阿尔茨海默病脑白质损害的病理及功能影像学特征研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
阿尔茨海默病(Alzheimer’s disease, AD)是最常见的痴呆原因,早期表现记忆力下降,以后逐渐出现语言、推理、判断、计算及定向能力的进行性下降,多伴有行为异常、人格改变和日常生活能力的下降。AD的病理特征为老年斑(senile plaques, SPs)、神经原纤维缠结(neurofibrillary tangles, NFTs)、神经元脱失和脑皮质变性萎缩。轻度认知障碍(mild cognitive impairment, MCI)被认为是一种介于正常老年人与AD之间的中间过渡状态,表现为能够被家人证实的记忆、语言或其他方面的智能损害,但不影响日常生活能力。一般认为多数遗忘型MCI(aMCI)最终将发展为AD,每年约10%~15%转化为AD。我国有数百万AD患者,正在成为一个庞大的人群。AD除增加家庭和社会的照料负担以外,还使家庭和政府付出了巨大的经济支出。目前AD仍无有效的治疗方法,早期诊断及早期干预是当前的研究热点。早期AD和MCI是很多药物和疫苗的治疗目标,目的是减慢或阻止AD病理的发展。然而,只有晚期AD才能做出准确的临床诊断,此时药物治疗几乎无效。
     结构影像学在AD的早期诊断中一直扮演着重要的角色,但以往的研究多致力于AD大脑形态学改变,如选择性颞叶内侧海马结构、内嗅皮层线性及体积变化可出现在AD早期阶段。有很多证据显示,仅凭视觉评估海马萎缩就能很精确地鉴别AD和认知功能正常的老年人。然而,当海马结构及内嗅皮层出现明显的形态学改变时,AD病程往往已进展到较晚期。最新的研究认为,早期AD及MCI在皮质结构未发生改变前,脑功能就发生了改变,这种改变可能与白质损害引起的皮质中枢的信息联络中断有关。
     血管性痴呆(vascular dementia, VD),尤其是皮质下缺血型血管性痴呆(包括Binswanger病)的特征性病理改变为皮质下腔隙性梗死和深部白质损害(white matter lesions, WMLs)。WMLs被认为与小血管病变引起的慢性缺血有关。然而,WMLs不只见于VD,多数AD患者及一部分MCI患者也存在着传统影像学上可见的白质损害。尽管神经影像学和神经病理学已经证实AD和MCI患者存在脑白质大体和微结构改变,但这些白质改变的临床意义及病理生理机制仍需要进一步研究确定。有些研究报道,与非痴呆老人比较AD患者WMLs更加明显,而另一些研究未得到同样的结论。此外,AD患者WMLs与认知功能的关系也仍不清楚,有些研究提示WMLs与认知功能有关,伴有WMLs的AD患者认知功能障碍更加明显;而其他一些研究未发现二者之间的关系。因此,AD患者尤其是早期患者WMLs的临床意义仍未明了。一项定量研究发现,WMLs与记忆障碍、处理速度和执行功能有关。另有很多研究一致认为,WMLs与年龄、高血压及其他心血管危险因素也有关,提示其可能是一种血管相关性疾病,尽管这种改变是一种非特异性病理改变。
     越来越多的病理学证据显示,AD患者存在着明显的白质损害和功能异常。有病理学证实,WMLs在AD临床症状显现中扮演着重要作用,WMLs的加重可能增加罹患AD的危险性。另有很多研究发现,除了常见于灰质区的典型病理损害神经元脱失外,AD患者脑白质组织中还存在广泛的常见于原发白质疾病的特征改变,包括轴突、少突胶质细胞及脂质成分的减少及星形胶质细胞反应性增生等。
     定量检测方法出现以前,WMLs研究多集中在影像学视觉评分法。近年来,随着磁共振液体衰减反转恢复(fluid-attenuated inversion recovery, FLAIR)新序列的出现,半自动定量测量成为研究热点。AD的研究多应用FLAIR序列以及基于强度阈值的半自动分割法定量检测WMLs的体积。
     虽然传统MRI能够显示AD患者的全脑及特异性脑结构的萎缩,但对皮质下白质的研究受到很多限制,尤其是当无明显白质高信号时,传统MRI就显得更加无能为力。弥散张量成像(diffusion tensor imaging, DTI)是近年发展起来的一种非侵入性水弥散成像技术,可用于活体定量检测水分子的弥散方向和程度,进而提供大脑结构的容量、方向和几何形状,同时也可反映传统MRI无明显WMLs的脑白质微细结构的改变。组织内水的弥散在各个方向上是不相同的,这是因为其受到细胞膜及细胞骨架神经微丝、微管的限制。水分子沿纤维方向更易弥散的特性称为各向异性,其中部分各向异性(fractional anisotropy, FA)最常用,其能够显示白质纤维功能和结构的完整性。平均弥散系数(mean diffusivity, MD)可以测量水弥散的程度,从而反映脑白质的结构和病理改变。有报道显示,白质区轴突、少突胶质细胞的减少以及星形胶质细胞反应性增生可以引起DTI参数的异常改变。
     磁共振质子波谱(proton magnetic resonance spectroscopy, ~1H- MRS)是一种非常有价值的活体评价大脑生化成分的方法。~1H-MRS检测的主要代谢产物包括N-乙酰天门冬氨酸(NAA)、肌醇(mI)、含胆碱复合物(Cho)及肌酸和磷酸肌酸(Cr)等。多数研究发现NAA的降低和mI的升高可能是AD的特征,反映患者脑组织中存在神经元损害或脱失,以及胶质细胞增生或细胞膜异常。
     本研究应用神经病理学、常规MRI、DTI及~1H-MRS等方法对AD患者脑白质结构损害的病理学及影像学特征进行研究,并分析了白质损害与认知功能障碍的关系,目的是进一步了解WMLs对患者认知功能和神经精神症状的影响。
     第一部分:阿尔茨海默病白质病理改变与影像学对照研究
     目的:通过对阿尔茨海默病(AD)患者脑白质区的病理和MRI研究,探讨AD血管性病理改变特征及其与影像学的相关性。
     方法:(1)病理学研究:4例经尸检确诊的AD患者脑组织经10%中性甲醛固定30天后,以乳头体为中心行冠状切,厚度1cm,在额叶、颞叶、顶叶、枕叶、Ammon角、海马、基底节及丘脑等部位常规取材后,在脑室周围白质区、弓状纤维等多处补取,进行石蜡包埋。行HE、刚果红、硝酸银、G-B银染色和Tau、Ubiquitin、βA4免疫组化染色等,显微镜下观察各脑叶皮层、扣带回、杏仁核、海马、海马旁回、Meynert基底核、脑干的黑质、蓝斑、迷走神经背核等部位的神经元脱失、老年斑(SPs)和神经原纤维缠结(NFTs)的多少与分布;同时详细观察白质区域的病理改变,尤其是神经元变性、髓鞘脱失、少突胶质细胞密度、星形胶质细胞增生及小血管改变的特征。(2)影像学方法:研究4例患者生前MRI的脑萎缩特征及脑室周围及皮层下深部白质损害(WMLs)程度,并与病理结果进行对照。
     结果:(1)组织病理学结果显示,所有4例AD患者均以颞叶及顶叶的萎缩为重,尤其是颞叶内侧萎缩更明显,额叶、岛叶皮质也有不同程度的萎缩;4例AD患者均有不同程度的脑室周围及皮层下深部白质损害及小血管变性,以额叶为重,主要表现为神经纤维脱髓鞘、少突胶质细胞及轴突减少、胶质细胞增生及小血管壁纤维素变性或淀粉样蛋白沉积。(2)AD病理(包括神经元脱失、SPs及NFTs)明显的部位颞叶内侧、海马及额叶,其影像学提示的局部脑叶萎缩也更加明显;影像学上白质区异常信号与病理改变也相一致。
     结论:AD患者不仅灰质受累,白质区也存在损害;病理学所见与影像学改变基本一致。
     第二部分:轻中度阿尔茨海默病白质病变与认知功能的关系
     目的:应用高场强磁共振液体衰减反转恢复(FLAIR)序列,采用半定量和定量两种方法研究轻中度阿尔茨海默病(AD)患者脑白质病变(WMLs),并探讨其与认知功能的关系。
     方法:收集轻中度AD患者56例,年龄及性别相当的健康老年人40例,记录患者的年龄、性别、受教育程度及既往病史,进行神经心理学评分并行常规头颅磁共振(MRI)扫描。应用改良Fazekas半定量评分法及半自动定量方法测定FLAIR序列上侧脑室周围WMLs(PVWMLs)和深部白质WMLs(DWMLs)评分,以及总WMLs(VWMLs)体积,并分析其与简易精神状态量表(MMSE)、画钟试验(DCT)及ADAS-Cog评分之间的相关关系。
     结果:(1)AD患者VWMLs为27.4±13.9cm3,PVWMLs评分为1.31±0.60,DWMLs评分为0.93±0.68,均高于对照组(分别为15.6±13.2 cm3,0.75±0.54和0.38±0.49)(均P﹤0.05)。控制年龄后上述结果无变化。(2)相关分析显示,AD患者年龄与VWMLs无相关性(P﹥0.05)。AD组伴有或不伴高血压病史2组比较VWMLs差异有统计学意义(t=2.26, P﹤0.05),PVWMLs及DWMLs评分2组比较差异无统计学意义(P﹥0.05)。(3)控制年龄变量后,AD患者VWMLs与MMSE呈显著负相关(r=-0.569, P﹤0.05),与ADAS-Cog呈显著正相关(r=0.515, P﹤0.01),与画钟试验评分呈显著负相关(r=-0.399, P﹤0.05)。
     结论:AD患者白质病变,无论是PVWMLs还是DWMLs均较正常同龄人明显;高血压是WMLs的危险因素,提示血管性危险因素可能与AD的发病有关;WMLs能影响AD患者的全面认知功能及执行功能。
     第三部分:磁共振弥散张量成像评价轻中度阿尔茨海默病脑白质微细结构损害的研究
     目的:应用磁共振弥散张量成像技术(DTI)研究轻度认知障碍(MCI)及轻中度阿尔茨海默病(AD)患者脑白质微细结构的改变,同时探讨DTI参数与认知功能之间的关系。
     方法:对12例MCI患者、12例轻中度AD患者及12例年龄及性别相当的健康对照(NC)老人行常规MRI及DTI检查,测量胼胝体压部、额叶、顶叶、颞叶、枕叶、内囊前肢及内囊后肢白质区的部分各向异性分数(FA)和平均弥散率(MD)。统计分析3组之间DTI参数的差别,并与神经心理测试结果进行相关性分析。结果:(1)与健康对照组相比,MCI患者只有顶叶白质FA值显著下降,FA值分别为0.558±0.079和0.489±0.079(P﹤0.05),MD值与对照组均无差别(P﹥0.05)。(2)健康对照组额叶、顶叶及颞叶FA值分别为0.499±0.081、0.558±0.079和0.440±0.061,AD患者额叶、顶叶及颞叶FA值分别为0.405±0.072、0.454±0.069和0.363±0.056,2组比较差别均有统计学意义(P﹤0.05)。AD患者胼胝体压部、额叶及顶叶MD值分别为0.978±0.082、0.920±0.054和0.817±0.045,与健康对照组比较显著升高(P﹤0.05)。内囊前后肢及枕叶3组FA及MD值比较均无差别(P﹥0.05)。(3)所有被研究者参加的相关分析显示,顶叶及颞叶FA值与MMSE、单词回忆及单词再认评分均相关(P﹤0.05),胼胝体压部FA值与单词再认评分相关(P﹤0.05)。胼胝体压部及顶叶MD值与MMSE、单词回忆及单词再认评分均相关(P﹤0.05)。
     结论:MCI及轻中度AD患者存在脑白质选择性微细结构损害,其可能是由AD病理与血管因素共同作用所引起,这种损害出现在与高级皮层功能相关的脑区,而与初级功能相关的区域未见明显受损。
     第四部分:~1H-磁共振波谱成像评价轻中度阿尔茨海默病患者侧脑室顶旁白质损害的研究
     目的:应用~1H-磁共振波谱(~1H-MRS)及弥散张量成像(DTI)2种磁共振新技术联合评价轻中度阿尔茨海默病(AD)患者侧脑室顶旁的白质损害。
     方法:AD患者20例,健康对照组20例,均进行临床检查、神经心理评估和GE Signa3.0T超导磁共振检查,采用PRESS序列,对双侧侧脑室顶旁白质感兴趣区N-乙酰天门冬氨酸(NAA)、肌醇(mI)、含胆碱复合物(Cho)及肌酸和磷酸肌酸(Cr)浓度进行采集,并计算NAA/Cr、mI/Cr及Cho/Cr比值。同时进行常规MRI和DTI扫描,对双侧侧脑室顶旁相同部位白质感兴趣区的部分各向异性分数(FA)和平均弥散率(MD)的平均值进行测量,并行统计学处理。
     结果:AD组NAA/Cr比值与对照组比较无明显差别(P﹥0.05),mI/Cr及Cho/Cr比值较对照组明显升高(P﹤0.05)。AD组FA及MD值分别为0.470±0.082和0.771±0.099,对照组FA及MD值分别为0.539±0.068和0.691±0.064,AD组FA值较对照组明显降低(P﹤0.05),MD值较对照组明显升高(P﹤0.05)。偏相关分析显示,控制年龄后,mI/Cr比值与FA值呈负相关关系(P﹤0.05),与MD值无相关关系(P﹥0.05)。
     结论:AD患者侧脑室顶旁白质区mI及Cho浓度增加,DTI检测出相同部位FA值降低,MD值升高,提示AD患者不仅存在着灰质病变,白质亦受累,推测这可能与AD病理和共存的血管性病理改变有关;~1H-MRS与DTI结合能更好地检测出AD患者的白质损害。
Alzheimer’s disease (AD) is the leading cause of dementia in the world. Clinical manifestation is memory decline in the early stage, and then show the decreased abilities of language, reasoning, judgment, calculation and orientation , mostly accompanied by behavioral disorders, personality change and daily living disturbances. AD is characterized pathologically by senile plaques (SPs), neurofibrillary tangles (NFTs), neuronal loss, and degeneration and atrophy of cerebral cortex. Mild cognitive impairment (MCI) has been described as a transitional period from healthy aging to clinically probable AD, when patients experience problems with memory, language, or other mental functions that are severe enough to be noticed by other people, but not serious enough to interfere with daily life. Patients who have amnestic MCI, suffering from symptoms that relate primarily to memory loss, are at the greatest risk of ultimately developing AD, and as a group convert to clinically probable AD over time at a rate of 10%~15% per year. Millions of Chinese now have AD, and the prevalence of the disease is accelerating rapidly as the population aging. Beyond the significant individual and societal burden of the disease, the economic impact of AD is staggering. There is no effective therapies for AD at present, and many researches focus on early diagnosis and intervention. Early AD and MCI is the primary target of several pharmacologic and vaccine treatments that are aimed at slowing or possibly halting the progression of AD pathology. Unfortunately, the diagnosis of AD can be made with high accuracy only in its late stage, at a time when there is little hope for therapeutic intervention.
     Structural neuroimaging has been playing a role in the early diagnosis of AD. Most previous studies went in for morphologic changes on MR imaging examinations of AD. For example, selective medial temporal lobe ,hippocampus, entorhinal cortex atrophy has been found in early AD. There is moderately strong evidence that visual hippocampal atrophy can accurately distinguish between patients who have AD and cognitively normal elders.However, when morphologic changes of hippocampus and entorhinal cortex are observed in patients with AD, the patients has become late stage. Recent study suggested that before changes of cortex, brain functions have been damaged, which may relate with interruption of information connection of cortex to cortex resulted from white matter lesions.
     White matter changes and lacunar infarcts are found frequently in brain of patients with vascular dementia(VD), especially of subcortical subtypes including Binswanger’s disease. These pathological changes are generally considered to be a consequence of chronic ischemia associated with microangiopathy. However, abnormalities of white matter are not associated exclusively with VD and are common in most of patients with AD and some MCI patients. Although neuroimaging and pathoanatomic studies have confirmed both macroscopic and microscopic white matter changes in patients with AD and MCI, controversy exists regarding the clinical significance of these changes and the mechanisms underlying them. Although some studies have reported that individuals with AD have elevated WMLs compared with nondemented aging individuals, this pattern has not been uniformly observed. In addition, the relationship between WMLs and cognition in AD remains unclear. Some studies suggest that subjects with AD and WMLs perform worse than nondemented aging individuals on cognitive tasks, and others find no relationship between WMLs and cognition. Therefore, the clinical significance of WMLs in AD remains unclear, particularly in the earliest clinical stage of the disease. A quantitative study showed that WMLs was associated with reduced memory, processing speed, and executive functions. WMLs are consistently associated with age, hypertension, and other cardiovascular risk factors and are commonly considered part of the spectrum of vascular-related injury, despite nonspecific underlying pathologic changes.
     There is a increasing pathological evidence of marked damage and dysfunction in the white matter of patients with AD. Pathological evidence suggests that WMLs may play a role in the clinical symptoms of AD. Individuals with more WMLs have a higher risk of developing AD. Other studies indicate that changes in white matter in AD consist not only of neuronal loss, which would be typical of a primary gray matter process, but also loss of axons, oligodendrocytes, and lipid components, together with reactive astrocytosis, microscopic features that are more characteristic of primary white matter diseases.
     Before the development of quantitative measures, WMLs were assessed using visual rating scales. The development of fluid-attenuated inversion recovery (FLAIR) sequences has enabled semiautomated methods to be developed. Recently, WMLs volumes were measured in patients with AD using FLAIR images and a semiautomated segmentation method based on intensity thresholding to quantify WMLs.
     Conventional MRI imaging can show overall brain atrophy or atrophy of key brain structures in patients with AD, but has a limited capability to quantify changes in the subcortical white matter, particularly subtle changes not visualized on conventional MRI. Diffusion tensor imaging (DTI) is a non-invasive water diffusion technique and can be used for quantitatively in vivo measuring the degree and directionality of the displacement distribution of water molecules to provide information about the size, orientation, and geometry of brain structures, as well as to demonstrate the white matter abnormalities, including subtle changes not visualized on conventional MRI.
     Restricted by many factors including cell membranes, axonal membranes, cytoskeletal structure, such as neurofilaments and microtubules, the diffusion of water molecules in biological tissues may not be same in all direction. The preference of diffusion in fiber direction is called anisotropy. Fractional anisotropy (FA), one of the most robust measures of anisotropy, is useful for mapping the functional integrity and specific organization of white matter fibers. Mean diffusivity (MD) is a measure for randomized mean water diffusion. It can be used as a measure of alterations of brain white matter. Loss of oligodendrocytes and axons, together with reactive astrocytosis, in the white matter could explain some of the DTI abnormalities reported.
     Proton magnetic resonance spectroscopy (1H- MRS) is a valuable tool for the assessment of several biochemical compounds in the brain in vivo, such as N-acetylaspartate (NAA), myoinositol (mI), Choline (Cho) and Creatine (Cr). Most studies have found that a decreased NAA levels and increased mI levels are characteristics of 1H- MRS in AD. This finding reflects neuronal loss or damage as well as an increase in glial content or membrane abnormalities.
     In this study we applied neuropathological methods, conventional MRI scanning, DTI and 1H-MRS techniques to estimate WMLs and characteristics of imaging in patients with AD. In addition, the relationship between regional WMLs and cognitive function impairment was also investigated. The aim of present study is to further understand the effect of WMLs on cognitive, neurological, and neuropsychiatric symptoms.
     Part 1: A contrast study on white matter pathology and MRI in patients with Alzheimer’s disease
     Objective:To explore the correlation of vascular pathologicl changes and MRI through a study on pathology and imaging of Alzheimer’s disease (AD).
     Methods:(1) Neuropathological study: At autopsy, the brains of 4 cases with AD were fixed in formaldehyde, and were kept in it for 30 days and were later cut into 1cm thick whole-brain coronal slices. Histological sections were taken routinely from the frontal lobe, parietal lobe, occipital lobe, insula, Ammon’s horn and hippocampal gyrus, basal ganglia and thalamus, as well as periventricular and deep white matter. Specimens were embedded in paraffin and stained with hematoxylin-eosin, Congo red, silver stainings, Gallyas silver dyeing, and immunohistochemistry for Tau, Ubiquitin,βA4 were also performed. The loss of neurons in all lobes of cerebral cortex, cingulate gyrus, amygdaloid nucleus, hippocampal gyrus, parahippocampal gyrus, meynert basal nuleus, substantia nigra, dorsal nucleus, dorsal nucleus of vagus nerve, senile plaques (SPs) and the changes of neurofibrillary tangles (NFTs) were observed in detail. Additionally, all cases were carefully analysed for additional white matter pathology, including neuronal degeneration, myelin attenuation, oligodendrocytic reduction, astrocytosis and small blood vessel changes. (2) Imaging study: Characteristics of brain atrophy and the severity of periventricular and subcortical deep white matter lesions (WMLs) were observed by magnetic resonance imaging (MRI) in all cases, and were compared to main pathological features.
     Results:(1) The degeneration of temporal lobe and parietal lobe, as well as frontal lobe, insula, was marked in all 4 cases, and the degeneration of medial temporal lobe was the most obvious; mild to severe damages of WMLs and small blood vessel degeneration were observed in all brains, especially in frontal lobe. The degeneration of white matter included marked myelin attenuation, oligodendrocytic reduction, astrocytosis, and amyloid deposition and fibrohyalinosis in small blood vessels. (2) Severe AD neuropathological findings, including loss of neurons, senile plaques(SPs) and NFTs were found in medial temporal lobe, hippocampal gyrus and frontal lobe, which in coincidence with imaging results. The pathological findings of white matter were also basically conformity with the changes of MRI.
     Conclusion:Not only gray matters, but white matters are affected in brain of AD patients. Neuropathological features are basically in conformity with the changes of MRI in gray matter and white matter lesions.
     Part 2: Study on correlation between white matter lesions and cognitive function in patients with mild and moderate Alzheimer’s disease
     Objective: To investigate the nature of white matter lesions and its correlation to the cognitive function in patients with mild and moderate Alzheimer’s disease (AD) by using 3 Tesla magnetic resonance imaging (MRI)
     Methods: We enrolled 56 patients with mild and moderate Alzheimer’s disease, and 40 age and sex matched normal elderly controls. Age, sex, educational level and history were recorded. T2 fluid attenuated inversion recovery (FLAIR) sequence were used for analysis of load and extent of hyperintense lesions. A semi-quantitative rating scale described by Fazkas et al. and a semi-automated MRI quantitative method were used to measure the scores of periventricular white matter lesions (PVWMLs) and deep white matter lesions (DWMLs), and the volume of total WMLs (VWMLs). The relationship between white matter lesions and cognitive impairment [mini-mental status examination (MMSE); drawing clock test (DCT); ADAS-Cog] was analyzed.
     Results: (1) Volume of WMLs in AD patients was 27.4±13.9. Scores of PVWMLs and DWMLs in AD patients were 1.31±0.60 and 0.93±0.68 respectively, and in controls were 15.6±13.2,0.75±0.54 and 0.38±0.49, respectively. A significant difference between two groups were observed in VWMLs, scores of PVWMLs and DWMLs (P﹤0.05). When controlling for age the same results were found. (2) Correlation analysis revealed that there was no correlation between age and VWMLs in patients with AD (P﹥0.05). A significantly increased volume of VWMLs were found in AD patients with hypertension than without hypertension (t=2.26, P﹤0.05), and no significant differences between two groups were found in scores of PVWMLs and DWMLs. (3) After controlling for age, significant correlations between volume of WMLs and MMSE (r=-0.569, P﹤0.05), ADAS-Cog (r=0.515, P﹤0.01) and drawing clock test (r=-0.399, P﹤0.05).
     Conclusion: Our results reveal that patients with AD have more severe WMLs (including PVWMLs and DWMLs) than controls. Hypertension is the risk factor for WMLs, which supports the hypothesis that WMLs in AD patients are superimposed phenomena of vascular origin. Global cognitive functions, including executive function , may be disturbed by WMLs in AD patients.
     Part 3: Evaluation of microstructural white matter lesions in patients with mild and moderate Alzheimer’s disease using diffusion tensor imaging
     Objective:To investigate the microstructural white matter lesions and its correlation with the cognitive function in patients with mild cognitive impairment (MCI) and mild and moderate Alzheimer’s disease (AD) by using diffusion tensor imaging (DTI) technique.
     Methods:12 patients with MCI, 12 patients with mild and moderate AD, and 12 sex and age matched normal control (NC) were recruited. DTI images were acquired, and fractional anisotropy (FA),mean diffusivity (MD) of normal- appearing white matter (NAWM) in splenium of the corpus callosum, frontal, parietal, temporal, occipital lobes, and anterior and posterior limbs of the internal capsule were determined. These diffusion measurements were compared across the 3 groups, and significant differences were further performed for correlation with tests of cognitive function.
     Results:(1) Compared with NC group, MCI patients demonstrated decreased FA value only in the parietal lobe (P<0.05),FA values were 0.558±0.079 and 0.489±0.079, respectively. No significant difference in MD values was found between MCI patients and NC group in all brain regions (P﹥0.05). (2) FA values in NC group were 0.499±0.081, 0.558±0.079 and 0.440±0.061, and in AD patients were 0.405±0.072, 0.454±0.069 and 0.363±0.056 respectively in the frontal, parietal and temporal NAWM. FA values decreased significantly in AD patients (P<0.05). MD values in AD patients were 0.978±0.082, 0.920±0.054 and 0.817±0.045 in the splenium of the corpus callosum, frontal and parietal NAWM, respectively. MD values increased significantly in AD patients (P<0.05). No significant differences were found in the anterior and posterior limbs of the internal capsule and the occipital NAWM between AD patients and NC group (P﹥0.05). (3) Across all subjects, FA values in parietal and temporal lobes correlated with the scores of MMSE, word recall and word recognition (P<0.05), and FA values in the splenium of the corpus callosum NAWM correlated with word recognition (P<0.05). MD values in the splenium of the corpus callosum NAWM and parietal lobe correlated with MMSE, word recall and word recognition (P<0.05).
     Conclusions:The microstructural white matter in patients with MCI and mild and moderate AD may be selectively impaired, which is probably caused by combination of AD pathologies and vascular factors. These lesions are presented in the brain regions serving higher cortical functions, but not in the regions serving primary functions.
     Part 4: Evaluation of white matter lesions of the paraventricular white matter regions in patients with mild and moderate Alzheimer’s disease using proton magnetic resonance spectroscopy
     Objective:To investigate the pattern of the cerebral white matter lesions of the bilateral paraventricular white matter regions in patients with mild and moderate Alzheimer’s disease(AD) and healthy controls using proton magnetic resonance spectroscopy(~1H-MRS) and diffusion tensor imaging (DTI).
     Methods: 20 AD patients and 20 healthy controls were recruited. All subjects underwent clinical examination, neuropsychological assessment. The quantitative analysis of N-acetylaspartate (NAA), myoinositol (mI), Chotine(Cho) and Creatine(Cr) resonance signals in region of interests (ROIs) located in the paraventricular white matter region were bilaterally measured. Ratios of NAA/ Cr, mI/ Cr and Cho/ Cr were calculated in two groups. In addition, conventional MRI and DTI scanning were received, fractional anisotropy(FA) and mean diffusivity(MD) values of white matter in the same regions were measured respectively.
     Results:No significant difference between two groups was observed in NAA/ Cr ratio(P﹥0.05). A significantly increased mI/ Cr and Cho/ Cr were found in AD patients than in controls (P﹤0.05). FA and MD values in AD patients were 0.470±0.082 and 0.771±0.099, and in controls were 0.539±0.068 and 0.691±0.064, respectively. FA value decreased significantly in AD patients (P﹤0.05), MD value increased significantly in AD patients (P﹤0.05). After controlling for age-related, partial correlation analysis revealed a negtive correlation between mI/ Cr and FA value in the patients with AD (P﹤0.05). No correlation between mI/ Cr and MD was found(P﹥0.05).
     Conclusion:It is suggested that not only the gray matter is injured, but also the white matter is abnormal in AD patients. Combining 1H-MRS with DTI alterations could provide the valuable informations about white matter lesions in AD patients.
引文
1 De La Monte SM. Quantitation of cerebral atrophy in preclinical and end-stage Alzheimer’s disease. Ann Neurol, 1989, 25: 450-459
    2 Pantoni L, Garcia JH. Pathogenesis of leukoaraiosis: a review. Stroke, 1997, 28: 652-659
    3 Kurumatani T, Kudo T, Ikura Y, et al. White matter changes in the gerbil brain under chronic cerebral hypoperfusion. Stroke, 1998, 29: 1058-1062
    4 Furuta A, Ishil N, Nishihara Y, et al. Medullay arteries in aging and dementia. Stroke, 1991, 22: 442-446
    5 Wakita H, Tomimoto H, Akiguchi I, et al. Glial activation and white matter changes in the rat brain induced by chronic cerebral hypoperfusion: An immunohistochemical study. Acta Neurophol, 1994, 87: 484-492
    6 Hachinski VC, Potter P, Merskey H. Leuko-araiosis. Arch Neurol, 1987, 44: 21-23
    7 Mirra SS, Heyman A, Mckee D, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) PartⅡ. Standardization of the neuropathologic assessment of Alzheimer’s Disease. Neurology, 1991, 41: 479-486
    8 Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol(Berl), 1991, 82: 239-259
    9 Fazekas F, Chawluk JB, Alavi A, et al. MR signal abnormahties at 1.5T in Alzheimer’s dementia and normal aging. Am J Neuroradiol, 1987, 8: 421-426
    10 Murayama S, Saito Y. Neuropatholoical diagnostic criteria for Alzheimer’s disease. Neuropathology, 2004, 24: 254-260
    11 Gomez-Isla T, Hollister R, West H, et al. Neuronal loss correlates with but exceeds neurofibrillary tangles in Alzheimer’s disease. Ann Neurol, 1997, 41: 17-24
    12 Yamaguchi H, Haga C, Hirai S, et al. Distinctive, rapid, and easy labeling of diffuse plaques in the Alzheimer brains by a new methenamine silverstain. Acta Neuropathol(Berl), 1990, 79: 569-572
    13 Iadecola C, Gorelick PB. Converging pathogenic mechanisms in vascular and neurodegenerative dementia. Stroke, 2003, 34:335-337
    14 Tabaton M, Caponnetto C, Mancardi G, et al. Amyloid beta protein deposition in brains from elderly subjects with leukoaraiosis. J Neurol Sci, 1991, 106: 123-127
    15 Gray F, Dubas F, Roullet F, et al. Leukoencephalopathy in diffuse hemorrhagic cerebral amyloid angiopathy. Ann Neurol, 1985, 18: 54-59
    16 Morishima-Kawashima M, Ihara Y. Alzheimer’s disease: beta amyloid protein and tau. J Neurosci Res, 2002, 70: 392-401
    17 Seno H, Inagaki T, Yamamori C, et al. Dementia of Alzheimer type with and without multiple lacunar infarctions: Evaluation of white matter lesions. Neuropathology, 2000, 20: 204-209
    18 Olichney JM, Hansen LA, Hofstetter CR, et al. Association between severe cerebral amyloid angiopathy and cerebrovascular lesions in Alzheimer disease is not a spurious one attributable to apolipoprotein E4. Arch Neurol, 2000, 57: 869-874
    19 Borenstein Graves A. Alzheimer’s disease and vascular dementia. In: Nelson LM, Tanner CM, Van Den Eeden SK, McGuire VM, editors. Neuro- epidemiology: from principles to practice. New York: Oxford University Press, 2004, 102-130
    20 Tominoto H, Akiguchi I, Akiyama H, et al. Vascular changes in white matter lesions of Alzheimer’s Disease. Acta Neuropathol, 1999, 97: 629-634
    21 Sjobeck M, Haglund M, Englund E. White matter mapping in Alzheimer’s Disease: A Neuropathological study. Neurobiology of aging, 2006, 27: 673-680
    22 Bartzokis G. Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease. Neurobiol Aging, 2004, 25: 5-18
    23 Jellinger KA. Alzheimer disease and cerebrovascular pathology: an update.J Neural Transm, 2002, 109: 813-836
    24 Jellinger KA, Attems J. Incidence of cerebrovascular lesion in Alzheimer’s disease: a postmortem study. Acta Neuropathol(Berl), 2003, 105: 14-17
    25 Tomimoto H, Akiguchi I, Suenaga T, et al. Alterations of the blood-brain barrier and glial cells in white matter lesions in cerebrovascular and Alzheimer’s disease patients. Stroke, 1996, 27: 2069-2074
    26 Starr JM, Farrall AJ, Armitage P, et al. Blood-brain barrier permeability in Alzheimer’s disease: a case-control MRI study. Psychiatry Research: Neuroimaging, 2009, 171: 232- 241
    1 Cohen RA, Paul RH, Ott BR, et al. The relationship of subcortical MRI hyperintensities and brain volume to cognitive function in vascular dementia. J Intl Neuropsycholog Soc, 2002, 8: 743-752
    2 Fazekas F, Chawluk JB, Alavi A, et al. MR signal abnormalities at 1.5T in Alzheimer’s disease and normal aging. Am J Roentgenol, 1987, 149: 351-356
    3 Oosterman JM, Sergeant JA, Weinstein HC, et al. Timed executive functions and white matter in aging with and without cardiovascular risk factors. Rev Neurosci, 2004, 15: 469-462
    4 Mungas D, Harvey D, Reed BR, et al. Longitudinal volumetric MRI change and rate of cognitive decline. Neurology, 2005, 65: 565-571
    5 van der Flier WM, van Straaten EC, Barkhof F, et al. Medial temporal lobe atrophy and white matter hyperintensities areassociated with mild cognitive deficits in non-disabled elderly people: the LADIS study. J Neurol Neurosurg Psychiatry, 2005, 76: 1497-1500
    6 McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology, 1984, 34: 939-944
    7 Folstein MF, Folstein SE, McHugh PR. Mini-Mental State: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res, 1975, 12: 189-198
    8 Rosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer’s disease. Am J Psychiatry, 1984, 141: 1356-1364
    9 Skoog I, Lernfelt B, Landahl S, et al. 15-year longitudinal study of blood pressure and dementia. Lancet, 1996, 347: 1141-1145
    10 Head D, Buckner RL, Shimony JS, et al. Differential vulnerability of anterior white matter in nondemented aging with minimal acceleration in dementia of the Alzheimer type: evidence from diffusion tensor imaging.Cereb Cortex, 2004, 14: 410-423
    11 Bronge L, Bogdanovic N, Wahlund LO. Postmortem MRI and histopathology of white matter changes in Alzheimer brains: a quantitative, comparative study. Dement Geriatr Cogn Disord, 2002, 13: 205-212
    12 van Dijk EJ, Prins ND, Vrooman HA, et al. Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study. Stroke, 2008, 39: 2712-2719
    13 Burton EJ, McKeitb IG, Burn DJ et al. Progression of white matter hyperintensities in Alzheimer disease, dementia with Lewy Bodies, and Parkinson disease dementia: a comparison with normal Aging. Am J Geriatr Psychiatry, 2006, 14: 842-849
    14 Kivipelto M, Helkala EL, Laakso MP, et al. Midlife vascular risk factors and Alzheimer’s disease in later life: longitudinal, population based study. BMJ, 2001, 322: 1447-1451
    15 Gopalraj RK, Zhu H, Kelly JF, et al. Genetic association of low density lipoprotein receptor and Alzheimer's disease. Neurobiol Aging, 2005, 26: 1-7
    16 Laws SM, Hone E, Gandy S, et al. Expanding the association between the APOE gene and the risk of Alzheimer’s disease: possible roles for APOE promoter polymorphisms and alterations in APOE transcription. J Neurochem, 2003, 84: 1215-1236
    17 Kramer JH, Reed BR, Mungas D, et al. Executive dysfunction in subcortical ischaemic white matter disease. J Neurol Neurosurg Psychiatry, 2002, 72:217-220
    18 van den Heuvel DM, ten Darn VH, de Craen AJ, et al. Increase in periventricular, white matter hyperintensities parallels decline in mental processing speed in a non-demented elderly population. J Neurol Neurosurg Psychiatry, 2006, 77: 149-153
    19 Hirono N, Kitagaki H, Kazui H, et al. Impact of white rnatter changes on clinical manifestation of Alzheimer’s disease: a quantitative study. Stroke, 2000, 31: 2182-2188
    20 Scheltefls P, Barkhof F, Valk J, et al. White matter lesions on magnetic resonance imaging in clinically diagnosed Alzheimer’s disease: evidence for heterogeneity. Brain, 1992, 115: 735-748
    21 Esiri MM, Nagy Z, Smith MZ, et al. Cerebrovascular disease and threshold for dementia in the early stages of Alzheimer’s disease. Lancet, 1999, 354: 919-920
    22 Snowdon DA, Greiner LH, Mortimer JA, et al. Brain infarction and the clinical expression of Alzheimer disease. JAMA, 1997, 277: 813-817
    23 Buckner RL. Memory and executive function in aging and AD: multiple factors that cause decline and reserve factors that compensate. Neuron, 2004, 44: 195-208
    24 Galasko D, Hansen LA, Katzman R, et al. Clinical-neuropathological correlations in Aizheimer’s disease and related dementias. Arch Neurol, 1994, 51: 888-895
    25冯亚青,朱明伟,刘桂芳,等.阿尔茨海默病临床病理报告一例.中华老年医学杂志,2007,26:65-67
    1 Jack CR, Shiung MM, Gunter JL, et al. Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology, 2004, 62: 591-600
    2 De Toledo-Morrell L, Stoub TR, Bulgakova M, et al. MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiol Aging, 2004, 25: 1197-1203
    3 Chen YF, Wang HL, Chu Y, et al. Regional quantification of white matter hyperintensity in normal aging, mild cognitive impairment, and Alzheimer’s disease. Dement Geriatr Cogn Disord, 2006, 22: 177-184
    4贾艳滨,王颖,凌雪英,等.首发精神分裂症患者脑白质纤维束各向异性特征的扩散张量磁共振成像研究.中华行为医学与脑科学杂志, 2009, 18: 40-42
    5 Huang J, Friedland RP, Auchus AP, et al. Diffusion tensor imaging of normal- appearing white matter in mild cognitive impairment and early Alzheimer disease: preliminary evidence of axonal degeneration in the temporal lobe. Am J Neuroradio, 2007, 28: 1943–1948
    6 Mckhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA work group under the auspices of the Department of Health and Human Services Task Force on Alzheier’s disease. Neurology, 1984, 34: 939-944
    7 Petersen RC, Thomas RG, Grundman M, et al. Vitamin E and donepezil for the treatment of mild cognitive impairment. N Engl J Med, 2005, 352: 2379-2388
    8 Mukherjee P. Diffusion tensor imaging and fiber tractography in acute stroke. Neuroimaging Clin N Am, 2005, 15: 655-665
    9 Kealey SM, Kim Y, Whiting WL, et al. Determination of multiple sclerosis plaque size with diffusion-tensor MR imaging: comparison study with healthy volunteers. Radiology, 2005, 236: 615-620
    10 Bronge L, Bogdanovic N, Wahlund LO. Postmortem MRI andhistopathology of white matter changes in Alzheimer brains: A quantitative, comparative study. Dement Geriatr Cogn Disord, 2002, 13: 205-212
    11 Le-Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and application. J Magn Reson Imaging, 2001, 13: 534-546
    12 Buchel C, Raedler T, Sommer M, et al. White matter asymmetry in human brain: a diffusion tensor MRI study. Cereb Cortex, 2004, 14: 945-951
    13 Choi SJ, Lim KO, Monteiro I, et al. Diffusion tensor imaging of frontal white matter microstructure in early Alzheimer’s disease: a preliminary study. J Geriatr Psychiatry Neurol, 2005, 18: 12-19
    14 Naggaraa O, Oppenheim C, Rieu D, et al. Diffusion tensor imaging in early Alzheimer's disease. Psychiatry Research: Neuroimaging, 2006, 146: 243-249
    15 Mielke MM, Kozauer NA, Chan KCG, et al. Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease. Neuro Image, 2009, 46: 47-55
    16 Noble M. The possible role of myelin destruction as a precipitating event in Alzheimer’s disease. Neurobiol Aging, 2004, 25: 25-31
    17 0’Sullivan M, Morris RG, Huckstep B, et al. Diffusion tensor MRl correlates with executive dysfunction in patients with ischaemic leukoaraiosis. J Neurol Neurosurg Psychiatry, 2004, 75: 441-447
    18 Xie S, Xiao JX, Gong GL, et al. Voxel-based detection of white matter abnormalities in mild Alzheimer disease. Neurology, 2006, 66: 1845-1849
    1 Jack CR JR, Shiung MM, Gunter JL, et al. Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology, 2004, 62: 591-600
    2 De Toledo-Morrell L, Stoub TR, Bulgakova M, et al. MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiol Aging, 2004, 25: 1197-1203
    3李国海,刘捃,申变红,等.抑郁症患者额叶、前扣带回、海马N-乙酰天冬氨酸磁共振质子波谱研究.中华行为医学与脑科学杂志, 2009, 18: 499-501
    4 Kantarci K, Weigand SD, Petersen RC, et al. Longitudinal 1H MRS changes in mild cognitive impairment and Alzheimer’s disease. Neurobiol Aging, 2007, 28: 1330-1339
    5 Valenzuela MJ, Sachdev P. Magnetic resonace spectroscopy in AD. Neurology, 2001, 56: 592-598
    6 Catani M, Mecocci P, Tarducci R, et al. Proton magnetic resonance spectroscopy reveals similar white matter biochemical changes in patients with chronic hypertension and early Alzheimer’s disease. J Am Geriatr Soc, 2002, 50: 1707-1710
    7 Cianfoni A, Niku S, Imbesi SG. Metabolite findings in tumefactive demyelinating lesions utilizing short echo time proton magnetic resonance spectroscopy. AJNR Am J Neuroradiol, 2007, 28: 272-277
    8 Modrego PJ, Fayed N, Pina MA. Conversion from mild cognitive impairment to probable Alzheimer’s disease predicted by brain magnetic resonance spectroscopy. Am J Psychiatry, 2005, 162: 667-675
    9 Kantarci K, Jack CR, Xu YC, et al. Regional metabolic patterns in mild cognitive impairment and Alzheimer’s disease: a 1H MRS study. Neurology, 2000, 55: 210-217
    10 Klunk WE, Xu C, Panchalingam K, et al. Quantitative 1H and 31P MRS of PCA extracts of postmortem Alzheimer’s disease brain. Neurobiol Aging,1996, 17: 349-357
    11 Le-Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and application. J Magn Reson Imaging, 2001, 13: 534-546
    12 Buchel C, Raedler T, Sommer M, et al. White matter asymmetry in human brain: a diffusion tensor MRI study. Cereb Cortex, 2004, 14: 945-951
    13 Naggaraa O, Oppenheim C, Rieu D, et al. Diffusion tensor imaging in early Alzheimer's disease. Psychiatry Research: Neuroimaging, 2006, 146: 243-249
    14 Wakana S, Jiang H, Nagae-Poetscher LM, et al. Fiber tract-based atlas of human white matter anatomy. Radiology, 2004, 230: 77-87
    15 Noble M. The possible role of myelin destruction as a precipitating event in Alzheimer’s disease. Neurobiol Aging, 2004, 25:25-31
    16 Bronge L, Bogdanovic N, Wahlund LO. Postmortem MRI and histopathology of white matter changes in Alzheimer brains: A quantitative, comparative study. Dement Geriatr Cogn Disord, 2002, 13: 205-212
    17 Kantarci K, Knopman DS, Dickson DW, et al. Alzheimer disease: Postmortem neuropathologic correlates of antemortem 1H MR spectroscopy metabolite measurements. Radiology, 2008, 248: 210-220
    18 Mielke MM, Kozauer NA, Chan KCG, et al. Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease. NeuroImage, 2009, 46: 47-55
    19 Ding B, Chen KM, Ling HW, et al. Diffusion tensor imaging correlates with proton magnetic resonance spectroscopy in posterior cingulate region of patients with Alzheimer’s disease. Dement Geriatr Cogn Disord, 2008, 25: 218-225
    1 Delacourte A, David JP, Sergeant N, et al. The biochemical pathway of neurofibrillary degeneration in aging and Alzheimer’s disease. Neurology, 1999, 52: 1158-1165
    2 Mark RJ, Pang Z, Geddes JW, et al. Amyloidβ-peptide impairs glucose transport in hippocampal and cortical neurons: involvement of membrane lipid peroxidation. J Neurosci, 1997, 17: 1046-1054
    3 St.George-Hyslop P. Molecular genetics of Alzheimer’s disease. Biol Psychiatry, 2000, 47: 183-199
    4 Schoenberg BS. Epidemiology of Alzheimer’s disease and other dementing disorders. J Chronic Dis, 1986, 39: 1095-1104
    5 Fratiglioni L, Grut M, Forsell Y, et al. Prevalence of Alzheimer’s disease and other dementias in an elderly urban population: relationship with age sex, and education. Neurology, 1991, 41: 1886-1892
    6 Brookmeyer R, Gray S, Kawas C. Projections of Alzheimer’s disease in the United States and the public health impact of delaying disease onset. Am J Public Health, 1998, 88: 1337-1342
    7 Hirata Y, Matsuda H, Nemoto K, et al. Voxel-based morphometry to discriminate early Alzheimer’s disease from controls. Neurosci Lett, 2005, 382: 269-274
    8 Chetelat G, Desgranges B, De La Sayette V, et al. Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment. Neuroreport, 2002, 13: 1939-1943
    9 Du AT, Schuff N, Amend D, et al. Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J Neurol Neurosurg Psychiatry, 2001, 71: 441-447
    10 Ishii K, Kawachi T, Sasaki H, et al. Voxel-based morphometric comparison between early- and late-onset mild Alzheimer’s disease and assessment of diagnostic performance of z score images. AJNR, 2005, 26: 333-340
    11 Kadir A, Darreh-Shori T, Almkvist O, et al. Changes in brain 11C-nicotinebinding sites in patients with mild Alzheimer’s disease following rivastigmine treatment as assessed by PET. Psychopharmacology (Berl), 2007, 191: 1005-1014
    12 Kadir A, Darreh-Shori T, Almkvist O, et al. PET imaging of the in vivo brain acetylcholinesterase activity and nicotine binding in galantamine-treated patients with AD. Neurobiol Aging, 2008, 29: 1204-1217
    13 Ellis JR, Nathan EJ, Villemagne VL, et al. Improvements in cognitive function are not related to alterations inα4β2 nicotinic receptors in early Alzheimer’s disease as measured in vivo by 2-[18F]Fluoro-A-85380 PET. Psychopharmacology, 2009, 202: 79-91
    14 Truchot L, Costes N, Zimmer L, et al. A distinct [18F]MPPF PET profile in amnestic mild cognitive impairment compared to mild Aizheimer’s disease. NeuroImage, 2008, 40: 1251-1256
    15 Hirao K, Ohnishi T, Hirata Y, et al. The prediction of rapid conversion to Alzheimer’s disease in mild cognitive impairment using regional cerebral blood flow SPECT. NeuroImage, 2005, 28: 1014-1021
    16 Huang J, Friedland RP, Auchus AP, et al. Diffusion tensor imaging of normal-appearing white matter in mild cognitive impairment and early Alzheimer disease: preliminary evidence of axonal degeneration in the temporal lobe. Am J Neuroradio, 2007, 28: 1943–1948
    17 Mukherjee P. Diffusion tensor imaging and fiber tractography in acute stroke. Neuroimaging Clin N Am, 2005, 15: 655-665
    18 Kealey SM, Kim Y, Whiting WL, et al. Determination of multiple sclerosis plaque size with diffusion-tensor MR imaging: comparison study with healthy volunteers. Radiology, 2005, 236: 615-620
    19 Kantarci K, Knopman DS, Dickson DW, et al. Alzheimer disease: Postmortem neuropathologic correlates of antemortem 1H MR spectroscopy metabolite measurements. Radiology, 2008, 248: 210-220
    20 Ding B, Chen KM, Ling HW, et al. Diffusion tensor imaging correlates with proton magnetic resonance spectroscopy in posterior cingulate regionof patients with Alzheimer’s disease. Dement Geriatr Cogn Disord, 2008, 25:218–225
    21 O’Brien JT, Colloby SJ, Pakrasi S, et al. Alpha4beta2 nicotinic receptor status in Alzheimer’s disease using 123I-5IA-85380 single-photon-emission computed tomography. J Neurol Neurosurg Psychiatry, 2007, 78: 356-362
    22 Staley JK, van Dyck CH, Weinzimmer D, et al. 123I-5-IA-85380 SPECT measurement of nicotinic acetylcholine receptors in human brain by the constant infusion paradigm: feasibility and reproducibility. J Nucl Med 2005, 46: 1466-1472
    23 Huang C, Wahlund LO, Svensson L, et al. Cingulate cortex hypoperfusion predicts Alzheimer’s disease in mild cognitive impairment. BMC Neurol, 2002, 2: 9
    24 Chetelat G, Desgranges B, de la Sayette V,et al. Mild cognitive impairment: can FDG-PET predict who is to rapidly convert to Alzheimer’s disease? Neurology, 2003, 60: 1374-1377
    25 Mosconi L, Perani D, Sorbi S, et al. MCI conversion to dementia and the APOE genotype: a prediction study with FDG-PET. Neurology, 2004, 63: 2332-2340
    26 Drzezga A, Lautenschlager N, Siebner H, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study. Eur J Nucl Med Mol, Imaging, 30: 1104- 1113
    27 Imabayashi, E, Matsuda, H, Asada, T et al. Superiority of 3-dimensional stereotactic surface projection analysis over visual inspection in discrimination of patients with very early Alzheimer’s disease from controls using brain perfusion SPECT. J Nucl Med, 2004, 45: 1450-1457
    28 Nihashi T, Yatsuya H, Hayasaka K, et al. Direct comparison study between FDG-PET and IMP-SPECT for diagnosing Alzheimer’s disease using 3D-SSP analysis in the same patients. Radiat Med, 2007, 25: 255-262
    29 Mielke R, Pietrzyk U, Jacobs A, et al. HMPAO SPET and FDG PET in Alzheimer’s disease and vascular dementia: comparison of perfusion andmetabolic pattern. Eur J Nucl Med, 1994, 21: 1052-1060
    30 Messa C, Perani D, Lucignani G, et al. High-resolution technetium-99m- HMPAO SPECT in patients with probable Alzheimer’s disease: comparison with fluorine-18-FDG PET. J Nucl Med, 1994, 35: 210-216
    31 Tohgi H, Yonezawa H, Takahashi S, et al. Cerebral blood flow and oxygen metabolism in senile dementia of Alzheimer's type and vascular dementia with deep white matter changes. Neuroradiology, 1998, 40: 131-137
    32 de Leon MJ, Convit A, Wolf OT, et al. Prediction of cognitive decline in normal elderly subjects with 2-[18F]fluoro-2-deoxy-D-glucose/positron- emission tomography (FDG/PET). Proc Natl Acad Sci USA, 2001, 98: 10966-10971
    33 Silverman DHS. Brain 18F-FDG PET in the diagnosis of neurodegenerative dementias: comparison with perfusion SPECT and with clinical evaluations lacking nuclear imaging. J Nucl Med, 2004, 45: 594-607
    34 Herholz K, Salmon E, Perani D, et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage, 2002, 17: 302-316
    35 Perani D, Grassi F, Sorbi S, et al. PET study in subjects from two Italian FAD families with APP717 Val to llue mutation. Eur J Neurol, 1997, 4: 214- 220
    36 Mosconi L, Sorbi S, Nacmias B, et al. Brain metabolic differences between sporadic and familial Alzheimer’s disease. Neurol, 2003, 61: 1138-1140
    37 Kennedy AM, Frackowiak RSJ, Newman SK, et al. Deficits in cerebral glucose metabolism demonstrated by positron emission tomography in individuals at risk of familial Alzheimer’s disease. Neurosci Lett, 1995, 186: 17-20
    38 Ellis JR, Ellis KA, Bartholomeusz CF, et al. Muscarinic and nicotinic receptors synergistically modulate working memory and attention in humans. Int J Neuropsychopharmacol, 2006, 9: 175-189
    39 Ellis JR, Villemagne VL, Nathan PJ, et al. Relationship between nicotinic receptors and cognitive function in early Alzheimer’s disease: A2-[18F]Fluoro-A-85380 PET study. Neurobiol Learn Mem, 2008, 90: 404-412
    40 Yetkin FZ, Rosenberg RN, Weiner MR, et al. FMRI of working memory in patients with mild cognitive impairment and probableAlzheimer’s disease. Eur Radiol, 2006, 16: 193-206
    41 Dickerson BC. Functional magnetic resonance imaging of cholinergic modulation in mild cognitive impairment. Curt Opin Psychiatry, 2006, 19: 299-306
    42 Bondi MW, Houston WS, Eyler LT, et al. fMRI evidence of compensatory mechanisms in older adults at genetic risk for Alzheimer disease. Neurology, 2005, 64: 501-5
    43 Kantarci K, Petersen Rc, Boeve BF, et al. DWI predicts future progression to Alzheimer disease in amnestic mild congnitive impairment. Neurology, 2005, 64: 902
    44 Naggaraa O, Oppenheim C, Rieu D,et al. Diffusion tensor imaging in early Alzheimer's disease. Psychiatry Research: Neuroimaging, 2006, 146: 243-249
    45 Mielke MM, Kozauer NA, Chan KCG, et al. Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease. NeuroImage, 2009, 46: 47-55
    46 Le-Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and application. J Magn Reson Imaging, 2001, 13: 534-546
    47 Maas LC, Harris G, Satlin A, et al. Regional cerebral blood volume measured by dynamic susceptibility contrast MR imaging in Alzheimer's disease: a principal components analysis. J Magn Reson Imaging, 1997, 7: 215
    48 Bozzao A, Floris R, Baviera ME, et al. Diffusion and perfusion MR imaging in cases of Alzheimer's disease: correlations with cortical atrophy and lesion load. AJNR Am J Neuroradiol, 2001, 22: 1030
    49 Kantarci K, Weigand SD, Petcrsen RC, et al. Longitudinal H MRS changes in mild cognitive impairment and Alzheimer’s disease. Neurobiol Aging,2007, 28: 1330-1339
    50 Lehericy S, Marjanska M, Mesrob L, et al. Magnetic resonance imaging of Alzheimer’s disease. Eur Radiol, 2007, 17: 347-362
    1 Masters CL, Simms G, Weinman NA, et al. Amyloid plaque core protein in Alzheimer disease and Down syndrome. Proc Natl Acad Sci, 1985, 82: 4245-4249
    2 Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science, 2002, 297: 353-356
    3 Joseph JA, Shukitt HB, Denisova NA, et al. Copernicus revisited: amyloid beta in Alzheimer’s disease. Neurobiol Aging, 2001, 22: 161-163
    4 de la Torre JC. Alzheimer’s disease: how does it start? J Alz Dis, 2002, 4: 497-512
    5 Austin L, Arendash GW, Gordon MN, et al. Short-term beta-amyloid vaccinations do not improve PS1 mice. Behav Neurosci, 2003, 117: 478-484
    6 de la Torre JC. Vascular pathophysiology in Alzheimer’s disease. Neurobiol Aging, 2000, 21: 153- 383
    7 de la Torre JC, Kalaria RN, Nakajima K, et al. Alzheimer’s disease: vacular etiology and pathology. Ann NY Acad Sci, 2002, 977: 1-526
    8 Meyer JS, Rauch G, Ruach RA, et al. Risk factors for cerebral hypoperfusion, mild cognitive impairment and dementia. Neurobiol Aging, 2000, 21: 161-169
    9 Polidori MC, Marvardi M, Cherubini A, et al. Heart disease and vascular risk factors in the cognitively impaired elderly: implications for Alzheimer’s dementia. Aging, 2001, 13: 231-239
    10 Masliah E, Sisk A, Mallory M, et al. Neurofibrillary pathology in transgenic mice overexpressing V717Fβ-amyloid precursor protein. J Neurolpathol Exp Neurol, 2001, 60: 357-368
    11 Vagnucci AH, Li WW. Alzheimer’s disease and angiogenesis. Lancet, 2003, 361: 605-608
    12 Johnson KA, Albert MS. Perfusion abnormalities in prodromal Alzheimer’sdisease. Neurobiol Aging, 2000, 21: 289-292
    13 Sinforiani E, Curci R, Fancellu R, et al. Neuropsychological changes after carotid endarterectomy. Funct Neurol, 2001, 16: 329-336
    14 Kalaria RN. Small vessel disease and Alzheimer’s dementia: pathological considerations. Cerebrovasc Dis, 2002, 13(suppl 2): 48-52
    15 Kalaria R. Similarities between Alzheimer’s disease and vascular dementia. J Neurol Sci, 2002, 203: 605-608
    16 Anthony H , Vagnucci JR, William WL. Alzheimer’s disease and angiogenesis. Lancet, 2003, 361: 605-608
    17 Shah S, Tangalos EG, Petersen R. Mild cognitive impairment: when is it a precursor of Alzheimer’s disease? Geriatrics, 2000, 55: 65-68
    18 Johnson KA, Albert MS. Perfusion abnormalities in prodormal Alzheimer’s disease. Neurobiol Aging, 2000, 21: 189-292
    19 Huang J, Friedland RP, Auchus AP, et al. Diffusion tensor imaging of normal- appearing white matter in mild cognitive impairment and early Alzheimer disease: preliminary evidence of axonal degeneration in the temporal lobe. Am J Neuroradio, 2007, 28: 1943–1948
    20 Mukherjee P. Diffusion tensor imaging and fiber tractography in acute stroke. Neuroimaging Clin N Am, 2005, 15: 655-665
    21 Kealey SM, Kim Y, Whiting WL, et al. Determination of multiple sclerosis plaque size with diffusion-tensor MR imaging: comparison study with healthy volunteers. Radiology, 2005, 236: 615-620
    22 Kantarci K, Knopman DS, Dickson DW, et al. Alzheimer disease: Postmortem neuropathologic correlates of antemortem 1H MR spectroscopy metabolite measurements. Radiology, 2008, 248: 210-220
    23 Ding B, Chen KM, Ling HW, et al. Diffusion tensor imaging correlates with proton magnetic resonance spectroscopy in posterior cingulate region of patients with Alzheimer’s disease. Dement Geriatr Cogn Disord, 2008, 25:218–225
    24 Klunk WE, Xu C, Panchalingam K, et al. Quantitative 1H and 31P MRS of PCA extracts of postmortem Alzheimer’s disease brain. Neurobiol Aging,1996, 17: 349-357
    25 Kantarci K, Jack CR, Xu YC, et al. Regional metabolic patterns in mild cognitive impairment and Alzheimer’s disease: a 1H-MRS study. Neurology, 2000, 55: 210-217
    26 Kantarci K, Weigand SD, Petersen RC, et al. Longitudinal 1H MRS changes in mild cognitive impairment and Alzheimer’s disease. Neurobiol Aging, 2007, 28: 1330-1339
    27 Valenzuela MJ, Sachdev P. Magnetic resonace spectroscopy in AD. Neurology, 2001, 56: 592-598
    28 Jellinger KA, Mitter-Ferstl E. The impact of cerebrovascular lesions in Alzheimer disease–a comparative autopsy study. J Neurol, 2003, 250: 1050-1055
    29 Revesz T, Ghiso J, Lashley T, et al. Cerebral amyloid angiopathies: a pathologic, biochemical, and genetic view. J Neuropathol Exp Neurol, 2003, 62: 885-898
    30 Wakutani Y, Kowa H, Kusumi M, et al. Genetic analysis of vascular factors in Alzheimer’s disease. Ann NY Acad Sci, 2002, 977: 232-238
    31 Tatsuguchi M, Furutani M, Hinagata J, et al. Oxidized LDL receptor gene(OLR1) is associated with the risk of myocardial infarction. Biochem Biophys Res Commun, 2003, 303: 247-250
    32 Ng CL, Wadleigh DJ, Gangopadhyay A, et al. Paraoxonase-2 is a ubiquitously expressed protein with antioxidant properties and is capable of preventing cell-mediated oxidative modification of low density lipoprotein. J Biol Chem, 2001, 276: 44444-44449
    33 Elbaz A, Poirier O, Moulin T, et al.Association between the Glu298Asp polymorphism in the endothelial constitutive nitric oxide synthase gene and brain infarction. Stroke, 2000, 31(7): 1634-1639
    34 Gopalraj RK, Zhu H, Kelly JF, et al. Genetic association of low density lipoprotein receptor and Alzheimer's disease. Neurobiol Aging, 2005, 26(1): 1-7
    35 Mehta JL, Li D. Identification, regulation and function of a novellectin-like oxidized low-density lipoprotein receptor. L Am Coll Cardiol, 2002, 39: 1429-1435
    36 Panza F, Solfrizzi V, Torres F, et al. Apolipoprotein E in Southern Italy: protective effect ofε2 allele in early- and late-onset sporadic Alzheimer’s disease. Neurosci Lett, 2000, 292: 79-82
    37 Laws SM, Hone E, Gandy S, et al. Expanding the association between the APOE gene and the risk of Alzheimer’s disease: possible roles for APOE promoter polymorphisms and alterations in APOE transcription. J Neurochem, 2003, 84: 1215-1236
    38 Lambert JC, Araria GL, Myllykangas L, et al. Contribution of APOE promoter polymorphisms to Alzheimer’s disease risk. Neurology, 2002, 59: 59-66
    39 Seshadri S, Beiser A, Selhub J, et al. Plasma homocysteine as a risk factor for dementia and Alzheimer’s disease. N Engl J Med, 2002, 346: 476-483
    40 Pritchard A, St Clair D, Lemmon H, et al. No association between polymorphisms in the lectin-like oxidised low density lipoprotein receptor (ORL1) gene on chromosome 12 and Alzheimer's disease in a UK cohort. Neurosci Lett, 2004, 366(2): 126-129
    41 Janka Z, Juhasz A, Rimanoczy AA, et al. Codon 311(Cys→Ser) polymorphism of paraoxonase 2 gene is associated with apolipoprotein E4 allele in both Alzheimer’s and vascular dementias. Mol Psychiatry, 2002, 7: 110-112