磁共振扩散成像技术在轻度认知障碍的研究进展

轻度认知障碍(mild cognitive impairment,MCI)被认为是正常老龄化和阿尔茨海默病(Alzheimer'disease,AD)以及其他类型痴呆的中间状态。给予MCI患者积极的干预治疗,有助于改善认知功能并减缓MCI向AD的转变。因此,寻找MCI诊断和进展监测的敏感影像标记物是非常必要的。磁共振扩散成像技术能够通过描述脑组织中水分子的扩散运动来检测微观结构的变化,可以为MCI的病理机制研究和认知障碍严重程度的评估提供重要的信息。近年来,新型磁共振扩散成像技术的不断发展为MCI的研究提供了额外的价值。作者对扩散张量成像(diffusion tensor imaging,DTI)、扩散峰度成像(diffusion kurtosis imaging,DKI)、自由水扩散磁共振成像(free-water diffusion magnetic resonance imaging,FW diffusion MRI)、神经突方向离散度和密度成像(neurite orientation dispersion and density imaging,NODDI)技术在MCI中的研究进行综述。     

多种MRI技术在轻型颅脑损伤中的应用研究进展

随着社会、经济等的迅猛发展,创伤性颅脑损伤(traumatic brain injury,TBI)的发生率逐年升高,其中最常见的轻型颅脑损伤(mild traumatic brain injurym,m TBI)由于其临床表现相对主观,相关辅助检查阳性率不高,生活中往往存在责任争议等而越来越受到各界学者的高度关注。作者通过回顾性分析文献,就多种MRI技术如磁敏感加权成像(susceptibility weighted imaging,SWI)、扩散张量成像(diffusion tensor imaging,DTI)以及静息态功能MRI(resting state function magnetic resonance imaging,rs-f MRI)在m TBI中的应用进展进行综述。     

MRI影像组学在轻度认知障碍中的研究进展

轻度认知障碍(mild cognitive impairment,MCI)是阿尔茨海默病(Alzheimer’s disease,AD)的早期表现。目前尚无有效根治AD的方法。因此,MCI早期诊断和干预对预防或延缓AD的发展具有重要意义。MRI影像组学以非侵入性方式高通量提取和分析MCI患者影像图像特征,提供更多潜在的影像学生物标志物信息,进而指导临床进行精准诊疗,具有广阔的发展前景。本文就影像组学概念、MRI影像组学在MCI诊断、分类及进展预测中的相关研究加以综述。     

基于Adaboost的轻度认知障碍和阿尔茨海默病分类

目的 采用Adaboost集成分类方法区分轻度认知障碍(MCI)、阿尔茨海默病(AD)患者与正常对照(NC)的功能与结构磁共振成像数据.方法 对26例MCI患者(MCI组)、26例AD患者(AD组)及30名健康老年人(NC组)的MRI图像进行分析,选择双侧海马体积及3组间存在显著差异脑区的低频振幅值(ALFF)作为分类特征,采用Adaboost集成分类器对3组被试进行两两分类,利用留一交叉验证估算分类准确率.结果 增加性别、年龄和MMSE特征后,Adaboost集成分类方法对AD与MCI、MCI与NC、AD与NC分类准确率分别达98.08%、80.36%和100%.结论 Adaboost集成分类方法可较好地区分MCI、AD与NC.     

扩散张量成像观察遗忘型轻度认知障碍患者联合纤维束

目的 通过磁共振扩散张量成像(DTI)探讨遗忘型轻度认知障碍(aMCI)患者联合纤维束FA值和ADC值的变化特点,评价DTI对aMCI的诊断及aMCI与AD鉴别诊断的应用价值.方法 对20例aMCI患者(aMCI组)、20例AD患者(AD组)及20名正常对照者(对照组)行DTI扫描,以额枕下束、胼胝体膝部及压部、上纵束Ⅱ、扣带束作为感兴趣区(ROI)测FA值和ADC值.结果 aMCI组与NC组比较额枕下束和扣带束FA值差异有统计学意义(P<0.05);aMCI组与AD组比较扣带束FA值差异有统计学意义(P<0.05).结论 aMCI患者额枕下束、扣带束FA值的异常改变,提示DTI检查可作为aMCI的一个诊断指标.aMCI患者与AD患者扣带束FA值有差异,有助于aMCI与AD的鉴别诊断.     

结构网络拓扑属性改变对早期帕金森病伴轻度认知障碍的预测价值

目的利用弥散张量成像(diffusion tensor imaging, DTI)探讨脑白质网络拓扑属性改变对早期帕金森病(Parkinson′s disease,PD)患者发生轻度认知障碍(mild cognitive impairment,MCI)的潜在预测价值。材料与方法 从Parkinson′s Progression Markers Initiative (PPMI)数据库中纳入83例在基线时认知正常的PD患者,且均行4年的随访;4年后,有26例转化为PD-MCI,其余57例仍保持正常认知(PD patients with normal cognition,PD-NC)。采用图论分析研究PD-MCI患者结构网络全局和局部拓扑属性的改变;采用受试者工作特征曲线和向前逐步逻辑回归分析评估网络拓扑属性和认知量表对PD-MCI的预测价值。结果 PD-MCI患者在第4年随访时网络属性较PD-NC患者发生广泛改变。PD-MCI患者4年随访后的全局效率、局部效率较基线时显著降低,同时伴有特征路径长度的增加(P<0.05);且在前额叶、颞叶、枕叶、顶叶及纹状体-边缘系统多个节点的中心性...     

中医治疗轻度认知障碍的静息态功能磁共振成像研究进展

中医治疗认知障碍已经取得了一定成果,但其疗效机制仍不明确。功能磁共振成像(functional magnetic resonance imaging,fMRI)是目前脑影像领域较常用的一种非损伤性活体脑功能检测技术,其中静息态功能磁共振成像(resting-state fMRI,rs-fMRI)是目前研究认知类疾病的首选方法。基于该技术发现与轻度认知障碍(mild cognitive impairment,MCI)相关的主要脑区为额叶、海马和扣带回。研究表明,中医治疗可以调控MCI患者的脑功能网络及神经环路。rs-fMRI技术可客观地评价治疗前后受试者脑区功能连通性和局部脑区活动指标,了解中医治疗脑效应机制,为探讨神经系统疾病的中医疗效提供新思路和新方法。     

阿尔茨海默病患者扣带束和后扣带回的改变

目的:探讨轻中度阿尔茨海默病(AD)患者扣带束及后扣带回的各项异性(FA)值及功能连接改变。方法:采用3.0T磁共振扫描仪对19例AD患者(AD组)及14例正常对照(NC组)进行DTI及rsf MRI扫描。采用GE 4.4工作站测量,分别测量扣带束的FA值,对各部位的FA值进行独立样本t检验分析,比较其组间差异。采用DPARSF_v2.和rest_vl.4软件对rsf MRI数据进行分析,计算后扣带回与全脑的功能连接,随后对2组的功能连接进行独立样本t检验分析,比较其组间差异。结果:AD组双侧扣带束扣带回部和海马部的FA值均明显低于NC组(P<0.05)。与NC组相比,AD组后扣带回与左侧楔前叶/扣带回、左侧额上/中回、左侧额上/中内侧回、右侧楔前叶/扣带回、右侧颞下/中回、右侧角回的功能连接明显减弱,全脑没有出现与后扣带回连接增强的脑区。结论:扣带束FA值的变化和后扣带回功能连接的变化可作为AD早期诊断的敏感指标。     

遗忘型轻度认知障碍的磁共振成像研究进展

轻度认知障碍(mild cognitive impairment,MCI)是正常衰老过程与阿尔茨海默病(Alzheimer disease,AD)之间的过渡阶段,分为遗忘型MCI(amnestic MCI,aMCI)和非遗忘型MCI,前者以记忆损伤为主,被认为是AD的前期.aMCI临床亚型包括单域(single domain,SD)和多域(multi domain,MD),不同的亚型进展为AD的可能性不同.目前,AD的病因和发病机制尚不清楚,没有确切的治愈方法.因此,对aMCI进行早期诊断、干预和治疗,延缓其向AD的进展具有重要意义.近年来,磁共振成像(magnetic resonance imaging,MRI)结合不同的分析方法被应用于aMCI机制的研究,可以客观、间接地反映异常的大脑结构和功能活动,为解释其机制提供一定的线索.作者回顾了aMCI的MRI研究进展.     

Automatic morphometry in Alzheimer's disease and mild cognitive impairment

This paper presents a novel, publicly available repository of anatomically segmented brain images of healthy subjects as well as patients with mild cognitive impairment and Alzheimer's disease. The underlying magnetic resonance images have been obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. T1-weighted screening and baseline images (1.5T and 3T) have been processed with the multi-atlas based MAPER procedure, resulting in labels for 83 regions covering the whole brain in 816 subjects. Selected segmentations were subjected to visual assessment. The segmentations are self-consistent, as evidenced by strong agreement between segmentations of paired images acquired at different field strengths (Jaccard coefficient: 0.802±0.0146). Morphometric comparisons between diagnostic groups (normal; stable mild cognitive impairment; mild cognitive impairment with progression to Alzheimer's disease; Alzheimer's disease) showed highly significant group differences for individual regions, the majority of which were located in the temporal lobe. Additionally, significant effects were seen in the parietal lobe. Increased left/right asymmetry was found in posterior cortical regions. An automatically derived white-matter hypointensities index was found to be a suitable means of quantifying white-matter disease. This repository of segmentations is a potentially valuable resource to researchers working with ADNI data.     

Multimodal classification of Alzheimer's disease and mild cognitive impairment

Effective and accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment (MCI)), has attracted more and more attention recently. So far, multiple biomarkers have been shown to be sensitive to the diagnosis of AD and MCI, i.e., structural MR imaging (MRI) for brain atrophy measurement, functional imaging (e.g., FDG-PET) for hypometabolism quantification, and cerebrospinal fluid (CSF) for quantification of specific proteins. However, most existing research focuses on only a single modality of biomarkers for diagnosis of AD and MCI, although recent studies have shown that different biomarkers may provide complementary information for the diagnosis of AD and MCI. In this paper, we propose to combine three modalities of biomarkers, i.e., MRI, FDG-PET, and CSF biomarkers, to discriminate between AD (or MCI) and healthy controls, using a kernel combination method. Specifically, ADNI baseline MRI, FDG-PET, and CSF data from 51AD patients, 99 MCI patients (including 43 MCI converters who had converted to AD within 18 months and 56 MCI non-converters who had not converted to AD within 18 months), and 52 healthy controls are used for development and validation of our proposed multimodal classification method. In particular, for each MR or FDG-PET image, 93 volumetric features are extracted from the 93 regions of interest (ROIs), automatically labeled by an atlas warping algorithm. For CSF biomarkers, their original values are directly used as features. Then, a linear support vector machine (SVM) is adopted to evaluate the classification accuracy, using a 10-fold cross-validation. As a result, for classifying AD from healthy controls, we achieve a classification accuracy of 93.2% (with a sensitivity of 93% and a specificity of 93.3%) when combining all three modalities of biomarkers, and only 86.5% when using even the best individual modality of biomarkers. Similarly, for classifying MCI from healthy controls, we achieve a classification accuracy of 76.4% (with a sensitivity of 81.8% and a specificity of 66%) for our combined method, and only 72% even using the best individual modality of biomarkers. Further analysis on MCI sensitivity of our combined method indicates that 91.5% of MCI converters and 73.4% of MCI non-converters are correctly classified. Moreover, we also evaluate the classification performance when employing a feature selection method to select the most discriminative MR and FDG-PET features. Again, our combined method shows considerably better performance, compared to the case of using an individual modality of biomarkers.     

Atlas-based hippocampus segmentation in Alzheimer's disease and mild cognitive impairment

This study assesses the performance of public-domain automated methodologies for MRI-based segmentation of the hippocampus in elderly subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Structural MR images of 54 age- and gender-matched healthy elderly individuals, subjects with probable AD, and subjects with MCI were collected at the University of Pittsburgh Alzheimer's Disease Research Center. Hippocampi in subject images were automatically segmented by using AIR, SPM, FLIRT, and the fully deformable method of Chen to align the images to the Harvard atlas, MNI atlas, and randomly selected, manually labeled subject images ("cohort atlases"). Mixed-effects statistical models analyzed the effects of side of the brain, disease state, registration method, choice of atlas, and manual tracing protocol on the spatial overlap between automated segmentations and expert manual segmentations. Registration methods that produced higher degrees of geometric deformation produced automated segmentations with higher agreement with manual segmentations. Side of the brain, presence of AD, choice of reference image, and manual tracing protocol were also significant factors contributing to automated segmentation performance. Fully automated techniques can be competitive with human raters on this difficult segmentation task, but a rigorous statistical analysis shows that a variety of methodological factors must be carefully considered to insure that automated methods perform well in practice. The use of fully deformable registration methods, cohort atlases, and user-defined manual tracings are recommended for highest performance in fully automated hippocampus segmentation.     

Combining MRI and CSF measures for classification of Alzheimer's disease and prediction of mild cognitive impairment conversion

The suggested revision of the NINCDS-ADRDA criterion for the diagnosis of Alzheimer's disease (AD) includes at least one abnormal biomarker among magnetic resonance imaging (MRI), positron emission tomography (PET) and cerebrospinal fluid (CSF). We aimed to investigate if the combination of baseline MRI and CSF could enhance the classification of AD compared to using either alone and predict mild cognitive impairment (MCI) conversion at multiple future time points. 369 subjects from the Alzheimer's disease Neuroimaging Initiative (ADNI) were included in the study (AD=96, MCI=162 and CTL=111). Freesurfer was used to generate regional subcortical volumes and cortical thickness measures. A total of 60 variables were used for orthogonal partial least squares to latent structures (OPLS) multivariate analysis (57 MRI measures and 3 CSF measures: Aβ(42), t-tau and p-tau). Combining MRI and CSF gave the best results for distinguishing AD vs. CTL. We found an accuracy of 91.8% for the combined model at baseline compared to 81.6% for CSF measures and 87.0% for MRI measures alone. The combined model also gave the best accuracy when distinguishing between MCI vs. CTL (77.6%) at baseline. MCI subjects who converted to AD by 12 and 18month follow-up were accurately predicted at baseline using an AD vs. CTL model (82.9% and 86.4% respectively), with lower prediction accuracies for those MCI subjects converting by 24 and 36month follow up (75.4% and 68.0% respectively). The overall prediction accuracies for converters and non-converters ranged from 58.6% to 66.4% at different time points. Combining MRI and CSF measures in a multivariate model at baseline gave better accuracy for discriminating between AD and CTL, between MCI and CTL and for predicting future conversion from MCI to AD, than using either MRI or CSF separately.     

灌注成像在阿尔茨海默病与轻度认知障碍中的应用

随着世界老龄人口比重逐渐加大,痴呆的发病率不断增加。近年来,作为痴呆的最常见类型阿尔茨海默病及其超早期阶段——轻度认知功能障碍成为研究热点,早期、及时、准确诊断对延缓病情进展、提高生活质量、改善预后有十分重要的意义。笔者主要就目前各种影像学灌注成像技术,如正电子发射体层成像(PET)、单光子发射计算机断层成像(SPECT)、氙气增强CT(Xe-CT)、CT灌注成像(CTPI)、动态磁敏感对比增强灌注加权成像(DSC-PWI)、动脉自旋标记(ASL-PI)、体素内不相干运动(IVIM)等在阿尔茨海默病及轻度认知功能障碍研究中的应用进展进行综述。     

阿尔茨海默病及轻度认知损伤患者PET与MRI分析

目的 探讨PET葡萄糖代谢成像与MR结构成像诊断阿尔茨海默病（AD）与轻度认知损伤（MCI）的临床价值。方法 收集AD患者18例（AD组）、MCI患者6例（MCI组）,其中AD患者包括11例中重度AD） 中重度AD组）及7例轻度AD） 轻度AD组）,另招募10名健康志愿者（对照组）,同期进行PET与MR结构成像,通过视觉评价与定量分析法观察脑内放射性分布及海马萎缩情况。结果 所有AD患者（18/18,100%）均可见脑内特定区域葡萄糖代谢减低,其中11例中重度AD患者均同时伴有海马萎缩,7例轻度AD患者中3例可见海马萎缩;MCI患者中,5例（5/6,83.33%）未见海马萎缩,但其中2例可见葡萄糖代谢减低。对照组（10/10,100%）均未见海马萎缩,其中2例可见轻度脑萎缩,FDG分布对称性轻度减低。结论 PET及MRI均可用于诊断AD与MCI,但各有侧重,二者联合应用有利于进一步提高对AD的诊断能力。     

PET/MRI海马纹理特征诊断阿尔茨海默病与遗忘型轻度认知障碍

目的 观察PET/MRI海马纹理特征诊断阿尔茨海默病(AD)及遗忘型轻度认知障碍(aMCI)的价值。方法 回顾性分析55例AD(AD组)、60例aMCI患者(aMCI组)及55名健康受试者(HC组),按7 ∶ 3比例随机分为训练集与测试集,行一体化PET/MRI,获取3D T1WI和¹⁸F-FDG PET图;对训练集提取双侧海马ROI纹理特征,分别以逻辑回归(LR)、支持向量机(SVM)及随机森林(RF)算法建立3D T1WI模型、¹⁸F-FDG PET模型及联合模型,以受试者工作特征曲线评估各模型诊断AD与aMCI的效能。结果 小波特征在可用于诊断AD与aMCI的最优海马纹理特征中占比最高。基于各算法的联合模型诊断测试集AD的曲线下面积(AUC)均最高(0.996、0.993、0.991),¹⁸F-FDG PET模型次之(0.941、0.941、0.967)而3D T1WI模型最低(0.801、0.801、0.750)。基于LR、RF算法的联合模型诊断测试集aMCI的AUC最高(0.967、0.992),¹⁸F-FDG PET模型次之(0.951、0.971),3D T1WI模型最低(0.833、0.824)。基于SVM算法的联合模型与¹⁸F-FDG PET模型诊断测试集aMCI的AUC相同(0.951)并均高于3D T1WI模型(0.833)。结论 PET/MRI海马纹理分析有助于诊断AD及aMCI;多模态联合诊断优于单模态,且具有良好稳定性。     

Global and local gray matter loss in mild cognitive impairment and Alzheimer's disease

PURPOSE: Mild cognitive impairment (MCI) is thought to be the prodromal phase to Alzheimer's disease (AD). We analyzed patterns of gray matter (GM) loss to examine what characterizes MCI and what determines the difference with AD. MATERIALS AND METHODS: Thirty-three subjects with AD, 14 normal elderly controls (NCLR), and 22 amnestic MCI subjects were included and underwent brain MR imaging. Global GM volume was assessed using segmentation and local GM volume was assessed using voxel-based morphometry (VBM); VBM was optimized for template mismatch and statistical mass. RESULTS: AD subjects had significantly (12.3%) lower mean global GM volume when compared to controls (517 +/- 58 vs. 590 +/- 52 ml; P < 0.001). Global GM volume in the MCI group (552 +/- 52) was intermediate between these two: 6.2% lower than AD and 6.5% higher than the controls but not significantly different from either group. VBM showed that subjects with MCI had significant local reductions in gray matter in the medial temporal lobe (MTL), the insula, and thalamus compared to NCLR subjects. By contrast, when compared to subjects with AD, MCI subjects had more GM in the parietal association areas and the anterior and the posterior cingulate. CONCLUSION: GM loss in the MTL characterizes MCI, while GM loss in the parietal and cingulate cortices might be a feature of AD.     

轻度认知功能障碍脑结构与功能MRI研究进展

轻度认知功能障碍（MCI）患者被认为是阿尔茨海默病的高危人群,并且在MCI阶段进行干预治疗,有利于延缓病情进展甚至逆转认知功能破坏,故对于MCI的研究,具有重要的临床意义。MRI技术包含多个序列成像,可从不同角度发现MCI的大脑结构和功能异常,有利于早期诊断、预测病情进展情况和揭示病理机制,促进MCI和阿尔茨海默病的防治。本文主要对于近些年来结构磁共振成像、功能磁共振成像、扩散张量成像、动脉自旋标记和质子磁共振波谱分析在MCI的诊断、分类、预测病情方面的研究现状进行了论述,希望为今后的临床诊疗及科研提供借鉴。     

Using Reiki to decrease memory and behavior problems in mild cognitive impairment and mild Alzheimer's disease

OBJECTIVES: This empirical study explored the efficacy of using Reiki treatment to improve memory and behavior deficiencies in patients with mild cognitive impairment or mild Alzheimer's disease. Reiki is an ancient hands-on healing technique reputedly developed in Tibet 2500 years ago. DESIGN: This study was a quasi-experimental study comparing pre- and post-test scores of the Annotated Mini-Mental State Examination (AMMSE) and Revised Memory and Behavior Problems Checklist (RMBPC) after four weekly treatments of Reiki to a control group. SETTINGS/LOCATION: The participants were treated at a facility provided by the Pleasant Point Health Center on the Passamaquoddy Indian Reservation. SUBJECTS: The sample included 24 participants scoring between 20 and 24 on the AMMSE. Demographic characteristics of the sample included an age range from 60 to 80, with 67% female, 46% American Indian, and the remainder white. INTERVENTIONS: Twelve participants were exposed to 4 weeks of weekly treatments of Reiki from two Reiki Master-level practitioners; 12 participants served as controls and received no treatment. OUTCOME MEASURES: The two groups were compared on pre- and post-treatment scores on the AMMSE and the Revised Memory and Behavior Problems Checklist (RMBPC). RESULTS: Results indicated statistically significant increases in mental functioning (as demonstrated by improved scores of the AMMSE) and memory and behavior problems (as measured by the RMBPC) after Reiki treatment. This research adds to a very sparse database from empirical studies on Reiki results. CONCLUSION: The results indicate that Reiki treatments show promise for improving certain behavior and memory problems in patients with mild cognitive impairment or mild Alzheimer's disease. Caregivers can administer Reiki at little or no cost, resulting in significant societal value by potentially reducing the needs for medication and hospitalization.