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首页> 外文期刊>Journal of Neuroscience Methods >Assessing the reliability to detect cerebral hypometabolism in probable Alzheimer's disease and amnestic mild cognitive impairment.
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Assessing the reliability to detect cerebral hypometabolism in probable Alzheimer's disease and amnestic mild cognitive impairment.

机译：评估在可能的阿尔茨海默氏病和遗忘性轻度认知障碍中检测脑代谢不足的可靠性。

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Fluorodeoxyglucose positron emission tomography (FDG-PET) studies report characteristic patterns of cerebral hypometabolism in probable Alzheimer's disease (pAD) and amnestic mild cognitive impairment (aMCI). This study aims to characterize the consistency of regional hypometabolism in pAD and aMCI patients enrolled in the AD neuroimaging initiative (ADNI) using statistical parametric mapping (SPM) and bootstrap resampling, and to compare bootstrap-based reliability index to the commonly used type-I error approach with or without correction for multiple comparisons. Batched SPM5 was run for each of 1000 bootstrap iterations to compare FDG-PET images from 74 pAD and 142 aMCI patients, respectively, to 82 normal controls. Maps of the hypometabolic voxels detected for at least a specific percentage of times over the 1000 runs were examined and compared to an overlap of the hypometabolic maps obtained from 3 randomly partitioned independent sub-datasets. The results from the bootstrap derived reliability of regional hypometabolism in the overall data set were similar to that observed in each of the three non-overlapping sub-sets using family-wise error. Strong but non-linear association was found between the bootstrap-based reliability index and the type-I error. For threshold p=0.0005, pAD was associated with extensive hypometabolic voxels in the posterior cingulate/precuneus and parietotemporal regions with reliability between 90% and 100%. Bootstrap analysis provides an alternative to the parametric family-wise error approach used to examine consistency of hypometabolic brain voxels in pAD and aMCI patients. These results provide a foundation for the use of bootstrap analysis characterize statistical ROIs or search regions in both cross-sectional and longitudinal FDG-PET studies. This approach offers promise in the early detection and tracking of AD, the evaluation of AD-modifying treatments, and other biologically or clinical important measurements using brain images and voxel-based data analysis techniques.
机译：氟脱氧葡萄糖正电子发射断层扫描（FDG-PET）研究报告了可能的阿尔茨海默氏病（pAD）和轻度轻度认知障碍（aMCI）的脑代谢不足的特征性模式。这项研究的目的是使用统计参数映射（SPM）和自举重采样方法，对参与AD神经影像倡议（ADNI）的pAD和aMCI患者的区域性低代谢进行一致性研究，并将基于自举的可靠性指标与常用的I型进行比较带有或不带有多个比较的校正的错误方法。批量SPM5运行1000次自举迭代，分别将74位pAD和142位aMCI患者的FDG-PET图像与82位正常对照进行比较。检查在1000次运行中检测到的特定时间以上的代谢紊乱图谱，并将其与从3个随机分区的独立子数据集获得的代谢紊乱图谱的重叠进行比较。引导程序得出的总体数据集中区域代谢不足的可靠性与使用家庭误差在三个不重叠的子集中的每个观测到的结果相似。在基于引导程序的可靠性指标和I型错误之间发现了强烈但非线性的关联。对于阈值p = 0.0005，pAD与后扣带/前胎和顶颞区的广泛代谢不足体素相关，可靠性介于90％和100％之间。 Bootstrap分析提供了一种替代参数化家庭错误方法的方法，该方法用于检查pAD和aMCI患者中代谢不足的大脑体素的一致性。这些结果为使用引导分析表征横截面和纵向FDG-PET研究中的统计ROI或搜索区域提供了基础。这种方法为早期检测和追踪AD，评估AD修饰疗法以及使用脑图像和基于体素的数据分析技术提供的其他生物学或临床重要测量指标提供了希望。

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