Mild cognitive impairment (MCI) gained a lot of interest recently, especially that the conversion rate to Alzheimer Disease (AD) in the amnestic subtype (aMCI) is higher than in the non-amnestic subtype (naMCI). We aimed to determine whether and how diffusion-weighted MRI (DWI) using the diffusion tensor model (DTI) can differentiate MCI subtypes from healthy subjects. High resolution 3D T1W and DWI images of patients (aMCI, n = 18; naMCI, n = 20; according to Petersen criteria) and controls (n = 27) were acquired at 3T and processed using ExploreDTI and SPM. Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) were performed with ANCOVA; MD was higher in aMCI compared to controls or naMCI in several grey and white matter (GM, WM) regions (especially in the temporal pole and the inferior temporal lobes), while FA was lower in WM ROI-s (e.g. left Cingulum). Moreover, significant correlations were identified between verbal fluency, visual and verbal memory performance and DTI metrics. Logistic regression showed that measuring FA of the crus of fornix along GM volumetry improves the discrimination of aMCI from naMCI. Additional information from DWI/DTI aids preclinical detection of AD and may help detecting early non-Alzheimer type dementia, too.
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http://dx.doi.org/10.1016/j.pscychresns.2017.10.007 | DOI Listing |
J Psychiatry Neurosci
January 2025
From the Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China (X. Liu, Chen, K. Liu, Yan, Wu); the Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, Zhejiang Province, China (X. Liu, Chen, K. Liu, Yan); the Jinhua Municipal Central Hospital, Jinhua, Zhejiang 321000, China (Chen); the Hebei General Hospital, Shijiazhuang, Hebei 050050, China (Cheng); the Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang 310012, China (Wei, Hou, Li, Guo); the Zhoushan Second People's Hospital, Zhoushan, Zhejiang 316000, China (Guo)
Background: Both depressive symptoms and neurotransmitter changes affect the characteristics of functional brain networks in clinical patients. We sought to explore how brain functional grading is organized among patients with mild cognitive impairment and depressive symptoms (D-MCI) and whether changes in brain organization are related to neurotransmitter distribution.
Methods: Using 3 T magnetic resonance imaging (MRI) we acquired functional MRI (fMRI) data from patients with D-MCI, patients with mild cognitive impairment without depression (nD-MCI), and healthy controls.
Biomarkers that aid in early detection of neurodegeneration are needed to enable early symptomatic treatment and enable identification of people who may benefit from neuroprotective interventions. Increasing evidence suggests that sleep biomarkers may be useful, given the bi-directional relationship between sleep and neurodegeneration and the prominence of sleep disturbances and altered sleep architectural characteristics in several neurodegenerative disorders. This study aimed to demonstrate that sleep can accurately characterize specific neurodegenerative disorders (NDD).
View Article and Find Full Text PDFMov Disord Clin Pract
December 2024
Department of Neurology, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
Background: Nowadays, cognitive impairment has been characterized as one of the most vital clinical symptoms in progressive supranuclear palsy (PSP).
Objectives: Based on a relatively large cohort, we aimed to show the cognitive deterioration in different PSP subtypes during 1-year follow-up and investigate potential contributors for disease prognosis.
Methods: One hundred seventeen patients from Progressive Supranuclear Palsy Neuroimage Initiative (PSPNI) cohort underwent neuropsychological tests and 1-year follow-up, with 73 diagnosed as PSP-Richardson syndrome (PSP-RS) and 44 as PSP-non-RS.
Neuropsychol Dev Cogn B Aging Neuropsychol Cogn
December 2024
Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, Ontario, Canada.
Individuals with amnestic mild cognitive impairment (aMCI), a prodromal stage of Alzheimer's disease and other dementias, show inhibition deficits in addition to episodic memory. How the latent processes of selective attention (i.e.
View Article and Find Full Text PDFDiscov Appl Sci
December 2024
Institute of Informatics, University of Applied Sciences and Arts Western Switzerland (HES-SO Valais Wallis), TechnoPole 3, 3960 Sierre, Valais Switzerland.
Unlabelled: Early diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) is crucial to prevent their progression. In this study, we proposed the analysis of magnetic resonance imaging (MRI) based on features including; hippocampus (HC) area size, HC grayscale statistics and texture features (mean, standard deviation, skewness, kurtosis, contrast, correlation, energy, homogeneity, entropy), lateral ventricle (LV) area size, gray matter area size, white matter area size, cerebrospinal fluid area size, patient age, weight, and cognitive score. Five machine learning classifiers; K-nearest neighborhood (KNN), support vector machine (SVM), random forest (RF), decision tree (DT), and multi-layer perception (MLP) were used to distinguish between groups: cognitively normal (CN) vs AD, early MCI (EMCI) vs late MCI (LMCI), CN vs EMCI, CN vs LMCI, AD vs EMCI, and AD vs LMCI.
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