Modeling seeding and neuroanatomic spread of pathology in amyotrophic lateral sclerosis.

The neurodegenerative disorder amyotrophic lateral sclerosis (ALS) is characterized by the progressive loss of upper and lower motor neurons, with pathological involvement of cerebral motor and extra-motor areas in a clinicopathological spectrum with frontotemporal dementia (FTD). A key unresolved issue is how the non-random distribution of pathology in ALS reflects differential network vulnerability, including molecular factors such as regional gene expression, or preferential spread of pathology via anatomical connections. A system of histopathological staging of ALS based on the regional burden of TDP-43 pathology observed in postmortem brains has been supported to some extent by analysis of distribution of in vivo structural MRI changes. In this paper, computational modeling using a Network Diffusion Model (NDM) was used to investigate whether a process of focal pathological 'seeding' followed by structural network-based spread recapitulated postmortem histopathological staging and, secondly, whether this had any correlation to the pattern of expression of a panel of genes implicated in ALS across the healthy brain. Regionally parcellated T1-weighted MRI data from ALS patients (baseline n=79) was studied in relation to a healthy control structural connectome and a database of associated regional cerebral gene expression. The NDM provided strong support for a structural network-based basis for regional pathological spread in ALS, but no simple relationship to the spatial distribution of ALS-related genes in the healthy brain. Interestingly, OPTN gene was identified as a significant but a weaker non-NDM contributor within the network-gene interaction model (LASSO). Intriguingly, the critical seed regions for spread within the model were not within the primary motor cortex but basal ganglia, thalamus and insula, where NDM recapitulated aspects of the postmortem histopathological staging system. Within the ALS-FTD clinicopathological spectrum, non-primary motor structures may be among the earliest sites of cerebral pathology.

A method to remove the influence of fixative concentration on postmortem T2 maps using a kinetic tensor model.

Formalin fixation has been shown to substantially reduce T2 estimates, primarily driven by the presence of fixative in tissue. Prior to scanning, post-mortem samples are often placed into a fluid that has more favourable imaging properties. This study investigates whether there is evidence for a change in T2 in regions close to the tissue surface due to fixative outflux into this surrounding fluid. Furthermore, we investigate whether a simulated spatial map of fixative concentration can be used as a confound regressor to reduce T2 inhomogeneity. To achieve this, T2 maps and diffusion tensor estimates were obtained in 14 whole, formalin-fixed post-mortem brains placed in Fluorinert approximately 48 hr prior to scanning. Seven brains were fixed with 10% formalin and seven brains were fixed with 10% neutral buffered formalin (NBF). Fixative outflux was modelled using a proposed kinetic tensor (KT) model, which incorporates voxelwise diffusion tensor estimates to account for diffusion anisotropy and tissue-specific diffusion coefficients. Brains fixed with 10% NBF revealed a spatial T2 pattern consistent with modelled fixative outflux. Confound regression of fixative concentration reduced T2 inhomogeneity across both white and grey matter, with the greatest reduction attributed to the KT model versus simpler models of fixative outflux. No such effect was observed in brains fixed with 10% formalin. Correlations between the transverse relaxation rate R2 and ferritin/myelin proteolipid protein (PLP) histology lead to an increased similarity for the relationship between R2 and PLP for the two fixative types after KT correction.

Investigation of urinary storage symptoms in Parkinson's disease utilizing structural MRI techniques.

BACKGROUND: Lower urinary tract symptoms occur in 27% to 86% of patients with Parkinson's disease (PD), however, the mechanisms responsible for bladder dysfunction are not fully understood. This study utilized magnetic resonance imaging (MRI) to test the hypothesis that key brainstem bladder control areas (including the pontine micturition center and the pontine continence center (PCC) and their links with the basal ganglia are important in the development of urinary storage symptoms in PD. METHODS: Seventeen patients with PD completed a "bladder symptom questionnaire" and underwent diffusion-weighted MRI (1.5 T). Storage symptom severity and MRI measures of white matter microstructural integrity were correlated using tract-based spatial statistics. RESULTS: Mean diffusivity in the ventral brainstem correlated significantly with the bladder symptom severity in areas close to the predicted anatomical co-ordinates of the PCC. Tracts seeded from these regions passed via areas involved in pelvic floor musculature control and urinary voiding including the cerebellum, pallidum, and precentral gyrus. CONCLUSION: We used diffusion-weighted MRI to investigate the role of the brainstem and its structural connections in the development of urinary storage symptoms in PD. Our data suggest that the brainstem degenerative change in the vicinity of the PCC may be implicated in the pathogenesis of storage symptoms in these patients.

Dissecting the pathobiology of altered MRI signal in amyotrophic lateral sclerosis: A post mortem whole brain sampling strategy for the integration of ultra-high-field MRI and quantitative neuropathology.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a clinically and histopathologically heterogeneous neurodegenerative disorder, in which therapy is hindered by the rapid progression of disease and lack of biomarkers. Magnetic resonance imaging (MRI) has demonstrated its potential for detecting the pathological signature and tracking disease progression in ALS. However, the microstructural and molecular pathological substrate is poorly understood and generally defined histologically. One route to understanding and validating the pathophysiological correlates of MRI signal changes in ALS is to directly compare MRI to histology in post mortem human brains. RESULTS: The article delineates a universal whole brain sampling strategy of pathologically relevant grey matter (cortical and subcortical) and white matter tracts of interest suitable for histological evaluation and direct correlation with MRI. A standardised systematic sampling strategy that was compatible with co-registration of images across modalities was established for regions representing phosphorylated 43-kDa TAR DNA-binding protein (pTDP-43) patterns that were topographically recognisable with defined neuroanatomical landmarks. Moreover, tractography-guided sampling facilitated accurate delineation of white matter tracts of interest. A digital photography pipeline at various stages of sampling and histological processing was established to account for structural deformations that might impact alignment and registration of histological images to MRI volumes. Combined with quantitative digital histology image analysis, the proposed sampling strategy is suitable for routine implementation in a high-throughput manner for acquisition of large-scale histology datasets. Proof of concept was determined in the spinal cord of an ALS patient where multiple MRI modalities (T1, T2, FA and MD) demonstrated sensitivity to axonal degeneration and associated heightened inflammatory changes in the lateral corticospinal tract. Furthermore, qualitative comparison of R2* and susceptibility maps in the motor cortex of 2 ALS patients demonstrated varying degrees of hyperintense signal changes compared to a control. Upon histological evaluation of the same region, intensity of signal changes in both modalities appeared to correspond primarily to the degree of microglial activation. CONCLUSION: The proposed post mortem whole brain sampling methodology enables the accurate intraindividual study of pathological propagation and comparison with quantitative MRI data, to more fully understand the relationship of imaging signal changes with underlying pathophysiology in ALS.

Regional thalamic MRI as a marker of widespread cortical pathology and progressive frontotemporal involvement in amyotrophic lateral sclerosis.

BACKGROUND: The thalamus is a major neural hub, with selective connections to virtually all cortical regions of the brain. The multisystem neurodegenerative syndrome amyotrophic lateral sclerosis (ALS) has pathogenic overlap with frontotemporal dementia, and objective in vivo markers of extra-motor pathological spread are lacking. To better consider the role of the thalamus in neurodegeneration, the present study assessed the integrity of the thalamus and its connectivity to major cortical regions of the brain in a longitudinal manner. METHODS: Diffusion-based MRI tractography was used to parcellate the thalamus into distinct regions based on structural thalamo-cortical connectivity in 20 patients with ALS, half of whom were scanned at two time points, and 31 matched controls scanned on a single occasion. RESULTS: At baseline, widespread diffusivity alterations in motor- and extramotor-associated thalamic parcellations were detectable. Longitudinal decline selectively affected thalamic regions associated with frontal and temporal lobe connectivity. Diffusivity measures were significantly correlated with clinical measures of disease burden. Progression of functional disability, as indicated by change on the ALS functional rating scale, was associated with longitudinal change in mean diffusivity of the right frontal lobe thalamic parcellation (r=0.59, p=0.05). CONCLUSIONS: Regional thalamic connectivity changes mirror the progressive frontotemporal cortical involvement associated with the motor functional decline in ALS. Longitudinal MRI thalamic parcellation has potential as a non-invasive surrogate marker of cortical dysfunction in ALS.

Basal ganglia dysfunction in idiopathic REM sleep behaviour disorder parallels that in early Parkinson's disease.

SEE POSTUMA DOI101093/AWW131 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Resting state functional magnetic resonance imaging dysfunction within the basal ganglia network is a feature of early Parkinson's disease and may be a diagnostic biomarker of basal ganglia dysfunction. Currently, it is unclear whether these changes are present in so-called idiopathic rapid eye movement sleep behaviour disorder, a condition associated with a high rate of future conversion to Parkinson's disease. In this study, we explore the utility of resting state functional magnetic resonance imaging to detect basal ganglia network dysfunction in rapid eye movement sleep behaviour disorder. We compare these data to a set of healthy control subjects, and to a set of patients with established early Parkinson's disease. Furthermore, we explore the relationship between resting state functional magnetic resonance imaging basal ganglia network dysfunction and loss of dopaminergic neurons assessed with dopamine transporter single photon emission computerized tomography, and perform morphometric analyses to assess grey matter loss. Twenty-six patients with polysomnographically-established rapid eye movement sleep behaviour disorder, 48 patients with Parkinson's disease and 23 healthy control subjects were included in this study. Resting state networks were isolated from task-free functional magnetic resonance imaging data using dual regression with a template derived from a separate cohort of 80 elderly healthy control participants. Resting state functional magnetic resonance imaging parameter estimates were extracted from the study subjects in the basal ganglia network. In addition, eight patients with rapid eye movement sleep behaviour disorder, 10 with Parkinson's disease and 10 control subjects received (123)I-ioflupane single photon emission computerized tomography. We tested for reduction of basal ganglia network connectivity, and for loss of tracer uptake in rapid eye movement sleep behaviour disorder and Parkinson's disease relative to each other and to controls. Connectivity measures of basal ganglia network dysfunction differentiated both rapid eye movement sleep behaviour disorder and Parkinson's disease from controls with high sensitivity (96%) and specificity (74% for rapid eye movement sleep behaviour disorder, 78% for Parkinson's disease), indicating its potential as an indicator of early basal ganglia dysfunction. Rapid eye movement sleep behaviour disorder was indistinguishable from Parkinson's disease on resting state functional magnetic resonance imaging despite obvious differences on dopamine transported single photon emission computerized tomography. Basal ganglia connectivity is a promising biomarker for the detection of early basal ganglia network dysfunction, and may help to identify patients at risk of developing Parkinson's disease in the future. Future risk stratification using a polymodal approach could combine basal ganglia network connectivity with clinical and other imaging measures, with important implications for future neuroprotective trials in rapid eye movement sleep behaviour disorder.

Challenges in the reproducibility of clinical studies with resting state fMRI: An example in early Parkinson's disease.

Resting state fMRI (rfMRI) is gaining in popularity, being easy to acquire and with promising clinical applications. However, rfMRI studies, especially those involving clinical groups, still lack reproducibility, largely due to the different analysis settings. This is particularly important for the development of imaging biomarkers. The aim of this work was to evaluate the reproducibility of our recent study regarding the functional connectivity of the basal ganglia network in early Parkinson's disease (PD) (Szewczyk-Krolikowski et al., 2014). In particular, we systematically analysed the influence of two rfMRI analysis steps on the results: the individual cleaning (artefact removal) of fMRI data and the choice of the set of independent components (template) used for dual regression. Our experience suggests that the use of a cleaning approach based on single-subject independent component analysis, which removes non neural-related sources of inter-individual variability, can help to increase the reproducibility of clinical findings. A template generated using an independent set of healthy controls is recommended for studies where the aim is to detect differences from a "healthy" brain, rather than an "average" template, derived from an equal number of patients and controls. While, exploratory analyses (e.g. testing multiple resting state networks) should be used to formulate new hypotheses, careful validation is necessary before promising findings can be translated into useful biomarkers.

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

OBJECTIVE: To discern presymptomatic changes in brain structure or function using advanced MRI in carriers of mutations predisposing to amyotrophic lateral sclerosis (ALS). METHODS: T1-weighted, diffusion weighted and resting state functional MRI data were acquired at 3 T for 12 asymptomatic mutation carriers (psALS), 12 age-matched controls and affected patients with ALS. Cortical thickness analysis, voxel-based morphometry, volumetric and shape analyses of subcortical structures, tract-based spatial statistics of metrics derived from the diffusion tensor, and resting state functional connectivity (FC) analyses were performed. RESULTS: Grey matter cortical thickness and shape analysis revealed significant atrophy in patients with ALS (but not psALS) compared with controls in the right primary motor cortex and right caudate. Comparison of diffusion tensor metrics showed widespread fractional anisotropy and radial diffusivity differences in patients with ALS compared to controls and the psALS group, encompassing parts of the corpus callosum, corticospinal tracts and superior longitudinal fasciculus. While FC in the resting-state sensorimotor network was similar in psALS and controls, FC between the cerebellum and a network comprising the precuneus, cingulate & middle frontal lobe was significantly higher in psALS and affected ALS compared to controls. CONCLUSIONS: Rather than structural brain changes, increased FC may be among the earliest detectable brain abnormalities in asymptomatic carriers of ALS-causing gene mutations. With replication and significant refinement, this technique has potential in the future assessment of neuroprotective strategies.

Thalamo-Cortical Disruption Contributes to Short-Term Memory Deficits in Patients with Medial Temporal Lobe Damage.

Short-term (STM) and long-term memory (LTM) have largely been considered as separate brain systems reflecting fronto-parietal and medial temporal lobe (MTL) functions, respectively. This functional dichotomy has been called into question by evidence of deficits on aspects of working memory in patients with MTL damage, suggesting a potentially direct hippocampal contribution to STM. As the hippocampus has direct anatomical connections with the thalamus, we tested the hypothesis that damage to thalamic nuclei regulating cortico-cortical interactions may contribute to STM deficits in patients with hippocampal dysfunction. We used diffusion-weighted magnetic resonance imaging-based tractography to identify anatomical subdivisions in patients with MTL epilepsy. From these, we measured resting-state functional connectivity with detailed cortical divisions of the frontal, temporal, and parietal lobes. Whereas thalamo-temporal functional connectivity reflected LTM performance, thalamo-prefrontal functional connectivity specifically predicted STM performance. Notably, patients with hippocampal volume loss showed thalamic volume loss, most prominent in the pulvinar region, not detected in patients with normal hippocampal volumes. Aberrant thalamo-cortical connectivity in the epileptic hemisphere was mirrored in a loss of behavioral association with STM performance specifically in patients with hippocampal atrophy. These findings identify thalamo-cortical disruption as a potential mechanism contributing to STM deficits in the context of MTL damage.

Widespread grey matter pathology dominates the longitudinal cerebral MRI and clinical landscape of amyotrophic lateral sclerosis.

Diagnosis, stratification and monitoring of disease progression in amyotrophic lateral sclerosis currently rely on clinical history and examination. The phenotypic heterogeneity of amyotrophic lateral sclerosis, including extramotor cognitive impairments is now well recognized. Candidate biomarkers have shown variable sensitivity and specificity, and studies have been mainly undertaken only cross-sectionally. Sixty patients with sporadic amyotrophic lateral sclerosis (without a family history of amyotrophic lateral sclerosis or dementia) underwent baseline multimodal magnetic resonance imaging at 3 T. Grey matter pathology was identified through analysis of T1-weighted images using voxel-based morphometry. White matter pathology was assessed using tract-based spatial statistics analysis of indices derived from diffusion tensor imaging. Cross-sectional analyses included group comparison with a group of healthy controls (n = 36) and correlations with clinical features, including regional disability, clinical upper motor neuron signs and cognitive impairment. Patients were offered 6-monthly follow-up MRI, and the last available scan was used for a separate longitudinal analysis (n = 27). In cross-sectional study, the core signature of white matter pathology was confirmed within the corticospinal tract and callosal body, and linked strongly to clinical upper motor neuron burden, but also to limb disability subscore and progression rate. Localized grey matter abnormalities were detected in a topographically appropriate region of the left motor cortex in relation to bulbar disability, and in Broca's area and its homologue in relation to verbal fluency. Longitudinal analysis revealed progressive and widespread changes in the grey matter, notably including the basal ganglia. In contrast there was limited white matter pathology progression, in keeping with a previously unrecognized limited change in individual clinical upper motor neuron scores, despite advancing disability. Although a consistent core white matter pathology was found cross-sectionally, grey matter pathology was dominant longitudinally, and included progression in clinically silent areas such as the basal ganglia, believed to reflect their wider cortical connectivity. Such changes were significant across a range of apparently sporadic patients rather than being a genotype-specific effect. It is also suggested that the upper motor neuron lesion in amyotrophic lateral sclerosis may be relatively constant during the established symptomatic period. These findings have implications for the development of effective diagnostic versus therapeutic monitoring magnetic resonance imaging biomarkers. Amyotrophic lateral sclerosis may be characterized initially by a predominantly white matter tract pathological signature, evolving as a widespread cortical network degeneration.

Brain microstructure reveals early abnormalities more than two years prior to clinical progression from mild cognitive impairment to Alzheimer's disease.

Diffusion imaging is a promising marker of microstructural damage in neurodegenerative disorders, but interpretation of its relationship with underlying neuropathology can be complex. Here, we examined both volumetric and brain microstructure abnormalities in 13 amnestic patients with mild cognitive impairment (MCI), who progressed to probable Alzheimer's disease (AD) no earlier than 2 years after baseline scanning, in order to focus on early, and hence more sensitive, imaging markers. We compared them to 22 stable amnestic MCI patients with similar cognitive performance and episodic memory impairment but who did not show progression of symptoms for at least 3 years. Significant group differences were mainly found in the volume and microstructure of the left hippocampus, while white matter group differences were also found in the body of the fornix, left fimbria, and superior longitudinal fasciculus (SLF). Diffusion index abnormalities in the SLF were the sign of a subtle microstructural injury not detected by standard atrophy measures in the corresponding gray matter regions. The microstructural measure obtained in the left hippocampus using diffusion imaging showed the most substantial differences between the two groups and was the best single predictor of future progression to AD. An optimal prediction model (91% accuracy, 85% sensitivity, 96% specificity) was obtained by combining MRI measures and CSF protein biomarkers. These results highlight the benefit of using the information of brain microstructural damage, in addition to traditional gray matter volume, to detect early, subtle abnormalities in MCI prior to clinical progression to probable AD and, in combination with CSF markers, to accurately predict such progression.

Comprehensive morphometry of subcortical grey matter structures in early-stage Parkinson's disease.

Previous imaging studies that investigated morphometric group differences of subcortical regions outside the substantia nigra between non-demented Parkinson's patients and controls either did not find any significant differences, or reported contradictory results. Here, we performed a comprehensive morphometric analysis of 20 cognitively normal, early-stage PD patients and 19 matched control subjects. In addition to relatively standard analyses of whole-brain grey matter volume and overall regional volumes, we examined subtle localized surface shape differences in striatal and limbic grey matter structures and tested their utility as a diagnostic marker. Voxel-based morphometry and volumetric comparisons did not reveal significant group differences. Shape analysis, on the other hand, demonstrated significant between-group shape differences for the right pallidum. Careful diffusion tractography analysis showed that the affected parts of the pallidum are connected subcortically with the subthalamic nucleus, the pedunculopontine nucleus, and the thalamus and cortically with the frontal lobe. Additionally, microstructural measurements along these pathways, but not along other pallidal connections, were significantly different between the two groups. Vertex-wise linear discriminant analysis, however, revealed limited accuracy of pallidal shape for the discrimination between patients and controls. We conclude that localized disease-related changes in the right pallidum in early Parkinson's disease, undetectable using standard voxel-based morphometry or volumetry, are evident using sensitive shape analysis. However, the subtle nature of these changes makes it unlikely that shape analysis alone will be useful for early diagnosis.

The Digital Brain Bank, an open access platform for post-mortem imaging datasets.

Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.

DTI measures in crossing-fibre areas: increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease.

Though mild cognitive impairment is an intermediate clinical state between healthy aging and Alzheimer's disease (AD), there are very few whole-brain voxel-wise diffusion MRI studies directly comparing changes in healthy control, mild cognitive impairment (MCI) and AD subjects. Here we report whole-brain findings from a comprehensive study of diffusion tensor indices and probabilistic tractography obtained in a very large population of healthy controls, MCI and probable AD subjects. As expected from the literature, all diffusion indices converged to show that the cingulum bundle, the uncinate fasciculus, the entire corpus callosum and the superior longitudinal fasciculus are the most affected white matter tracts in AD. Significant differences between MCI and AD were essentially confined to the corpus callosum. More importantly, we introduce for the first time in a degenerative disorder an application of a recently developed tensor index, the "mode" of anisotropy, as well as probabilistic crossing-fibre tractography. The mode of anisotropy specifies the type of anisotropy as a continuous measure reflecting differences in shape of the diffusion tensor ranging from planar (e.g., in regions of crossing fibres from two fibre populations of similar density or regions of "kissing" fibres) to linear (e.g., in regions where one fibre population orientation predominates), while probabilistic crossing-fibre tractography allows to accurately trace pathways from a crossing-fibre region. Remarkably, when looking for whole-brain diffusion differences between MCI patients and healthy subjects, the only region with significant abnormalities was a region of crossing fibres in the centrum semiovale, showing an increased mode of anisotropy. The only white matter region demonstrating a significant difference in correlations between neuropsychological scores and a diffusion measure (mode of anisotropy) across the three groups was the same region of crossing fibres. Further examination using probabilistic tractography established explicitly and quantitatively that this previously unreported increase of mode and co-localised increase of fractional anisotropy was explained by a relative preservation of motor-related projection fibres (at this early stage of the disease) crossing the association fibres of the superior longitudinal fasciculus. These findings emphasise the benefit of looking at the more complex regions in which spared and affected pathways are crossing to detect very early alterations of the white matter that could not be detected in regions consisting of one fibre population only. Finally, the methods used in this study may have general applicability for other degenerative disorders and, beyond the clinical sphere, they could contribute to a better quantification and understanding of subtle effects generated by normal processes such as visuospatial attention or motor learning.

Connectivity-based segmentation of the substantia nigra in human and its implications in Parkinson's disease.

The aims of this study were to i) identify substantia nigra subregions i.e. pars reticulata (SNr) and pars compacta (SNc), in human, and ii) to assess volumetric changes in these subregions in the diagnosis of Parkinson's disease. Current MR imaging techniques are unable to distinguish SNr and SNc. Segmentation of these regions may be clinically useful in Parkinson's disease (PD) as substantia nigra is invariably affected in PD. We acquired quantitative T1 as well as diffusion tensor imaging (DTI) data from ten healthy subjects and ten PD patients. For each subject, the left and right SN were manually outlined on T1 images and then classified into two discrete regions based on the characteristics of their connectivity with the rest of the brain using an automated clustering method on the DTI data. We identified two regions in each subjects' SN: an internal region that is likely to correspond with SNc because it was mainly connected with posterior striatum, pallidum, anterior thalamus, and prefrontal cortex; and an external region that corresponds with SNr because it was chiefly connected with posterior thalamus, ventral thalamus, and motor cortex. Volumetric study of these regions in PD patients showed a general atrophy in PD particularly in the right SNr. This pilot study showed that automated DTI-based parcellation of SN subregions may provide a useful tool for in-vivo identification of SNc and SNr and might therefore assist to detect changes that occur in patients with PD.

Regional callosal integrity and bilaterality of limb weakness in amyotrophic lateral sclerosis.

Background and Objectives: The corpus callosum is a site of pathological involvement in the neurodegenerative disorder amyotrophic lateral sclerosis (ALS). The corpus callosum shows widespread cortical connectivity topographically distributed along its length. Initial limb weakness in ALS is typically unilateral, becoming bilateral with disease progression. The precise anatomical substrate for this spread is uncertain. The present study investigated sub-regional variations in corpus callosum integrity in ALS, and whether these reflect a relationship with the development of unilateral or bilateral limb weakness. Methods: Sporadic ALS patients were categorized into unilateral (n = 14) or bilateral (n = 25) limb weakness at the time of assessment and underwent diffusion tensor imaging. Probabilistic bundle-specific tracking was carried out using MRtrix and TractSeg to parcellate the corpus callosum into seven anatomical segments (rostrum; genu; rostral body; anterior midbody; posterior midbody; isthmus; splenium). White matter tract integrity was assessed in all segments and compared with MRI data acquired from 25 healthy controls. Results: In the combined patient group, the most prominent differences in diffusivity metrics were in the rostral body, posterior midbody and isthmus of the corpus callosum (p < 0.04). Loss of corpus callosum integrity was most prominent in the sub-group with unilateral limb weakness at the time of scanning (p < 0.05). Conclusions: Corpus callosum involvement in ALS is detectable across multiple segments, in keeping with a widespread cortical distribution of pathology. The association of unilateral limb weakness with greater loss of corpus callosum integrity informs connectivity-based hypotheses of symptom propagation in ALS.

Cohort profile: the Oxford Parkinson's Disease Centre Discovery Cohort MRI substudy (OPDC-MRI).

PURPOSE: The Oxford Parkinson's Disease Centre (OPDC) Discovery Cohort MRI substudy (OPDC-MRI) collects high-quality multimodal brain MRI together with deep longitudinal clinical phenotyping in patients with Parkinson's, at-risk individuals and healthy elderly participants. The primary aim is to detect pathological changes in brain structure and function, and develop, together with the clinical data, biomarkers to stratify, predict and chart progression in early-stage Parkinson's and at-risk individuals. PARTICIPANTS: Participants are recruited from the OPDC Discovery Cohort, a prospective, longitudinal study. Baseline MRI data are currently available for 290 participants: 119 patients with early idiopathic Parkinson's, 15 Parkinson's patients with pathogenic mutations of the leucine-rich repeat kinase 2 or glucocerebrosidase (GBA) genes, 68 healthy controls and 87 individuals at risk of Parkinson's (asymptomatic carriers of GBA mutation and patients with idiopathic rapid eye movement sleep behaviour disorder-RBD). FINDINGS TO DATE: Differences in brain structure in early Parkinson's were found to be subtle, with small changes in the shape of the globus pallidus and evidence of alterations in microstructural integrity in the prefrontal cortex that correlated with performance on executive function tests. Brain function, as assayed with resting fMRI yielded more substantial differences, with basal ganglia connectivity reduced in early Parkinson'sand RBD. Imaging of the substantia nigra with the more recent adoption of sequences sensitive to iron and neuromelanin content shows promising results in identifying early signs of Parkinsonian disease. FUTURE PLANS: Ongoing studies include the integration of multimodal MRI measures to improve discrimination power. Follow-up clinical data are now accumulating and will allow us to correlate baseline imaging measures to clinical disease progression. Follow-up MRI scanning started in 2015 and is currently ongoing, providing the opportunity for future longitudinal imaging analyses with parallel clinical phenotyping.

Evolution of white matter damage in amyotrophic lateral sclerosis.

OBJECTIVE: To characterize disease evolution in amyotrophic lateral sclerosis using an event-based model designed to extract temporal information from cross-sectional data. Conventional methods for understanding mechanisms of rapidly progressive neurodegenerative disorders are limited by the subjectivity inherent in the selection of a limited range of measurements, and the need to acquire longitudinal data. METHODS: The event-based model characterizes a disease as a series of events, each comprising a significant change in subject state. The model was applied to data from 154 patients and 128 healthy controls selected from five independent diffusion MRI datasets acquired in four different imaging laboratories between 1999 and 2016. The biomarkers modeled were mean fractional anisotropy values of white matter tracts implicated in amyotrophic lateral sclerosis. The cerebral portion of the corticospinal tract was divided into three segments. RESULTS: Application of the model to the pooled datasets revealed that the corticospinal tracts were involved before other white matter tracts. Distal corticospinal tract segments were involved earlier than more proximal (i.e., cephalad) segments. In addition, the model revealed early ordering of fractional anisotropy change in the corpus callosum and subsequently in long association fibers. INTERPRETATION: These findings represent data-driven evidence for early involvement of the corticospinal tracts and body of the corpus callosum in keeping with conventional approaches to image analysis, while providing new evidence to inform directional degeneration of the corticospinal tracts. This data-driven model provides new insight into the dynamics of neuronal damage in amyotrophic lateral sclerosis.