The Study Of Grey-matter Volume As A Potential Biomarker Of Alzheimer’s Disease And Initial Establishment Of Assistant Recognition System For This Disease In Primary Medical Institution

Chapter Ⅰ The study of grey-matter volume as a potential biomarker of Alzheimer’s diseasePart Ⅰ Grey matter atrophy of Alzheimer’s disease and amnestic mild cognitive impairment and its relationship with cognitionObjective:To identify the grey matter atrophy pattern of Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) and assess the relationship between the grey matter atrophy and cognitive impairment.Materials and method:Voxel-based morphometric analyses were performed on structural MRIs from35AD patients,27aMCI patients, and27normal controls (NCs) A two-sample two-tailed t-test was computed between the NC and AD groups, NC and aMCI groups, aMCI and AD groups to identify the grey matter atrophy in AD or aMCI. The brain areas with significant decreased grey matter volume in AD were extracted as regions of interest (ROIs), and the grey-matter volumes in the ROIs of the aMCI patients were included to evaluate the patterns of change across different disease severities. And then, correlation analyses between the grey-matter volumes in the ROIs and all clinical variables were performed in aMCI and AD patients to determine whether they varied with disease progression.Results:The results revealed significantly decreased grey matter volume in the bilateral hippocampus/parahippocampus, the bilateral superior/middle temporal gyri, and the right precuneus in AD patients. Whole-brain voxel-wise analyses revealed no significant differences between the NC and aMCI groups or between the aMCI and AD group. The grey-matter volumes in ROIs were decreased in the aMCI patients relative to the NCs, and the grey matter volumes in the bilateral Hip/Phip and bilateral STG/MTG were lower in the AD than in the aMCI patients. In the aMCI plus AD group, the grey-matter volumes of all identified regions exhibited significant correlations with the MMSE and AVLT delayed-recall scores, and the grey-matter volumes of all identified regions except the right precuneus exhibited significant correlations with the new word recognition scores. In the aMCI group, the grey-matter volumes of the bilateral Hip/Phip and the left STG/MTG showed significant correlations with the AVLT delayed-recall and new word recognition scores. The grey-matter volumes of the right STG/MTG were significantly correlated with the AVLT immediate-recall scores.Conclusion:Grey matter atrophy of AD located primary in bilateral temporal lobe and the degree of atrophy positively correlated with cognitive impairment. Grey matter volume may be a potential feature for AD. Part II Grey-matter volume in bilateral hippocampus and parahippocampus as a potential feature for the classification of Alzheimer’s disease and mild cognitive impairment:an exploratory studyObjective:To assess the changes of the grey-matter volume in hippocampus and parahippocampus of Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI), and identify whether they can be taken as features for classifying AD and aMCI.Materials and method:Structural MRIs from35AD patients,27aMCI patients, and27NC were preprocessed with SPM8. The bilateral hippocampus and parahippocampus were selected in AAL template as regions of interest (ROIs), and then each ROI were divided into four subregions (head, body1and body2, tail), that’s means each participant has16features. The grey matter in each ROI was compared between each pair of AD, aMCI and NC group, and correlation analyses between the grey-matter volumes in the ROIs and all clinical variables were performed in aMCI and AD patients. Fisher’s linear discriminative method and leave-one-out cross-validation analyses were performed to assess the utility of grey-matter volumes to classify patients.Results:The gray matter volumes of these subdivided regions were significantly decreased in AD compared to NC subjects. In the aMCI plus AD group, the grey-matter volumes in the left hippocampus head, the head-to-body2of right hippocampus, the body2of the left parahippocampus, the body1-to-tail of right parahippocampus exhibited significant correlations with the MMSE; the tail of right parahippocampus exhibited significant correlations with the AVLT immediate recall; grey matter volumes in all the subregions exhibited significant correlations with the AVLT delayed recall; the grey matter volumes in the tail of the left hippocampus, body2-to-tail of the right hippocampus, bodyl-to-body2of left parahippocampus and body2-to-tail of right parahippocampus exhibited significant correlations with new word recognition. In the aMCI group, the body2-to-tail of both the right hippocampus and the right parahippocampus exhibited significant correlations with the AVLT immediate recall; the grey matter in all subregions except the tail of the right parahippocampus exhibited significant correlations with the AVLT delayed recall; the grey matter in all subregions except the head of the right hippocampus exhibited significant correlations with the new word recognition. In the AD group, the grey matter volume in the tail of the right parahippocampus exhibited significant correlations with the AVLT immediate recall; the grey matter in the body1of the right hippocampus and the tail of the left parahippocampus exhibited significant correlations with the old word recognition. Discriminative analysis with these16features revealed～82%accuracy in discriminating AD patients from NC participants. And～58%of the cases were correctly classified when the same protocol was used to distinguish all three groups.Conclusion:The grey-matter volumes are useful in the classification of AD and may be a potential feature of AD. But its capacity for classifying MCI is limited Chapter II The initial establishment of assistant automatic recognition system of Alzheimer’s disease for primary hospitalsObjective:Attempt to establish automatic system for assistant recognition of Alzheimer’s disease (AD) initially.Materials and method:50AD patients,44aMCI patients and46normal controls underwent a neuropsychological test battery that comprised the Mini-Mental State Examination (MMSE), the Auditory Verbal Learning Test (AVLT), the Activities of Daily Living scale (ADL), Clinical Dementia Rating(CDR), Similarity test, Comprehension test, Trail making test A, Complex figure test, Animal fluency test, the Geriatric Depression Scale (GDS).34subtests’data was reduced based on the rough set theory, and the results were used to establish automatic recognition system of Alzheimer’s disease based on Bayesian network.10-fold cross validation method was used to test the system.Result:The results of the subtraction including the followed:3-stage command subtest in MMSE; visualspacial and executive function, naming and attention subtests in MoCA; Complex figure test; immediate recall and delayed recall in AVLT test; IADL. Based on the automatic recognition system, the sensitivity for identifying NC was88.2%and specificity was89.3%, sensitivity for aMCI was78.7%and specificity was86.8%, sensitivity for AD was82.6%and specificity was97.2%.Conclusion:The automatic recognition system for AD may be useful for the recognizing AD especially for primary hospitals.