BACKGROUND & AIMS: :The pathogenic relevance in Alzheimer's disease (AD) presents a decrease of cerebrospinal fluid amyloid-ß42 (Aß42) burden and an increase in cerebrospinal fluid total tau (T-tau) levels. In this work, we performed genome-wide association study (GWAS) and genome-wide interaction study of T-tau/Aß42 ratio as an AD imaging quantitative trait on 843 subjects and 563,980 single-nucleotide polymorphisms (SNPs) in ADNI cohort. We aim to identify not only SNPs with significant main effects but also SNPs with interaction effects to help explain "missing heritability". Linear regression method was used to detect SNP-SNP interactions among SNPs with uncorrected p-value ≤0.01 from the GWAS. Age, gender, and diagnosis were considered as covariates in both studies. The GWAS results replicated the previously reported AD-related genes APOE, APOC1, and TOMM40, as well as identified 14 novel genes, which showed genome-wide statistical significance. Genome-wide interaction study revealed 7 pairs of SNPs meeting the cell-size criteria and with bonferroni-corrected p-value ≤0.05. As we expect, these interaction pairs all had marginal main effects but explained a relatively high-level variance of T-tau/Aß42, demonstrating their potential association with AD pathology.

背景与目标： : 阿尔茨海默氏病 (AD) 的致病相关性表明脑脊液淀粉样蛋白42 (a ß 42) 负担减少，脑脊液总tau (T-tau) 水平增加。在这项工作中，我们对843受试者进行了全基因组关联研究 (GWAS) 和全基因组相互作用研究，研究T-tau/a ß 42比率作为AD成像定量性状，并在ADNI队列中563,980单核苷酸多态性 (snp)。我们的目标是不仅确定具有显着主效应的snp，而且还确定具有相互作用效应的snp，以帮助解释 “缺失遗传力”。线性回归方法用于检测来自GWAS的p值 ≤ 0.01的SNP之间的SNP-SNP相互作用。在两项研究中，年龄、性别和诊断均被视为协变量。GWAS结果复制了先前报道的AD相关基因APOE，APOC1和tom40，并鉴定了14个新基因，这些新基因显示了全基因组的统计意义。全基因组相互作用研究揭示了7对符合细胞大小标准且bonferroni校正的p值 ≤ 0.05的snp。正如我们所期望的那样，这些相互作用对都具有边际主效应，但解释了T-tau/a ß 42的相对高水平方差，表明它们与AD病理的潜在关联。

BACKGROUND & AIMS: OBJECTIVE:The pathologic validation of European Alzheimer's Disease Consortium Alzheimer's Disease Neuroimaging Initiative Center Harmonized Hippocampal Segmentation Protocol (HarP). METHODS:Temporal lobes of nine Alzheimer's disease (AD) and seven cognitively normal subjects were scanned post-mortem at 7 Tesla. Hippocampal volumes were obtained with HarP. Six-micrometer-thick hippocampal slices were stained for amyloid beta (Aβ), tau, and cresyl violet. Hippocampal subfields were manually traced. Neuronal counts, Aβ, and tau burden for each hippocampal subfield were obtained. RESULTS:We found significant correlations between hippocampal volume and Braak and Braak staging (ρ = -0.75, P = .001), tau (ρ = -0.53, P = .034), Aβ burden (ρ = -0.61, P = .012), and neuronal count (ρ = 0.77, P < .001). Exploratory subfield-wise significant associations were found for Aβ in Cornu Ammonis (CA)1 (ρ = -0.58, P = .019) and subiculum (ρ = -0.75, P = .001), tau in CA2 (ρ = -0.59, P = .016), and CA3 (ρ = -0.5, P = .047), and neuronal count in CA1 (ρ = 0.55, P = .028), CA3 (ρ = 0.65, P = .006), and CA4 (ρ = 0.76, P = .001). CONCLUSIONS:The observed associations provide pathological confirmation of hippocampal morphometry as a valid biomarker for AD and pathologic validation of HarP.

背景与目标：

BACKGROUND & AIMS: BACKGROUND:Patients with Mild Cognitive Impairment (MCI) are at high risk of progression to Alzheimer's dementia. Identifying MCI individuals with high likelihood of conversion to dementia and the associated biosignatures has recently received increasing attention in AD research. Different biosignatures for AD (neuroimaging, demographic, genetic and cognitive measures) may contain complementary information for diagnosis and prognosis of AD. METHODS:We have conducted a comprehensive study using a large number of samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to test the power of integrating various baseline data for predicting the conversion from MCI to probable AD and identifying a small subset of biosignatures for the prediction and assess the relative importance of different modalities in predicting MCI to AD conversion. We have employed sparse logistic regression with stability selection for the integration and selection of potential predictors. Our study differs from many of the other ones in three important respects: (1) we use a large cohort of MCI samples that are unbiased with respect to age or education status between case and controls (2) we integrate and test various types of baseline data available in ADNI including MRI, demographic, genetic and cognitive measures and (3) we apply sparse logistic regression with stability selection to ADNI data for robust feature selection. RESULTS:We have used 319 MCI subjects from ADNI that had MRI measurements at the baseline and passed quality control, including 177 MCI Non-converters and 142 MCI Converters. Conversion was considered over the course of a 4-year follow-up period. A combination of 15 features (predictors) including those from MRI scans, APOE genotyping, and cognitive measures achieves the best prediction with an AUC score of 0.8587. CONCLUSIONS:Our results demonstrate the power of integrating various baseline data for prediction of the conversion from MCI to probable AD. Our results also demonstrate the effectiveness of stability selection for feature selection in the context of sparse logistic regression.

背景与目标：

BACKGROUND & AIMS: BACKGROUND:Previous work examining normal controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) identified substantial biological heterogeneity. We hypothesized that ADNI mild cognitive impairment (MCI) subjects would also exhibit heterogeneity with possible clinical implications. METHODS:ADNI subjects diagnosed with amnestic MCI (n=138) were clustered based on baseline magnetic resonance imaging, cerebrospinal fluid, and serum biomarkers. The clusters were compared with respect to longitudinal atrophy, cognitive trajectory, and time to conversion. RESULTS:Four clusters emerged with distinct biomarker patterns: The first cluster was biologically similar to normal controls and rarely converted to Alzheimer's disease (AD) during follow-up. The second cluster had characteristics of early Alzheimer's pathology. The third cluster showed the most severe atrophy but barely abnormal tau levels and a substantial proportion converted to clinical AD. The fourth cluster appeared to be pre-AD and nearly all converted to AD. CONCLUSIONS:Subjects with MCI who were clinically similar showed substantial heterogeneity in biomarkers.

背景与目标：

BACKGROUND & AIMS: :We propose a framework for feature extraction from learned low-dimensional subspaces that represent inter-subject variability. The manifold subspace is built from data-driven regions of interest (ROI). The regions are learned via sparse regression using the mini-mental state examination (MMSE) score as an independent variable which correlates better with the actual disease stage than a discrete class label. The sparse regression is used to perform variable selection along with a re-sampling scheme to reduce sampling bias. We then use the learned manifold coordinates to perform visualization and classification of the subjects. Results of the proposed approach are shown using the ADNI and ADNI-GO datasets. Three types of classification techniques, including a new MRI Disease-State-Score (MRI-DSS) classifier, are tested in conjunction with two learning strategies. In the first case Alzheimer's Disease (AD) and progressive mild cognitive impairment (pMCI) subjects were grouped together, while cognitive normal (CN) and stable mild cognitive impaired (sMCI) subjects were also grouped together. In the second approach, the classifiers are learned using the original class labels (with no grouping). We show results that are comparable to other state-of-the-art methods. A classification rate of 71%, of arguably the most clinically relevant subjects, sMCI and pMCI, is shown. Additionally, we present classification accuracies between CN and early MCI (eMCI) subjects, from the ADNI-GO dataset, of 65%. To our knowledge this is the first time classification accuracies for eMCI patients have been reported.

背景与目标： : 我们提出了一个从学习的低维子空间中提取特征的框架，这些子空间表示主体间的可变性。流形子空间是从数据驱动的感兴趣区域 (ROI) 构建的。使用迷你精神状态检查 (MMSE) 得分作为自变量，通过稀疏回归来学习区域，该自变量与实际疾病阶段的相关性比离散类标签更好。稀疏回归用于执行变量选择以及重新抽样方案，以减少抽样偏差。然后，我们使用学习的流形坐标对主题进行可视化和分类。使用ADNI和ADNI-GO数据集显示了所提出方法的结果。结合两种学习策略测试了三种类型的分类技术，包括新的MRI疾病状态评分 (mri-dss) 分类器。在第一种情况下，阿尔茨海默氏病 (AD) 和进行性轻度认知障碍 (pMCI) 受试者被分组在一起，而认知正常 (CN) 和稳定的轻度认知障碍 (sMCI) 受试者也被分组在一起。在第二种方法中，使用原始类标签 (不分组) 学习分类器。我们展示的结果与其他最先进的方法相当。显示了可以说是最临床相关的受试者sMCI和pMCI的71% 的分类率。此外，我们从65% 的ADNI-GO数据集介绍了CN和早期MCI (eMCI) 受试者之间的分类准确性。据我们所知，这是首次报道eMCI患者的分类准确性。

BACKGROUND & AIMS: :We investigated the genome-wide distribution of CNVs in the Alzheimer's disease (AD) Neuroimaging Initiative (ADNI) sample (146 with AD, 313 with Mild Cognitive Impairment (MCI), and 181 controls). Comparison of single CNVs between cases (MCI and AD) and controls shows overrepresentation of large heterozygous deletions in cases (p-value<0.0001). The analysis of CNV-Regions identifies 44 copy number variable loci of heterozygous deletions, with more CNV-Regions among affected than controls (p=0.005). Seven of the 44 CNV-Regions are nominally significant for association with cognitive impairment. We validated and confirmed our main findings with genome re-sequencing of selected patients and controls. The functional pathway analysis of the genes putatively affected by deletions of CNV-Regions reveals enrichment of genes implicated in axonal guidance, cell-cell adhesion, neuronal morphogenesis and differentiation. Our findings support the role of CNVs in AD, and suggest an association between large deletions and the development of cognitive impairment.

背景与目标： : 我们调查了阿尔茨海默氏病 (AD) 神经成像倡议 (ADNI) 样品 (与AD 146，轻度认知障碍 (MCI) 313和181对照) 中cnv的全基因组分布。病例 (MCI和AD) 和对照之间的单个cnv的比较显示病例中大杂合缺失的过度表示 (p值 <0.0001)。对CNV区的分析确定了44个杂合缺失的拷贝数可变基因座，受影响的CNV区比对照组更多 (p = 0.005)。44个CNV区域中有7个名义上与认知障碍相关。我们通过对选定的患者和对照组进行基因组重新测序来验证和证实我们的主要发现。对受CNV区缺失影响的基因的功能途径分析揭示了与轴突引导，细胞-细胞粘附，神经元形态发生和分化有关的基因的富集。我们的发现支持CNVs在AD中的作用，并表明大量缺失与认知障碍的发展之间存在关联。

BACKGROUND & AIMS: OBJECTIVE:To determine the optimal accumulation time for three-dimensional positron emission tomography (3D-PET) with (18)F-2-fluoro-2-deoxy-D-glucose ((18)F-FDG) to detect the brain uptake pattern typical of Alzheimer's disease (AD). METHODS:Patients with mild AD or amnestic mild cognitive impairment (MCI) and normal control subjects were recruited in the Japanese Alzheimer's disease neuroimaging initiative and examined with a PET scan during the 30-60 min after FDG injection. Three independent blinded experts interpreted the 30- to 60-min sum images, and images of patients with AD and MCI presenting AD patterns and normal subjects presenting normal patterns were used in the analysis. Early-scan (ES) and late-scan (LS) images were obtained from the data acquired at 30-35 min and 55-60 min after the injection, respectively. Separate target regions of interest (ROI) for ES and LS were defined as areas of significant reductions in the posterior cingulate and parietotemporal lobe in both hemispheres from the results of an initial cohort with 21 patients (AD 16, MCI 5) and 19 controls. A subsequent sample of 36 (AD 9, MCI 27) patients and 38 controls were used to compare the diagnostic capability of ES and LS using Z scores within the target ROI in individual statistical parametric mapping analysis. RESULTS:Compared to LS, ES showed lower activity in the frontal lobes and higher activity in the venous sinus than LS; however, the diagnostic capability of ES and LS did not significantly differ (sensitivity 0.97 and 0.97, specificity 0.82 and 0.84, area under the receiver-operating characteristic curve 0.96 and 0.97, respectively). CONCLUSIONS:For a qualitative diagnosis of the AD pattern in 3D FDG-PET, results of ES were equivalent to those of LS. ES may be an option to shorten the entire PET procedure time, particularly in diagnosing early stages of AD.

背景与目标：

BACKGROUND & AIMS: :Analysis of data derived from the Alzheimer's Disease Neuroimaging Initiative (ADNI) program showed plasma leptin levels in individuals with Mild Cognitive Impairment (MCI) or Alzheimer's disease (AD) to be lower than those of subjects with normal cognition (NC). Approximately 70% of both men and women with MCI have plasma leptin levels lower than the median values of NC. Additionally, half of these subjects carry at least one apolipoprotein-E4 (APOE-ε4) allele. A subgroup of participants also had cerebrospinal fluid (CSF) leptin measured. Plasma leptin typically reflected the levels of leptin in CSF in all groups (Control/MCI/AD) in both genders. The data suggest that plasma leptin deficiency provides an indication of potential CNS leptin deficiency, further supporting the exploration of plasma leptin as a diagnostic marker for MCI or AD. The important question is whether leptin deficiency plays a role in the causation of AD and/or its progression. If this is the case, individuals with early AD or MCI with low plasma leptin may benefit from leptin replacement therapy. Thus, these data indicate that trials of leptin in low leptin MCI/early-stage AD patients should be conducted to test the hypothesis.

背景与目标： : 对来自阿尔茨海默氏病神经影像倡议 (ADNI) 计划的数据进行的分析显示，患有轻度认知障碍 (MCI) 或阿尔茨海默氏病 (AD) 的个体的血浆瘦素水平低于具有正常认知 (NC) 的受试者。患有MCI的男性和女性中约有70% 的血浆瘦素水平低于NC的中值。此外，这些受试者中有一半携带至少一个apolipoprotein-E4 (APOE-ε4) 等位基因。一组参与者还测量了脑脊液 (CSF) 瘦素。血浆瘦素通常反映男女所有组 (对照组/MCI/AD) 中CSF中的瘦素水平。数据表明，血浆瘦素缺乏症提供了潜在的CNS瘦素缺乏症的指示，进一步支持血浆瘦素作为MCI或AD的诊断标志物的探索。重要的问题是瘦素缺乏症是否在AD的病因和/或其进展中起作用。如果是这种情况，患有早期AD或MCI且血浆瘦素低的个体可能会从瘦素替代治疗中受益。因此，这些数据表明，应该对低瘦素MCI/早期AD患者进行瘦素试验以检验这一假设。

BACKGROUND & AIMS: OBJECTIVES:CSF levels of Aβ1-42, t-tau, and p-tau181p are potential early diagnostic markers for probable Alzheimer disease (AD). The influence of genetic variation on these markers has been investigated for candidate genes but not on a genome-wide basis. We report a genome-wide association study (GWAS) of CSF biomarkers (Aβ1-42, t-tau, p-tau181p, p-tau181p/Aβ1-42, and t-tau/Aβ1-42). METHODS:A total of 374 non-Hispanic Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative cohort with quality-controlled CSF and genotype data were included in this analysis. The main effect of single nucleotide polymorphisms (SNPs) under an additive genetic model was assessed on each of 5 CSF biomarkers. The p values of all SNPs for each CSF biomarker were adjusted for multiple comparisons by the Bonferroni method. We focused on SNPs with corrected p<0.01 (uncorrected p<3.10×10(-8)) and secondarily examined SNPs with uncorrected p values less than 10(-5) to identify potential candidates. RESULTS:Four SNPs in the regions of the APOE, LOC100129500, TOMM40, and EPC2 genes reached genome-wide significance for associations with one or more CSF biomarkers. SNPs in CCDC134, ABCG2, SREBF2, and NFATC4, although not reaching genome-wide significance, were identified as potential candidates. CONCLUSIONS:In addition to known candidate genes, APOE, TOMM40, and one hypothetical gene LOC100129500 partially overlapping APOE; one novel gene, EPC2, and several other interesting genes were associated with CSF biomarkers that are related to AD. These findings, especially the new EPC2 results, require replication in independent cohorts.

背景与目标：

BACKGROUND & AIMS: BACKGROUND:Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally. OBJECTIVE:To characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures. METHODS:A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials. RESULTS:The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures. CONCLUSION:The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.

背景与目标：

BACKGROUND & AIMS: :Careful selection of the reference region for non-quantitative positron emission tomography (PET) analyses is critically important for Region of Interest (ROI) data analyses. We introduce an empirical method of deriving the most suitable reference region for computing neurodegeneration sensitive (18)fluorodeoxyglucose (FDG) PET ratios based on the dataset collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Candidate reference regions are selected based on a heat map of the difference in coefficients of variation (COVs) of FDG ratios over time for each of the Automatic Anatomical Labeling (AAL) atlas regions normalized by all other AAL regions. Visual inspection of the heat map suggests that the portion of the cerebellum and vermis superior to the horizontal fissure is the most sensitive reference region. Analyses of FDG ratio data show increases in significance on the order of ten-fold when using the superior portion of the cerebellum as compared with the traditionally used full cerebellum. The approach to reference region selection in this paper can be generalized to other radiopharmaceuticals and radioligands as well as to other disorders where brain changes over time are hypothesized and longitudinal data is available. Based on the empirical evidence presented in this study, we demonstrate the usefulness of the COV heat map method and conclude that intensity normalization based on the superior portion of the cerebellum may be most sensitive to measuring change when performing longitudinal analyses of FDG-PET ratios as well as group comparisons in Alzheimer's disease. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

背景与目标： : 对于非定量正电子发射断层扫描 (PET) 分析，仔细选择参考区域对于感兴趣区域 (ROI) 数据分析至关重要。我们介绍了一种基于阿尔茨海默氏病神经影像倡议 (ADNI) 研究收集的数据集得出最合适的参考区域的经验方法，用于计算神经变性敏感 (18) 氟脱氧葡萄糖 (FDG) PET比率。基于由所有其他AAL区域归一化的每个自动解剖标记 (AAL) 图谱区域的FDG比率的变异系数 (cov) 随时间的差异的热图来选择候选参考区域。对热图的目视检查表明，小脑和ver部高于水平裂的部分是最敏感的参考区域。FDG比率数据的分析表明，与传统使用的全小脑相比，使用小脑的上部分的显着性增加了十倍。本文中参考区域选择的方法可以推广到其他放射性药物和放射性配体，以及其他假设大脑随时间变化且可获得纵向数据的疾病。基于本研究中提出的经验证据，我们证明了COV热图方法的有用性，并得出结论，当对fdg-pet进行纵向分析时，基于小脑上部的强度归一化可能对测量变化最敏感。以及阿尔茨海默氏病的组比较。本文是题为 “脑老化和神经退行性疾病的成像” 的特刊的一部分。

BACKGROUND & AIMS: :The European Union AddNeuroMed program and the US-based Alzheimer Disease Neuroimaging Initiative (ADNI) are two large multi-center initiatives designed to collect and validate biomarker data for Alzheimer's disease (AD). Both initiatives use the same MRI data acquisition scheme. The current study aims to compare and combine magnetic resonance imaging (MRI) data from the two study cohorts using an automated image analysis pipeline and a multivariate data analysis approach. We hypothesized that the two cohorts would show similar patterns of atrophy, despite demographic differences and could therefore be combined. MRI scans were analyzed from a total of 1074 subjects (AD=295, MCI=444 and controls=335) using Freesurfer, an automated segmentation scheme which generates regional volume and regional cortical thickness measures which were subsequently used for multivariate analysis (orthogonal partial least squares to latent structures (OPLS)). OPLS models were created for the individual cohorts and for the combined cohort to discriminate between AD patients and controls. The ADNI cohort was used as a replication dataset to validate the model created for the AddNeuroMed cohort and vice versa. The combined cohort model was used to predict conversion to AD at baseline of MCI subjects at 1 year follow-up. The AddNeuroMed, the ADNI and the combined cohort showed similar patterns of atrophy and the predictive power was similar (between 80 and 90%). The combined model also showed potential in predicting conversion from MCI to AD, resulting in 71% of the MCI converters (MCI-c) from both cohorts classified as AD-like and 60% of the stable MCI subjects (MCI-s) classified as control-like. This demonstrates that the methods used are robust and that large data sets can be combined if MRI imaging protocols are carefully aligned.

背景与目标： : 欧盟AddNeuroMed计划和美国的阿尔茨海默氏病神经成像计划 (ADNI) 是两个大型多中心计划，旨在收集和验证阿尔茨海默氏病 (AD) 的生物标志物数据。两种计划都使用相同的MRI数据采集方案。当前的研究旨在使用自动图像分析管道和多变量数据分析方法比较和组合来自两个研究队列的磁共振成像 (MRI) 数据。我们假设，尽管人口统计学存在差异，但这两个队列将显示相似的萎缩模式，因此可以合并。使用Freesurfer对总共1074名受试者 (AD = 295，MCI = 444和对照组 = 335) 的MRI扫描进行分析，Freesurfer是一种自动分割方案，其生成区域体积和区域皮质厚度测量，随后将其用于多变量分析 (正交偏最小二乘法到潜在结构 (OPLS))。为各个队列和组合队列创建了OPLS模型，以区分AD患者和对照组。ADNI队列用作复制数据集，以验证为AddNeuroMed队列创建的模型，反之亦然。联合队列模型用于预测MCI受试者在1年随访时的基线转换为AD。Adneuromed，ADNI和联合队列显示出相似的萎缩模式，并且预测能力相似 (介于80和90% 之间)。组合模型还显示出预测从MCI到AD的转化的潜力，导致来自被分类为AD-like的两个队列的MCI转换器 (MCI-c) 的71% 和被分类为对照-like的稳定MCI受试者 (MCI-s) 的60%。这表明所使用的方法是可靠的，并且如果仔细对齐MRI成像协议，则可以组合大数据集。

BACKGROUND & AIMS: :Rates of brain atrophy derived from serial magnetic resonance (MR) studies may be used to assess therapies for Alzheimer's disease (AD). These measures may be confounded by changes in scanner voxel sizes. For this reason, the Alzheimer's Disease Neuroimaging Initiative (ADNI) included the imaging of a geometric phantom with every scan. This study compares voxel scaling correction using a phantom with correction using a 9 degrees of freedom (9DOF) registration algorithm. We took 129 pairs of baseline and 1-year repeat scans, and calculated the volume scaling correction, previously measured using the phantom. We used the registration algorithm to quantify any residual scaling errors, and found the algorithm to be unbiased, with no significant (p=0.97) difference between control (n=79) and AD subjects (n=50), but with a mean (SD) absolute volume change of 0.20 (0.20) % due to linear scalings. 9DOF registration was shown to be comparable to geometric phantom correction in terms of the effect on atrophy measurement and unbiased with respect to disease status. These results suggest that the additional expense and logistic effort of scanning a phantom with every patient scan can be avoided by registration-based scaling correction. Furthermore, based upon the atrophy rates in the AD subjects in this study, sample size requirements would be approximately 10-12% lower with (either) correction for voxel scaling than if no correction was used.

背景与目标： : 来自连续磁共振 (MR) 研究的脑萎缩率可用于评估阿尔茨海默氏病 (AD) 的治疗方法。这些措施可能会因扫描仪体素大小的变化而混淆。因此，阿尔茨海默氏病神经成像计划 (ADNI) 每次扫描都包括几何体模的成像。本研究比较了使用体模的体素缩放校正与使用9自由度 (9DOF) 配准算法的校正。我们进行了129对基线和1年重复扫描，并计算了先前使用体模测量的体积缩放校正。我们使用配准算法来量化任何残余缩放误差，发现该算法是无偏的，对照 (n = 79) 和AD受试者 (n = 50) 之间没有显着 (p = 0.97) 差异，但由于线性定标，平均 (SD) 绝对体积变化为0.20 (0.20) %。就萎缩测量的影响而言，9DOF配准与几何体模校正相当，并且在疾病状态方面没有偏见。这些结果表明，通过基于配准的缩放校正可以避免每次患者扫描时扫描幻影的额外费用和后勤工作。此外，基于本研究中AD受试者的萎缩率，与不使用校正的情况相比，使用 (任一) 体素标度校正的样本量要求将低约10-12%。

BACKGROUND & AIMS: :The goal of this work was to assess statistical power to detect treatment effects in Alzheimer's disease (AD) clinical trials using magnetic resonance imaging (MRI)-derived brain biomarkers. We used unbiased tensor-based morphometry (TBM) to analyze n = 5,738 scans, from Alzheimer's Disease Neuroimaging Initiative 2 participants scanned with both accelerated and nonaccelerated T1-weighted MRI at 3T. The study cohort included 198 healthy controls, 111 participants with significant memory complaint, 182 with early mild cognitive impairment (EMCI) and 177 late mild cognitive impairment (LMCI), and 155 AD patients, scanned at screening and 3, 6, 12, and 24 months. The statistical power to track brain change in TBM-based imaging biomarkers depends on the interscan interval, disease stage, and methods used to extract numerical summaries. To achieve reasonable sample size estimates for potential clinical trials, the minimal scan interval was 6 months for LMCI and AD and 12 months for EMCI. TBM-based imaging biomarkers were not sensitive to MRI scan acceleration, which gave results comparable with nonaccelerated sequences. ApoE status and baseline amyloid-beta positron emission tomography data improved statistical power. Among healthy, EMCI, and LMCI participants, sample size requirements were significantly lower in the amyloid+/ApoE4+ group than for the amyloid-/ApoE4- group. ApoE4 strongly predicted atrophy rates across brain regions most affected by AD, but the remaining 9 of the top 10 AD risk genes offered no added predictive value in this cohort.

背景与目标： : 这项工作的目的是评估使用磁共振成像 (MRI) 衍生的脑生物标志物在阿尔茨海默氏病 (AD) 临床试验中检测治疗效果的统计能力。我们使用基于无偏张量的形态计量学 (TBM) 来分析n = 5,738次扫描，这些扫描来自阿尔茨海默氏病神经成像倡议2参与者，在3T时使用加速和非加速T1-weighted MRI扫描。该研究队列包括198名健康对照者，111名具有明显记忆不适的参与者，早期轻度认知障碍 (EMCI) 和177晚期轻度认知障碍 (LMCI) 的182，以及155名AD患者，在筛查和3、6、12和24个月时进行扫描。在基于TBM的成像生物标志物中跟踪大脑变化的统计能力取决于扫描间隔，疾病阶段以及用于提取数值摘要的方法。为了获得潜在临床试验的合理样本量估计，LMCI和AD的最小扫描间隔为6个月，EMCI为12个月。基于TBM的成像生物标志物对MRI扫描加速不敏感，其结果与非加速序列相当。ApoE状态和基线淀粉样蛋白-β 正电子发射断层扫描数据提高了统计能力。在健康、EMCI和LMCI参与者中，淀粉样蛋白 +/ApoE4 + 组的样本量要求显著低于淀粉样蛋白/ApoE4-组.ApoE4强烈预测了受AD影响最大的大脑区域的萎缩率，但在该队列中，前10个AD风险基因中的其余9个没有提供额外的预测价值。

BACKGROUND & AIMS: :The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's disease. Magnetic resonance imaging (MRI), (18F)-fluorodeoxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquired at multiple time points. All data will be cross-linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications that guided protocol development. A major effort was devoted to evaluating 3D T(1)-weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced-scale clinical trial. The protocol selected for the ADNI study includes: back-to-back 3D magnetization prepared rapid gradient echo (MP-RAGE) scans; B(1)-calibration scans when applicable; and an axial proton density-T(2) dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom-based monitoring of all scanners could be used as a model for other multisite trials.

背景与目标： : 阿尔茨海默氏病神经影像学倡议 (ADNI) 是一项针对健康老年人，轻度认知障碍 (MCI) 和阿尔茨海默氏病的纵向多站点观察研究。在多个时间点获得磁共振成像 (MRI)，(18F)-氟脱氧葡萄糖正电子发射断层扫描 (FDG PET)，尿液血清和脑脊液 (CSF) 生物标志物以及临床/心理评估。所有数据都将相互链接，并提供给一般科学界。本报告的目的是描述ADNI中使用的MRI方法。ADNI MRI核心建立了指导协议开发的规范。致力于评估3D T(1) 加权序列以进行形态计量分析。针对该序列的几种选择已针对相关制造商平台进行了优化，然后在缩减规模的临床试验中进行了比较。为ADNI研究选择的协议包括: 背靠背3D磁化准备的快速梯度回波 (MP-RAGE) 扫描; B(1)-适用时的校准扫描; 和轴向质子密度-T(2) 双重对比度 (即，echo) 快速自旋回波/turbo自旋回波 (FSE/TSE) 用于病理检测。ADNI MRI方法寻求最大程度地提高科学效用，同时最大程度地减少参与者的负担。ADNI采取的跨MRI协议的站点和平台标准化，采集后校正和所有扫描仪的基于幻影的监视的方法可以用作其他多站点试验的模型。