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.
•CNNs predict AD and MCI with high accuracy based on a single T1-weighted image•CNNs discriminate c-MCI from s-MCI patients with an accuracy up to 75%•CNNs are exploitable by not-trained operators•CNNs are likely to be generalizable to unseen patient data
Imaging and histopathological studies have demonstrated that structural changes of the retina affect subjects with Alzheimer's disease (AD) or mild cognitive impairment (MCI). The aim of this study ...was to quantitatively investigate the retinal vessels in these disorders, using dynamic vessel analyzer (DVA) and optical coherence tomography angiography (OCTA) analysis. Twelve subjects with AD, 12 subjects with MCI, and 32 gender- and age-matched controls were prospectively enrolled. Mean ± SD age was 72.9 ± 7.2 years in the AD group, 76.3 ± 6.9 years in the MCI group, and 71.6 ± 5.9 years in the control group (p = 0.104). In the DVA dynamic analysis, the arterial dilation was decreased in the AD group (0.77 ± 2.06%), in the comparison with the control group (3.53 ± 1.25%, p = 0.002). The reaction amplitude was decreased both in AD (0.21 ± 1.80%, <0.0001) and MCI (2.29 ± 1.81%, p = 0.048) subjects, compared with controls (3.86 ± 1.94%). OCTA variables did not differ among groups. In the Pearson correlation analysis, amyloid β level in the cerebrospinal fluid was directly correlated with the arterial dilation (R = 0.441, p = 0.040) and reaction amplitude (R = 0.580, p = 0.005). This study demonstrate that Alzheimer's and MCI subjects are characterized by a significant impairment of the retinal neurovascular coupling. This impairment is inversely correlated with the level of amyloid β in the cerebrospinal fluid.
The aim of this study was two-fold: (i) to investigate structural and functional brain network architecture in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), ...stratified in converters (c-aMCI) and non-converters (nc-aMCI) to AD; and to assess the relationship between healthy brain network functional connectivity and the topography of brain atrophy in patients along the AD continuum. Ninety-four AD patients, 47 aMCI patients (25 c-aMCI within 36 months) and 53 age- and sex-matched healthy controls were studied. Graph analysis and connectomics assessed global and local, structural and functional topological network properties and regional connectivity. Healthy topological features of brain regions were assessed based on their connectivity with the point of maximal atrophy (epicenter) in AD and aMCI patients. Brain network graph analysis properties were severely altered in AD patients. Structural brain network was already altered in c-aMCI patients relative to healthy controls in particular in the temporal and parietal brain regions, while functional connectivity did not change. Structural connectivity alterations distinguished c-aMCI from nc-aMCI cases. In both AD and c-aMCI, the point of maximal atrophy was located in left hippocampus (disease-epicenter). Brain regions most strongly connected with the disease-epicenter in the healthy functional connectome were also the most atrophic in both AD and c-aMCI patients. Progressive degeneration in the AD continuum is associated with an early breakdown of anatomical brain connections and follows the strongest connections with the disease-epicenter. These findings support the hypothesis that the topography of brain connectional architecture can modulate the spread of AD through the brain.
Purpose
Given the challenges posed by the clinical diagnosis of atypical Alzheimer’s disease (AD) variants and the limited imaging evidence available in the prodromal phases of atypical AD, we ...assessed brain hypometabolism patterns at the single-subject level in the AD variants spectrum. Specifically, we tested the accuracy of
18
FFDG-PET brain hypometabolism, as a biomarker of neurodegeneration, in supporting the differential diagnosis of atypical AD variants in individuals with dementia and mild cognitive impairment (MCI).
Methods
We retrospectively collected
N
= 67 patients with a diagnosis of typical AD and AD variants according to the IWG-2 criteria (22 typical-AD, 15 frontal variant-AD, 14 logopenic variant-AD and 16 posterior variant-AD). Further, we included
N
= 11 MCI subjects, who subsequently received a clinical diagnosis of atypical AD dementia at follow-up (21 ± 11 months). We assessed brain hypometabolism patterns at group- and single-subject level, using W-score maps, measuring their accuracy in supporting differential diagnosis. In addition, the regional prevalence of cerebral hypometabolism was computed to identify the most vulnerable core regions.
Results
W-score maps pointed at distinct, specific patterns of hypometabolism in typical and atypical AD variants, confirmed by the assessment of core hypometabolism regions, showing that each variant was characterized by specific regional vulnerabilities, namely in occipital, left-sided, or frontal brain regions. ROC curves allowed discrimination among AD variants and also non-AD dementia (i.e., dementia with Lewy bodies and behavioral variant of frontotemporal dementia), with high sensitivity and specificity. Notably, we provide preliminary evidence that, even in AD prodromal phases, these specific
18
FFDG-PET patterns are already detectable and predictive of clinical progression to atypical AD variants at follow-up.
Conclusions
The AD variant-specific patterns of brain hypometabolism, highly consistent at single-subject level and already evident in the prodromal stages, represent relevant markers of disease neurodegeneration, with highly supportive diagnostic and prognostic role.
Background
Early recognition and treatment of autoimmune encephalitis (AE) are crucial for patients, but diagnosis is often difficult and time-consuming. For this purpose, a syndrome-based diagnostic ...approach was published by Graus et al. (Lancet Neurol 15:391–404, 2016), but very little is known in the literature about its application in clinical practice.
Aim
Our aims are to test the feasibility of such approach in a real-world single-centre setting and to analyse the most relevant factors in criteria fulfilment.
Methods
We retrospectively applied these criteria to our cohort of patients discharged from our hospital with diagnosis of autoimmune encephalitis (
n
= 33, 58% antibody-positive).
Results
All the subjects fulfilled criteria for possible AE (pAE), with EEG and MRI playing a central role in diagnosis, while CSF was useful mainly to rule out other conditions. Three patients respected criteria for probable anti-NMDA-R encephalitis (pNMDA). Definite anti-NMDAR encephalitis was diagnosed in 4 patients with detection of the autoantibody but, surprisingly, none of these subjects had fulfilled criteria for pNMDA. 18 patients were diagnosed with definite limbic AE (15 patients were antibody-positive, three antibody-negative). Need for MRI bilateral involvement in antibody-negative limbic AE limited diagnosis. One patient fulfilled criteria for probable antibody-negative AE, while ten patients remained classified as pAE.
Conclusion
From our retrospective analysis, some suggestions for a better definition of the criteria may emerge. Larger studies on prospective cohorts may be more helpful to explore possible important issues.
OBJECTIVE:To investigate whether brain functional network connectivity is disrupted in patients with the behavioral variant of frontotemporal dementia (bvFTD).
METHODS:Graph theoretical analysis was ...applied to resting state functional MRI data from 18 patients with probable bvFTD and 50 healthy individuals. Functional connectivity between 90 cortical and subcortical brain regions was estimated using bivariate correlation analysis and thresholded to construct a set of undirected graphs. Correlations between network properties and cognitive variables were tested.
RESULTS:Global topologic organization of the functional brain network in bvFTD was significantly disrupted as indicated by reduced mean network degree, clustering coefficient, and global efficiency and increased characteristic path length and assortativity relative to normal subjects. Compared to controls, bvFTD data showed retention of major “hub” regions in the medial parietal, temporal, and occipital lobes, but cortical hubs were not noted in the frontal lobes. Medial and dorsal frontal regions, left caudate nucleus, left insular cortices, and some regions of the temporal, parietal, and occipital lobes showed decreased nodal centrality. BvFTD patients showed the greatest decrease in inter-regional connectivity between the frontal and occipital regions, and the insular cortices and occipital, temporal, subcortical, and frontal regions. In bvFTD, altered global network properties correlated with executive dysfunction.
CONCLUSIONS: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.
Purpose
To know whether mild cognitive impairment (MCI) patients will develop Alzheimer’s disease (AD) dementia in very short time or remain stable is of crucial importance, also considering new ...experimental drugs usually tested within very short time frames. Here we combined cerebrospinal fluid (CSF) AD biomarkers and a neurodegeneration marker such as brain FDG-PET to define an objective algorithm, suitable not only to reliably detect MCI converters to AD dementia but also to predict timing of conversion.
Methods
We included 77 consecutive MCI patients with neurological/neuropsychological assessment, brain 18F-FDG-PET and CSF analysis available at diagnosis and a neuropsychological/neurological evaluation every 6 months for a medium- to a long-term follow-up (at least 2 and up to 8 years). Binomial logistic regression models and Kaplan-Meier survival analyses were performed to determine the best biomarker (or combination of biomarkers) in detecting MCI converters to AD dementia and then, among the converters, those who converted in short time frames.
Results
Thirty-five out of 77 MCI patients (45%) converted to AD dementia, with an average conversion time since MCI diagnosis of 26.07 months. CSF p-tau/Aβ42 was the most accurate predictor of conversion from MCI to AD dementia (82.9% sensitivity; 90% specificity). CSF p-tau/Aβ42 and FDG-PET-positive MCIs converted to AD dementia significantly earlier than the CSF-positive-only MCIs (median conversion time, 17.1 vs 31.3 months).
Conclusions
CSF p-tau/Aβ42 ratio and brain FDG-PET may predict both occurrence and timing of MCI conversion to full-blown AD dementia. MCI patients with both biomarkers suggestive for AD will likely develop an AD dementia shortly, thus representing the ideal target for any new experimental drug requiring short periods to be tested for.
Early-onset Alzheimer's disease (EOAD) is characterized by young age of onset (< 65 years), severe neurodegeneration, and rapid disease progression, thus differing significantly from typical ...late-onset Alzheimer's disease. Growing evidence suggests a primary role of neuroinflammation in AD pathogenesis. However, the role of microglia activation in EOAD remains a poorly explored field. Investigating microglial activation and its influence on the development of synaptic dysfunction and neuronal loss in EOAD may contribute to the understanding of its pathophysiology and to subject selection in clinical trials. In our study, we aimed to assess the amount of neuroinflammation and neurodegeneration and their relationship in EOAD patients, through positron emission tomography (PET) measures of microglia activation and brain metabolic changes.
We prospectively enrolled 12 EOAD patients, classified according to standard criteria, who underwent standard neurological and neuropsychological evaluation, CSF analysis, brain MRI, and both
F-FDG PET and
C-(R)-PK11195 PET. Healthy controls databases were used for statistical comparison.
F-FDG PET brain metabolism in single subjects and as a group was assessed by an optimized SPM voxel-wise single-subject method.
C-PK11195 PET binding potentials were obtained using reference regions selected with an optimized clustering procedure followed by a parametric analysis. We performed a topographic interaction analysis and correlation analysis in AD-signature metabolic dysfunctional regions and regions of microglia activation. A network connectivity analysis was performed using the interaction regions of hypometabolism and
C-PK11195 PET BP increases.
EOAD patients showed a significant and extended microglia activation, as
C-PK11195 PET binding potential increases, and hypometabolism in typical AD-signature brain regions, i.e., temporo-parietal cortex, with additional variable frontal and occipital hypometabolism in the EOAD variants. There was a spatial concordance in the interaction areas and significant correlations between the two biological changes. The network analysis showed a disruption of frontal connectivity induced by the metabolic/microglia effects.
The severe microglia activation characterizing EOAD and contributing to neurodegeneration may be a marker of rapid disease progression. The coupling between brain glucose hypometabolism and local immune response in AD-signature regions supports their biological interaction.
The aim of this study was to investigate, using resting state (RS) functional magnetic resonance imaging (fMRI), the functional connectivity within and among brain networks in patients with the ...behavioral variant of frontotemporal dementia (bvFTD), compared with healthy controls and patients with probable Alzheimer's disease (pAD).
Twelve bvFTD patients were compared with 30 controls and 18 pAD patients. Functional connectivity within the salience, default mode (DMN), executive (EXN), attention/working memory (ATT/WM), and dorsal attentional networks was assessed using independent component analysis. The temporal associations among RS networks (RSNs) were explored using the functional network connectivity toolbox.
A decreased dorsal salience network (DSN) connectivity, mainly involving the anterior cingulum, was observed in bvFTD versus controls and pAD. BvFTD was also characterized by a decreased ventral salience network connectivity in the basal ganglia, and divergent connectivity effects versus controls in the dorsolateral prefrontal cortex (decreased) and precuneus (enhanced) within the right ATT/WM network. The dorsal attentional network had a decreased connectivity with the DMN and EXN in bvFTD versus controls, and a decreased connectivity with the DSN versus pAD.
RSN functional abnormalities occur in bvFTD, involving not only the salience network, but also the DMN and fronto-parietal network associated with ATT and WM modulation. The pattern of functional changes differs from that seen in pAD. The altered interactions among RSN observed in bvFTD and pAD may provide a new venue to explore the functional correlates of cognitive abnormalities in neurodegenerative and psychiatric disorders.
Abstract Objectives In this work long term stability of a zirconia toughened alumina (ZTA) composite was investigated. Methods Accelerated aging tests under hydrothermal environment, in autoclave and ...hot water, at different temperature, was conducted on material sample. Tetragonal to monoclinic transformation was evaluated by XRD analysis and the monoclinic content was plot as a function of the exposure time. The kinetic of transformation was studied by means Mehl-Avrami-Johnson (MAJ) nucleation and growth model. Results An activation energy for tetragonal to monoclinic transformation of 99 kJ/mol was found by the Arrhenius plot of reaction rate, value in agreement with other bibliography works regarding Y-TZP and alumina-zirconia composites. The in vivo hydrothermal stability simulation, estimated by the obtained activation energy, predicts in 65 years the time necessary to reach 25 vol% of monoclinic phase. Significance These results support the material suitability in biomedical field, especially in dentistry applications as implantology.
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