Multimodal Magnetic Resonance Imaging Quantification of Brain Changes in Progressive Supranuclear Palsy.

BACKGROUND: Progressive supranuclear palsy (PSP) is a neurodegenerative clinically heterogeneous disorder, formal diagnosis being based on postmortem histological brain examination. OBJECTIVE: We aimed to perform a precise in vivo staging of neurodegeneration in PSP using quantitative multimodal MRI. The ability of MRI biomarkers to differentiate PSP from PD was also evaluated. METHODS: Eleven PSP patients were compared to 26 age-matched healthy controls and 51 PD patients. Images were acquired at 3 Tesla (three-dimensional T1 -weighted, diffusion tensor, and neuromelanin-sensitive images) and 7 Tesla (three-dimensional-T2 * images). Regions of interest included the cortical areas, hippocampus, amygdala, basal ganglia, basal forebrain, brainstem nuclei, dentate nucleus, and cerebellum. Volumes, mean diffusivity, and fractional anisotropy were measured. In each region, a threshold value for group categorization was calculated, and four grades of change (0-3) were determined. RESULTS: PSP patients showed extensive volume decreases and diffusion changes in the midbrain, SN, STN, globus pallidus, basal forebrain, locus coeruleus, pedunculopontine nucleus, and dentate nucleus, in close agreement with the degrees of impairment in histological analyses. The predictive factors for the separation of PSP and healthy controls were, in descending order, the neuromelanin-based SN volume; midbrain fractional anisotropy; volumes of the midbrain, globus pallidus, and putamen; and fractional anisotropy in the locus coeruleus. The best predictors for separating PSP from PD were the neuromelanin-based volume in the SN, fractional anisotropy in the pons, volumes of the midbrain and globus pallidus, and fractional anisotropy in the basal forebrain. CONCLUSIONS: These results suggest that it is possible to evaluate brain neurodegeneration in PSP noninvasively, even in small brainstem nuclei, in close agreement with previously published histological data. © 2019 International Parkinson and Movement Disorder Society.

Multimodal magnetic resonance imaging investigation of basal forebrain damage and cognitive deficits in Parkinson's disease.

BACKGROUND: Cognitive deficits in Parkinson's disease (PD) may result from damage in the cortex as well as in the dopaminergic, noradrenergic, and cholinergic inputs to the cortex. Cholinergic inputs to the cortex mainly originate from the basal forebrain and are clustered in several regions, called Ch1 to Ch4, that project to the hippocampus (Ch1-2), the olfactory bulb (Ch3), and the cortex and amygdala (Ch4). OBJECTIVE: We investigated changes in basal forebrain and their role in cognitive deficits in PD. METHODS: We studied 52 nondemented patients with PD (Hoehn & Yahr 1-2) and 25 age-matched healthy controls using diffusion and resting state functional MRI. RESULTS: PD patients had a loss of structural integrity within the Ch1-2 and Ch3-4 nuclei of the basal forebrain as well as in the fornix. Tractography showed that the probability of anatomical connection was decreased in PD between Ch3-4 and the associative prefrontal cortex, occipital cortex, and peri-insular regions. There was a reduction in functional connectivity between Ch1-2 and the bilateral hippocampi and parahippocampal gyri, the left middle and superior temporal gyri, and the left fusiform gyrus and between Ch3-4 and the right inferior frontal gyrus and the right and left thalamus. In Ch1-2, loss of structural integrity and connectivity correlated with scores at the memory tests, whereas changes in Ch3-4 correlated with scores of global cognition and executive functions. CONCLUSION: This study highlights the association between deficits of different cholinergic nuclei of the basal forebrain and the extent of cognitive impairments in nondemented PD patients. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Longitudinal changes in functional connectivity of cortico-basal ganglia networks in manifests and premanifest huntington's disease.

Huntington's disease (HD) is a genetic neurological disorder resulting in cognitive and motor impairments. We evaluated the longitudinal changes of functional connectivity in sensorimotor, associative and limbic cortico-basal ganglia networks. We acquired structural MRI and resting-state fMRI in three visits one year apart, in 18 adult HD patients, 24 asymptomatic mutation carriers (preHD) and 18 gender- and age-matched healthy volunteers from the TRACK-HD study. We inferred topological changes in functional connectivity between 182 regions within cortico-basal ganglia networks using graph theory measures. We found significant differences for global graph theory measures in HD but not in preHD. The average shortest path length (L) decreased, which indicated a change toward the random network topology. HD patients also demonstrated increases in degree k, reduced betweeness centrality bc and reduced clustering C. Changes predominated in the sensorimotor network for bc and C and were observed in all circuits for k. Hubs were reduced in preHD and no longer detectable in HD in the sensorimotor and associative networks. Changes in graph theory metrics (L, k, C and bc) correlated with four clinical and cognitive measures (symbol digit modalities test, Stroop, Burden and UHDRS). There were no changes in graph theory metrics across sessions, which suggests that these measures are not reliable biomarkers of longitudinal changes in HD. preHD is characterized by progressive decreasing hub organization, and these changes aggravate in HD patients with changes in local metrics. HD is characterized by progressive changes in global network interconnectivity, whose network topology becomes more random over time. Hum Brain Mapp 37:4112-4128, 2016. © 2016 Wiley Periodicals, Inc.

Parkinson Disease Propagation Using MRI Biomarkers and Partial Least Squares Path Modeling.

OBJECTIVES: The classic Braak neuropathologic staging model in Parkinson disease (PD) suggests that brain lesions progress from the medulla oblongata to the cortex. An alternative model in which neurodegeneration first occurs in the cortex has also been proposed. These 2 models may correspond to different patient phenotypes. To test these 2 models and to investigate whether they were influenced by the presence of REM sleep behavior disorder (RBD), we used multimodal MRI and partial least squares path modeling (PLS-PM) assuming that patients with RBD followed distinct neurodegeneration pattern. METHODS: Fifty-four patients with PD (34 with RBD) and 25 healthy volunteers were scanned with T1-weighted, diffusion tensor, and neuromelanin-sensitive imaging. Volume, signal, and mean, axial, and radial diffusivities were calculated in brainstem, basal forebrain, and cortical regions. PLS-PM, estimating a network of causal relationships between blocks of variables, was used to build and test an analytical model based on Braak staging. The overall quality of the model was assessed with goodness of fit coefficient (Gof). RESULTS: PLS-PM was run on patients with PD with RBD and without RBD separately. In PD with RBD, a brainstem-to-cortex model had significant Gof (0.71, p = 0.01), whereas a cortex-to-brainstem model did not. In contrast, in patients with PD without RBD, the brainstem-to-cortex model was not significant (Gof = 0.64, p = 0.27), and the cortex-to-brainstem model was highly significant (Gof = 0.72, p = 0.008). CONCLUSIONS: With the PLS-PM imaging-based model, the neurodegeneration pattern of patients with PD with RBD was consistent with the Braak brainstem-to-cortex model, whereas that of patients without RBD followed the cortex-to-brainstem model.

The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI.

Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg) . Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

White matter predicts functional connectivity in premanifest Huntington's disease.

OBJECTIVES: The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's. METHODS: Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease. RESULTS: We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases. INTERPRETATION: Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero-posterior dissociation that is in keeping with the caudo-rostral gradient of striatal pathology in HD.