7% of the variance in treatment resistance (sensitivity = 75%; specificity = 71.9%). DISCUSSION: The anatomical and functional connectivity of the Hb may be a predictor of treatment success in psychiatric populations. Limitations include the Hb small size and the limited time (5 min) of resting state data obtained.

Estimating the local false discovery rate via a bootstrap solution to the reference class problem.

Methods of estimating the local false discovery rate (LFDR) have been applied to different types of datasets such as high-throughput biological data, diffusion tensor imaging (DTI), and genome-wide association (GWA) studies. We present a model for LFDR estimation that incorporates a covariate into each test. Incorporating the covariates may improve the performance of testing procedures, because it contains additional information based on the biological context of the corresponding test. This method provides different estimates depending on a tuning parameter. We estimate the optimal value of that parameter by choosing the one that minimizes the estimated LFDR resulting from the bias and variance in a bootstrap approach. This estimation method is called an adaptive reference class (ARC) method. In this study, we consider the performance of ARC method under certain assumptions on the prior probability of each hypothesis test as a function of the covariate. We prove that, under these assumptions, the ARC method has a mean squared error asymptotically no greater than that of the other method where the entire set of hypotheses is used and assuming a large covariate effect. In addition, we conduct a simulation study to evaluate the performance of estimator associated with the ARC method for a finite number of hypotheses. Here, we apply the proposed method to coronary artery disease (CAD) data taken from a GWA study and diffusion tensor imaging (DTI) data.

Spatially resolved kinetics of skeletal muscle exercise response and recovery with multiple echo diffusion tensor imaging (MEDITI): a feasibility study.

OBJECTIVES: We describe measurement of skeletal muscle kinetics with multiple echo diffusion tensor imaging (MEDITI). This approach allows characterization of the microstructural dynamics in healthy and pathologic muscle. MATERIALS AND METHODS: In a Siemens 3-T Skyra scanner, MEDITI was used to collect dynamic DTI with a combination of rapid diffusion encoding, radial imaging, and compressed sensing reconstruction in a multi-compartment agarose gel rotation phantom and within in vivo calf muscle. An MR-compatible ergometer (Ergospect Trispect) was employed to enable in-scanner plantar flexion exercise. In a HIPAA-compliant study with written informed consent, post-exercise recovery of DTI metrics was quantified in eight volunteers. Exercise response of DTI metrics was compared with that of T2-weighted imaging and characterized by a gamma variate model. RESULTS: Phantom results show quantification of diffusivities in each compartment over its full dynamic rotation. In vivo calf imaging results indicate larger radial than axial exercise response and recovery in the plantar flexion-challenged gastrocnemius medialis (fractional response: nT2w = 0.385 ± 0.244, nMD = 0.163 ± 0.130, nλ1 = 0.110 ± 0.093, nλrad = 0.303 ± 0.185). Diffusion and T2-weighted response magnitudes were correlated (e.g., r = 0.792, p = 0.019 for nMD vs. nT2w). CONCLUSION: We have demonstrated the feasibility of MEDITI for capturing spatially resolved diffusion tensor data in dynamic systems including post-exercise skeletal muscle recovery following in-scanner plantar flexion.

Frequency of Acute and Subacute Infarcts in a Population-Based Study.

OBJECTIVE: To determine the frequency of incidental acute or subacute cerebral infarction (CI) in a population-based study. PATIENTS AND METHODS: We identified 2095 participants aged 50 to 98 years in the population-based Mayo Clinic Study of Aging from October 23, 2009, to October 5, 2016, with a usable diffusion tensor imaging (DTI) sequence (total scans=3230). Acute and subacute infarcts were identified by neuroradiologists. For each participant, vascular risk factors, medications, clinical symptoms, and neurological examination near the time of the CI were abstracted from the medical record. The probable etiologic mechanism for the CI was determined. RESULTS: Nine CIs were identified with a frequency of 0.28% among individual magnetic resonance imaging (MRI) scans and 0.43% among unique individuals. Infarctions were detected in 0.097% of scans from participants younger than 70 years and in 0.36% of scans of those 70 years or older. Six CIs were acute, and 3 were subacute. Most participants with infarcts were men (78%), with a mean age of 76.9±6.74 years. All were asymptomatic at the time of CI detection. The probable mechanisms of CI were small vessel (n=6), cardioembolic (n=2), and cryptogenic (n=1). CONCLUSION: Acute and subacute cerebral infarcts occur as incidental findings in approximately 1 in 230 people aged 50 to 98 years, particularly in elderly men and those with vascular risk factors. As brain MRI becomes more widely used, incidentally detected acute or subacute infarcts will provide an opportunity to improve stroke prevention.

A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread.

Gliomas are primary brain tumours arising from the glial cells of the nervous system. The diffuse nature of spread, coupled with proximity to critical brain structures, makes treatment a challenge. Pathological analysis confirms that the extent of glioma spread exceeds the extent of the grossly visible mass, seen on conventional magnetic resonance imaging (MRI) scans. Gliomas show faster spread along white matter tracts than in grey matter, leading to irregular patterns of spread. We propose a mathematical model based on Diffusion Tensor Imaging, a new MRI imaging technique that offers a methodology to delineate the major white matter tracts in the brain. We apply the anisotropic diffusion model of Painter and Hillen (J Thoer Biol 323:25-39, 2013) to data from 10 patients with gliomas. Moreover, we compare the anisotropic model to the state-of-the-art Proliferation-Infiltration (PI) model of Swanson et al. (Cell Prolif 33:317-329, 2000). We find that the anisotropic model offers a slight improvement over the standard PI model. For tumours with low anisotropy, the predictions of the two models are virtually identical, but for patients whose tumours show higher anisotropy, the results differ. We also suggest using the data from the contralateral hemisphere to further improve the model fit. Finally, we discuss the potential use of this model in clinical treatment planning.

Quantitative assessment of changes in diffusion tensor imaging (DTI) metrics along the courses of the cortico-ponto-cerebellar tracts secondary to supratentorial human brain glial tumors.

BACKGROUND: The cortico-ponto-cerebellar tract (CPCT) is the largest projection pathway, which synapses at the pons. Remote effects of supratentorial brain tumors have not been evaluated along the infratentorial course of the CPCT. AIM: The purpose of this study is to evaluate the possible lateralization of the diffusion tensor metrics of the affected CPCT in patients with supratentorial brain tumor. METHODS AND RESULTS: We included 39 patients with 29 left-sided tumors (LST) and 10 right-sided tumors, retrospectively. We measured the magnitude of changes of the fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of the CPCT prior to the brain surgery at the level of crus cerebri and middle cerebellar peduncle. Regions of interest (ROIs) were placed on the lateral side of crus cerebri, and ROI-1 (anterior 1/3), ROI-2 (middle 1/3), ROI-3 (posterior 1/3), and ROI-4 were placed at the level of middle cerebellar peduncle. We hypothesized that there would be decreased FA and increased ADC values of the ipsilesional CPCT compared with contralesional CPCT. Ipsilesional FA values were decreased with simultaneous increased ADC value along the CPCT compared with contralesional CPCT in following ROIs, ROI-1 (LST FA: P = .005, ADC: P = .037) and ROI-3 (LST FA: P = .049, ADC: P = .049), respectively. Affected ROI-4 in LST cases also showed lower FA values, although not statistically significant. CONCLUSION: We observed a statistically significant FA value decrease and ADC increase along the left ROI-1 and ROI-3 as well as the nonstatistically significant FA decrease of the left ROI-4 at the second neuron level when there was a related supratentorial tumor. These findings are suggestive of presynaptic and postsynaptic microstructural changes of these tracts following the presynaptic involvement by a primary supratentorial brain tumor.

What can DTI tell about early cognitive impairment? - Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging.

Mild cognitive impairment (MCI) gained a lot of interest recently, especially that the conversion rate to Alzheimer Disease (AD) in the amnestic subtype (aMCI) is higher than in the non-amnestic subtype (naMCI). We aimed to determine whether and how diffusion-weighted MRI (DWI) using the diffusion tensor model (DTI) can differentiate MCI subtypes from healthy subjects. High resolution 3D T1W and DWI images of patients (aMCI, n = 18; naMCI, n = 20; according to Petersen criteria) and controls (n = 27) were acquired at 3T and processed using ExploreDTI and SPM. Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) were performed with ANCOVA; MD was higher in aMCI compared to controls or naMCI in several grey and white matter (GM, WM) regions (especially in the temporal pole and the inferior temporal lobes), while FA was lower in WM ROI-s (e.g. left Cingulum). Moreover, significant correlations were identified between verbal fluency, visual and verbal memory performance and DTI metrics. Logistic regression showed that measuring FA of the crus of fornix along GM volumetry improves the discrimination of aMCI from naMCI. Additional information from DWI/DTI aids preclinical detection of AD and may help detecting early non-Alzheimer type dementia, too.

A comparative study of the sensitivity of diffusion-related parameters obtained from diffusion tensor imaging, diffusional kurtosis imaging, q-space analysis and bi-exponential modelling in the early disease course (24 h) of hyperacute (6 h) ischemic stroke patients.

OBJECTIVES: To compare the sensitivity and early temporal changes of diffusion parameters obtained from diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), q-space analysis (QSA) and bi-exponential modelling in hyperacute stroke patients. MATERIALS AND METHODS: A single investigational acquisition allowing the four diffusion analyses was performed on seven hyperacute stroke patients with a 3T system. The percentage change between ipsi- and contralateral regions were compared at admission and 24 h later. Two out of the seven patients were imaged every 6 h during this period. RESULTS: Kurtoses from both DKI and QSA were the most sensitive of the tested diffusion parameters in the few hours following ischemia. An early increase-maximum-decrease pattern of evolution was highlighted during the 24-h period for all parameters proportional to diffusion coefficients. A similar pattern was observed for both kurtoses in only one of two patients. CONCLUSION: Our comparison was performed using identical diffusion encoding timings and on patients in the same stage of their condition. Although preliminary, our findings confirm those of previous studies that showed enhanced sensitivity of kurtosis. A fine time mapping of diffusion metrics in hyperacute stroke patients was presented which advocates for further investigations on larger animal or human cohorts.