Diffusion tensor imaging of the brain in patients with Alzheimer's disease and cerebrovascular lesions

Background:Recent autopsy study showed a high incidence of cerebrovascular lesions in Alzheimer's disease(AD).To assess the impact of cerebrovascular pathology in AD,we used diffusion tensor imaging(DTI) to study AD patients with and without cerebrovascular lesions.Materials and Methods:Conventional and DTI scans were obtained from 10 patients with probable AD,10 AD/V patients(probable AD with cerebrovascular lesions) and ten normal controls.Mean diffusivity(D) and fractional anisotropy(FA) values of some structures involved with AD pathology were measured.Results:D value was higher in AD patients than in controls in hippocampus and the cingulate gyrus.In AD/V patients,increased D value was found in the same structures and also in the thalamus and basal ganglia compared to controls.There was a significant difference of D value between AD and AD/V patients.FA value reduced in the white matter of left inferior temporal gyrus and in the bilateral middle cingulate gyrus in patients with AD/V compared with controls.The MMSE(mini-mental state examination) score significantly correlated with FA value in the right hippocampus(r=0.639,P<0.019),in the right anterior cingulate gyrus(r=0.587,P<0.035) and in left parahippocampal gyrus(r=0.559,P<0.047).Conclusion:Cerebrovascular pathology had stronger impact on the D value than the AD pathology alone did.Elevated D value in thalamic and basal ganglia may contribute to cognitive decline in AD/V patients.Reduced FA values in AD/V patients may indicate that cerebrovascular pathology induced more severe white matter damage than the AD pathology alone did.

White Matter Changes in Alzheimer’s Disease Revealed by Diffusion Tensor Imaging with TBSS

Alzheimer’s disease (AD) is a progressive, neurodegenerative disorder characterized by impairments in multiple cognitive domains and it is hard to diagnose in early stage because it’s not easy to recognize and develop slowly. In this study, we try to evaluate the difference of white matter between AD and health volunteers using diffusion tensor imaging (DTI) and try to provide some evidence for diagnose AD in early stage. Twelve elderly Chinese patients with AD and twelve healthy volunteers were recruited and underwent DTI. The raw diffusion data were dealt with the toolkit of FSL image post-processing. Fractional anisotrogy (FA) data were then carried out by using tract-based spatial statistics (TBSS). The result showed that the FA of cingulum, hippocampus, corticospinal tract, and inferior fronto-occipital fasciculus significantly reduced in AD patients than that of volunteers. This indicated that the integrity of white matter tracts in these regions with AD was disturbed. On the other hand, the FA of other encephalic regions had no discrepancy compared with that of healthy volunteers. FA values were found reduced significantly in AD patients, especially in the posterior of the brain. These findings may provide image methods to diagnose patients with early stage of AD.

Detecting dopaminergic neuronal degeneration using diffusion tensor imaging in a rotenone-induced rat model of Parkinson's disease: fractional anisotropy and mean diffusivity values

Dopamine content in the basal ganglia is strongly associated with the degree of dopaminergic neuron loss in the substantia nigra pars com- pacta. Symptoms of Parkinson＇s disease might not arise until more than 50% of the substantia nigra pars compacta is lost and the dopamine content in the basal ganglia is reduced by more than 80%. Greater diagnostic sensitivity and specificity would allow earlier detection of Parkinson＇s disease. Diffusion tensor imaging is a recently developed magnetic resonance imaging technique that measures mean diffusiv- ity and fractional anisotropy, and responds to changes in brain microstructure. When the microscopic barrier （including cell membranes, microtubules and other structures that interfere with the free diffusion of water） is destroyed and extracellular fluid volume accumulates, the mean diffusivity value increases; when the integrity of the microstructure （such as myelin） is destroyed, fractional anisotropy value decreases. However, there is no consensus as to whether these changes can reflect the early pathological alterations in Parkinson＇s disease. Here, we established a rat model of Parkinson＇s disease by injecting rotenone （or sunflower oil in controls） into the right suhstantia nigra. Diffusion tensor imaging results revealed that in the stages of disease, at 1, 2, 4, and 6 weeks after rotenone injection, fiactional anisotropy value decreased, but mean diffusivity values increased in the right substantia nigra in the experimental group. Fractional anisotropy values were lower at 4 weeks than at 6 weeks in the right substantia nigra of rats from the experimental group. Mean diffusivity values were mark- edly greater at 1 week than at 6 weeks in the right corpus striatum of rats from the experimental group. These findings suggest that mean diffusivity and fractional anisotropy values in the brain of rat models of Parkinson＇s disease 4 weeks after model establishment can reflect early degeneration of dopaminergic neurons. ＇The change in fractional anisotropy values after destruction of myelin integrity is likely to be of greater early diagnostic significance than the change in mean diffusivity values.

Abnormal white matter microstructure in Parkinson's disease revealed by diffusion tensor imaging A non-randomized concurrent control observation

BACKGROUND： Imaging has been used to determine gray matter volume and metabolism in subjects with depressed Parkinson＇s disease （DPD）. OBJECTIVE： To reveal abnormalities in orbitofrontal white matter and the anterior cingulate bundle in depressed and non-depressed Parkinson＇s disease （NDPD） patients using diffusion tensor imaging. DESIGN, TIME AND SETTING： A non-randomized, concurrent, control, neuroimaging study was performed at the Laboratory of Neurodegenerative Diseases and Center of Neuroimage, Xuanwu Hospital of Capital Medical University from July 2008 to January 2009. PARTICIPANTS： A total of 30 Parkinson＇s disease patients, including 14 males and 16 females, were included in the present study. All patients met Brain Bank criteria for idiopathic Parkinson＇s disease formulated by the United Kingdom Parkinson＇s Disease Society. Patients, who underwent previous head surgery, exhibited abnormal density on T2-weighted images, or Mini-Mental State Examination scores 〈 corresponding education level, were excluded from the study. METHODS： All 35 patients underwent MRI scans, including traditional T2-weighted and DTI scans. The patients were assigned to DPD （n = 16） and NDPD （n = 14） groups according to the Diagnostic and Statistical Manual of Mental Disorders-IV （DSM-IV） criteria. The fractional anisotropy values of regions of interest were compared between the NDPD and DPD groups. MAIN OUTCOME MEASURES： Abnormalities in the orbitofrontal white matter and anterior cingulate bundle. RESULTS： Compared with the NDPD group, the DPD group exhibited significantly lower fractional anisotropy values in orbitofrontal white matter and anterior cingulate bundle （P 〈 0.05）. CONCLUSION： Microstructure abnormalities existed in the orbitofrontal and anterior cingulate regions in DPD patients. This is the first report of abnormalities in the orbitofrontal white matter region in DPD patients.

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.

An abnormal resting-state functional brain network indicates progression towards Alzheimer's disease

Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer＇s disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations （nor- mal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer＇s disease） using the Alzheimer＇s Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer＇s disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the rest- ing-state functional network gradually increased, while clustering coefficients gradually decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In addi- tion, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and AIz- heimer＇s disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventually lead to diffuse brain injury and other cognitive impairments.

A novel method for evaluating brain function and microstructural changes in Parkinson's disease

In this study,microstructural brain damage in Parkinson＇s disease patients was examined using diffusion tensor imaging and tract-based spatial statistics.The analyses revealed the presence of neuronal damage in the substantia nigra and putamen in the Parkinson＇s disease patients.Moreover,disease symptoms worsened with increasing damage to the substantia nigra,confirming that the substantia nigra and basal ganglia are the main structures affected in Parkinson＇s disease.We also found that microstructural damage to the putamen,caudate nucleus and frontal lobe positively correlated with depression.Based on the tract-based spatial statistics,various white matter tracts appeared to have microstructural damage,and this correlated with cognitive disorder and depression.Taken together,our results suggest that diffusion tensor imaging and tract-based spatial statistics can be used to effectively study brain function and microstructural changes in patients with Parkinson＇s disease.Our novel findings should contribute to our understanding of the histopathological basis of cognitive dysfunction and depression in Parkinson＇s disease.

Cerebellum and neurodegenerative diseases:Beyond conventional magnetic resonance imaging

The cerebellum plays a key role in movement control and in cognition and cerebellar involvement is described in several neurodegenerative diseases.While conventional magnetic resonance imaging(MRI) is widely used for brain and cerebellar morphologic evaluation,advanced MRI techniques allow the investigation of cerebellar microstructural and functional characteristics.Volumetry,voxel-based morphometry,diffusion MRI based fiber tractography,resting state and task related functional MRI,perfusion,and proton MR spectroscopy are among the most common techniques applied to the study of cerebellum.In the present review,after providing a brief description of each technique's advantages and limitations,we focus on their application to the study of cerebellar injury in major neurodegenerative diseases,such as multiple sclerosis,Parkinson's and Alzheimer's disease and hereditary ataxia.A brief introduction to the pathological substrate of cerebellar involvement is provided for each disease,followed by the review of MRI studies exploring structural and functional cerebellar abnormalities and by a discussion of the clinical relevance of MRI measures of cerebellar damage in terms of both clinical status and cognitive performance.

Differences in brain pathological changes between rotenone and 6-hydroxydopamine Parkinson＇s disease models

Rotenone and 6-hydroxydopamine are two drugs commonly used to generate Parkinson＇s disease animal models.They not only achieve degenerative changes of dopaminergic neurons in the substantia nigra,but also satisfy the requirements for iron deposition.However,few studies have compared the characteristics of these two models by magnetic resonance imaging.In this study,rat models of Parkinson＇s disease were generated by injection of 3 μg rotenone or 10 μg 6-hydroxydopamine into the right substantia nigra.At 1,2,4,and 6 weeks after injection,coronal whole-brain T2-weighted imaging,transverse whole-brain T2-weighted imaging,and coronal diffusion tensor weighted imaging were conducted to measure fractional anisotropy and T2＊ values at the injury site.The fractional anisotropy value on the right side of the substantia nigra was remarkably lower at 6 weeks than at other time points in the rotenone group.In the 6-hydroxydopamine group,the fractional anisotropy value was decreased,but T2＊ values were increased on the right side of the substantia nigra at 1 week.Our findings confirm that the 6-hydroxydopamine-induced model is suitable for studying dopaminergic neurons over short periods,while the rotenone-induced model may be appropriate for studying the pathological and physiological processes of Parkinson＇s disease over long periods.

Why psychosis is frequently associated with Parkinson's disease?

Psychosis is a common non-motor symptom of Parkinson’s disease whose pathogenesis remains poorly understood. Parkinson’s disease in conjunction with psychosis has been shown to induce injury to extracorticospinal tracts as wel as within some cortical areas. In this study, Parkinson’s disease patients with psychosis who did not receive antipsychotic treatment and those without psychosis underwent diffusion tensor imaging. Results revealed that in Parkinson’s disease patients with psychosis, damage to the left frontal lobe, bilateral occipital lobe, left cingulated gyrus, and left hippocampal white-matter fibers were greater than damage to the substantia nigra or the globus pal idus. Damage to white-matter fibers in the right frontal lobe and right cingulate gyrus were also more severe than in the globus pal idus, but not the substantia nigra. Damage to frontal lobe and cingulate gyrus white-matter fibers was more apparent than that to occipital or hippocampal fiber damage. Compared with Parkinson’s disease patients without psychosis, those with psychosis had significantly lower fractional anisotropy ratios of left frontal lobe, bilateral occipital lobe, left cingu-lated gyrus, and left hippocampus to ipsilateral substantia nigra or globus pal idus, indicating more severe damage to white-matter fibers. These results suggest that psychosis associated with Par-kinson’s disease is probably associated with an imbalance in the ratio of white-matter fibers be-tween brain regions associated with psychiatric symptoms （frontal lobe, occipital lobe, cingulate gyrus, and hippocampus） and those associated with the motor symptoms of Parkinson’s disease （the substantia nigra and globus pal idus）. The relatively greater damage to white-matter fibers in psychiatric symptom-related brain regions than in extracorticospinal tracts might explain why psy-chosis often occurs in Parkinson’s disease patients.

Magnetic resonance imaging markers for early diagnosis of Parkinson's disease

Parkinson＇s disease （PD） is a neurodegenerative disorder characterized by selective and progressive degeneration, as well as loss of dopaminergic neurons in the substantia nigra. In PD, approximately 60-70% of nigrostriatal neurons are degenerated and 80% of content of the striatal dopamine is reduced before the diagnosis can be established according to widely accepted clinical diagnostic criteria. This condition describes a stage of disease called ＂prodromal＂, where non-motor symptoms, such as olfactory dysfunction, constipation, rapid eye movement behaviour disorder, depression, precede motor sign of PD. Detection of prodromal phase of PD is becoming an important goal for determining the prognosis and choosing a suitable treatment strategy. In this review, we present some non-invasive instrumental approaches that could be useful to identify patients in the prodromal phase of PD or in an early clinical phase, when the first motor symptoms begin to be apparent. Conventional magnetic resonance imaging （MRI） and advanced MRI techniques, such as magnetic resonance spectroscopy imaging, diffusion-weighted and diffusion tensor imaging and functional MRI, are useful to differentiate early PD with initial motor symptoms from atypical parkinsonian disorders, thus, making easier early diagnosis. Functional MRI and diffusion tensor imaging techniques can show abnormalities in the olfactory system in prodromal PD.

Microstructural white matter lesion in Alzheimer's disease: a diffusion tensor imaging study using voxel-based analysis

Objective To study the microscopic changes of white matter and the relationship between white matter changes and cognitive impairment in Alzheimer’s disease(AD)using voxel-based analysis of DTI.Methods Thirty-seven patients with probable AD,and 32 normal controls(NC)were all examined by MMSE scores,and un-

Divergent topological networks in Alzheimer’s disease:a diffusion kurtosis imaging analysis

Background:Brain consists of plenty of complicated cytoarchitecture.Gaussian-model based diffusion tensor imaging(DTI)is far from satisfactory interpretation of the structural complexity.Diffusion kurtosis imaging(DKI)is a tool to determine brain non-Gaussian diffusion properties.We investigated the network properties of DKI parameters in the whole brain using graph theory and further detected the alterations of the DKI networks in Alzheimer’s disease(AD).Methods:Magnetic resonance DKI scanning was performed on 21 AD patients and 19 controls.Brain networks were constructed by the correlation matrices of 90 regions and analyzed through graph theoretical approaches.Results:We found small world characteristics of DKI networks not only in the normal subjects but also in the AD patients;Grey matter networks of AD patients tended to be a less optimized network.Moreover,the divergent small world network features were shown in the AD white matter networks,which demonstrated increased shortest paths and decreased global efficiency with fiber tractography but decreased shortest paths and increased global efficiency with other DKI metrics.In addition,AD patients showed reduced nodal centrality predominantly in the default mode network areas.Finally,the DKI networks were more closely associated with cognitive impairment than the DTI networks.Conclusions:Our results suggest that DKImight be superior to DTI and could serve as a novel approach to understand the pathogenic mechanisms in neurodegenerative diseases.

轻度Alzheimer病人的弥散张量成像研究

目的 研究轻度Alzheimer患者弥散张量成像的异常 ,并与正常老年人进行比较。方法 对 16例正常志愿者和14例轻度Alzheimer患者进行了弥散张量成像扫描 ,测量双侧杏仁核、海马头和丘脑的ADC和FA值 ,并对结果进行统计学比较。结果 对照组和AD组的双侧海马头部的ADC值均存在显著性差异 (P <0 .0 1) ,而FA值无显著性差异 ;对照组和AD组的双侧杏仁核的ADC值之间无显著性差异 ,右侧杏仁核的FA值在对照组和AD组之间存在显著性差异 ;双侧丘脑的ADC和FA值都没有显著性差异。结论 弥散张量成像能发现轻度Alzheimer患者双侧海马头部的扩散系数的异常 ,从而探测到组织结构间隙的变化。

Alzheimer病患者扣带回后部损害磁共振扩散张量成像的研究

目的探讨Alzheimer病(AD)患者扣带回后部磁共振扩散张量成像(DTI)的特点及其与认知功能改变的相关性。方法对16例AD患者和12名健康老人(正常对照组)行DTI、T1Flair及T2Flari检查,测量扣带回后部各向异性分数值(FA)、平均弥散度(MD)及其λ1、λ2及λ33个特征值,分析上述诸项数值与简易精神状态检查量表(MMSE)评分之间的相关性。结果与正常对照组相比,AD组患者扣带回后部的FA值显著降低(P<0.05),而MD、λ1、λ2及λ3值明显升高(均P<0.05);FA值与MMSE评分不相关(r=-0.054,P>0.05),而MD值与MMSE评分呈显著负相关(r=-0.664,P<0.01);λ1、λ2及λ3值均与MMSE评分呈负相关(r=-0.643,r=-0.69,r=-0.654,均P<0.01)。结论AD患者表现为扣带回后部各向异性损害,且损害程度与临床认知功能评分呈负相关;这种损害反映了AD病理机制中皮质-皮质及皮质-皮质下联系的丢失;DTI可以用来监测AD疾病的进展及评价药物的临床疗效。

Alzheimer病患者基于体素的脑结构特征研究

目的用基于体素的形态学分析(voxel-based morphometry,VBM)方法,探讨Alzheimer病(AD)患者大脑灰质萎缩区域及分布特征。方法运用优化的VBM(OVBM)方法,在场强最高的3.0TMR扫描仪上采集数据,对12例Alzheimer病患者及11例正常对照的大脑灰质进行比较,对两组数据的灰质密度和灰质体积进行基于体素的两样本t检验,对比结果采用国际通用的统计参数图(SPM2)表示出来,分析AD患者大脑灰质密度减少区域、分布特征及其临床意义。结果和正常老年人对照组相比,AD患者的脑灰质密度较对照组降低,这些区域多为双侧对称分布,包括双侧海马、杏仁核、颞下回、中央前回、尾状核、扣带回等区域,另外,一些区域只累及单侧,主要包括右侧岛叶、右侧额叶。相对保持完好的区域是小脑、体感觉皮层和枕叶。结论用基于3T的优化VBM方法能更全面、客观、自动、准确地体现AD患者存在的广泛的脑灰质密度降低区域。

扩散张量成像在遗忘型轻度认知障碍和Alzheimer病中的应用

目的:探讨磁共振扩散张量成像(DTI)在遗忘型轻度认知障碍(AMCI)、Alzheimer病(AD)诊断中的作用。方法:对20名aMCI患者、20名AD患者、20名正常对照者(NC)行DTI检查,分别在颞叶白质、顶叶白质、海马、胼胝体膝部及压部、上纵束Ⅱ、扣带束测ROI的FA值和ADC值。结果:NC组与aMCI组、aMCI组与AD组比较扣带束FA值均有显著性差异(P<0.05);NC组与AD组比较颞叶、海马、胼胝体膝部、扣带束FA值,颞叶、海马ADC值有显著性差异(P<0.05)。结论:aMCI患者扣带束FA值异常降低;AD患者颞叶、海马、胼胝体膝部、扣带束FA值降低和颞叶、海马ADC值增高,提示DTI检查有助于aMCI、AD患者的早期诊断。

Atlas-based deep gray matter and white matter analysis in Alzheimer's disease: diffusion abnormality and correlation with cognitive function

Objective To identify the diffusion alterations of deep gray matter(GM)and white matter(WM)among Alzheimer’s disease(AD),mild cognitive impairment(MCI)and healthy people by atlas-based analysis(ABA),and to investigate the respective relationship with cognitive function.Methods Twenty-one AD patients(AD group),8 MCI patients(MCI group)and

Altered white matter microarchitecture in Parkinson’s disease:a voxel-based meta-analysis of diffusion tensor imaging studies

This study aimed to define the most consistent white matter microarchitecture pattern in Parkinson’s disease(PD)reflected by fractional anisotropy(FA),addressing clinical profiles and methodology-related heterogeneity.Web-based publication databases were searched to conduct a meta-analysis of whole-brain diffusion tensor imaging studies comparing PD with healthy controls(HC)using the anisotropic effect size–signed differential mapping.A total of 808 patients with PD and 760 HC coming from 27 databases were finally included.Subgroup analyses were conducted considering heterogeneity with respect to medication status,disease stage,analysis methods,and the number of diffusion directions in acquisition.Compared with HC,patients with PD had decreased FA in the left middle cerebellar peduncle,corpus callosum(CC),left inferior fronto-occipital fasciculus,and right inferior longitudinal fasciculus.Most of the main results remained unchanged in subgroup metaanalyses of medicated patients,early stage patients,voxel-based analysis,and acquisition with˂30 diffusion directions.The subgroup meta-analysis of medication-free patients showed FA decrease in the right olfactory cortex.The cerebellum and CC,associated with typical motor impairment,showed the most consistent FA decreases in PD.Medication status,analysis approaches,and the number of diffusion directions have an important impact on the findings,needing careful evaluation in future meta-analyses.