Assessment of Linear and Non-linear Feature Projections for the Classification of 3-D MR Images on Cognitively Normal, Mild Cognitive Impairment and Alzheimer’s Disease

2021 ◽  
pp. 18-33
Author(s):  
Marcelo R. Moura Araújo ◽  
Katia M. Poloni ◽  
Ricardo J. Ferrari
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Mr Images ◽  
Cognitively Normal ◽  
Linear Feature ◽  
Non Linear

scholarly journals Combining Multimodal Behavioral Data of Gait, Speech, and Drawing for Classification of Alzheimer’s Disease and Mild Cognitive Impairment

2021 ◽  
pp. 1-13
Author(s):  
Yasunori Yamada ◽  
Kaoru Shinkawa ◽  
Masatomo Kobayashi ◽  
Vittorio Caggiano ◽  
Miyuki Nemoto ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Impairments ◽  
Classification Performance ◽  
Behavioral Data ◽  
Cognitively Normal ◽  
Clinical Measures

Background: Gait, speech, and drawing behaviors have been shown to be sensitive to the diagnosis of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). However, previous studies focused on only analyzing individual behavioral modalities, although these studies suggested that each of these modalities may capture different profiles of cognitive impairments associated with AD. Objective: We aimed to investigate if combining behavioral data of gait, speech, and drawing can improve classification performance compared with the use of individual modality and if each of these behavioral data can be associated with different cognitive and clinical measures for the diagnosis of AD and MCI. Methods: Behavioral data of gait, speech, and drawing were acquired from 118 AD, MCI, and cognitively normal (CN) participants. Results: Combining all three behavioral modalities achieved 93.0%accuracy for classifying AD, MCI, and CN, and only 81.9%when using the best individual behavioral modality. Each of these behavioral modalities was statistically significantly associated with different cognitive and clinical measures for diagnosing AD and MCI. Conclusion: Our findings indicate that these behaviors provide different and complementary information about cognitive impairments such that classification of AD and MCI is superior to using either in isolation.

scholarly journals An evaluation on changes in Hippocampus size for Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and Alzheimer’s disease (AD) patients using Fuzzy Membership Function

2021 ◽  
Author(s):  
Ruhul Amin Hazarika ◽  
Arnab Kumar Maji ◽  
Debdatta Kandar ◽  
Prasun Chakrabarti ◽  
Tulika Chakrabarti ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Memory Loss ◽  
Fuzzy Membership Function ◽  
Average Difference ◽  
Mr Images ◽  
Cognitively Normal ◽  
The Brain

Background: Alzheimer’s disease (AD) is a neurological disorder where the hippocampus in the brain gets affected severely. Hippocampus is a part of the limbic system, which is mainly responsible for forming memories. The transition from Cognitively Normal (CN) to AD is having one intermittent stage, popularly known as Mild Cognitive Impairment (MCI). In this study, segmentation operation has been performed first to separate the hippocampus, and then an analysis has been made on the basis of changes in area and atrophy in the hippocampus. A total of “2008” numbers of MR images have been analyzed for three different subject groups consist of “210” different subjects (Male:105, Female: 105) namely, CN, MCI, and AD.Objective: The objective of this study is to analyze the size and atrophy of the hippocampus due to AD and MCI in comparison with CN patients.Material and Methods: All the experiments have done using MATLAB tools. All the data used is acquired from the online dataset “Alzheimer’s Disease Neuroimaging Initiative (ADNI)”.Results: From the study, it is found that the average difference in the size of the hippocampus between CN and MCI is 17.05%, between CN and AD is 31.90%, and between MCI and AD is 18.24%. The average atrophy per year in the hippocampus is found to be as 4.62% for AD, 2.33% for MCI, and 1.10% for CN subjects.Conclusions: From the study, it is observed that, for AD patients, hippocampus atrophy is highest, and hence they experience the highest memory loss followed by the MCI and CN patients.

scholarly journals An evaluation on changes in Hippocampus size for Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and Alzheimer’s disease (AD) patients using Fuzzy Membership Function

2021 ◽  
Author(s):  
Ruhul Amin Hazarika ◽  
Arnab Kumar Maji ◽  
Debdatta Kandar ◽  
Prasun Chakrabarti ◽  
Tulika Chakrabarti ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Memory Loss ◽  
Fuzzy Membership Function ◽  
Average Difference ◽  
Mr Images ◽  
Cognitively Normal ◽  
The Brain

Background: Alzheimer’s disease (AD) is a neurological disorder where the hippocampus in the brain gets affected severely. Hippocampus is a part of the limbic system, which is mainly responsible for forming memories. The transition from Cognitively Normal (CN) to AD is having one intermittent stage, popularly known as Mild Cognitive Impairment (MCI). In this study, segmentation operation has been performed first to separate the hippocampus, and then an analysis has been made on the basis of changes in area and atrophy in the hippocampus. A total of “2008” numbers of MR images have been analyzed for three different subject groups consist of “210” different subjects (Male:105, Female: 105) namely, CN, MCI, and AD.Objective: The objective of this study is to analyze the size and atrophy of the hippocampus due to AD and MCI in comparison with CN patients.Material and Methods: All the experiments have done using MATLAB tools. All the data used is acquired from the online dataset “Alzheimer’s Disease Neuroimaging Initiative (ADNI)”.Results: From the study, it is found that the average difference in the size of the hippocampus between CN and MCI is 17.05%, between CN and AD is 31.90%, and between MCI and AD is 18.24%. The average atrophy per year in the hippocampus is found to be as 4.62% for AD, 2.33% for MCI, and 1.10% for CN subjects.Conclusions: From the study, it is observed that, for AD patients, hippocampus atrophy is highest, and hence they experience the highest memory loss followed by the MCI and CN patients.

scholarly journals Financial Capacity and Regional Cerebral Tau in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer’s Disease Dementia

2020 ◽  
pp. 1-10
Author(s):  
Christopher Gonzalez ◽  
Nicole S. Tommasi ◽  
Danielle Briggs ◽  
Michael J. Properzi ◽  
Rebecca E. Amariglio ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Stage ◽  
Cognitively Normal ◽  
Financial Capacity ◽  
Posterior Cingulate ◽  
Dorsolateral Prefrontal

Background: Financial capacity is often one of the first instrumental activities of daily living to be affected in cognitively normal (CN) older adults who later progress to amnestic mild cognitive impairment (MCI) and Alzheimer’s disease (AD) dementia. Objective: The objective of this study was to investigate the association between financial capacity and regional cerebral tau. Methods: Cross-sectional financial capacity was assessed using the Financial Capacity Instrument –Short Form (FCI-SF) in 410 CN, 199 MCI, and 61 AD dementia participants who underwent flortaucipir tau positron emission tomography from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Linear regression models with backward elimination were used with FCI-SF total score as the dependent variable and regional tau and tau-amyloid interaction as predictors of interest in separate analyses. Education, age sex, Rey Auditory Verbal Learning Test Total Learning, and Trail Making Test B were used as covariates. Results: Significant associations were found between FCI-SF and tau regions (entorhinal: p <  0.001; inferior temporal: p <  0.001; dorsolateral prefrontal: p = 0.01; posterior cingulate: p = 0.03; precuneus: p <  0.001; and supramarginal gyrus: p = 0.005) across all participants. For the tau-amyloid interaction, significant associations were found in four regions (amyloid and dorsolateral prefrontal tau interaction: p = 0.005; amyloid and posterior cingulate tau interaction: p = 0.005; amyloid and precuneus tau interaction: p <  0.001; and amyloid and supramarginal tau interaction: p = 0.002). Conclusion: Greater regional tau burden was modestly associated with financial capacity impairment in early-stage AD. Extending this work with longitudinal analyses will further illustrate the utility of such assessments in detecting clinically meaningful decline, which may aid clinical trials of early-stage AD.

scholarly journals 12-year prediction of mild cognitive impairment aided by Alzheimer’s brain signatures at mean age 56

2021 ◽  
Author(s):  
McKenna E Williams ◽  
Jeremy A Elman ◽  
Linda K McEvoy ◽  
Ole A Andreassen ◽  
Anders M Dale ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Mean Diffusivity ◽  
Area Under The Curve ◽  
Polygenic Risk Score ◽  
Age Difference ◽  
Cognitively Normal ◽  
Brain Age

Abstract Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer’s disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Toward that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: 1) a validated MRI-derived Alzheimer’s disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and 2) a novel gray matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246–367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51–60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer’s disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61–71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply aging-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P=0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently-derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step toward improving very early identification of Alzheimer’s disease risk and the potential value of mean diffusivity and/or multimodal brain signatures.

scholarly journals Visual Object Discrimination Impairment as an Early Predictor of Mild Cognitive Impairment and Alzheimer’s Disease

2019 ◽  
Vol 25 (7) ◽  
pp. 688-698 ◽  
Author(s):  
Leslie S. Gaynor ◽  
Rosie E. Curiel Cid ◽  
Ailyn Penate ◽  
Mónica Rosselli ◽  
Sara N. Burke ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Discrimination Task ◽  
Inverse Function ◽  
Visual Object ◽  
Object Discrimination ◽  
Cognitively Normal ◽  
Novel Object

AbstractObjective:Detection of cognitive impairment suggestive of risk for Alzheimer’s disease (AD) progression is crucial to the prevention of incipient dementia. This study was performed to determine if performance on a novel object discrimination task improved identification of earlier deficits in older adults at risk for AD.Method:In total, 135 participants from the 1Florida Alzheimer’s Disease Research Center [cognitively normal (CN), Pre-mild cognitive impairment (PreMCI), amnestic mild cognitive impairment (aMCI), and dementia] completed a test of object discrimination and traditional memory measures in the context of a larger neuropsychological and clinical evaluation.Results:The Object Recognition and Discrimination Task (ORDT) revealed significant differences between the PreMCI, aMCI, and dementia groups versus CN individuals. Moreover, relative risk of being classified as PreMCI rather than CN increased as an inverse function of ORDT score.Discussion:Overall, the obtained results suggest that a novel object discrimination task improves the detection of very early AD-related cognitive impairment, increasing the window for therapeutic intervention. (JINS, 2019,25, 688–698)

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