scholarly journals HAVAs: Alzheimer’s Disease Detection using Normative and Pathological Lifespan Models

2021 ◽  
Author(s):  
Pierrick Coupé ◽  
José V. Manjón ◽  
Boris Mansencal ◽  
Thomas Tourdias ◽  
Gwenaëlle Catheline ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Cognitive Impairment ◽  
Clinical Practice ◽  
State Of The Art ◽  
Brain Structures ◽  
Volumetric Analysis ◽  
Classification Performance

AbstractIn this paper, we present an innovative MRI-based method for Alzheimer’s Disease (AD) detection and mild cognitive impairment (MCI) prognostic, using lifespan trajectories of brain structures. After a full screening of the most discriminant structures between AD and normal aging based on MRI volumetric analysis of 3032 subjects, we propose a novel Hippocampal-Amygdalo-Ventricular Alzheimer score (HAVAs) based on normative lifespan models and AD lifespan models. During a validation on three external datasets on 1039 subjects, our approach showed very accurate detection (AUC ≥ 94%) of patients with AD compared to control subjects and accurate discrimination (AUC=78%) between progressive MCI and stable MCI (during a 3 years follow-up). Compared to normative modelling and recent state-of-the-art deep learning methods, our method demonstrated better classification performance. Moreover, HAVAs simplicity makes it fully understandable and thus well-suited for clinical practice or future pharmaceutical trials.

scholarly journals Neuropsychiatric, cognitive and brain morphology characteristics of conversion from Mild Cognitive Impairment to Alzheimer’s Disease

2021 ◽  
Author(s):  
Ronat Lucas ◽  
Hanganu Alexandru ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Performance ◽  
Brain Structures ◽  
Analysis Of Covariance ◽  
Brain Morphology ◽  
The Impact

AbstractThe impact of neuropsychiatric symptoms (NPS) on cognitive performance has been extensively reported, and this impact was better defined in the aging population. Yet a potential impact of NPS on brain morphology, cognitive performance and interactions between them in a longitudinal setting, as well as the potential of using these values as prediction of conversion – have remained questionable. We studied 156 participants with mild cognitive impairment (MCI) from the Alzheimer’s Disease Neuroimaging Initiative database who maintained the same level of cognitive performance after a 4-year follow-up and compared them to 119 MCI participants who converted to dementia. Additionally, we assessed the same analysis in 170 healthy controls who remained healthy at follow-up. Compared to 15 controls who converted to MCI. Their neuropsychological, neuropsychiatric, and brain morphology data underwent statistical analyses of 1) baseline comparison between the groups; (2) analysis of covariance model controlling for age, sex, education, and MMSE score, to specify the cognitive performance and brain structures that distinguish the two subgroups, and 3) used the significant ANCOVA variables to construct a binary logistic regression model that generates a probability equation for a given individual to convert to a lower cognitive performance state.Results showed that MCI who converted to AD in comparison to those who did not convert, exhibited a higher NPS prevalence, a lower cognitive performance and a higher number of involved brain structures. Furthermore, agitation, memory and the volumes of inferior temporal, hippocampal and amygdala sizes were significant predictors of MCI to AD conversion.

Elucidating the risk factors for progression from amyloid-negative amnestic mild cognitive impairment to dementia

2020 ◽  
Vol 17 ◽  
Author(s):  
Hyung-Ji Kim ◽  
Jae-Hong Lee ◽  
E-nae Cheong ◽  
Sung-Eun Chung ◽  
Sungyang Jo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Amnestic Mild Cognitive Impairment ◽  
Amyloid Pet ◽  
Clinical Progression ◽  
Amnestic Mci

Background: Amyloid PET allows for the assessment of amyloid β status in the brain, distinguishing true Alzheimer’s disease from Alzheimer’s disease-mimicking conditions. Around 15–20% of patients with clinically probable Alzheimer’s disease have been found to have no significant Alzheimer’s pathology on amyloid PET. However, a limited number of studies had been conducted this subpopulation in terms of clinical progression. Objective: We investigated the risk factors that could affect the progression to dementia in patients with amyloid-negative amnestic mild cognitive impairment (MCI). Methods: This study was a single-institutional, retrospective cohort study of patients over the age of 50 with amyloidnegative amnestic MCI who visited the memory clinic of Asan Medical Center with a follow-up period of more than 36 months. All participants underwent brain magnetic resonance imaging (MRI), detailed neuropsychological testing, and fluorine-18[F18]-florbetaben amyloid PET. Results: During the follow-up period, 39 of 107 patients progressed to dementia from amnestic MCI. In comparison with the stationary group, the progressed group had a more severe impairment in verbal and visual episodic memory function and hippocampal atrophy, which showed an Alzheimer’s disease-like pattern despite the lack of evidence for significant Alzheimer’s disease pathology. Voxel-based morphometric MRI analysis revealed that the progressed group had a reduced gray matter volume in the bilateral cerebellar cortices, right temporal cortex, and bilateral insular cortices. Conclusion: Considering the lack of evidence of amyloid pathology, clinical progression of these subpopulation may be caused by other neuropathologies such as TDP-43, abnormal tau or alpha synuclein that lead to neurodegeneration independent of amyloid-driven pathway. Further prospective studies incorporating biomarkers of Alzheimer’s diseasemimicking dementia are warranted.

Searching for Primary Predictors of Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: A Multivariate Follow-Up Study

2016 ◽  
Vol 52 (1) ◽  
pp. 133-143 ◽  
Author(s):  
María Eugenia López ◽  
Agustín Turrero ◽  
Pablo Cuesta ◽  
David López-Sanz ◽  
Ricardo Bruña ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Follow Up Study

scholarly journals To Explore the Predictive Power of Visuomotor Network Dysfunctions in Mild Cognitive Impairment and Alzheimer’s Disease

2021 ◽  
Vol 15 ◽  
Author(s):  
Justine Staal ◽  
Francesco Mattace-Raso ◽  
Hennie A. M. Daniels ◽  
Johannes van der Steen ◽  
Johan J. M. Pel
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Support Vector Machine ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Predictive Power ◽  
Area Under The Curve ◽  
Classification Performance ◽  
Support Vector ◽  
Potential Biomarker

BackgroundResearch into Alzheimer’s disease has shifted toward the identification of minimally invasive and less time-consuming modalities to define preclinical stages of Alzheimer’s disease.MethodHere, we propose visuomotor network dysfunctions as a potential biomarker in AD and its prodromal stage, mild cognitive impairment with underlying the Alzheimer’s disease pathology. The functionality of this network was tested in terms of timing, accuracy, and speed with goal-directed eye-hand tasks. The predictive power was determined by comparing the classification performance of a zero-rule algorithm (baseline), a decision tree, a support vector machine, and a neural network using functional parameters to classify controls without cognitive disorders, mild cognitive impaired patients, and Alzheimer’s disease patients.ResultsFair to good classification was achieved between controls and patients, controls and mild cognitive impaired patients, and between controls and Alzheimer’s disease patients with the support vector machine (77–82% accuracy, 57–93% sensitivity, 63–90% specificity, 0.74–0.78 area under the curve). Classification between mild cognitive impaired patients and Alzheimer’s disease patients was poor, as no algorithm outperformed the baseline (63% accuracy, 0% sensitivity, 100% specificity, 0.50 area under the curve).Comparison with Existing Method(s)The classification performance found in the present study is comparable to that of the existing CSF and MRI biomarkers.ConclusionThe data suggest that visuomotor network dysfunctions have potential in biomarker research and the proposed eye-hand tasks could add to existing tests to form a clear definition of the preclinical phenotype of AD.

scholarly journals Anticholinergics and Benzodiazepines on Cognitive Impairment among Elderly with Alzheimer’s Disease: a One year Follow-Up Study

2019 ◽  
Author(s):  
Rewadee Jenraumjit ◽  
Surarong Chinwong ◽  
Dujrudee Chinwong ◽  
Tipaporn Kanjanarach ◽  
Thanat Kshetradat ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Psychological Symptoms ◽  
Esterase Inhibitors ◽  
One Year ◽  
State Examination ◽  
Harmful Effects

Abstract Objective Age-associated decline in central cholinergic activity makes older adults susceptible to harmful effects of anticholinergics (ACs). Evidence exists of an association between effects of AC medications on cognition. This retrospective cohort study examines how ACs affect cognition among older adults with Alzheimer’s disease (AD) who received acetylcholine esterase inhibitors (AChEIs) over the course of 12 months. Results A total of 133 (80% women, mean age 78.38 years, SD 7.4) were recruited. No difference in sex, age and comorbid diseases was observed between participants who took ACs, Benzodiazepines (BZDs) and AChEIs. The most common prescribed ACs was quetiapine, being used for behavioral and psychological symptoms (BPSD). Multilevel analysis showed that the change of mental state examination scores were significantly predicted in the group using ACs (t (169), -2.52, p = .020) but not with the groups using BZD (t (162), 0.84, p = .440). Evidence showed that older adults with Alzheimer’s disease and exposed to ACs exhibited lower global cognitive scores than those without AC exposure. Using ACs could be a trade-off between controlling BPSD and aggravating cognitive impairment. Highlighting the awareness of the potential anticholinergic effect is important and may be the best policy.

Subjective cognitive impairment and Alzheimer's disease: a two year follow up of 51 subjects during two years

2015 ◽  
Vol 13 (4) ◽  
pp. 462-471 ◽  
Author(s):  
Nathalie Sambuchi ◽  
Isabelle Muraccioli ◽  
Béatrice Alescio-Lautier ◽  
Véronique Paban ◽  
Roland Sambuc ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Subjective Cognitive Impairment
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