scholarly journals Influence of MRI on Diagnostic Efficacy and Satisfaction of Patients with Alzheimer’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Zheng Dong ◽  
Xinyu Yang ◽  
Liming Chang ◽  
Xin Song ◽  
Xiangchun Li ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Statistical Difference ◽  
Control Group ◽  
Diagnostic Efficacy ◽  
Right Brain ◽  
Total Satisfaction ◽  
Temporal Horn ◽  
Brain Lobe ◽  
Magnetic Resonance Imaging Mri

Objective. To inquire into the influence of magnetic resonance imaging (MRI) on the diagnostic efficacy and satisfaction of patients with Alzheimer’s disease (AD). Methods. This study included 42 healthy people (control group) and 66 patients with AD (AD group). The hippocampus volume, temporal sulcus spacing, left-right brain diameter, brain lobe volume, hippocampal height, temporal horn width, lateral fissure width, and degree of leukoaraiosis were all measured using an MRI scan. After diagnosis, the satisfaction of patients in both arms was investigated and the satisfaction degree was recorded. Results. Compared with the control group, the left and right hippocampal volumes and hippocampal height of AD patients were smaller, while the temporal sulcus spacing, temporal horn width, lateral fissure width, and left-right brain diameter were remarkably higher. A statistical difference was present in the degree of leukoaraiosis between the two arms. The frontal and temporal lobe volumes of AD patients were notably lower while the volumes of parietal and occipital lobes were similar, versus the control group. The total satisfaction was 83.33% in the control group and 86.36% in the AD group, with no statistical difference between the two arms. Conclusions. MRI can effectively mine the brain information of AD patients with a high patient satisfaction, which has potential value in clinical application.

Alzheimer’s Disease: Erythrocyte 2,3-diphosphoglycerate Content and Circulating Erythropoietin

2019 ◽  
Vol 16 (9) ◽  
pp. 834-835
Author(s):  
Petter Järemo ◽  
Alenka Jejcic ◽  
Vesna Jelic ◽  
Tasmin Shahnaz ◽  
Homira Behbahani ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Cell Damage ◽  
Control Group ◽  
Red Cell ◽  
Oxygen Release ◽  
Regulatory Pathways ◽  
Β Amyloid ◽  
2,3 Dpg

Background: Alzheimer’s Disease (AD) features the accumulation of β-amyloid in erythrocytes. The subsequent red cell damage may well affect their oxygen-carrying capabilities. 2,3- diphosphoglycerate (2,3-DPG) binds to the hemoglobin thereby promoting oxygen release. It is theorized that 2,3-DPG is reduced in AD and that the resulting hypoxia triggers erythropoietin (EPO) release. Methods & Objective: To explore this theory, we analyzed red cell 2,3-DPG content and EPO in AD, mild cognitive impairment, and the control group, subjective cognitive impairment. Results: We studied (i) 2,3-DPG in red cells, and (ii) circulating EPO in AD, and both markers were unaffected by dementia. Disturbances of these oxygen-regulatory pathways do not appear to participate in brain hypoxia in AD.

scholarly journals Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease: Current Evidence and Future Perspectives

2021 ◽  
Vol 11 (2) ◽  
pp. 215
Author(s):  
Donovan A. McGrowder ◽  
Fabian Miller ◽  
Kurt Vaz ◽  
Chukwuemeka Nwokocha ◽  
Cameil Wilson-Clarke ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Late Onset ◽  
Amyloid Β ◽  
Current Evidence ◽  
Csf Biomarkers ◽  
Diagnostic Efficacy ◽  
Neurofilament Light ◽  
New Biomarkers

Alzheimer’s disease is a progressive, clinically heterogeneous, and particularly complex neurodegenerative disease characterized by a decline in cognition. Over the last two decades, there has been significant growth in the investigation of cerebrospinal fluid (CSF) biomarkers for Alzheimer’s disease. This review presents current evidence from many clinical neurochemical studies, with findings that attest to the efficacy of existing core CSF biomarkers such as total tau, phosphorylated tau, and amyloid-β (Aβ42), which diagnose Alzheimer’s disease in the early and dementia stages of the disorder. The heterogeneity of the pathophysiology of the late-onset disease warrants the growth of the Alzheimer’s disease CSF biomarker toolbox; more biomarkers showing other aspects of the disease mechanism are needed. This review focuses on new biomarkers that track Alzheimer’s disease pathology, such as those that assess neuronal injury (VILIP-1 and neurofilament light), neuroinflammation (sTREM2, YKL-40, osteopontin, GFAP, progranulin, and MCP-1), synaptic dysfunction (SNAP-25 and GAP-43), vascular dysregulation (hFABP), as well as CSF α-synuclein levels and TDP-43 pathology. Some of these biomarkers are promising candidates as they are specific and predict future rates of cognitive decline. Findings from the combinations of subclasses of new Alzheimer’s disease biomarkers that improve their diagnostic efficacy in detecting associated pathological changes are also presented.

scholarly journals Women have Farther to Fall: Gender Differences Between Normal Elderly and Alzheimer's Disease in Verbal Memory Engender Better Detection of Alzheimer's Disease in Women

2011 ◽  
Vol 17 (4) ◽  
pp. 654-662 ◽  
Author(s):  
Robert M. Chapman ◽  
Mark Mapstone ◽  
Margaret N. Gardner ◽  
Tiffany C. Sandoval ◽  
John W. McCrary ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gender Differences ◽  
Verbal Memory ◽  
Control Group ◽  
Large Drop ◽  
Delayed Recall ◽  
Logical Memory ◽  
Wechsler Memory Scale ◽  
Immediate Recall

AbstractWe analyzed verbal episodic memory learning and recall using the Logical Memory (LM) subtest of the Wechsler Memory Scale-III to determine how gender differences in AD compare to those seen in normal elderly and whether or not these differences impact assessment of AD. We administered the LM to both an AD and a Control group, each comprised of 21 men and 21 women, and found a large drop in performance from normal elders to AD. Of interest was a gender interaction whereby the women's scores dropped 1.6 times more than the men's did. Control women on average outperformed Control men on every aspect of the test, including immediate recall, delayed recall, and learning. Conversely, AD women tended to perform worse than AD men. Additionally, the LM achieved perfect diagnostic accuracy in discriminant analysis of AD versus Control women, a statistically significantly higher result than for men. The results indicate the LM is a more powerful and reliable tool in detecting AD in women than in men. (JINS, 2011, 17, 654–662)

Neuroprotective Activity of the Methanolic Extract of Indigofera aspalathoides against Scopalamine induced Alzheimer's Disease in Experimental Rats

2021 ◽  
pp. 5163-5168
Author(s):  
Rajaram C. ◽  
S. Nelson Kumar ◽  
S. S. Sheeba Tabassum ◽  
Manohar R. ◽  
Sumanjali C.
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Traditional Medicine ◽  
Methanolic Extract ◽  
Therapeutic Potential ◽  
Neuroprotective Effect ◽  
Neuroprotective Activity ◽  
Control Group ◽  
Histological Structure ◽  
Anticancer Activities

The plant Indigofera aspalathoides is a traditional medicine with tremendous therapeutic potential which finds it use in treatment of various ailments such as antibacterial, antioxidant, anti-inflammatory, antidiabetic, and anticancer activities. There are no reports that related to the use of this plant in treating patients with Alzheimer’s disease (AD). Hence present study was aimed to scientifically evaluate the neuroprotective effect of the methanolic extract of Indigofera aspalathoides against scopalamine induced Alzheimer’s disease in experimental rats using behavioral tests like elevated plus maze, Y-maze, and rota-rod tests. In addition to this, biochemical evaluation for acetylcholinesterase activity and histopathological evaluation of brain were done. The results suggests that methanolic extract Indigofera aspalathoides (200mg/kg B.wt and 400mg/kg B.wt) used in this study shows significant improvement of various behavioral parameters like locomotion, anxiety, memory, motor integrity and coordination etc when compared to control group. MEIA inhibited brain AChE enzyme, thereby elevating Ach concentration in brain homogenate and ultimately improved memory of rats. Further, more or less normal histological structure of the hippocampus and all amyloid plaques and neurofibrillary tangles that are formed under the influence of scopolamine disappeared in the rats pretreated with MEIA (200mg/kg B.wt and 400mg/kg B.wt). It can be concluded that our results strongly support the anti-Alzheimer’s potential of the methanolic extract of the plant I.aspalathoides and its use in traditional medicine.

scholarly journals Gestational Stress Augments Postpartum β-Amyloid Pathology and Cognitive Decline in a Mouse Model of Alzheimer’s Disease

2018 ◽  
Vol 29 (9) ◽  
pp. 3712-3724 ◽  
Author(s):  
Zahra Jafari ◽  
Jogender Mehla ◽  
Bryan E Kolb ◽  
Majid H Mohajerani
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Factor ◽  
Cognitive Decline ◽  
Noise Exposure ◽  
Amyloid Β ◽  
Control Group ◽  
Plaque Size ◽  
Model Of Alzheimer’S Disease ◽  
Gestational Stress

Abstract Besides well-known risk factors for Alzheimer’s disease (AD), stress, and in particular noise stress (NS), is a lifestyle risk factor common today. It is known that females are at a significantly greater risk of developing AD than males, and given that stress is a common adversity in females during pregnancy, we hypothesized that gestational noise exposure could exacerbate the postpartum development of the AD-like neuropathological changes during the life span. Pregnant APPNL-G-F/NL-G-F mice were randomly assigned to either the stress condition or control group. The stress group was exposed to the NS on gestational days 12–16, which resulted in a markedly higher hypothalamic–pituitary–adrenal (HPA) axis responsivity during the postpartum stage. Higher amyloid-β (Aβ) deposition and larger Aβ plaque size in the olfactory area were the early onset impacts of the gestational stress (GS) seen at the age of 4 months. This pattern of increased Aβ aggregation and larger plaque size were observed in various brain areas involved in both AD and stress regulation, especially in limbic structures, at the age of 6 months. The GS also produced anxiety-like behavior, deficits in learning and memory, and impaired motor coordination. The findings suggest that environmental stresses during pregnancy pose a potential risk factor in accelerating postpartum cognitive decline and AD-like neuropathological changes in the dams (mothers) later in life.

scholarly journals A Large-scale Comparison of Cortical and Subcortical Structural Segmentation Methods in Alzheimer’s Disease: a Statistical Approach

2020 ◽  
Author(s):  
Jafar Zamani ◽  
Ali Sadr ◽  
Amir-Homayoun Javadi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Automated Segmentation ◽  
Resonance Imaging ◽  
Brain Areas ◽  
Segmentation Methods ◽  
Magnetic Resonance Imaging Mri ◽  
Underlying Mechanisms ◽  
The Brain

AbstractBackgroundAlzheimer’s disease (AD) is a neurodegenerative disease that leads to anatomical atrophy, as evidenced by magnetic resonance imaging (MRI). Automated segmentation methods are developed to help with the segmentation of different brain areas. However, their reliability has yet to be fully investigated. To have a more comprehensive understanding of the distribution of changes in AD, as well as investigating the reliability of different segmentation methods, in this study we compared volumes of cortical and subcortical brain segments, using automated segmentation methods in more than 60 areas between AD and healthy controls (HC).MethodsA total of 44 MRI images (22 AD and 22 HC, 50% females) were taken from the minimal interval resonance imaging in Alzheimer’s disease (MIRIAD) dataset. HIPS, volBrain, CAT and BrainSuite segmentation methods were used for the subfields of hippocampus, and the rest of the brain.ResultsWhile HIPS, volBrain and CAT showed strong conformity with the past literature, BrainSuite misclassified several brain areas. Additionally, the volume of the brain areas that successfully discriminated between AD and HC showed a correlation with mini mental state examination (MMSE) scores. The two methods of volBrain and CAT showed a very strong correlation. These two methods, however, did not correlate with BrainSuite.ConclusionOur results showed that automated segmentation methods HIPS, volBrain and CAT can be used in the classification of AD and HC. This is an indication that such methods can be used to inform researchers and clinicians of underlying mechanisms and progression of AD.

scholarly journals Accelerating Hyperparameter Tuning in Machine Learning for Alzheimer’s Disease With High Performance Computing

2021 ◽  
Vol 4 ◽  
Author(s):  
Fan Zhang ◽  
Melissa Petersen ◽  
Leigh Johnson ◽  
James Hall ◽  
Sid E. O’Bryant
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
High Performance ◽  
Support Vector ◽  
Massive Datasets ◽  
Complexity Of Algorithms ◽  
Magnetic Resonance Imaging Mri ◽  
Research Challenge ◽  
Improved Accuracy

Driven by massive datasets that comprise biomarkers from both blood and magnetic resonance imaging (MRI), the need for advanced learning algorithms and accelerator architectures, such as GPUs and FPGAs has increased. Machine learning (ML) methods have delivered remarkable prediction for the early diagnosis of Alzheimer’s disease (AD). Although ML has improved accuracy of AD prediction, the requirement for the complexity of algorithms in ML increases, for example, hyperparameters tuning, which in turn, increases its computational complexity. Thus, accelerating high performance ML for AD is an important research challenge facing these fields. This work reports a multicore high performance support vector machine (SVM) hyperparameter tuning workflow with 100 times repeated 5-fold cross-validation for speeding up ML for AD. For demonstration and evaluation purposes, the high performance hyperparameter tuning model was applied to public MRI data for AD and included demographic factors such as age, sex and education. Results showed that computational efficiency increased by 96%, which helped to shed light on future diagnostic AD biomarker applications. The high performance hyperparameter tuning model can also be applied to other ML algorithms such as random forest, logistic regression, xgboost, etc.

scholarly journals Lipid Peroxidation in Chronic Cerebral HypoperfusionInduced Neurodegeneration in Rats

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Anil Kumar S ◽  
Saif SA ◽  
Oothuman P ◽  
Mustafa MIA
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Lipid Peroxidation ◽  
Neurodegenerative Disorders ◽  
Neuronal Damage ◽  
Neuronal Cell ◽  
Chronic Cerebral Hypoperfusion ◽  
Cerebral Hypoperfusion ◽  
Control Group ◽  
Vessel Occlusion

Introduction: Reduced cerebral blood fl ow is associated with neurodegenerative disorders and dementia, in particular. Experimental evidence has demonstrated the initiating role of chronic cerebral hypoperfusion in neuronal damage to the hippocampus, the cerebral cortex, the white matter areas and the visual system. Permanent, bilateral occlusion of the common carotid arteries of rats (two vessel occlusion - 2VO) has been introduced for the reproduction of chronic cerebral hypoperfusion as it occurs in Alzheimer’s disease and human aging. Increased generation of free radicals through lipid peroxidation can damage neuronal cell membrane. Markers of lipid peroxidation have been found to be elevated in brain tissues and body fl uids in neurodegenerative diseases, including Alzheimer’s disease, Parkinson disease and amyotrophic lateral sclerosis. Materials and Methods: Malondialdehyde (MDA), final product of lipid peroxidation, was estimated by thiobarbituric acid-reactive substances (TBARS) assay kit at eight weeks after induction of 2VO in the rats and control group. Results: Our study revealed a highly signifi cant (p<0.001) increase in the mean MDA concentration (12.296 ± 1.113 μM) in 2VO rats as compared to the control group (5.286 ± 0.363 μM) rats. Conclusion: Therapeutic strategies to modulate lipid peroxidation early throughout the course of the disease may be promising in slowing or possibly preventing neurodegenerative disorders.

scholarly journals The Diagnosis of Alzheimer’s Disease: An Ensemble Approach

2020 ◽  
Author(s):  
Jingyan Qiu ◽  
Linjian Li ◽  
Yida Liu ◽  
Yingjun Ou ◽  
Yubei Lin
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Large Scale ◽  
Early Stage ◽  
Training Transfer ◽  
Detection And Diagnosis ◽  
Magnetic Resonance Imaging Mri ◽  
Deep Learning Model ◽  
The Brain

Alzheimer’s disease (AD) is one of the most common forms of dementia. The early stage of the disease is defined as Mild Cognitive Impairment (MCI). Recent research results have shown the prospect of combining Magnetic Resonance Imaging (MRI) scanning of the brain and deep learning to diagnose AD. However, the CNN deep learning model requires a large scale of samples for training. Transfer learning is the key to enable a model with high accuracy by using limited data for training. In this paper, DenseNet and Inception V4, which were pre-trained on the ImageNet dataset to obtain initialization values of weights, are, respectively, used for the graphic classification task. The ensemble method is employed to enhance the effectiveness and efficiency of the classification models and the result of different models are eventually processed through probability-based fusion. Our experiments were completely conducted on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) public dataset. Only the ternary classification is made due to a higher demand for medical detection and diagnosis. The accuracies of AD/MCI/Normal Control (NC) of different models are estimated in this paper. The results of the experiments showed that the accuracies of the method achieved a maximum of 92.65%, which is a remarkable outcome compared with the accuracies of the state-of-the-art methods.

Preclinical Cognitive Trajectories Differ for Alzheimer's Disease and Vascular Dementia

2012 ◽  
Vol 18 (2) ◽  
pp. 191-199 ◽  
Author(s):  
Erika J. Laukka ◽  
Stuart W.S. MacDonald ◽  
Laura Fratiglioni ◽  
Lars Bäckman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vascular Dementia ◽  
Early Stage ◽  
Block Design ◽  
Word Recall ◽  
Cognitive Tasks ◽  
Control Group ◽  
Age Related ◽  
Preclinical Ad

AbstractWe investigated differences between Alzheimer's disease (AD) and vascular dementia (VaD) from the appearance of the first cognitive symptoms, focusing on both time of onset and rate of accelerated decline for different cognitive functions before dementia diagnosis. Data from a longitudinal population-based study were used, including 914 participants (mean age = 82.0 years, SD = 5.0) tested with a cognitive battery (word recall and recognition, Block Design, category fluency, clock reading) on up to four occasions spanning 10 years. We fit a series of linear mixed effects models with a change point to the cognitive data, contrasting each dementia group to a control group. Significant age-related decline was observed for all five cognitive tasks. Relative to time of diagnosis, the preclinical AD persons deviated from the normal aging curve earlier (up to 9 years) compared to the preclinical VaD persons (up to 6 years). However, once the preclinical VaD persons started to decline, they deteriorated at a faster rate than the preclinical AD persons. The results have important implications for identifying the two dementia disorders at an early stage and for selecting cognitive tasks to evaluate treatment effects for persons at risk of developing AD and VaD. (JINS, 2012, 18, 191–199)

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