Advances in longitudinal studies of amnestic mild cognitive impairment and Alzheimer's disease based on multi-modal MRI techniques.
Ontology highlight
ABSTRACT:
SUBMITTER: Hu Z
PROVIDER: S-EPMC5562653 | biostudies-other | 2014 Apr
REPOSITORIES: biostudies-other
Similar Datasets
Project description:A sensitive marker for monitoring progression of early Alzheimer's disease would help to develop and test new therapeutic strategies. The present study is aimed at investigating brain metabolism changes over time, as a potential monitoring marker, in patients with amnestic mild cognitive impairment, according to their clinical outcome (converters or non-converters), and in relation to their cognitive decline. Seventeen amnestic mild cognitive impairment patients underwent magnetic resonance imaging and 18FDG-positron emission tomography scans both at inclusion and 18 months later. Baseline and follow-up positron emission tomography data were corrected for partial volume effects and spatially normalized using magnetic resonance imaging data, scaled to the vermis and compared using SPM2. 'PET-PAC' maps reflecting metabolic per cent annual changes were created for correlation analyses with cognitive decline. In the whole sample, the greatest metabolic decrease concerned the posterior cingulate-precuneus area. Converters had significantly greater metabolic decrease than non-converters in two ventro-medial prefrontal areas, the subgenual (BA25) and anterior cingulate (BA24/32). PET-PAC in BA25 and BA24/32 combined allowed complete between-group discrimination. BA25 PET-PAC significantly correlated with both cognitive decline and PET-PAC in the hippocampal region and temporal pole, while BA24/32 PET-PAC correlated with posterior cingulate PET-PAC. Finally, the metabolic change in BA8/9/10 was inversely related to that in BA25 and showed relative increase with cognitive decline, suggesting that compensatory processes may occur in this dorso-medial prefrontal region. The observed ventro-medial prefrontal disruption is likely to reflect disconnection from the hippocampus, both indirectly through the cingulum bundle and posterior cingulate cortex for BA24/32, and directly through the uncinate fasciculus for BA25. Altogether, our findings emphasize the potential of 18FDG-positron emission tomography for monitoring early Alzheimer's disease progression.
| S-EPMC2936690 | biostudies-literature
Project description:BACKGROUND:Amyloid-? positivity (A?+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease (AD), particularly in trials for amyloid-targeted therapy. Predicting A? positivity prior to PET imaging can decrease unnecessary patient burden and costs of running these trials. OBJECTIVE:The aim of this study was to evaluate the performance of a machine learning model in estimating the individual risk of A?+ based on gold-standard of PET imaging. METHODS:We used data from an amnestic mild cognitive impairment (aMCI) subset of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to develop and validate the models. The predictors of A? status included demographic and ApoE4 status in all models plus a combination of neuropsychological tests (NP), MRI volumetrics, and cerebrospinal fluid (CSF) biomarkers. RESULTS:The models that included NP and MRI measures separately showed an area under the receiver operating characteristics (AUC) of 0.74 and 0.72, respectively. However, using NP and MRI measures jointly in the model did not improve prediction. The models including CSF biomarkers significantly outperformed other models with AUCs between 0.89 to 0.92. CONCLUSIONS:Predictive models can be effectively used to identify persons with aMCI likely to be amyloid positive on a subsequent PET scan.
| S-EPMC7376527 | biostudies-literature
Project description:IntroductionIt has been reported that environmental factors such as hypoxia could contribute to the pathogenesis of Alzheimer's disease (AD). Therapeutics like hyperbaric oxygen treatment, which improves tissue oxygen supply and ameliorates hypoxic conditions in the brain, may be an alternative therapy for AD and amnestic mild cognitive impairment (aMCI). The present work aims to investigate the potential therapeutic effect of hyperbaric oxygen treatment for AD and aMCI.MethodsWe recruited 42 AD, 11 aMCI, and 30 control AD patients in this study. AD and aMCI patients were treated with 40 minutes of hyperbaric oxygen once a day for 20 days and assessed by neuropsychiatric assessments including Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Activities of Daily Living (ADL) scale before and at 1-, 3-, and 6-month follow-up after treatment. Control AD patients who were not given hyperbaric oxygen treatment had similar clinical profile as hyperbaric oxygen treated AD. We examined 10 of the AD/aMCI patients with fluorodeoxyglucose positron emission tomography.ResultsIn self-comparison study, one course of hyperbaric oxygen treatment significantly improved the cognitive function assessed by MMSE and MoCA in AD patients after 1-month follow-up; such treatment also significantly improved MMSE score at 3-month follow-up and MoCA score at 1- and 3-month follow-up in aMCI patients. The ADL scale was significantly improved in AD patients after 1- and 3-month follow-up. Compared to the control AD patients, the MMSE and MoCA in hyperbaric oxygen treated AD patients were significantly improved after 1-month follow-up. Hyperbaric oxygen treatment also ameliorated the reduced brain glucose metabolism in some of the AD and aMCI patients.ConclusionBased on previous studies and our recent findings, we propose that hyperbaric oxygen treatment may be a promising alternative therapy for AD and aMCI.
| S-EPMC7293997 | biostudies-literature
Project description:Disproportionately greater deficits in semantic relative to phonemic verbal fluency are seen in Alzheimer's disease (AD) and have been attributed to neurodegenerative changes in the temporal lobe. Amnestic (AMN) mild cognitive impairment (MCI), which often represents incipient AD, is also characterized by early temporal lobe neuropathology, but previous comparisons of verbal fluency between AD and AMN MCI have yielded mixed results. We examined semantic and phonemic verbal fluency performance in 399 individuals (78 AD, 138 AMN MCI, 72 non-amnestic MCI, and 111 cognitively normal controls). Similar verbal fluency patterns were seen in AMN MCI and AD; both groups exhibited disproportionately poorer performance on semantic verbal fluency relative to normal controls. However, relative verbal fluency indices performed more poorly than individual semantic or phonemic verbal fluency indices for discriminating AMN MCI or AD participants from normal controls, suggesting that they are unlikely to provide additional utility for predicting progression from MCI to AD.
| S-EPMC3711375 | biostudies-other
Project description:To date, most diagnostic imaging comparisons between amyloid labelling ligands and other imaging modalities have been between the use of amyloid labelling ligand (11)C Pittsburgh Compound B (PiB) and FDG-PET. Our objectives were to compare cognitive performance and diagnostic group-wise discrimination between cognitively normal, amnestic mild cognitive impairment (MCI) and Alzheimer's disease subjects with MRI-based measures of hippocampal volume and PiB retention, and secondly to evaluate the topographic distribution of PiB retention and grey matter loss using 3D voxel-wise methods. Twenty cognitively normal, 17 amnestic MCI and 8 probable Alzheimer's disease subjects were imaged with both MRI and PiB. PiB retention was quantified as the ratio of uptake in cortical to cerebellar regions of interest (ROIs) 40-60 min post-injection. A global cortical PiB retention summary measure was derived from six cortical ROIs. Statistical parametric mapping (SPM) and voxel-based morphometry (VBM) were used to evaluate PiB retention and grey matter loss on a 3D voxel-wise basis. Alzheimer's disease subjects had high global cortical PiB retention and low hippocampal volume; most cognitively normal subjects had low PiB retention and high hippocampal volume; and on average amnestic MCI subjects were intermediate on both PiB and hippocampal volume. A target-to-cerebellar ratio of 1.5 was used to designate subjects with high or low PiB cortical retention. All Alzheimer's disease subjects fell above this ratio, as did 6 out of 20 cognitively normal subjects and 9 out of 17 MCI subjects, indicating bi-modal PiB retention in the latter two groups. Interestingly, we found no consistent differences in learning and memory performance between high versus low PiB cognitively normal or amnestic MCI subjects. The SPM/VBM voxel-wise comparisons of Alzheimer's disease versus cognitively normal subjects provided complementary information in that clear and meaningful similarities and differences in topographical distribution of amyloid deposition and grey matter loss were shown. The frontal lobes had high PiB retention with little grey matter loss, anteromedial temporal areas had low PiB retention with significant grey matter loss, whereas lateral temporoparietal association cortex displayed both significant PiB retention and grey matter loss. A voxel-wise SPM conjunction analysis revealed that subjects with high PiB retention shared a common PiB retention topographical pattern regardless of clinical category, and this matched that of amyloid plaque distribution from autopsy studies of Alzheimer's disease. Both global cortical PiB retention and hippocampal volumes demonstrated significant correlation in the expected direction with cognitive testing performance; however, correlations were stronger with MRI than PiB. Pair-wise inter-group diagnostic separation was significant for all group-wise pairs for both PiB and hippocampal volume with the exception of the comparison of cognitively normal versus amnestic MCI, which was not significant for PiB. PiB and MRI provided complementary information such that clinical diagnostic classification using both methods was superior to using either in isolation.
| S-EPMC2730157 | biostudies-literature
Project description:Alzheimer's disease (AD) is characterized by progressive dementia, especially in episodic memory, and amnestic mild cognitive impairment (aMCI) is associated with a high risk of developing AD. Hippocampal atrophy/shape changes are believed to be the most robust magnetic resonance imaging (MRI) markers for AD and aMCI. Radiomics, a method of texture analysis, can quantitatively examine a large set of features and has previously been successfully applied to evaluate imaging biomarkers for AD. To test whether radiomic features in the hippocampus can be employed for early classification of AD and aMCI, 1692 features from the caudal and head parts of the bilateral hippocampus were extracted from 38 AD patients, 33 aMCI patients and 45 normal controls (NCs). One way analysis of variance (ANOVA) showed that 111 features exhibited statistically significant group differences (P < 0.01, Bonferroni corrected). Among these features, 98 were significantly correlated with Mini-Mental State Examination (MMSE) scores in AD and aMCI subjects (P < 0.01). The support vector machine (SVM) model demonstrated that radiomic features allowed us to distinguish AD from NC with an accuracy of 86.75% (specificity = 88.89% and sensitivity = 84.21%) and an area under curve (AUC) of 0.93. In conclusion, these findings provide evidence showing that radiomic features are beneficial in detecting early cognitive decline, and SVM classification analysis provides encouraging evidence for using hippocampal radiomic features as a potential biomarker for clinical applications in AD.
| S-EPMC6167420 | biostudies-literature
Project description:Amnestic MCI is often considered an early clinical stage of AD, but its subtle presentation leads to infrequent neurological evaluations. Early plasma biomarker screening during routine check-ups in community hospitals could enhance aMCI detection rates. Advances in proteomics, particularly mass spectrometry, have enabled the detection of low-abundance plasma proteins, opening new possibilities for aMCI biomarker identification. This study included 84 participants from the STAR cohort. We utilized deep plasma proteomics to detect low-abundance proteins, enriched with biofunctional magnetic beads. An early diagnostic model for aMCI was developed through bioinformatics and machine learning, with performance compared to the Simoa assay.
2024-09-26 | PXD056265 |
Project description:Impaired structure and function of the hippocampus is a valuable predictor of progression from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD). As a part of the medial temporal lobe memory system, the hippocampus is one of the brain regions affected earliest by AD neuropathology, and shows progressive degeneration as aMCI progresses to AD. Currently, no validated biomarkers can precisely predict the conversion from aMCI to AD. Therefore, there is a great need of sensitive tools for the early detection of AD progression. In this review, we summarize the specific structural and functional changes in the hippocampus from recent aMCI studies using neurophysiological and neuroimaging data. We suggest that a combination of advanced multi-modal neuroimaging measures in discovering biomarkers will provide more precise and sensitive measures of hippocampal changes than using only one of them. These will potentially affect early diagnosis and disease-modifying treatments. We propose a new sequential and progressive framework in which the impairment spreads from the integrity of fibers to volume and then to function in hippocampal subregions. Meanwhile, this is likely to be accompanied by progressive impairment of behavioral and neuropsychological performance in the progression of aMCI to AD.
| S-EPMC5562641 | biostudies-other
Project description:Although the presence of anosognosia in amnestic mild cognitive impairment (aMCI) may be predictive of conversion to Alzheimer's disease (AD), little is known about its neural correlates in AD and aMCI. Four different groups were compared using volumetric and diffusion magnetic resonance imaging metrics in regions of interest (hippocampus and cingulum cortex gray matter, cingulum bundle white matter): aMCI subjects with anosognosia (n = 6), aMCI subjects without anosognosia (n = 12), AD subjects with anosognosia (n = 6), and AD subjects without anosognosia (n = 9). aMCI subjects with anosognosia displayed a significantly lower gray matter density (GMD) in the bilateral hippocampus than aMCI subjects without anosognosia, which was accounted for by bilateral hippocampal differences. Furthermore, we identified that the mean hippocampal gray matter density of aMCI subjects with anosognosia was not statistically different than that of AD subjects. The groups of aMCI and AD subjects with anosognosia also displayed a lower GMD in the bilateral cingulum cortex compared to subjects without anosognosia, but these differences were not statistically significant. No statistically significant differences were found in the fractional anisotropy or mean diffusivity of the hippocampus or cingulum between subjects with and without anosognosia in aMCI or AD groups. While these findings are derived from a small population of subjects and are in need of replication, they suggest that anosognosia in aMCI might be a useful clinical marker to suspect brain changes associated with AD neuropathology.
| S-EPMC8581404 | biostudies-literature
Project description:Degeneration of the corpus callosum (CC) is evident in the pathogenesis of Alzheimer's disease (AD). However, the correlation of microstructural damage in the CC on the cognitive performance of patients with amnestic mild cognitive impairment (aMCI) and AD dementia is undetermined. We enrolled 26 normal controls, 24 patients with AD dementia, and 40 single-domain aMCI patients with at least grade 1 hippocampal atrophy and isolated memory impairment. Diffusion tensor imaging (DTI) with fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR) were measured. The entire CC was parcellated based on fiber trajectories to specific cortical Brodmann areas using a probabilistic tractography method. The relationship between the DTI measures in the subregions of the CC and cognitive performance was examined. Although the callosal degeneration in the patients with aMCI was less extended than in the patients with AD dementia, degeneration was already exhibited in several subregions of the CC at the aMCI stage. Scores of various neuropsychological tests were correlated to the severity of microstructural changes in the subregional CC connecting to functionally corresponding cortical regions. Our results confirm that CC degeneration is noticeable as early as the aMCI stage of AD and the disconnection of the CC subregional fibers to the corresponding Brodmann areas has an apparent impact on the related cognitive performance.
| S-EPMC6869324 | biostudies-literature