NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2020
Computational quantification of brain perivascular space morphologies: Associations with vascular risk factors and white matter hyperintensities. A study in the Lothian Birth Cohort 1936.
Perivascular Spaces (PVS), also known as Virchow-Robin spaces, seen on structural brain MRI, are important fluid drainage conduits and are associated with small vessel disease (SVD). Computational quantification of visible PVS may enable efficient analyses in large datasets and increase sensitivity to detect associations with brain disorders. We assessed the associations of computationally-derived PVS parameters with vascular factors and white matter hyperintensities (WMH), a marker of SVD. ⋯ Computational measures reflecting individual PVS size, length and width were more strongly associated with WMH, stroke and hypertension than computational count or visual PVS score. Multidimensional computational PVS metrics may increase sensitivity to detect associations of PVS with risk exposures, brain lesions and neurological disease, provide greater anatomic detail and accelerate understanding of disorders of brain fluid and waste clearance.
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NeuroImage. Clinical · Jan 2020
Post-acute white matter microstructure predicts post-acute and chronic post-concussive symptom severity following mild traumatic brain injury in children.
Mild traumatic brain injury (TBI) is a global public health concern that affects millions of children annually. Mild TBI tends to result in subtle and diffuse alterations in brain tissue, which challenges accurate clinical detection and prognostication. Diffusion tensor imaging (DTI) holds promise as a diagnostic and prognostic tool, but little research has examined DTI in post-acute mild TBI. The current study compared post-acute white matter microstructure in children with mild TBI versus those with mild orthopedic injury (OI), and examined whether post-acute DTI metrics can predict post-acute and chronic post-concussive symptoms (PCS). ⋯ Post-acute white matter microstructure did not differ for children with mild TBI versus OI after correcting for multiple comparisons, but was predictive of post-acute and chronic PCS in both injury groups. These findings support the potential prognostic utility of this advanced DTI technique.
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Regional cortical thinning in dementia with Lewy bodies (DLB) and Parkinson disease dementia (PDD) may underlie some aspect of their clinical impairments; cortical atrophy likely reflects extensive Lewy body pathology with alpha-synuclein deposits, as well as associated Alzheimer's disease co-pathologies, when present. Here we investigated the topographic distribution of cortical thinning in these Lewy body diseases compared to cognitively normal PD and healthy non-PD control subjects, explored the association of regional thinning with clinical features and evaluated the impact of amyloid deposition. ⋯ The pattern of cortical thinning is similar in DLB and PD-associated cognitive impairment, overlapping with and extending beyond AD signature regions to involve fusiform, precentral, and paracentral regions. Cortical thinning in AD signature and fusiform regions in these diseases reflects cognitive impairment and is markedly accentuated by amyloid co-pathology. Further work will be required to determine whether the distinct topography of cortical thinning in DLB and PD-associated cognitive impairment might have value as a diagnostic and/ or outcome biomarker in clinical trials.
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NeuroImage. Clinical · Jan 2020
A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis.
Longitudinal magnetic resonance imaging (MRI) has an important role in multiple sclerosis (MS) diagnosis and follow-up. Specifically, the presence of new T2-w lesions on brain MR scans is considered a predictive biomarker for the disease. In this study, we propose a fully convolutional neural network (FCNN) to detect new T2-w lesions in longitudinal brain MR images. ⋯ Our proposal shows the benefits of combining a learning-based registration network with a segmentation network. Compared to other methods, the proposed model decreases the number of false positives. During testing, the proposed model operates faster than the other two state-of-the-art methods based on the DF obtained by Demons.
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Huntington's disease (HD) is a fatal genetic neurodegenerative disorder with no effective treatment currently available. Progressive basal ganglia and whole-brain atrophy and concurrent cognitive deterioration are prototypical aspects of HD. However, the specific patterns of brain atrophy underlying cognitive impairment of different severity in HD are poorly understood. The aim of this study was to investigate the specific structural brain correlates of major cognitive deficits in HD and to explore its association with neuropsychological indicators. ⋯ Major cognitive impairment in the range of dementia in HD is associated with brain and cognitive alterations exceeding the prototypical frontal-executive deficits commonly recognized in HD. The observed posterior-cortical damage identified by MRI and its association with memory, language, and visuoconstructive dysfunction suggest a strong involvement of extra-striatal atrophy in the onset of severe cognitive dysfunction in HD patients. Critically, major cognitive impairment in this sample was not associated with CAG repeat length, age or education. This finding could support a possible involvement of additional neuropathological mechanisms aggravating cognitive deterioration in HD.