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Magnetic resonance alzheimer

Ken-Ichiro Yamashita, Taira Uehara, Pukovisa Prawiroharjo, Koji Yamashita, Osamu Togao, Akio Hiwatashi, Yoshihide Taniwaki, Hidetsuna Utsunomiya, Takuya Matsushita, Ryo Yamasaki, Jun-Ichi Kira
Alzheimer's disease (AD) patients exhibit various cognitive dysfunctions, including impairment of orientation for time (OT). The brain regions underlying OT impairment remain to be elucidated. A previous single-photon emission computed tomography study has indicated hypoperfusion of the posterior cingulate cortex (PCC) in relation to deterioration of OT. In this study, we investigated whole brain functional connectivity changes of PCC using resting-state functional magnetic resonance imaging. Voxel-based functional connectivity with PCC was analyzed in OT-poor or OT-good AD patients, classified according to the mean OT scores of the Mini-Mental State Examination subscale...
April 12, 2018: Brain Imaging and Behavior
E Liu, Y X Zhang, L L Sun, Z Teng, A B Wang, H B Han, J H Yan
OBJECTIVE: To observe the characteristics of the interstitial fluid (ISF) drainage in the Alzheimer's disease (AD) rats through magnetic resonance imaging (MRI) tracer gadolinium-diethylene triamine pentacetic acid (Gd-DTPA)spread in the brain extracellular space (ECS) and to discuss the role of aquaporin-4 (Aqp4) in the AD. METHODS: Wild type SD rats (300-350 g) and Aqp4 gene knock out (Aqp4-/- ) SD rats (300-350g) were divided into Sham group, AD group, Aqp4-/- -Sham group and Aqp4-/- -AD group...
April 18, 2018: Beijing da Xue Xue Bao. Yi Xue Ban, Journal of Peking University. Health Sciences
Eun Jung Choi, Young Don Son, Young Noh, Hyon Lee, Young Bo Kim, Kee Hyung Park
BACKGROUND AND PURPOSE: Atrophy of the hippocampus is an important clinical diagnostic marker of Alzheimer's disease (AD), and so assessments of hippocampal activity and its subdivisions might provide invaluable information. This study compared the glucose metabolism of hippocampal subdivisions in mild-AD patients and healthy controls. METHODS: High-resolution T2*-weighted gradient-echo magnetic resonance imaging (MRI) images and ¹⁸F-fluorodeoxyglucose (FDG) positron-emission tomography (PET) images were acquired using 7...
April 2018: Journal of Clinical Neurology
Michelle M Mielke, Clinton E Hagen, Jing Xu, Xiyun Chai, Prashanthi Vemuri, Val J Lowe, David C Airey, David S Knopman, Rosebud O Roberts, Mary M Machulda, Clifford R Jack, Ronald C Petersen, Jeffrey L Dage
INTRODUCTION: We examined and compared plasma phospho-tau181 (pTau181) and total tau: (1) across the Alzheimer's disease (AD) clinical spectrum; (2) in relation to brain amyloid β (Aβ) positron emission tomography (PET), tau PET, and cortical thickness; and (3) as a screening tool for elevated brain Aβ. METHODS: Participants included 172 cognitively unimpaired, 57 mild cognitively impaired, and 40 AD dementia patients with concurrent Aβ PET (Pittsburgh compound B), tau PET (AV1451), magnetic resonance imaging, plasma total tau, and pTau181...
April 4, 2018: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
Taejoon Eo, Yohan Jun, Taeseong Kim, Jinseong Jang, Ho-Joon Lee, Dosik Hwang
PURPOSE: To demonstrate accurate MR image reconstruction from undersampled k-space data using cross-domain convolutional neural networks (CNNs) METHODS: Cross-domain CNNs consist of 3 components: (1) a deep CNN operating on the k-space (KCNN), (2) a deep CNN operating on an image domain (ICNN), and (3) an interleaved data consistency operations. These components are alternately applied, and each CNN is trained to minimize the loss between the reconstructed and corresponding fully sampled k-spaces...
April 6, 2018: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
Xiaoli Liu, Peng Cao, Jinzhu Yang, Dazhe Zhao
Alzheimer's disease (AD) has been not only the substantial financial burden to the health care system but also the emotional burden to patients and their families. Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI) measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer's disease. Recently, the multitask learning (MTL) methods with sparsity-inducing norm (e.g., ℓ 2,1 -norm) have been widely studied to select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures...
2018: Computational and Mathematical Methods in Medicine
Zhong-Bao Gao, Wei Wang, Xing-Li Zhao, Tong Chen, Li-Ping Fu, Bai-Xuan Xu, Zhen-Fu Wang
Objective Dementia with Lewy bodies (DLB) is a common type of neurodegenerative dementia. Molecular neuroimaging using dopamine transporter (DaT), Pittsburgh compound B (PIB), and fluorodeoxyglucose (FDG) positron emission tomography (PET) has advantages in detecting dopaminergic neuron loss, abnormal amyloid β-protein deposition, and glucose metabolism changes in patients with neurodegenerative disorders. However, the multi-modality molecular imaging features of patients with DLB have rarely been reported...
January 1, 2018: Journal of International Medical Research
Stefan Klöppel, Maria Kotschi, Jessica Peter, Karl Egger, Lucrezia Hausner, Lutz Frölich, Alex Förster, Bernhard Heimbach, Claus Normann, Werner Vach, Horst Urbach, Ahmed Abdulkadir
Older patients with depression or Alzheimer's disease (AD) at the stage of early dementia or mild cognitive impairment may present with objective cognitive impairment, although the pathology and thus therapy and prognosis differ substantially. In this study, we assessed the potential of an automated algorithm to categorize a test set of 65 T1-weighted structural magnetic resonance images (MRI). A convenience sample of elderly individuals fulfilling clinical criteria of either AD (n = 28) or moderate and severe depression (n = 37) was recruited from different settings to assess the potential of the pattern recognition method to assist in the differential diagnosis of AD versus depression...
March 29, 2018: Journal of Alzheimer's Disease: JAD
Mark J R J Bouts, Christiane Möller, Anne Hafkemeijer, John C van Swieten, Elise Dopper, Wiesje M van der Flier, Hugo Vrenken, Alle Meije Wink, Yolande A L Pijnenburg, Philip Scheltens, Frederik Barkhof, Tijn M Schouten, Frank de Vos, Rogier A Feis, Jeroen van der Grond, Mark de Rooij, Serge A R B Rombouts
BACKGROUND/OBJECTIVE: Overlapping clinical symptoms often complicate differential diagnosis between patients with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). Magnetic resonance imaging (MRI) reveals disease specific structural and functional differences that aid in differentiating AD from bvFTD patients. However, the benefit of combining structural and functional connectivity measures to-on a subject-basis-differentiate these dementia-types is not yet known...
January 24, 2018: Journal of Alzheimer's Disease: JAD
Ayşe Demirhan
Clinical predictions performed using structural magnetic resonance (MR) images are crucial in neuroimaging studies and can be used as a successful complementary method for clinical decision making. Multivariate pattern analysis (MVPA) is a significant tool that helps correct predictions by exhibiting a compound relationship between disease-related features. In this study, the effectiveness of determining the most relevant features for MVPA of the brain MR images are examined using ReliefF and minimum Redundancy Maximum Relevance (mRMR) algorithms to predict the Alzheimer's disease (AD), schizophrenia, autism, and attention deficit and hyperactivity disorder (ADHD)...
March 2018: Physica Medica: PM
Jennifer L Whitwell, Jonathan Graff-Radford, Nirubol Tosakulwong, Stephen D Weigand, Mary Machulda, Matthew L Senjem, Anthony J Spychalla, Prashanthi Vemuri, David T Jones, Daniel A Drubach, David S Knopman, Bradley F Boeve, Nilüfer Ertekin-Taner, Ronald C Petersen, Val J Lowe, Clifford R Jack, Keith A Josephs
INTRODUCTION: Neuroimaging modalities can measure different aspects of the disease process in Alzheimer's disease, although the relationship between these modalities is unclear. METHODS: We assessed subject-level regional correlations between tau on [18 F]AV-1451 positron emission tomography (PET), β amyloid on Pittsburgh compound B PET, hypometabolism on [18 F] fluorodeoxyglucose PET, and cortical thickness on magnetic resonance imaging in 96 participants with typical and atypical Alzheimer's disease presentations...
March 29, 2018: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
Giuliana Fusco, Maximo Sanz-Hernandez, Francesco S Ruggeri, Michele Vendruscolo, Christopher M Dobson, Alfonso De Simone
The aggregation process of peptides and proteins is of great relevance as it is associated with a wide range of highly debilitating disorders, including Alzheimer's and Parkinson's diseases. The natural product (-)-epigallocatechin-3-gallate (EGCG) can redirect this process away from amyloid fibrils and towards non-toxic oligomers. In this study we used nuclear magnetic resonance (NMR) spectroscopy to characterize the binding of EGCG to a set of natively structured and unstructured proteins. The results show that the binding process is dramatically dependent on the conformational properties of the protein involved, as EGCG interacts with different binding modes depending on the folding state of the protein...
March 30, 2018: Biopolymers
Bo Cheng, Mingxia Liu, Daoqiang Zhang, Dinggang Shen
Transfer learning has been successfully used in the early diagnosis of Alzheimer's disease (AD). In these methods, data from one single or multiple related source domain(s) are employed to aid the learning task in the target domain. However, most of the existing methods utilize data from all source domains, ignoring the fact that unrelated source domains may degrade the learning performance. Also, previous studies assume that class labels for all subjects are reliable, without considering the ambiguity of class labels caused by slight differences between early AD patients and normal control subjects...
March 27, 2018: Brain Imaging and Behavior
Ping Jin, Yongming Pan, Zhiyong Pan, Jianqin Xu, Min Lin, Zhichao Sun, Minli Chen, Maosheng Xu
BACKGROUND: Hypercholesterolemia is known to increase the risk of AD in later life, the purpose of this study is to illustrate brain metabolic and structural changes in a cholesterol-fed rabbit model of Alzheimer's Disease (AD) by using clinical 3 T Magnetic Resonance Imaging (MRI). METHODS: The Institutional Animal Care and Use Committee of Zhejiang Chinese Medical University approved the study. Totally 16 Japanese White Rabbits (JWR) were randomly divided into 2 groups including normal control group fed with routine diet (group NC) and high cholesterol diet group (group CD) fed a 2% cholesterol diet with 0...
March 27, 2018: Lipids in Health and Disease
Alice M Harper, Lauren Clayson, Joanna M Wardlaw, Maria Del C Valdés Hernández
Objective To analyse brain microbleed (BMB) progression, its possible underlying factors, and the influence of inter-observer differences, in older individuals with none or mild vascular pathology. Methods This study analysed magnetic resonance images, cognitive, demographic and laboratory data from all individuals from the Alzheimer's Disease (AD) Neuroimaging Initiative database who had the required sequences for identifying BMBs over three consecutive years at the time the database was accessed (January 2016)...
January 1, 2018: Journal of International Medical Research
Dongren Yao, Vince D Calhoun, Zening Fu, Yuhui Du, Jing Sui
Discriminating Alzheimer's disease (AD) from its prodromal form, mild cognitive impairment (MCI), is a significant clinical problem that may facilitate early diagnosis and intervention, in which a more challenging issue is to classify MCI subtypes, i.e., those who eventually convert to AD (cMCI) versus those who do not (MCI). To solve this difficult 4-way classification problem (AD, MCI, cMCI and healthy controls), a competition was hosted by Kaggle to invite the scientific community to apply their machine learning approaches on pre-processed sets of T1-weighted magnetic resonance images (MRI) data and the demographic information from the international Alzheimer's disease neuroimaging initiative (ADNI) database...
March 22, 2018: Journal of Neuroscience Methods
Jessica Colenutt, Bryony McCann, Michael J Knight, Elizabeth Coulthard, Risto A Kauppinen
BACKGROUND AND PURPOSE: Incomplete hippocampal inversion (IHI) is an atypical anatomical pattern presented by the hippocampus. It is associated with several neuropathological conditions and is thought to be a factor of susceptibility to hippocampal sclerosis and loss of volume. The volume loss of hippocampus is an inevitable consequence of aging, and when accelerated it is commonly considered an imaging biomarker of Alzheimer's disease dementia. METHODS: We have studied the relationship between IHI and hippocampal subfield volumes in a cohort of 60 healthy participants of 49-87 years of age...
March 25, 2018: Journal of Neuroimaging: Official Journal of the American Society of Neuroimaging
Zhen Liu, Xiangwei Dai, Wuhai Tao, Huilan Liu, He Li, Caishui Yang, Junying Zhang, Xin Li, Yaojing Chen, Chao Ma, Jing Pei, Haohao Mao, Kewei Chen, Zhanjun Zhang
Exploring how risk genes cumulatively impair brain function in preclinical phase (i.e., in cognitively normal elderly) could provide critical insights into the pathophysiology of Alzheimer's disease (AD). Working memory impairment has always been a considerable cognitive deficit in AD, which is likely under complex genetic control. Though, the APOE ɛ4 allele could damage the working memory performance in normal elderly, dissociable results have been reported. This allele may exert specific effects in contexts with other genetic variants...
March 24, 2018: Human Brain Mapping
Manhua Liu, Danni Cheng, Kundong Wang, Yaping Wang
Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD...
March 23, 2018: Neuroinformatics
Filippo Cieri, Roberto Esposito
Resting state functional magnetic resonance imaging (rs-fMRI) allows studying spontaneous brain activity in absence of task, recording changes of Blood Oxygenation Level Dependent (BOLD) signal. rs-fMRI enables identification of brain networks also called Resting State Networks (RSNs) including the most studied Default Mode Network (DMN). The simplicity and speed of execution make rs-fMRI applicable in a variety of normal and pathological conditions. Since it does not require any task, rs-fMRI is particularly useful for protocols on patients, children, and elders, increasing participant's compliance and reducing intersubjective variability due to the task performance...
2018: BioMed Research International
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