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Background: Alzheimer's disease (AD) is an increasingly common type of dementia. Apolipoprotein E (APOE) gene is a strong risk factor for AD. Objective: Here, we explored alterations in grey matter structure (GMV) and networks in AD, as well as the effects of the APOEɛ4 allele on neuroimaging regions based on structural magnetic resonance imaging (sMRI). Methods: All subjects underwent an sMRI scan. GMV and cortical thickness were calculated using voxel-based morphological analysis, and structural networks were constructed based on graph theory analysis to compare differences between AD and normal controls. Results: The volumes of grey matter in the bilateral inferior temporal gyrus, right middle temporal gyrus, right inferior parietal lobule, right limbic lobe, right frontal lobe, left anterior cingulate gyrus, and bilateral olfactory cortex of patients with AD were significantly decreased. The cortical thickness in patients with AD was significantly reduced in the left lateral occipital lobe, inferior parietal lobe, orbitofrontal region, precuneus, superior parietal gyrus, right precentral gyrus, middle temporal gyrus, pars opercularis gyrus, insular gyrus, superior marginal gyrus, bilateral fusiform gyrus, and superior frontal gyrus. In terms of local properties, there were significant differences between the AD and control groups in these areas, including the right bank, right temporalis pole, bilateral middle temporal gyrus, right transverse temporal gyrus, left postcentral gyrus, and left parahippocampal gyrus. Conclusion: There were significant differences in the morphological and structural covariate networks between AD patients and healthy controls under APOEɛ4 allele effects. [ABSTRACT FROM AUTHOR]

Background: Structural brain magnetic resonance imaging (MRI) scans may provide reliable neuroimaging markers for defining amnestic mild cognitive impairment (aMCI).Objective: We sought to characterize global and regional brain structures of aMCI among rural-dwelling older adults with limited education in China.Methods: This population-based study included 180 participants (aged≥65 years, 42 with aMCI and 138 normal controls) in the Shandong Yanggu Study of Aging and Dementia during 2014-2016. We defined aMCI following the Petersen's criteria. Global and regional brain volumes were automatically segmented on MRI scans and compared using a region-of-interest approach. Data were analyzed using general linear regression models.Results: Multi-adjusted β-coefficient (95% confidence interval) of brain volumes (cm3) associated with aMCI was -12.07 (-21.49, -2.64) for global grey matter (GM), -18.31 (-28.45, -8.17) for global white matter (WM), 28.17 (12.83, 44.07) for cerebrospinal fluid (CSF), and 2.20 (0.24, 4.16) for white matter hyperintensities (WMH). Furthermore, aMCI was significantly associated with lower GM volumes in bilateral superior temporal gyri, thalamus and right cuneus, and lower WM volumes in lateral areas extending from the frontal to the parietal, temporal, and occipital lobes, as well as right hippocampus (p < 0.05).Conclusion: Brain structure of older adults with aMCI is characterized by reduced global GM and WM volumes, enlarged CSF volume, increased WMH burden, reduced GM volumes in bilateral superior temporal gyri, thalamus, and right cuneus, and widespread reductions of lateral WM volumes. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a heterogeneous disease with different subtypes. Studying AD subtypes from brain structure, neuropathology, and cognition are of great importance for AD heterogeneity research. Starting from the study of constructing AD subtypes based on the features of T1-weighted structural magnetic resonance imaging, this paper introduces the major connections between the subtype definition and analysis strategies, including brain region-based subtype definition, and their demographic, neuropathological, and neuropsychological characteristics. The advantages and existing problems are analyzed, and reasonable improvement schemes are prospected. Overall, this review offers a more comprehensive view in the field of atrophy subtype in AD, along with their advantages, challenges, and future prospects, and provide a basis for improving individualized AD diagnosis. [ABSTRACT FROM AUTHOR]

Homotaurine supplementation may have a positive effect on early Alzheimer's disease. Here, we investigated its potential neuroprotective effect on the hippocampus structure and episodic memory performances in amnestic mild cognitive impairment (aMCI). Neuropsychological, clinical, and neuroimaging assessment in 11 treated and 22 untreated patients were performed at baseline and after 1 year. Magnetic resonance data were analyzed using voxel-based morphometry to explore significant differences (Family Wise Error corrected) between the two groups over time. Patients treated with homotaurine showed decreased volume loss in the left and right hippocampal tail, left and right fusiform gyrus, and right inferior temporal cortex which was associated with improved short-term episodic memory performance as measured by the recency effect of the Rey 15-word list learning test immediate recall. Thus, homotaurine supplementation in individuals with aMCI has a positive effect on hippocampus atrophy and episodic memory loss. Future studies should further clarify the mechanisms of its effects on brain morphometry. [ABSTRACT FROM AUTHOR]

A variety of imaging, neuropsychological, and genetic biomarkers have been suggested as potential biomarkers for the identification of mild cognitive impairment (MCI) in patients who later develop Alzheimer's disease (AD). Here, we systematically evaluated the most promising combinations of these biomarkers regarding discrimination between stable and converter MCI and reflection of disease staging. Alzheimer's Disease Neuroimaging Initiative data of AD (n = 144), controls (n = 112), stable (n = 265) and converter (n = 177) MCI, for which apolipoprotein E status, neuropsychological evaluation, and structural, glucose, and amyloid imaging were available, were included in this study. Naïve Bayes classifiers were built on AD and controls data for all possible combinations of these biomarkers, with and without stratification by amyloid status. All classifiers were then applied to the MCI cohorts. We obtained an accuracy of 76% for discrimination between converter and stable MCI with glucose positron emission tomography as a single biomarker. This accuracy increased to about 87% when including further imaging modalities and genetic information. We also identified several biomarker combinations as strong predictors of time to conversion. Use of amyloid validated training data resulted in increased sensitivities and decreased specificities for differentiation between stable and converter MCI when amyloid was included as a biomarker but not for other classifier combinations. Our results indicate that fully independent classifiers built only on AD and controls data and combining imaging, genetic, and/or neuropsychological biomarkers can more reliably discriminate between stable and converter MCI than single modality classifiers. Several biomarker combinations are identified as strongly predictive for the time to conversion to AD. [ABSTRACT FROM AUTHOR]

Identifying amnestic mild cognitive impairment (aMCI) is of great clinical importance because aMCI is a putative prodromal stage of Alzheimer's disease. The present study aimed to explore the feasibility of accurately identifying aMCI with a magnetic resonance imaging (MRI) biomarker. We integrated measures of both gray matter (GM) abnormalities derived from structural MRI and white matter (WM) alterations acquired from diffusion tensor imaging at the voxel level across the entire brain. In particular, multi-modal brain features, including GM volume, WM fractional anisotropy, and mean diffusivity, were extracted from a relatively large sample of 64 Han Chinese aMCI patients and 64 matched controls. Then, support vector machine classifiers for GM volume, FA, and MD were fused to distinguish the aMCI patients from the controls. The fused classifier was evaluated with the leave-one-out and the 10-fold cross-validations, and the classifier had an accuracy of 83.59% and an area under the curve of 0.862. The most discriminative regions of GM were mainly located in the medial temporal lobe, temporal lobe, precuneus, cingulate gyrus, parietal lobe, and frontal lobe, whereas the most discriminative regions of WM were mainly located in the corpus callosum, cingulum, corona radiata, frontal lobe, and parietal lobe. Our findings suggest that aMCI is characterized by a distributed pattern of GM abnormalities and WM alterations that represent discriminative power and reflect relevant pathological changes in the brain, and these changes further highlight the advantage of multi-modal feature integration for identifying aMCI. [ABSTRACT FROM AUTHOR]

Distinguishing amnestic mild cognitive impairment (MCI) from Alzheimer's disease (AD) and healthy aging depends mainly on clinical evaluation, and, ultimately, on investigator's judgment. Clinical evaluation in vivo is based primarily on cognitive assessments. The present study explores the potential of volumetric magnetic resonance imaging of parietal and lateral temporal brain structures to support the diagnosis of AD and to distinguish AD patients from patients with MCI and healthy control subjects (HCS). 52 age-matched HCS, 18 patients with MCI, and 59 patients with probable late onset AD were investigated. Using computational, neuromorphometric procedures gray matter (GM) was automatically parcellated into 28 local regions of interest, the volumes of which were computed. The left hippocampus (sensitivity/specificity: 80.8-90.4%/55.6-86.4%) and the right hippocampus (73.1-90.4%/66.7-84.7%) provided highest diagnostic accuracy in separating all three diagnostic groups. Promising diagnostic values for distinguishing MCI from HCS were found for the left superior parietal gyrus (61.5%/55.6%) and left supramarginal gyrus (65.4%/66.7%), and for distinguishing subjects with MCI from AD patients for the right middle temporal gyrus (77.8%/79.7%), left inferior temporal gyrus (83.3%/72.9%), and right superior temporal gyrus (77.8%/71.2%). The left superior temporal pole (92.3%/84.7%), left parahippocampal gyrus (86.5%/81.4%), left Heschl's gyrus (86.5%/79.7%), and the right superior temporal pole (82.7%/78.0%) revealed most promising diagnostic values for distinguishing AD patients from HCS. Data revealed that lateral temporal and parietal GM volumes distinguish between HCS, MCI, and AD as accurate as hippocampal volumes do; hence, these volumes can be used in the diagnostic procedure. Results also suggest that cognitive functions associated with these brain regions, e.g., language and visuospatial abilities, may be tested more extensively to obtain additional information that might enhance the diagnostic accuracy further. [ABSTRACT FROM AUTHOR]