Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and AD.However,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)individuals.This paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and NC.To improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized VGG-16.We performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed models.Our experimental results demonstrate superior performance in classifying the three binary classification tasks:NC vs.AD,NC vs.MCI,and MCI vs.AD.Specifically,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,respectively.Our study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM scans.Our findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

Estimating High-Order Functional Connectivity Networks for Mild Cognitive Impairment Identification Based on Topological Structure

Functional connectivity networks (FCNs) are important in the diagnosis of neurological diseases and the understanding of brain tissue patterns. Recently, many methods, such as Pearson’s correlation (PC), Sparse representation (SR), and Sparse low-rank representation have been proposed to estimate FCNs. Despite their popularity, they only capture the low-order connections of the brain regions, failing to encode more complex relationships (i.e. , high-order relationships). Although researchers have proposed high-order methods, like PC + PC and SR + SR, aiming to build FCNs that can reflect more real state of the brain. However, such methods only consider the relationships between brain regions during the FCN construction process, neglecting the potential shared topological structure information between FCNs of different subjects. In addition, the low-order relationships are always neglected during the construction of high-order FCNs. To address these issues, in this paper we proposed a novel method, namely Ho-FCNTops, towards estimating high-order FCNs based on brain topological structure. Specifically, inspired by the Group-constrained sparse representation (GSR), we first introduced a prior assumption that all subjects share the same topological structure in the construction of the low-order FCNs. Subsequently, we employed the Correlation-reserved embedding (COPE) to eliminate noise and redundancy from the low-order FCNs. Meanwhile, we retained the original low-order relationships during the embedding process to obtain new node representations. Finally, we utilized the SR method on the obtained new node representations to construct the Ho-FCNTops required for disease identification. To validate the effectiveness of the proposed method, experiments were conducted on 137 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database to identify Mild Cognitive Impairment (MCI) patients from the normal controls. The experimental results demonstrate superior performance compared to baseline methods.

Brain Functional Networks with Dynamic Hypergraph Manifold Regularization for Classification of End-Stage Renal Disease Associated with Mild Cognitive Impairment

The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.

Individual identification using multi-metric of DTI in Alzheimer's disease and mild cognitive impairment

Accurate identification of Alzheimer＇s disease （AD） and mild cognitive impairment （MCI） is crucial so as to improve diagnosis techniques and to better understand the neurodegenerative process. In this work, we aim to apply the machine learning method to individual identification and identify the discriminate features associated with AD and MCI. Diffusion tensor imaging scans of 48 patients with AD, 39 patients with late MCI, 75 patients with early MCI, and 51 age-matched healthy controls （HCs） are acquired from the Alzheimer＇s Disease Neuroimaging Initiative database. In addition to the common fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity metrics, there are two novel metrics, named local diffusion homogeneity that used Spearman＇s rank correlation coefficient and Kendall＇s coefficient concordance, which are taken as classification metrics. The recursive feature elimination method for support vector machine （SVM） and logistic regression （LR） combined with leave-one-out cross validation are applied to determine the optimal feature dimensions. Then the SVM and LR methods perform the classification process and compare the classification performance. The results show that not only can the multi-type combined metrics obtain higher accuracy than the single metric, but also the SVM classifier with multi-type combined metrics has better classification performance than the LR classifier. Statistically, the average accuracy of the combined metric is more than 92% for all between-group comparisons of SVM classifier. In addition to the high recognition rate, significant differences are found in the statistical analysis of cognitive scores between groups. We further execute the permutation test, receiver operating characteristic curves, and area under the curve to validate the robustness of the classifiers, and indicate that the SVM classifier is more stable and efficient than the LR classifier. Finally, the uncinated fasciculus, cingulum, corpus callosum, corona radiate, external capsule, and internal capsule have been regarded as the most important white matter tracts to identify AD, MCI, and HC. Our findings reveal a guidance role for machine-learning based image analysis on clinical diagnosis.

Brain imaging of mild cognitive impairment and Alzheimer's disease

The rapidly increasing prevalence of cognitive impairment and Alzheimer＇s disease has the potential to create a major worldwide healthcare crisis. Structural MRI studies in patients with Alzheimer＇s disease and mild cognitive impairment are currently attracting considerable interest. It is extremely important to study early structural and metabolic changes, such as those in the hippocampus, entorhinal cortex, and gray matter structures in the medial temporal lobe, to allow the early detection of mild cognitive impairment and AIzheimer＇s disease. The microstructural integrity of white matter can be studied with diffusion tensor imaging. Increased mean diffusivity and decreased fractional anisotropy are found in subjects with white matter damage. Functional imaging studies with positron emission tomography tracer compounds enable detection of amyloid plaques in the living brain in patients with Alzheimer＇s disease. In this review, we will focus on key findings from brain imaging studies in mild cognitive impairment and Alzheimer＇s disease, including structural brain changes studied with MRI and white matter changes seen with diffusion tensor imaging, and other specific imaging methodologies will also be discussed.

Proteomics of serum exosomes identified fibulin-1 as a novel biomarker for mild cognitive impairment

Mild cognitive impairment(MCI)is a prodrome of Alzheimer’s disease pathology.Cognitive impairment patients often have a delayed diagnosis because there are no early symptoms or conventional diagnostic methods.Exosomes play a vital role in cell-to-cell communications and can act as promising biomarkers in diagnosing diseases.This study was designed to identify serum exosomal candidate proteins that may play roles in diagnosing MCI.Mass spectrometry coupled with tandem mass tag approach-based non-targeted proteomics was used to show the differentially expressed proteins in exosomes between MCI patients and healthy controls,and these differential proteins were validated using immunoblot and enzyme-linked immunosorbent assays.Correlation of cognitive performance with the serum exosomal protein level was determined.Nanoparticle tracking analysis suggested that there was a higher serum exosome concentration and smaller exosome diameter in individuals with MCI compared with healthy controls.We identified 69 exosomal proteins that were differentially expressed between MCI patients and healthy controls using mass spectrometry analysis.Thirty-nine exosomal proteins were upregulated in MCI patients compared with those in control patients.Exosomal fibulin-1,with an area under the curve value of 0.81,may be a biomarker for an MCI diagnosis.The exosomal protein signature from MCI patients reflected the cell adhesion molecule category.In particular,higher exosomal fibulin-1 levels correlated with lower cognitive performance.Thus,this study revealed that exosomal fibulin-1 is a promising biomarker for diagnosing MCI.

Differentiating between Alzheimer’s disease, amnestic mild cognitive impairment, and normal aging via diffusion kurtosis imaging

Diffusion kurtosis imaging can be used to assess pathophysiological changes in tissue structure and to diagnose central nervous system diseases. However, its sensitivity in assessing hippocampal differences between patients with Alzheimer’s disease and those with amnestic mild cognitive impairment has not been characterized. Here, we examined 20 individuals with Alzheimer’s disease (11 men and 9 women, mean 73.2 ± 4.49 years), 20 with amnestic mild cognitive impairment (10 men and 10 women, mean 71.55 ± 4.77 years), and 20 normal controls (11 men and 9 women, mean 70.45 ± 5.04 years). We conducted diffusion kurtosis imaging, using a 3.0 T magnetic resonance scanner, to compare hippocampal differences among the three groups. The results demonstrated that the right hippocampal volume and bilateral mean kurtosis were remarkably smaller in individuals with Alzheimer’s disease compared with those with amnestic mild cognitive impairment and normal controls. Further, the mean kurtosis was lower in the amnestic mild cognitive impairment group compared with the normal control group. The mean diffusion in the left hippocampus was lower in the Alzheimer’s disease group than in the amnestic mild cognitive impairment and normal control groups, while the mean diffusion in the right hippocampus was lower in the Alzheimer’s disease group than in the normal control group. Fractional anisotropy was similar among the three groups. These results verify that bilateral mean kurtosis and mean diffusion are sensitive to the diagnosis of Alzheimer’s disease and amnestic mild cognitive impairment. This study was approved by the Ethics Review Board of Affiliated Sixth People’s Hospital of Shanghai Jiao Tong University, China on May 4, 2010 (approval No. 2010(C)-6).

Association of chronic obstructive pulmonary disease with mild cognitive impairment and dementia risk:A systematic review and meta-analysis

BACKGROUND Chronic obstructive pulmonary disease(COPD)is a common public health issue that has been linked to cognitive dysfunction.AIM To investigate the relationship between COPD and a risk of mild cognitive impairment(MCI)and dementia.METHODS A comprehensive literature search of the PubMed,Embase,Google Scholar,and Cochrane Library electronic databases was conducted.Pooled odds ratios(OR)and mean differences(MD)with 95%confidence intervals(CIs)were calculated using a random or fixed effects model.Studies that met the inclusion criteria were assessed for quality using the Newcastle Ottawa Scale.RESULTS Twenty-seven studies met all the inclusion criteria.Meta-analysis yielded a strong association between COPD and increased risk of MCI incidence(OR=2.11,95%CI:1.32-3.38).It also revealed a borderline trend for an increased dementia risk in COPD patients(OR=1.16,95%CI:0.98-1.37).Pooled hazard ratios(HR)using adjusted confounders also showed a higher incidence of MCI(HR=1.22,95%CI:-1.18 to-1.27)and dementia(HR=1.32,95%CI:-1.22 to-1.43)in COPD patients.A significant lower mini-mental state examination score in COPD patients was noted(MD=-1.68,95%CI:-2.66 to-0.71).CONCLUSION Our findings revealed an elevated risk for the occurrence of MCI and dementia in COPD patients.Proper clinical management and attention are required to prevent and control MCI and dementia incidence in COPD patients.

Usefulness of the Japanese version of Rapid Dementia Screening Test for mild cognitive impairment in older patients with cardiovascular disease:a cross-sectional study

BACKGROUND Cognitive decline is common among older patients with cardiovascular disease(CVD) and can decrease their self-management abilities. However, the instruments for identifying mild cognitive impairment(MCI) are not always feasible in clinical practice. Therefore, this study evaluated whether MCI could be detected using the Japanese version of the Rapid Dementia Screening Test(RDST-J), which is a simple screening tool for identifying cognitive decline.METHODS This retrospective single-center study included patients who were ≥ 65 years old and hospitalized because of CVD.Patients with a pre-hospitalization diagnosis of dementia were excluded. Each patient's cognitive function had been measured at discharge using the RDST-J and the Japanese version of the Montreal Cognitive Assessment(Mo CA-J), which is a standard tool for MCI screening. The correlation between the two scores was evaluated using Spearman's rank correlation coefficient. Receiver operating characteristic(ROC) analysis was also to evaluate whether the RDST-J could identify MCI, which was defined as a Mo CA-J score of ≤ 25 points.RESULTS The study included 78 patients(mean age: 77.2 ± 8.9 years). The RDST-J and Mo CA-J scores were strongly correlated(r = 0.835, P < 0.001). The ROC analysis revealed that an RDST-J score of ≤ 9 points provided 75.4% sensitivity and 95.2% specificity for identifying MCI, with an area under the curve of 0.899(95% CI: 0.835-0.964). The same cut-off value was identified when excluding patients with a high probability of dementia(RDST-J score of ≤ 4 points).CONCLUSIONS The RDST-J may be a simple and effective tool for identifying MCI in older patients with CVD.

IL-1β, TNF-α and Sambucus nigra Reactive Serum Proteins as Biomarkers of Mild Cognitive Impairment and Alzheimer Disease Progression

Amyloid-β (Aβ) can induce a chronic inflammatory immune response that is associated, amongst many others, to abnormal glycosylation, inducible nitric oxide synthase (iNOS) and nitric oxide (NO). The relation between development of Mild Cognitive Impairment (MCI) and Alzheimer’s disease progression and these serum markers has not been evaluated. Serum levels of iNOs, NO, TNF-α, IL-1β, IL-6, IL-8, IL-10, and IL-12 are determined with commercially available kits. Sialylation of albumin-free serum patterns is determined by Western blot analysis with Sambucus nigra (specific for sialic acid attached to terminal galactose in α2,6 linkage) lectin. Apolipoprotein E (ApoE) haplotype is determined by Western blot using specific anti-ApoE 2, 3 or 4 antibodies. A mini-mental state examination (MMSE) test is also performed in the 10 MCI patients, 19 Alzheimer’s disease (AD) patients and 46 healthy age-matched controls evaluated. The results show an increase of iNOS in MCI and AD but significantly higher NO concentrations are only found in MCI patients. TNF-α and IL-1β concentrations are the only significantly increased cytokines in MCI patients;no differences between control and MCI or AD patients are found in regard to the other cytokines. An abnormal MMSE test result only correlates with a decrease in serum NO concentration in MCI patients. The terminal sialic acid linkage pattern of serum proteins also shows highly significant differences between MCI and AD patient. ApoE3/4 or 4/4 haplotypes are characteristic of MCI and AD patients. Our results imply that increased serum TNF-α, IL-1β, iNOS, NO and alterations of serum proteins glycosylation patterns in adult individuals with an abnormal MMSE test may serve as an early biomarker of MCI and AD development.

Cognitive and Functional Profiles in Mild-to-Moderate Alzheimer’s Disease and Mild Cognitive Impairment Compared to Healthy Elderly

Background: Amnestic mild cognitive impairment (aMCI) and mild-to-moderate Alzheimer’s disease (AD) are clinically distinct but impact cognitive and functional ability similarly. Comprehensive assessment of cognitive and functional deficits may prove useful in informing differential diagnosis in early stages of dementia and in informing endpoint selection in therapeutic AD trials. Objective: The objective of this study was to characterize patterns of cognitive and functional impairment in aMCI and mild-to-moderate AD subjects compared to cognitively intact healthy elderly (HE). Methods: Thirty-one healthy elderly, 20 aMCI and 19 AD participants were administered a cognitive test battery that included the ADAS-Cog and functional assessments. Z-scores were calculated for all endpoints based on the HE reference group. Results: Cognitive deficits were observed in AD and aMCI participants relative to the referent group. On average, aMCI participants performed 1 - 2 standard deviations below HE on cognitive tests, and AD participants performed 2 - 3 standard deviations below HE. Domain-specific functional deficits among AD participants (z- score -0.4 to -6.4) were consistently greater than those of aMCI participants (z-score 0 to -1.7). Conclusion: This study provides further support for comprehensive assessment and monitoring of cognitive and functional domain scores in the diagnosis and treatment of aMCI and mild AD. Domain-specific cognitive scores may be more useful than composite scores in characterizing impairment and decline. Measuring domains such as attention, processing speed and executive function may increase the sensitivity of detecting disease progression and therapeutic effects, particularly in mild-moderate AD where memory decline may be too slow to detect drug effects during a typical clinical trial.

Evaluation of Montreal cognitive assessment for the differential diagnosis of mild cognitive impairment and Alzheimer’s disease in elderly patients with more than 5 years of schooling: Data from a Brazilian sample

Background: Diagnostic investigation of dementia is based on a series of tests which lie the neuropsychological evaluations. The Montreal Cognitive Assessment (MoCA) was developed as an instrument to recognize Mild Cognitive Impairment (MCI) and initial cases of Alzheimer’s disease. The present study aims to evaluate the predictive value of Brazilian MoCA test version in a sample of elderly above 5 years of education. Methods: Cross-sectional study with 136 elderly, above 60 years old at least 5 years of education. Diagnostic criteria is based on clinical and neuropsychological data classified Alzheimer’s disease n = 52, MCI n = 45 e normal controls n = 39. MoCA test was compared with Cambridge Cognitive Examination, Mini-Mental State Exam, Verbal Fluency, Clock Drawing Test, Geriatric Depression Scale and Pfeffer Functional Activities Questionnaire. Accuracy was evaluated by receiver operating characteristic (ROC) curve analyses. Pearson correlation coefficient was used to compare the MoCA with the other tests. It was also used logistic regression analysis to identify the main risk factors for the diagnostic groups. Results: MoCA was the best test to differentiate Alzheimer’s disease cases from MCI with 86.5% sensitivity and 75.6% specificity. Furthermore, analyzes of correlation test showed that MoCA correlates robust way of already validated with other tests and wide application inBrazil. Conclusions: It can be concluded that MoCA is a good screening tool for investigation of MCI among the elderly in Brazil with over 5 years of schooling. Studies with larger numbers of participants are needed to further validate the test also for elderly people with low education.

Acupuncture enhances brain function in patients with mild cognitive impairment: evidence from a functional-near infrared spectroscopy study

Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects of acupuncture therapy on MCI patients.Eleven healthy individuals and eleven MCI patients were recruited for this study.Oxy-and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy.Before acupuncture treatment,working-memory experiments were conducted for healthy control(HC)and MCI groups(MCI-0),followed by 24 sessions of acupuncture for the MCI group.The acupuncture sessions were initially carried out for 6 weeks(two sessions per week),after which experiments were performed again on the MCI group(MCI-1).This was followed by another set of acupuncture sessions that also lasted for 6 weeks,after which the experiments were repeated on the MCI group(MCI-2).Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed.The highest classification accuracies obtained using binary connectivity maps were 85.7%HC vs.MCI-0,69.5%HC vs.MCI-1,and 61.69%HC vs.MCI-2.The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum(i.e,max(5:28 seconds))values were 60.6%HC vs.MCI-0,56.9%HC vs.MCI-1,and 56.4%HC vs.MCI-2.The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture.This was reflected by a reduction in the classification accuracy after the therapy,indicating that the patients’brain responses improved and became comparable to those of healthy subjects.A similar trend was reflected in the classification using the image feature.These results indicate that acupuncture can be used for the treatment of MCI patients.

Modulatory effects of acupuncture on brain networks in mild cognitive impairment patients

Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in brain activation induced by acupuncture. Thus, the time course of the therapeutic effects of acupuncture remains unclear. In this study, 32 patients with amnestic mild cognitive impairment were randomly divided into two groups, where they received either Tiaoshen Yizhi acupuncture or sham acupoint acupuncture. The needles were either twirled at Tiaoshen Yizhi acupoints, including Sishencong（EX-HN1）, Yintang（EX-HN3）, Neiguan（PC6）, Taixi（KI3）, Fenglong（ST40）, and Taichong（LR3）, or at related sham acupoints at a depth of approximately 15 mm, an angle of ± 60°, and a rate of approximately 120 times per minute. Acupuncture was conducted for 4 consecutive weeks, five times per week, on weekdays. Resting-state functional magnetic resonance imaging indicated that connections between cognition-related regions such as the insula, dorsolateral prefrontal cortex, hippocampus, thalamus, inferior parietal lobule, and anterior cingulate cortex increased after acupuncture at Tiaoshen Yizhi acupoints. The insula, dorsolateral prefrontal cortex, and hippocampus acted as central brain hubs. Patients in the Tiaoshen Yizhi group exhibited improved cognitive performance after acupuncture. In the sham acupoint acupuncture group, connections between brain regions were dispersed, and we found no differences in cognitive function following the treatment. These results indicate that acupuncture at Tiaoshen Yizhi acupoints can regulate brain networks by increasing connectivity between cognition-related regions, thereby improving cognitive function in patients with mild cognitive impairment.

Effect and mechanism of electroacupuncture at"Baihui"and"Shenshu"on improving cognitive impairment in APP/PS1 mice

Objective:To observe the effect of electroacupuncture(EA)at"Baihui"(GV20)and"Shenshu"(BL23)on cognitive impairment in AD model mice,and to explore its mechanism.Methods:A total of 24 model mice were randomly divided into EA,medication and model groups,8 mice in each group.Another 8 C57BL/6J mice were used as the normal control.The rats in the EA group were treated with electrical stimulation at Baihui(GV20)and Shenshu(BL23),and those in the medication group were treated with donepezil hydrochloride,once a day for 21 days.Adopting the Maorris water maze method to detect the behavior of mice and using HE staining to observe the morphological structure of neurons in the hippocampal region of mice.Finally the expression of GSK-3βandβ-catenin protein contents in the hippocampus of mice in each group was detected by Western blot.Results:Compared to the model group,the evasion latency of the electroacupuncture group and the western medicine group were significantly shorter,and the dwell time in the target quadrant and the number of crossing the plateau were increased(P<0.05),and the hippocampal neurons in each treatment group were closely arranged and complete,with a clearer hierarchy.Western blot assay results showed that the expression ofβ-catenin protein was significantly increased and GSK-3βprotein expression was decreased in the hippocampal region of mice in the electroacupuncture and western medicine groups compared with the model group(P<0.05).Conclusion:Ea at"Baihui"(GV20)and"Shenshu"(BL23)can significantly improve the cognitive function of APP/PS1 mice,which may be connected with the activation of Wnt/β-catenin signaling pathway.

Psychophysiological Effects of Sideritis and Bacopa Extract and Three Combinations Thereof—A Quantitative EEG Study in Subjects Suffering from Mild Cognitive Impairment (MCI)

Mild cognitive impairment (MCI) is regarded as a transitional stage during the development of Alzheimer’s disease. Diagnosis of MCI can be obtained by the questionnaire “DemTect” in German speaking countries. Quantitative assessment has been successfully performed using psychometric testing concomitantly with quantitative EEG recording. The present investigation aimed at the possible treatment of MCI with two botanicals, namely extracts from Sideritis scardica (500 mg) or Bacopa monnieri (320 mg) and three combinations thereof using this method in order to find a new treatment. The performance of the d2-test, an arithmetic calculation test (CPT) and a memory-test revealed better performance for the d2-test only in the presence of Sideritis extract or the combinations with Bacopa extract. Quantitative EEG assessment during the different experimental conditions showed massive differences between both extracts. Whereas Sideritis extract and its combination with a low amount of Bacopa extract (160 mg) induced increases of spectral power in fronto-temporal brain areas, Bacopa and the combination of Sideritis with high amounts of Bacopa extract produced attenuation of all waves except for delta in fronto-temporal brain areas. These differences were also documented by quantitative EEG maps in comparison to Placebo. A different action of both extracts was confirmed by discriminant analysis, where Sideritis extract and its combination with low Bacopa grouped together quite at distance to Bacopa and the combination of Sideritis with high Bacopa. A combination of Sideritis extract with a low amount of Bacopa should be tested with daily repetitive dosing for at least 4 weeks as a consequence.

White matter changes in 80 mild cognitive impairment patients using magnetic resonance imaging

BACKGROUND： Many studies have suggested that one possible etiology of mild cognitive impairment is small vessel cerebrovascular disease, which is associated with small subcortical infarcts and white matter abnormalities. These white matter changes have been detected as white matter hyperintensity （WMH） using magnetic resonance imaging. WMH may be associated with frontal lobe dysfunction. OBJECTIVE： To examine white matter changes in mild cognitive impairment patients of different subtypes, and to evaluate the correlation between white matter changes and neuropsychological characteristics, demographic information, vascular risk factors, and mild cognitive impairment subtypes. DESIGN, TIME AND SETTING： The neurophysiological, comparison study was performed at the Department of Neurology Memory Clinic, Ulsan University Hospital, South Korea, between March 2007 and March 2008. PARTICIPANTS： Out of a total of 83 subjects with clinically diagnosed mild cognitive impairment at the out-patient clinic, 3 subjects with severe WMH were excluded. A total of 80 subjects were included in this study. No patients suffered from cognitive impairment induced by neurological diseases, mental disorders, or somatic diseases. In accordance with magnetic resonance imaging results, the patients were assigned to two subtypes： 56 subjects without WMH and 24 subjects with WMH. METHODS： All patients were subjected to a standard neuropsychological battery using the Korean version of the Mini-Mental State Examination, Clinical Dementia Rating, and comprehensive Seoul Neuropsychological Screening Battery. The Clinical Dementia Rating reflected general cognitive function of patients. Results from the Seoul Neuropsychological Screening Battery reflected attention, language function, visuospatial function, verbal memory, nonverbal memory, long-term memory, and frontal/executive function. Magnetic resonance imaging was used to map changes in the brain. MAIN OUTCOME MEASURES： The association between various white matter changes and neuropsychological characteristics, demographic information, vascular risk factors, and mild cognitive impairment subtypes was measured, based primarily on neuropsychological profiles using statistical methods. RESULTS： WMH was significantly associated with neuropsychological characteristics in MCI patients （P 〈 0.05 or P 〈 0.01）, in particular with frontal/executive dysfunction. WMH was significantly correlated with age （P = 0.022） and vascular risk factors （P = 0.006）, independent of gender and MCI subtypes. CONCLUSION： WMH was significantly associated with frontal/executive dysfunction in mild cognitive impairment.

Neurophysiological Biomarker of Mild Cognitive Impairment

Mild cognitive impairment is sometimes regarded as related to aging. However, statistically every second case turns into full dementia, which still is resistant to any treatment. It is therefore desir-able to recognize deviations from normality as early as possible. This might be feasible by using quantitative EEG analysis in the presence of mental work. The present retrospective data analysis revealed a new quantitative biomarker indicating the degree of impairment. Current source density was calculated from 16 channel EEG using CATEEM?? software. Four different conditions were analyzed: relaxed state, performing a d2-concentration test, a calculation performance test and a memory test for 5 min each. Subjects older than 40 years were divided into two groups according to their DemTect score: 13 - 18 (HC;n = 44) or 8 - 12 (MCI;n = 45). Spectral power was chopped into six frequency ranges (delta, theta, alpha 1, alpha 2, beta 1 and beta 2). Average spectral power was enhanced in the MCI group in comparison to healthy subjects with respect to delta (p = 0.05) during relaxed state when all electrode positions were regarded. With respect to EEG recording during performance of three different psychometric tests it was recognized that mainly spectral changes during performance of the d2-concentration test were related to mild cognitive impairment. With regard to all electrode positions statistically significantly lower spectral power values were reached during the d2-test for delta (p = 0.001), theta (p = 0.0001) and alpha 1 waves (p = 0.08) in impaired subjects in comparison to healthy subjects. Regarding regions of interest increases of delta and theta power were seen in the fronto-temporal brain during performance of the d2-concentration test. These increases disappeared when looking at MCI data. In the centro-parietal region decreases of alpha and beta 1 power emerged, which were even larger in MCI subjects. No MCI-dependent changes were observed in the other two tests. A correlation was found between psychometric performance of the d2-test and the DemTect score (r = 0.51). MCI subjects had statistically significant worse performance in all three mental challenges in comparison to healthy volunteers. It is concluded that MCI can be characterized at an early stage by EEG recording in the relaxed state. High spectral delta and theta power in general and specifically at fronto- temporal electrode positions (especially at T3) was recognized as a biomarker for MCI. A DemTect score of 8-12 was validated as indicative for MCI.

Advances in the application of Ba Duanjin in the treatment of mild cognitive impairment in the elderly

轻度认知障碍作为不可逆的阿尔茨海默病发展过程中可防治成分,对轻度认知障碍的防控具有重要意义。八段锦作为传统的有氧运动,不仅从中医角度,从具体疾病及神经学上都对轻度认知障碍有一定的影响。本文综述了八段锦对轻度认知障碍的临床应用进展,以期为今后八段锦在临床应用提供借鉴。