We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. Convolutional neural networks (CNNs) were applied on 3D T1-weighted images from ADNI and subjects recruited at our Institute (407 healthy controls [HC], 418 AD, 280 c-MCI, 533 stable MCI [s-MCI]). CNN performance was tested in distinguishing AD, c-MCI and s-MCI. High levels of accuracy were achieved in all the classifications, with the highest rates achieved in the AD vs HC classification tests using both the ADNI dataset only (99%) and the combined ADNI + non-ADNI dataset (98%). CNNs discriminated c-MCI from s-MCI patients with an accuracy up to 75% and no difference between ADNI and non-ADNI images. CNNs provide a powerful tool for the automatic individual patient diagnosis along the AD continuum. Our method performed well without any prior feature engineering and regardless the variability of imaging protocols and scanners, demonstrating that it is exploitable by not-trained operators and likely to be generalizable to unseen patient data. CNNs may accelerate the adoption of structural MRI in routine practice to help assessment and management of patients.

Gait disorders represent a therapeutic challenge in Parkinson's disease (PD). This study investigated the efficacy of 4-week action observation training (AOT) on disease severity, freezing of gait and motor abilities in PD, and evaluated treatment-related brain functional changes. 25 PD patients with freezing of gait were randomized into two groups: AOT (action observation combined with practicing the observed actions) and "Landscape" (same physical training combined with landscape-videos observation). At baseline and 4-week, patients underwent clinical evaluation and fMRI. Clinical assessment was repeated at 8-week. At 4-week, both groups showed reduced freezing of gait severity, improved walking speed and quality of life. Moreover, AOT was associated with reduced motor disability and improved balance. AOT group showed a sustained positive effect on motor disability, walking speed, balance and quality of life at 8-week, with a trend toward a persisting reduced freezing of gait severity. At 4-week vs. baseline, AOT group showed increased recruitment of fronto-parietal areas during fMRI tasks, while the Landscape group showed a reduced fMRI activity of the left postcentral and inferior parietal gyri and right rolandic operculum and supramarginal gyrus. In AOT group, functional brain changes were associated with clinical improvements at 4-week and predicted clinical evolution at 8-week. AOT has a more lasting effect in improving motor function, gait and quality of life in PD patients relative to physical therapy alone. AOT-related performance gains are associated with an increased recruitment of motor regions and fronto-parietal mirror neuron and attentional control areas.

Histological studies have suggested differing involvement of the hippocampal subfields in ageing and in Alzheimer's disease. The aim of this study was to assess in vivo local hippocampal changes in ageing and Alzheimer's disease based on high resolution MRI at 3 Tesla. T(1)-weighted images were acquired from 19 Alzheimer's disease patients [age 76 +/- 6 years, three males, Mini-Mental State Examination 13 +/- 4] and 19 controls (age 74 +/- 5 years, 11 males, Mini-Mental State Examination 29 +/- 1). The hippocampal formation was isolated by manual tracing. Radial atrophy mapping was used to assess group differences and correlations by averaging hippocampal shapes across subjects using 3D parametric surface mesh models. Percentage difference, Pearson's r, and significance maps were produced. Hippocampal volumes were inversely correlated with age in older healthy controls (r = 0.56 and 0.6 to the right and left, respectively, P < 0.05, corresponding to 14% lower volume for every 10 years of older age from ages 65 to 85 years). Ageing-associated atrophy mapped to medial and lateral areas of the tail and body corresponding to the CA1 subfield and ventral areas of the head corresponding to the presubiculum. Significantly increased volume with older age mapped to a few small spots mainly located to the CA1 sector of the right hippocampus. Volumes were 35% and 30% smaller in Alzheimer's disease patients to the right and left (P < 0.0005). Alzheimer's disease-associated atrophy mapped not only to CA1 areas of the body and tail corresponding to those also associated with age, but also to dorsal CA1 areas of the head unaffected by age. Regions corresponding to the CA2-3 fields were relatively spared in both ageing and Alzheimer's disease. Hippocampal atrophy in Alzheimer's disease maps to areas in the body and tail that partly overlap those affected by normal ageing. Specific areas in the anterior and dorsal CA1 subfield involved in Alzheimer's disease were not in normal ageing. These patterns might relate to differential neural systems involved in Alzheimer's disease and ageing.

White matter (WM) tract damage was assessed in patients with the behavioral variant frontotemporal dementia (bvFTD) and the 3 primary progressive aphasia (PPA) variants and compared with the corresponding brain atrophy patterns. Thirteen bvFTD and 20 PPA patients were studied. Tract-based spatial statistics and voxel-based morphometry were used. Patients with bvFTD showed widespread diffusion tensor magnetic resonance imaging (DT MRI) abnormalities affecting most of the WM bilaterally. In PPA patients, WM damage was more focal and varied across the 3 syndromes: left frontotemporoparietal in nonfluent, left frontotemporal in semantic, and left frontoparietal in logopenic patients. In each syndrome, DT MRI changes extended beyond the topography of gray matter loss. Left uncinate damage was the best predictor of frontotemporal lobar degeneration diagnosis versus controls. DT MRI measures of the anterior corpus callosum and left superior longitudinal fasciculus differentiated bvFTD from nonfluent cases. The best predictors of semantic PPA compared with both bvFTD and nonfluent cases were diffusivity abnormalities of the left uncinate and inferior longitudinal fasciculus. This study provides insights into the similarities and differences of WM damage in bvFTD and PPA variants. DT MRI metrics hold promise to serve as early markers of WM integrity loss that only at a later stage may be detectable by volumetric measures.

Global and local functional networks are altered in bvFTD, suggesting a loss of efficiency in information exchange between both distant and close brain areas. Altered brain regions are located in structures that are closely associated with neuropathologic changes in bvFTD. Aberrant topology of the functional brain networks in bvFTD appears to underlie cognitive deficits in these patients.

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This study suggests that FoG in PD can be the result of a poor structural and functional integration between motor and extramotor (cognitive) neural systems.