Automated detection of amnestic mild cognitive impairment in community-dwelling elderly adults: a combined spatial atrophy and white matter alteration approach.

Amnestic mild cognitive impairment (aMCI) is a syndrome widely considered to be prodromal Alzheimer's disease. Accurate diagnosis of aMCI would enable earlier treatment, and could thus help minimize the prevalence of Alzheimer's disease. The aim of the present study was to evaluate a magnetic resonance imaging-based automated classification schema for identifying aMCI. This was carried out in a sample of community-dwelling adults aged 70-90 years old: 79 with a clinical diagnosis of aMCI and 204 who were cognitively normal. Our schema was novel in using measures of both spatial atrophy, derived from T1-weighted images, and white matter alterations, assessed with diffusion tensor imaging (DTI) tract-based spatial statistics (TBSS). Subcortical volumetric features were extracted using a FreeSurfer-initialized Large Deformation Diffeomorphic Metric Mapping (FS+LDDMM) segmentation approach, and fractional anisotropy (FA) values obtained for white matter regions of interest. Features were ranked by their ability to discriminate between aMCI and normal cognition, and a support vector machine (SVM) selected an optimal feature subset that was used to train SVM classifiers. As evaluated via 10-fold cross-validation, the classification performance characteristics achieved by our schema were: accuracy, 71.09%; sensitivity, 51.96%; specificity, 78.40%; and area under the curve, 0.7003. Additionally, we identified numerous socio-demographic, lifestyle, health and other factors potentially implicated in the misclassification of individuals by our schema and those previously used by others. Given its high level of performance, our classification schema could facilitate the early detection of aMCI in community-dwelling elderly adults.

Cui Y ，Wen W ，Lipnicki DM ，Beg MF ，Jin JS ，Luo S ，Zhu W ，Kochan NA ，Reppermund S ，Zhuang L ，Raamana PR ，Liu T ，Trollor JN ，Wang L ，Brodaty H ，Sachdev PS ... -  《-》

White matter integrity in mild cognitive impairment: a tract-based spatial statistics study.

Mild cognitive impairment (MCI) as a clinical diagnosis has limited specificity, and identifying imaging biomarkers may improve its predictive validity as a pre-dementia syndrome. This study used diffusion tensor imaging (DTI) to detect white matter (WM) structural alterations in MCI and its subtypes, and aimed to examine if DTI can serve as a potential imaging marker of MCI. We studied 96 amnestic MCI (aMCI), 69 non-amnestic MCI (naMCI), and 252 cognitively normal (CN) controls. DTI was performed to measure fractional anisotropy (FA), and tract-based spatial statistics (TBSS) were applied to investigate the characteristics of WM changes in aMCI and naMCI. The diagnostic utility of DTI in distinguishing MCI from CN was further evaluated by using a binary logistic regression model. We found that FA was significantly reduced in aMCI and naMCI when compared with CN. For aMCI subjects, decreased FA was seen in the frontal, temporal, parietal, and occipital WM, together with several commissural, association, and projection fibres. The best discrimination between aMCI and controls was achieved by combining FA measures of the splenium of corpus callosum and crus of fornix, with accuracy of 74.8% (sensitivity 71.0%, specificity 76.2%). For naMCI subjects, WM abnormality was more anatomically widespread, but the temporal lobe WM was relatively spared. These results suggest that aMCI is best characterized by pathology consistent with early Alzheimer's disease, whereas underlying pathology in naMCI is more heterogeneous, and DTI analysis of white matter structural integrity can serve as a potential biomarker of MCI and its subtypes.

Zhuang L ，Wen W ，Zhu W ，Trollor J ，Kochan N ，Crawford J ，Reppermund S ，Brodaty H ，Sachdev P ... -  《-》

Comparison of diffusion tensor image study in association fiber tracts among normal, amnestic mild cognitive impairment, and Alzheimer's patients.

Zhang YZ ，Chang C ，Wei XE ，Fu JL ，Li WB ... -  《NEUROLOGY INDIA》

Disrupted topological organization in white matter structural networks in amnestic mild cognitive impairment: relationship to subtype.

To investigate the topological alterations of whole-brain white matter structural connectivity in patients with different types of amnestic mild cognitive impairment (aMCI), including single-domain (SD) and multidomain (MD) aMCI, and to explore the relationship of such connectivity with neuropsychologic performance. This study was approved by the institutional review board of Imaging Center for Brain Research, Beijing Normal University. Written informed consent was obtained from each participant. The present study involved 38 patients with aMCI (SD aMCI, n=18; MD aMCI, n=20) and 36 age- and sex-matched healthy control subjects. White-matter connectional architecture in each participant was depicted with diffusion-weighted MR imaging and represented in terms of a connectivity matrix by using a deterministic tractography method. Graph theory-based analyses were then performed to characterize brain network properties. The global topological organization of white matter networks was significantly disrupted in patients with MD aMCI (P<.01 for all) but not in those with SD aMCI, as compared with control subjects. Connectivity impairment in patients with MD aMCI was found in the temporal, frontal, and parietal cortices (P<.05, corrected). MD aMCI had decreased network efficiency relative to SD aMCI (P=.016), with the most pronounced differences located in the frontal cortex (P<.01 for all). Strong associations between cognitive impairments and disrupted topological features (global, P<.05; regional, P<.002) were identified in patients with aMCI. The present study suggests early onset disruption of whole-brain white matter connectivity in patients with aMCI, especially in those with the MD subtype, supporting the view that MD aMCI is a more advanced form of disease than is SD aMCI. Moreover, cognitive correlations with topological network properties suggest their potential use as markers to assess the risk of Alzheimer disease.

Shu N ，Liang Y ，Li H ，Zhang J ，Li X ，Wang L ，He Y ，Wang Y ，Zhang Z ... -  《-》

Longitudinal changes in fiber tract integrity in healthy aging and mild cognitive impairment: a DTI follow-up study.

Teipel SJ ，Meindl T ，Wagner M ，Stieltjes B ，Reuter S ，Hauenstein KH ，Filippi M ，Ernemann U ，Reiser MF ，Hampel H ... -  《-》