A tract-specific approach to assessing white matter in preterm infants.

Diffusion-weighted imaging (DWI) is becoming an increasingly important tool for studying brain development. DWI analyses relying on manually-drawn regions of interest and tractography using manually-placed waypoints are considered to provide the most accurate characterisation of the underlying brain structure. However, these methods are labour-intensive and become impractical for studies with large cohorts and numerous white matter (WM) tracts. Tract-specific analysis (TSA) is an alternative WM analysis method applicable to large-scale studies that offers potential benefits. TSA produces a skeleton representation of WM tracts and projects the group's diffusion data onto the skeleton for statistical analysis. In this work we evaluate the performance of TSA in analysing preterm infant data against results obtained from native space tractography and tract-based spatial statistics. We evaluate TSA's registration accuracy of WM tracts and assess the agreement between native space data and template space data projected onto WM skeletons, in 12 tracts across 48 preterm neonates. We show that TSA registration provides better WM tract alignment than a previous protocol optimised for neonatal spatial normalisation, and that TSA projects FA values that match well with values derived from native space tractography. We apply TSA for the first time to a preterm neonatal population to study the effects of age at scan on WM tracts around term equivalent age. We demonstrate the effects of age at scan on DTI metrics in commissural, projection and association fibres. We demonstrate the potential of TSA for WM analysis and its suitability for infant studies involving multiple tracts

Automated voxel-wise brain DTI analysis of fitness and aging

Diffusion Tensor Imaging (DTI) has become a widely used MR modality to investigate white matter integrity in the brain. This paper presents the application of an automated method for voxel-wise group comparisons of DTI images in a study of fitness and aging. The automated processing method consists of 3 steps: 1) preprocessing including image format converting, image quality control, eddy-current and motion artifact correction, skull stripping and tensor image estimation, 2) study-specific unbiased DTI atlas computation via diffeomorphic fluid-based and demons deformable registration and 3) voxel-wise statistical analysis via heterogeneous linear regression and a wild bootstrap technique for correcting for multiple comparisons. Our results show that this fully automated method is suitable for voxel-wise group DTI analysis. Furthermore, in older adults, the results suggest a strong link between reduced fractional anisotropy (FA) values, fitness and aging

White Matter Diffusion Alterations in Normal Women at Risk of Alzheimer\u27s Disease

Increased white matter mean diffusivity and decreased fractional anisotropy (FA) has been observed in subjects diagnosed with mild cognitive impairment (MCI) and Alzheimer\u27s disease (AD). We sought to determine whether similar alterations of white matter occur in normal individuals at risk of AD. Diffusion tensor images were acquired in 42 cognitively normal right-handed women with both a family history of dementia and at least one apolipoprotein E4 allele. These were compared with images from 23 normal women without either AD risk factor. Group analyses were performed using tract-based spatial statistics. Reduced FA was observed in the fronto-occipital and inferior temporal fasciculi (particularly posteriorly), the splenium of the corpus callosum, subcallosal white matter and the cingulum bundle. These findings demonstrate that specific white matter pathways are altered in normal women at increased risk of AD years before the expected onset of cognitive symptoms

Microstructural differences in white matter tracts across middle to late adulthood : a diffusion MRI study on 7167 UK Biobank participants

Acknowledgements This research was approved by the UK Biobank (application number: 24089) and was supported by the Roland Sutton Academic Trust (grant number: 0039/R/16) and Taiwan National Health Research Institute (NHRI-EX109-10928NI). We acknowledge the valuable contributions of members of the UK Biobank Imaging Working Group and the UK Biobank coordinating center. The UK Biobank (including the imaging enhancement) was supported by the UK Medical Research Council and the Wellcome Trust. The authors are grateful for the provision of simultaneous multislice (multiband) pulse sequence and reconstruction algorithms by the Center for Magnetic Resonance Research, University of Minnesota. Finally, the authors are extremely grateful to all UK Biobank study participants, who have generously donated their time to make this resource possible. This article was edited by Wallace Academic Editing.Peer reviewedPostprin

Cerebrospinal fluid biomarkers of neurofibrillary tangles and synaptic dysfunction are associated with longitudinal decline in white matter connectivity: A multi-resolution graph analysis

In addition to the development of beta amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) involves the loss of connecting structures including degeneration of myelinated axons and synaptic connections. However, the extent to which white matter tracts change longitudinally, particularly in the asymptomatic, preclinical stage of AD, remains poorly characterized. In this study we used a novel graph wavelet algorithm to determine the extent to which microstructural brain changes evolve in concert with the development of AD neuropathology as observed using CSF biomarkers. A total of 118 participants with at least two diffusion tensor imaging (DTI) scans and one lumbar puncture for CSF were selected from two observational and longitudinally followed cohorts. CSF was assayed for pathology specific to AD (Aβ42 and phosphorylated-tau), neurodegeneration (total-tau), axonal degeneration (neurofilament light chain protein; NFL), and synaptic degeneration (neurogranin). Tractography was performed on DTI scans to obtain structural connectivity networks with 160 nodes where the nodes correspond to specific brain regions of interest (ROIs) and their connections were defined by DTI metrics (i.e., fractional anisotropy (FA) and mean diffusivity (MD)). For the analysis, we adopted a multi-resolution graph wavelet technique called Wavelet Connectivity Signature (WaCS) which derives higher order representations from DTI metrics at each brain connection. Our statistical analysis showed interactions between the CSF measures and the MRI time interval, such that elevated CSF biomarkers and longer time were associated with greater longitudinal changes in white matter microstructure (decreasing FA and increasing MD). Specifically, we detected a total of 17 fiber tracts whose WaCS representations showed an association between longitudinal decline in white matter microstructure and both CSF p-tau and neurogranin. While development of neurofibrillary tangles and synaptic degeneration are cortical phenomena, the results show that they are also associated with degeneration of underlying white matter tracts, a process which may eventually play a role in the development of cognitive decline and dementia

Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative (GENFI) cohort

Abstract Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. 387 mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). W-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as “normal” or “abnormal” based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the “normal” and “abnormal” groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers. Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials

The impact of aerobic exercise on brain's white matter integrity in the Alzheimer's disease and the aging population

The brain is the most complex organ in the body. Currently, its complicated functionality has not been fully understood. However, in the last decades an exponential growth on research publications emerged thanks to the use of in-vivo brain imaging techniques. One of these techniques pioneered for medical use in the early 1970s was known as nuclear magnetic resonance imaging based (now called magnetic resonance imaging [MRI]). Nowadays, the advances of MRI technology not only allowed us to characterize volumetric changes in specific brain structures but now we could identify different patterns of activation (e.g. functional MRI) or changes in structural brain connectivity (e.g. diffusion MRI). One of the benefits of using these techniques is that we could investigate changes that occur in disease-specific cohorts such as in the case of Alzheimer’s disease (AD), a neurodegenerative disease that affects mainly older populations. This disease has been known for over a century and even though great advances in technology and pharmacology have occurred, currently there is no cure for the disease. Hence, in this work I decided to investigate whether aerobic exercise, an emerging alternative method to pharmacological treatments, might provide neuroprotective effects to slow down the evident brain deterioration of AD using novel in-vivo diffusion imaging techniques. Previous reports in animal and human studies have supported these exercise-related neuro-protective mechanisms. Concurrently in AD participants, increased brain volumes have been positively associated with higher cardiorespiratory fitness levels, a direct marker of sustained physical activity and increased exercise. Thus, the goal of this work is to investigate further whether exercise influences the brain using structural connectivity analyses and novel diffusion imaging techniques that go beyond volumetric characterization. The approach I chose to present this work combined two important aspects of the investigation. First, I introduced important concepts based on the neuro-scientific work in relation to Alzheimer’s diseases, in-vivo imaging, and exercise physiology (Chapter 1). Secondly, I tried to describe in simple mathematics the physics of this novel diffusion imaging technique (Chapter 2) and supported a tract-specific diffusion imaging processing methodology (Chapter 3 and 4). Consequently, the later chapters combined both aspects of this investigation in a manuscript format (Chapter 5-8). Finally, I summarized my findings, include recommendations for similar studies, described future work, and stated a final conclusion of this work (Chapter 9)

Detecting and tracking early neurodegeneration in familial Alzheimer’s disease

Alzheimer’s disease (AD) is recognized to have a long presymptomatic period, with initial deposition of extracellular amyloid and intracellular tau, followed by downstream neurodegeneration and cognitive decline. There is great interest in testing potential disease-modifying treatments for AD prior to the onset of symptoms, when minimal neuronal loss has occurred. To facilitate this, robust and sensitive methods are needed to identify at-risk individuals, stage their disease, and track progression. Familial Alzheimer’s disease (FAD) shares many features, clinically, radiologically, and neurophysiologically, with the more common sporadic form of disease. Carriers of autosomal dominantly inherited mutations in the presenilin 1, presenilin 2, and amyloid precursor protein genes have relatively predictable ages at symptom onset, based on family history. Study of FAD mutation carriers therefore provides the opportunity for the prospective study of asymptomatic individuals with known underlying AD pathology prior to the onset of clinical disease. The studies presented herein aim to improve the identification and characterization of early FAD neurodegenerative change and its earliest downstream cognitive effects. A multimodal approach is taken, with both presymptomatic and mildly symptomatic individuals included. Chapter one provides an introduction to AD and methods for measuring early neurodegeneration. Chapter two then outlines the general methodological approach across the different studies. Chapters three and four present results of magnetic resonance imaging studies of macrostructural (cortical thickness) and microstructural (diffusion-weighted imaging) cortical change. Chapter five reports results for a new blood-based biomarker of neurodegeneration – serum neurofilamentlight. Chapter six investigates a novel approach to presymptomatic cognitive testing – 6 assessing accelerated long-term forgetting. In all studies, significant differences between mutation carriers and non-carrier controls are detectable during the presymptomatic period. The thesis draws together these different approaches and discusses how they advance our understanding of the neurobiology of AD and their potential utility in both clinical assessment and presymptomatic therapeutic trials

Unconventional markers of Alzheimer Disease

Although typically conceptualized as a cortical disease, recent neuropathological and neuroimaging investigations on Alzheimer Disease suggest that other brain structures play an important role in the pathogenesis and progression of this devastating condition. In this thesis, we explored novel markers of Alzheimer Disease beyond the classical cortical pathology measures of amyloid, tau, and neurodegeneration. We focused on the role of white matter abnormalities, assessed with magnetic resonance imaging but also with amyloid positron emission tomography, in predicting early pathologic changes and disease progression, as well as on the added value of cognition to amyloid, tau, and neurodegeneration biomarkers. Overall, we found that these unconventional markers provide useful information to detect the earliest pathological changes of the disease, providing a better understanding of the mechanisms that lead to amyloid deposition and cognitive decline