scholarly journals Predicting amyloid positivity in patients with mild cognitive impairment using a radiomics approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun Pyo Kim ◽  
Jonghoon Kim ◽  
Hyemin Jang ◽  
Jaeho Kim ◽  
Sung Hoon Kang ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apoe Genotype ◽  
Texture Features ◽  
Structural Mri ◽  
Regularized Regression ◽  
Mr Images ◽  
Baseline Model ◽  
Imaging Model ◽  
T1 And T2

AbstractPredicting amyloid positivity in patients with mild cognitive impairment (MCI) is crucial. In the present study, we predicted amyloid positivity with structural MRI using a radiomics approach. From MR images (including T1, T2 FLAIR, and DTI sequences) of 440 MCI patients, we extracted radiomics features composed of histogram and texture features. These features were used alone or in combination with baseline non-imaging predictors such as age, sex, and ApoE genotype to predict amyloid positivity. We used a regularized regression method for feature selection and prediction. The performance of the baseline non-imaging model was at a fair level (AUC = 0.71). Among single MR-sequence models, T1 and T2 FLAIR radiomics models also showed fair performances (AUC for test = 0.71–0.74, AUC for validation = 0.68–0.70) in predicting amyloid positivity. When T1 and T2 FLAIR radiomics features were combined, the AUC for test was 0.75 and AUC for validation was 0.72 (p vs. baseline model < 0.001). The model performed best when baseline features were combined with a T1 and T2 FLAIR radiomics model (AUC for test = 0.79, AUC for validation = 0.76), which was significantly better than those of the baseline model (p < 0.001) and the T1 + T2 FLAIR radiomics model (p < 0.001). In conclusion, radiomics features showed predictive value for amyloid positivity. It can be used in combination with other predictive features and possibly improve the prediction performance.

Study on Texture Features of Cingulum in Different Gender Patients with Alzheimer’s Disease and Mild Cognitive Impairment Based on MR Images

2011 ◽  
Vol 301-303 ◽  
pp. 1060-1065 ◽  
Author(s):  
Xu Wang ◽  
Long Zheng Tong ◽  
Xin Li ◽  
Xiao Xia Zhou ◽  
Hui Fang Yang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Texture Features ◽  
Magnetic Resonance Images ◽  
Pathological Changes ◽  
Mr Images ◽  
Occurrence Matrix ◽  
Normal Controls

The aim of this article is to study the texture features of cingulum in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) based on magnetic resonance images, and explore the texture differences derived from different gender among each group. Texture analysis was performed on 7 AD patients, 14 MCI patients and 11 normal controls (NC). Texture features extracted from gray level co-occurrence matrix and run-length matrix were analyzed between each two groups. The results showed that texture features of the anterior cingulum had significant differences in the multiple comparisons and features of the posterior cingulum had significant differences between AD and MCI group as well as AD and NC group. There were significant differences between AD and MCI group as well as AD and NC group in male’s cingulum. While in female’s cingulaum, the differences were founded between AD and NC group. The results indicated that the pathological changes in cingulum could be reflected by texture features and the pathological changes may be different in the two genders.

scholarly journals Association between ApoE ε4 Carrier Status and Cardiovascular Risk Factors on Mild Cognitive Impairment among Mexican Older Adults

2021 ◽  
Vol 11 (1) ◽  
pp. 68
Author(s):  
Sara G. Aguilar-Navarro ◽  
Itzel I. Gonzalez-Aparicio ◽  
José Alberto Avila-Funes ◽  
Teresa Juárez-Cedillo ◽  
Teresa Tusié-Luna ◽  
...  
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Cognitive Impairment ◽  
Cardiovascular Risk ◽  
Mild Cognitive Impairment ◽  
Cardiovascular Risk Factors ◽  
Apoe Genotype ◽  
Carrier Status ◽  
Apoe Ε4 ◽  
Increased Risk

Mild cognitive impairment (MCI) (amnestic or non-amnestic) has different clinical and neuropsychological characteristics, and its evolution is heterogeneous. Cardiovascular risk factors (CVRF), such as hypertension, diabetes, or dyslipidemia, and the presence of the Apolipoprotein E ε4 (ApoE ε4) polymorphism have been associated with an increased risk of developing Alzheimer’s disease (AD) and other dementias but the relationship is inconsistent worldwide. We aimed to establish the association between the ApoE ε4 carrier status and CVRF on MCI subtypes (amnestic and non-amnestic) in Mexican older adults. Cross-sectional study including 137 older adults (n = 63 with normal cognition (NC), n = 24 with amnesic, and n = 50 with non-amnesic MCI). Multinomial logistic regression models were performed in order to determine the association between ApoE ε4 polymorphism carrier and CVRF on amnestic and non-amnestic-MCI. ApoE ε4 carrier status was present in 28.8% participants. The models showed that ApoE ε4 carrier status was not associated neither aMCI nor naMCI condition. The interaction term ApoE ε4 × CVRF was not statistically significant for both types of MCI. However, CVRF were associated with both types of MCI and the association remained statistically significant after adjustment by sex, age, and education level. The carrier status of the ApoE genotype does not contribute to this risk.

scholarly journals A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment

NeuroImage ◽  
2020 ◽  
Vol 215 ◽  
pp. 116795 ◽  
Author(s):  
F.R. Farina ◽  
D.D. Emek-Savaş ◽  
L. Rueda-Delgado ◽  
R. Boyle ◽  
H. Kiiski ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Resting State ◽  
Structural Mri

scholarly journals Relationship between Cognitive Performance and Measures of Neurodegeneration among Hispanic and White Non-Hispanic Individuals with Normal Cognition, Mild Cognitive Impairment, and Dementia

2017 ◽  
Vol 24 (2) ◽  
pp. 176-187 ◽  
Author(s):  
Shanna L. Burke ◽  
Miriam J. Rodriguez ◽  
Warren Barker ◽  
Maria T Greig-Custo ◽  
Monica Rosselli ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Performance ◽  
Entorhinal Cortex ◽  
Rating Scale ◽  
Structural Mri ◽  
Diagnostic Group ◽  
Disease Stage ◽  
Clinical Dementia Rating ◽  
Mild Dementia

AbstractObjectives:The aim of this study was to determine the presence and severity of potential cultural and language bias in widely used cognitive and other assessment instruments, using structural MRI measures of neurodegeneration as biomarkers of disease stage and severity.Methods:Hispanic (n=75) and White non-Hispanic (WNH) (n=90) subjects were classified as cognitively normal (CN), amnestic mild cognitive impairment (aMCI) and mild dementia. Performance on the culture-fair and educationally fair Fuld Object Memory Evaluation (FOME) and Clinical Dementia Rating Scale (CDR) between Hispanics and WNHs was equivalent, in each diagnostic group. Volumetric and visually rated measures of the hippocampus entorhinal cortex, and inferior lateral ventricles (ILV) were measured on structural MRI scans for all subjects. A series of analyses of covariance, controlling for age, depression, and education, were conducted to compare the level of neurodegeneration on these MRI measures between Hispanics and WNHs in each diagnostic group.Results:Among both Hispanics and WNH groups there was a progressive decrease in volume of the hippocampus and entorhinal cortex, and an increase in volume of the ILV (indicating increasing atrophy in the regions surrounding the ILV) from CN to aMCI to mild dementia. For equivalent levels of performance on the FOME and CDR, WNHs had greater levels of neurodegeneration than did Hispanic subjects.Conclusions:Atrophy in medial temporal regions was found to be greater among WNH than Hispanic diagnostic groups, despite the lack of statistical differences in cognitive performance between these two ethnic groups. Presumably, unmeasured factors result in better cognitive performance among WNH than Hispanics for a given level of neurodegeneration. (JINS, 2018,24, 176–187)

scholarly journals A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment

2019 ◽  
Author(s):  
FR Farina ◽  
DD Emek-Savaş ◽  
L Rueda-Delgado ◽  
R Boyle ◽  
H Kiiski ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Resting State ◽  
Healthy Aging ◽  
Neurodegenerative Disorder ◽  
Low Cost ◽  
Structural Mri ◽  
Lower Accuracy

AbstractAlzheimer’s disease (AD) is a neurodegenerative disorder characterised by severe cognitive decline and loss of autonomy. AD is the leading cause of dementia. AD is preceded by mild cognitive impairment (MCI). By 2050, 68% of new dementia cases will occur in low- and middle-income countries. In the absence of objective biomarkers, psychological assessments are typically used to diagnose MCI and AD. However, these require specialist training and rely on subjective judgements. The need for low-cost, accessible and objective tools to aid AD and MCI diagnosis is therefore crucial. Electroencephalography (EEG) has potential as one such tool: it is relatively inexpensive (cf. magnetic resonance imaging; MRI) and is portable. In this study, we collected resting state EEG, structural MRI and rich neuropsychological data from older adults (55+ years) with AD, with MCI and from healthy controls (n~60 per group). Our goal was to evaluate the utility of EEG, relative to MRI, for the classification of MCI and AD. We also assessed the performance of combined EEG and behavioural (Mini-Mental State Examination; MMSE) and structural MRI classification models. Resting state EEG classified AD and HC participants with moderate accuracy (AROC=0.76), with lower accuracy when distinguishing MCI from HC participants (AROC=0.67). The addition of EEG data to MMSE scores had no additional value compared to MMSE alone. Structural MRI out-performed EEG (AD vs HC, AD vs MCI: AROCs=1.00; HC vs MCI: AROC=0.73). Resting state EEG does not appear to be a suitable tool for classifying AD. However, EEG classification accuracy was comparable to structural MRI when distinguishing MCI from healthy aging, although neither were sufficiently accurate to have clinical utility. This is the first direct comparison of EEG and MRI as classification tools in AD and MCI participants.

scholarly journals Progressive Volume Atrophy in Hippocampal Subfields and the Correlation with Cognition in Alzheimer’s Disease and Mild Cognitive Impairment

2021 ◽  
Author(s):  
Guixia Kang ◽  
Peiqi Luo ◽  
Xin Xu ◽  
Ying Han ◽  
Xuemei Li ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Reference Value ◽  
Structural Mri ◽  
Volume Changes ◽  
Brain Scans ◽  
Left Hippocampus ◽  
The Right

Abstract Objective: To assess the progression of volume changes in hippocampus and its subfields of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI), and to explore the association of the hippocampus and its subfields volumes with cognitive function.Methods: Five groups of participants including 35 normal controls (NC) persons, 30 MCI patients, 30 Mild AD patients, 30 Moderate AD patients and 8 Severe AD patients received structural MRI brain scans. Freesurfer6.0 was used for automatically segmentation of MRI, and the left and right hippocampus were respectively divided into 12 subfields. By statistical analysis, the volumes of hippocampus and its subfields were compared between the five groups, and the correlation of the volumes with Mini-mental State Examination (MMSE) score was analyzed.Result & Conclusion: In the disease, each hippocampal subfield shows an uneven atrophy trajectory; The volumes of the subiculum and presubiculum are significantly different between Mild AD and MCI, which can contribute to the early diagnosis of AD; Parasubiculum is the least sensitive subfield for volume atrophy of AD, while subiculum, presubiculum, CA1, molecular_layer_HP and fimbria show much more significant volume changes. Meanwhile the volumes of these five subfields are positively correlated with MMSE, which may help in stage division of AD; Compared with the right hippocampus, the volume atrophy on the left side is more significantly, and the volumes are more significantly correlated with MMSE, So the left hippocampus and its subfields may provide a higher reference value for the clinical evaluation of AD than the right side.

scholarly journals Structural Neuroimaging in the Detection and Prognosis of Pre-Clinical and Early AD

2009 ◽  
Vol 21 (1-2) ◽  
pp. 3-12 ◽  
Author(s):  
Christine Fennema-Notestine ◽  
Linda K. McEvoy ◽  
Donald J. Hagler ◽  
Mark W. Jacobson ◽  
Anders M. Dale ◽  
...  
Keyword(s):  
At Risk ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Structural Change ◽  
Structural Mri ◽  
Cross Sectional ◽  
Structural Neuroimaging ◽  
Clinical Assessments ◽  
Structural Loss ◽  
Normal Controls

Current research supports the strong potential of structural MRI profiles, even within cross-sectional designs, as a promising method for the discrimination of Alzheimer's Disease (AD) from normal controls and for the prediction of Mild Cognitive Impairment (MCI) progression and conversion to AD. Findings suggest that measures of structural change in mesial and lateral temporal, cingulate, parietal and midfrontal areas may facilitate the assessment of a treatment's ability to halt the progressive structural loss that accompanies clinical decline in MCI. The performance of prediction is likely to continue to improve with the incorporation of measures from other neuroimaging modalities, clinical assessments, and neuromedical biomarkers, as the regional profile of individuals at risk for progression is refined.

3D Texture Analysis of Corpus Caliosum Based on MR Images Inpatients with Alzheimer’s Disease and Mild Cognitive Impairment

2014 ◽  
Vol 533 ◽  
pp. 415-420 ◽  
Author(s):  
Wei Fang Liu ◽  
Xu Wang ◽  
Hong Xia
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Corpus Callosum ◽  
Texture Analysis ◽  
Three Dimensional ◽  
Texture Features ◽  
Grey Level ◽  
Run Length ◽  
3D Texture ◽  
3D Texture Analysis

This study investigated three-dimensional (3D) texture as a possible diagnostic marker of Alzheimers disease (AD). Methods: T1-weighted MRI of 18 AD patients, 18 Mild Cognitive Impairment (MCI) patients and 18 normal controls (NC) were selected.3D Texture parameters of the corpus callosum,including contrast, inverse difference moment , entropy, short run emphasis, long run emphasis, grey level nonuniformity, run length nonuniformity and fraction were extracted from the gray level co-occurrence matrix and run length matrix. Finally statistic significance was tested among three groups, and the correlations between parameters and Mini-Mental State Examination (MMSE) scores were calculated. Results: The results showed that the 3D texture features had significant differences (p<0.05) among three groups except grey level nonuniformity and run length nonuniformity that the difference was not significant (p>0.05) between MCI and NC or AD and MCI , and they were correlated with MMSE scores.Conclusions: 3D texture analysis can reflect the pathological changes of corpus callosum in patients with AD and MCI, and it may be helpful to AD early diagnosis.

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