Microstructural Alterations in Hippocampal Subfields Mediate Age-Related Memory Decline in Humans.

Aging, even in the absence of clear pathology of dementia, is associated with cognitive decline. Neuroimaging, especially diffusion-weighted imaging, has been highly valuable in understanding some of these changes in live humans, non-invasively. Traditional tensor techniques have revealed that the integrity of the fornix and other white matter tracts significantly deteriorates with age, and that this deterioration is highly correlated with worsening cognitive performance. However, traditional tensor techniques are still not specific enough to indict explicit microstructural features that may be responsible for age-related cognitive decline and cannot be used to effectively study gray matter properties. Here, we sought to determine whether recent advances in diffusion-weighted imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI) and Constrained Spherical Deconvolution, would provide more sensitive measures of age-related changes in the microstructure of the medial temporal lobe. We evaluated these measures in a group of young (ages 20-38 years old) and older (ages 59-84 years old) adults and assessed their relationships with performance on tests of cognition. We found that the fiber density (FD) of the fornix and the neurite density index (NDI) of the fornix, hippocampal subfields (DG/CA3, CA1, and subiculum), and parahippocampal cortex, varied as a function of age in a cross-sectional cohort. Moreover, in the fornix, DG/CA3, and CA1, these changes correlated with memory performance on the Rey Auditory Verbal Learning Test (RAVLT), even after regressing out the effect of age, suggesting that they were capturing neurobiological properties directly related to performance in this task. These measures provide more details regarding age-related neurobiological properties. For example, a change in fiber density could mean a reduction in axonal packing density or myelination, and the increase in NDI observed might be explained by changes in dendritic complexity or even sprouting. These results provide a far more comprehensive view than previously determined on the possible system-wide processes that may be occurring because of healthy aging and demonstrate that advanced diffusion-weighted imaging is evolving into a powerful tool to study more than just white matter properties

Beyond Patient Reported Pain: Perfusion Magnetic Resonance Imaging Demonstrates Reproducible Cerebral Representation of Ongoing Post-Surgical Pain

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Unfolding the hippocampus: An intrinsic coordinate system for subfield segmentations and quantitative mapping

The hippocampus, like the neocortex, has a morphological structure that is complex and variable in its folding pattern, especially in the hippocampal head. The current study presents a computational method to unfold hippocampal grey matter, with a particular focus on the hippocampal head where complexity is highest due to medial curving of the structure and the variable presence of digitations. This unfolding was performed on segmentations from high-resolution, T2-weighted 7T MRI data from 12 healthy participants and one surgical patient with epilepsy whose resected hippocampal tissue was used for histological validation. We traced a critical image feature composed of the hippocampal sulcus and stratum radiatum lacunosum-moleculare, (SRLM) in these images, then employed user-guided semi-automated techniques to detect and subsequently unfold the surrounding hippocampal grey matter. This unfolding was performed by solving Laplace\u27s equation in three dimensions of interest (long-axis, proximal-distal, and laminar). The resulting ‘unfolded coordinate space’ provides an intuitive way of mapping the hippocampal subfields in 2D space (long-axis and proximal-distal), such that similar borders can be applied in the head, body, and tail of the hippocampus independently of variability in folding. This unfolded coordinate space was employed to map intracortical myelin and thickness in relation to subfield borders, which revealed intracortical myelin differences that closely follow the subfield borders used here. Examination of a histological resected tissue sample from a patient with epilepsy reveals that our unfolded coordinate system has biological validity, and that subfield segmentations applied in this space are able to capture features not seen in manual tracing protocols

Distinct subdivisions of the cingulum bundle revealed by diffusion MRI fibre tracking: Implications for neuropsychological investigations

The cingulum is a prominent white matter tract that supports prefrontal, parietal, and temporal lobe interactions. Despite being composed of both short and long association fibres, many MRI-based reconstructions ( tractography ) of the cingulum depict an essentially uniform tract that almost encircles the corpus callosum. The present study tested the validity of dividing this tract into subdivisions corresponding to the ‘parahippocampal’, ‘retrosplenial’, and ‘subgenual’ portions of the cingulum. These three cingulum subdivisions occupied different medial–lateral locations, producing a topographic arrangement of cingulum fibres. Other comparisons based on these different reconstructions indicate that only a small proportion of the total white matter in the cingulum traverses the length of the tract. In addition, both the radial diffusivity and fractional anisotropy of the subgenual subdivision differed from that of the retrosplenial subdivision which, in turn, differed from that of the parahippocampal subdivision. The extent to which the radial diffusivity scores and the fractional anisotropy scores correlated between the various cingulum subdivisions proved variable, illustrating how one subdivision may not act as a proxy for other cingulum subdivisions. Attempts to relate the status of the cingulum, as measured by MRI-based fibre tracking, with cognitive or affective measures will, therefore, depend greatly on how and where the cingulum is reconstructed. The present study provides a new framework for subdividing the cingulum, based both on its known connectivity and MRI-based properties

Investigating white matter changes underlying overactive bladder in multiple sclerosis with diffusion MRI

Lower urinary tract symptoms (LUTS) are presented in more than 80% of multiple sclerosis (MS) patients. Current understanding of LUT control is based on studies exploring activities in grey matter (GM) and investigating functional correlations with LUTS. The relationship between white matter (WM) changes and overactive bladder (OAB) symptoms are limited to findings in small vessel disease, and the nature of the association between WM changes and OAB symptoms is poorly understood. Advanced diffusion-weighted magnetic resonance imaging (MRI) techniques provide non-invasive techniques to study WM abnormalities and correlates to clinical observations. The overarching objectives of this work are to explore WM abnormalities subtending OAB symptoms in MS, and to reconstruct the structural network underpinning the working model of lower urinary tract (LUT) control. Using Tract-Based Spatial Statistics (TBSS), OAB symptoms related WM abnormalities in MS can be identified, and a structural network subtending OAB symptoms in MS can be subsequently created. The findings of this work illustrate the correlation between OAB symptoms severity and WM abnormalities in MS. These were observed in regions in frontal lobes and non-dominant hemisphere, including corpus callosum, anterior corona radiata bilaterally, right anterior thalamic radiation, superior longitudinal fasciculus bilaterally, and right inferior longitudinal fasciculus. The structural network created for OAB symptoms in MS connected regions known to be involved in the working model of LUT control, and the network identified connectivity between insula and frontal lobe, which is the key circuit for perception of bladder fullness. Moreover, structural connectivity between insula-temporal lobe and insula-occipital lobe were observed, which may underpin changes seen in functional MRI (fMRI) studies. The novel findings of this study present WM abnormalities and structural connectivity subtending LUTS in MS with diffusion-weighted imaging (DWI). The techniques used in this work can be applied to other patterns of LUTS and other neurological diseases

Understanding the Contributions of Alzheimer’s Disease & Cardiovascular Risks to Cerebral Small Vessel Disease Manifest as White Matter Hyperintensities on Magnetic Resonance Imaging (MRI)

Introduction: Alzheimer’s Diseases (AD) & cerebral small vessel disease associated with cardiovascular risk factors (cSVD) frequently coexist, differentially affecting both imaging and clinical features associated with aging and dementia. We hypothesized that Magnetic Resonance Imaging (MRI) can be used in novel ways to identify relative contributions of AD & cardiovascular risks to cSVD and brain atrophy, generating new biomarkers & insights into mixed disease states associated with cognitive decline and dementia. Methods: Three experiments were conducted to address the overarching hypothesis. First, we visually rated the clinical MRI of 325 participants from a community-based cross-sectional sample to elucidate the relative association of age, AD (visualized as hippocampal atrophy) and cSVD (visualized as white matter hyperintensities; WMH) with global brain atrophy in experiment 1. In experiment 2, we analyzed cross-sectional MRI scans from 62 participants from the University of Kentucky Alzheimer’s Disease Center (UKADC) with available clinical data on cardiovascular risk and cerebrospinal fluid (CSF) beta-amyloid levels as a marker of AD. Voxel wise regression was used to examine the association of white matter hyperintensities with AD and/or cardiovascular risk (hypertension). Experiment 3, examined longitudinal MRI changes in WMH volumes in 377 participants from the Alzheimer’s Disease Neuroimaging Initiative 2 (ADNI 2). Subjects were categorized into three groups based on WMH volume change, including those that demonstrated regression (n=96; 25.5%), stability (n=72; 19.1%), and progression (n=209; 55.4%) of WMH volume over time. Differences in brain atrophy measures and cognitive testing among the three group were conducted. Results: In the first experiment, logistic regression analysis demonstrated that a 1-year increase in age was associated with global brain atrophy (OR = 1.04; p = .04), medial temporal lobe atrophy (MTA; a surrogate of AD) (OR = 3.7; p \u3c .001), and WMH as surrogate of cSVD (OR = 8.80; p \u3c .001). Both MTA and WMH were strongly associated with global brain atrophy in our study population, with WMH showing the strongest relationship after adjusting for age. In the second experiment, linear regression as well as mediation and moderation analyses demonstrated significant main effects of hypertension (HTN; the strongest risk factor associated with cSVD) and CSF Aβ 1-42 (a surrogate of AD) on WMH volume, but no significant HTN×CSF Aβ 1-42 interaction. Further exploration of the independence of HTN and Aβ using a voxelwise analysis approach, demonstrated unique patterns of WM alteration associated with either hypertension or CSF Aβ 1-42, confirming that both independently contribute to WMH previously classified as cSVD. Extending this work into a longitudinal model rather than focusing on purely cross-sectional associations, we demonstrated that spontaneous WMH regression is common, and that such regression is associated with a reduced rate of global brain atrophy (p = 0.012), and improvement in memory function over time (p = 0.003). Conclusion: These data demonstrate that both AD and cSVD frequently coexist in the same brain, contributing differentially to alterations in brain structure, subcortical white matter injury, and cognitive function. These effects can be disentangled using MRI, and while we currently lack therapeutic interventions to halt or reverse AD, the dynamic WMH change evident in our data clearly suggests that the ability to reverse cSVD exists today

Tissue Damage Quantification in Alzheimer\u27s Disease Brain via Magnetic Resonance Gradient Echo Plural Contrast Imaging (GEPCI)

Alzheimer’s disease (AD) affected approximately 48 million people worldwide in 2015. Its devastating consequences have stimulated an intense search for AD prevention and treatment. Clinically, AD is characterized by memory deficits and progressive cognitive impairment, leading to dementia. Over the past two to three decades, researchers have found that amyloidbeta (Aβ) plaques and neurofibrillary tau tangles occur during a long pre-symptomatic period (preclinical stage) before the onset of clinical symptoms. As a result, identification of the preclinical stage is essential for the initiation of prevention trials in asymptomatic individuals. Currently, Positron Emission Tomography (PET) imaging with injected 11C or 18F containing radiotracers (e.g., Pittsburgh compound B, PiB or florbetapir-fluorine-18, 18F-AV-45) is widely used to detect amyloid deposition in vivo and to identify this preclinical stage. However, PET scans are time consuming (about 1 hour), require injection of a radiotracer, thus, exposing the patient to ionizing radiation. After the preclinical stage, AD patients begin to show clinical symptoms, referred as a very mild or mild AD group. Post-mortem studies show that neuronal damage is the most proximate pathological substrate of cognitive impairment in AD compared with amyloid and tau deposition. Thus, a diagnostic tool is needed for detection of neuronal loss in vivo. As a faster, non-invasive, and radiation free imaging technique, Magnetic Resonance Imaging (MRI) plays an important role in the diagnosis of cognitive diseases. Conventional MRI yields superb definition of brain anatomy and structure and provide important volumetric information (e.g., brain atrophy). However, conventional MRI cannot provide microstructural and functional insight into the pathology of AD. The approach developed in Yablonskiy’s lab is based on the Gradient Echo Plural Contrast Imaging (GEPCI) protocol, which provides quantitative in vivo measurements of transverse relaxation properties of the tissue water 1H spins as determined from the gradient echo MRI signal. The measurements are corrected for macroscopic magnetic field inhomogeneity effects and physiologic-motion-driven fluctuations in magnetic field as these are the major artifacts present with the gradient echo technique. The principal relaxation property used in this dissertation is the tissue-specific transverse relaxation rate constant, R2*. The R2* value reflects the microscopic and mesoscopic magnetic field inhomogeneities rising from the complex tissuewater-environment within the human brain. In turn, changes in R2* reflect changes in the tissue’s microscopic and mesoscopic tissue structure. However, because of the presence of the cerebral blood vessel network, the magneticsusceptibility-driven blood-oxygen-level dependent (BOLD) effect also makes a significant contribution to R2*. A previously developed approach, quantitative BOLD (qBOLD), allows the separation of R2* into a tissue specific R2t* without blood vessel effects and the BOLD component. Quantifying the BOLD component allows the calculation of cerebral hemodynamics parameters, such as oxygen extraction fraction (OEF) and deoxygenated cerebral blood volume (dCBV). These parameters (R2*, R2t*, OEF, dCBV) describe structural and functional properties of tissue at the microstructural level in the human brain. In the study of normal aging, quantitative GEPCI measurements showed that R2t* increases with age while hemodynamic parameters, i.e., relative OEF and dCBV remain constant in most cerebral cortical regions. The comparison between quantitative GEPCI measurements and literature information suggest that (a) age-related increases in the cortical R2t* mostly reflect the age-related increases in the cellular packing density (or neuronal density); (b) regions in a brain characterized by higher R2t* contain a higher concentration of neurons with less developed cellular processes (dendrites, spines, etc.); and (c) brain regions characterized by lower R2t* represent regions with lower concentration of neurons but more developed cellular processes. In the Alzheimer study, R2* and R2t* together demonstrated significant differences among the normal, preclinical and mild AD groups. First, the results uncovered strong correlations between R2* and Aβ deposition measured by the PiB PET-tracer in several cortical regions (e.g., medial temporal lobe and precuneus). This finding indicates that R2* may be a potential surrogate marker for Aβ deposition. The strongest correlation was found in the medial temporal lobe (MTL), particularly in the parahippocampal cortex, which can be used to distinguish the normal and preclinical groups. Second, R2t* in the hippocampus, which characterized the hippocampal cellular integrity demonstrated much stronger correlations with psychometric tests than volume quantification of hippocampal atrophy. Importantly, decreased R2t* characterizing cellular damage was detected even in the hippocampal areas not affected by atrophy. In addition, R2t* significantly decreased in the mild AD group but was preserved in the preclinical group compared with the normal group. These results indicate a significant cellular density decrease in the mild group but not in the preclinical group, which is consistent with previous histological studies. In summary, GEPCI provides a new approach for evaluation of AD-related tissue pathology in vivo in the preclinical and early symptomatic stages of AD. Since MRI is widely available worldwide and does not require radiation exposure, it provides the opportunity to obtain new information on the pathogenesis of AD and for pre-screening cohorts (stratification) for clinical drug trials

Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression

Real-time fMRI neurofeedback (rtfMRI-nf) is an emerging approach for studies and novel treatments of major depressive disorder (MDD). EEG performed simultaneously with an rtfMRI-nf procedure allows an independent evaluation of rtfMRI-nf brain modulation effects. Frontal EEG asymmetry in the alpha band is a widely used measure of emotion and motivation that shows profound changes in depression. However, it has never been directly related to simultaneously acquired fMRI data. We report the first study investigating electrophysiological correlates of the rtfMRI-nf procedure, by combining rtfMRI-nf with simultaneous and passive EEG recordings. In this pilot study, MDD patients in the experimental group (n=13) learned to upregulate BOLD activity of the left amygdala using an rtfMRI-nf during a happy emotion induction task. MDD patients in the control group (n=11) were provided with a sham rtfMRI-nf. Correlations between frontal EEG asymmetry in the upper alpha band and BOLD activity across the brain were examined. Average individual changes in frontal EEG asymmetry during the rtfMRI-nf task for the experimental group showed a significant positive correlation with the MDD patients' depression severity ratings, consistent with an inverse correlation between the depression severity and frontal EEG asymmetry at rest. Temporal correlations between frontal EEG asymmetry and BOLD activity were significantly enhanced, during the rtfMRI-nf task, for the amygdala and many regions associated with emotion regulation. Our findings demonstrate an important link between amygdala BOLD activity and frontal EEG asymmetry. Our EEG asymmetry results suggest that the rtfMRI-nf training targeting the amygdala is beneficial to MDD patients, and that alpha-asymmetry EEG-nf would be compatible with the amygdala rtfMRI-nf. Combination of the two could enhance emotion regulation training and benefit MDD patients.Comment: 28 pages, 16 figures, to appear in NeuroImage: Clinica

Multi-parametric Imaging Using Hybrid PET/MR to Investigate the Epileptogenic Brain

Neuroimaging analysis has led to fundamental discoveries about the healthy and pathological human brain. Different imaging modalities allow garnering complementary information about brain metabolism, structure and function. To ensure that the integration of imaging data from these modalities is robust and reliable, it is fundamental to attain deep knowledge of each modality individually. Epilepsy, a neurological condition characterised by recurrent spontaneous seizures, represents a field in which applications of neuroimaging and multi-parametric imaging are particularly promising to guide diagnosis and treatment. In this PhD thesis, I focused on different imaging modalities and investigated advanced denoising and analysis strategies to improve their application to epilepsy. The first project focused on fluorodeoxyglucose (FDG) positron emission tomography (PET), a well-established imaging modality assessing brain metabolism, and aimed to develop a novel, semi-quantitative pipeline to analyse data in children with epilepsy, thus aiding presurgical planning. As pipelines for FDG-PET analysis in children are currently lacking, I developed age-appropriate templates to provide statistical parametric maps identifying epileptogenic areas on patient scans. The second and third projects focused on two magnetic resonance imaging (MRI) modalities: resting-state functional MRI (rs-fMRI) and arterial spin labelling (ASL), respectively. The aim was to i) probe the efficacy of different fMRI denoising pipelines, and ii) formally compare different ASL data acquisition strategies. In the former case, I compared different pre-processing methods and assessed their impact on fMRI signal quality and related functional connectivity analyses. In the latter case, I compared two ASL sequences to investigate their ability to quantify cerebral blood flow and interregional brain connectivity. The final project addressed the combination of rs-fMRI and ASL, and leveraged graph-theoretical analysis tools to i) compare metrics estimated via these two imaging modalities in healthy subjects and ii) assess topological changes captured by these modalities in a sample of temporal lobe epilepsy patients