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Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule‐associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello‐subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first‐degree relatives of known symptomatic carriers. Voxel‐wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello‐subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers. [ABSTRACT FROM AUTHOR]

Although multiple sclerosis has traditionally been considered a white matter disease, extensive research documents the presence and importance of grey matter injury including cortical and deep regions. The deep grey matter exhibits a broad range of pathology and is uniquely suited to study the mechanisms and clinical relevance of tissue injury in multiple sclerosis using magnetic resonance techniques. Deep grey matter injury has been associated with clinical and cognitive disability. Recently, MRI characterization of deep grey matter properties, such as thalamic volume, have been tested as potential clinical trial end points associated with neurodegenerative aspects of multiple sclerosis. Given this emerging area of interest and its potential clinical trial relevance, the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative held a workshop and reached consensus on imaging topics related to deep grey matter. Herein, we review current knowledge regarding deep grey matter injury in multiple sclerosis from an imaging perspective, including insights from histopathology, image acquisition and post-processing for deep grey matter. We discuss the clinical relevance of deep grey matter injury and specific regions of interest within the deep grey matter. We highlight unanswered questions and propose future directions, with the aim of focusing research priorities towards better methods, analysis, and interpretation of results. [ABSTRACT FROM AUTHOR]

Early detection of Alzheimer's disease (AD) has been challenging as current biomarkers are invasive and costly. Strong predictors of future AD diagnosis include lower volume of the hippocampus and entorhinal cortex, as well as the ɛ4 allele of the Apolipoprotein E gene (APOE) gene. Therefore, studying functions that are critically mediated by the hippocampus and entorhinal cortex, such as spatial memory, in APOE ɛ4 allele carriers, may be key to the identification of individuals at risk of AD, prior to the manifestation of cognitive impairments. Using a virtual navigation task developed in-house, specifically designed to assess spatial versus non-spatial strategies, the current study is the first to differentiate functional and structural differences within APOE ɛ4 allele carriers. APOE ɛ4 allele carriers that predominantly use non-spatial strategies have decreased fMRI activity in the hippocampus and increased atrophy in the hippocampus, entorhinal cortex, and fimbria compared to APOE ɛ4 allele carriers who use spatial strategies. In contrast, APOE ɛ4 allele carriers who use spatial strategies have grey matter levels comparable to non-APOE ɛ4 allele carriers. Furthermore, in a leave-one-out analysis, grey matter in the entorhinal cortex could predict navigational strategy with 92% accuracy. [ABSTRACT FROM AUTHOR]

Hippocampal atrophy rate-measured using automated techniques applied to structural MRI scans-is considered a sensitive marker of disease progression in Alzheimer's disease, frequently used as an outcome measure in clinical trials. Using publicly accessible data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we examined 1-year hippocampal atrophy rates generated by each of five automated or semiautomated hippocampal segmentation algorithms in patients with Alzheimer's disease, subjects with mild cognitive impairment, or elderly controls. We analyzed MRI data from 398 and 62 subjects available at baseline and at 1 year at MRI field strengths of 1.5 T and 3 T, respectively. We observed a high rate of hippocampal segmentation failures across all algorithms and diagnostic categories, with only 50.8% of subjects at 1.5 T and 58.1% of subjects at 3 T passing stringent segmentation quality control. We also found that all algorithms identified several subjects (between 2.94% and 48.68%) across all diagnostic categories showing increases in hippocampal volume over 1 year. For any given algorithm, hippocampal 'growth' could not entirely be explained by excluding patients with flawed hippocampal segmentations, scan-rescan variability, or MRI field strength. Furthermore, different algorithms did not uniformly identify the same subjects as hippocampal 'growers,' and showed very poor concordance in estimates of magnitude of hippocampal volume change over time (intraclass correlation coefficient 0.319 at 1.5 T and 0.149 at 3 T). This precluded a meaningful analysis of whether hippocampal 'growth' represents a true biological phenomenon. Taken together, our findings suggest that longitudinal hippocampal volume change should be interpreted with considerable caution as a biomarker. Hum Brain Mapp 38:2875-2896, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]