Use of brain MRI atlases to determine boundaries of age-related pathology: the importance of statistical method.
Use of brain MRI atlases to determine boundaries of age-related pathology: the importance of statistical method.
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DOI：
10.1371/journal.pone.0127939
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Wardlaw JM
中科院分区：
文献类型：
--
作者：
Dickie DA;Job DE;Gonzalez DR;Shenkin SD;Wardlaw JM
神经退行性疾病的诊断可以通过将单个患者的脑磁共振图像(MRI)与正常脑MRI的基于体素的图谱进行比较来支持。目前的大多数脑MRI图谱都是年轻到中年的成年人和参数，例如均值±标准差(SD)；这些图谱要求数据为高斯。来自正常老年人的脑MRI数据，例如灰质(GM)比例图像，显然不是高斯的。我们创建了老年受试者GM比例正常范围的非参数和参数图谱，并比较了他们在阿尔茨海默病(AD)患者中GM比例的分类。使用138名正常受试者和138名确诊为AD患者(年龄均为55-90岁)的公开脑MRI数据，我们创建了一个均值±标准差图谱，用于参数估计正常衰老GM的百分位数等级和界限；以及，分别从相同的正常老龄化受试者中创建了一个非参数的、基于等级顺序的GM图谱。然后根据每个图谱对AD患者的GM图像进行分类，以确定统计分布对AD患者GM比例分类的影响。参数地图集经常将GM比例的正常下限定义为负值(这在生理学上没有意义，因为可能的最低比例为零)。因此，对于大约一半的AD受试者，与参数图谱相比，25%-45%的体素被归类为正常；但与非参数图谱相比，被归类为异常。这些体素主要集中在额叶和枕叶。据我们所知，我们已经提出了第一个非参数脑MRI图谱。在脑结构变异性增加的情况下，例如在老年，非参数脑MRI图谱可能比参数方法更准确地反映正常脑结构的极限。因此，我们认为，构建脑MRI图谱所使用的统计方法应该考虑到研究的人群和目标。参数方法对于定义大脑结构的中心趋势，例如，手段，通常是稳健的。在研究衰老和神经退行性疾病中大脑结构的极限时，非参数方法是可取的。
Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease.
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影响因子：
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Braak, H;Braak, E
通讯作者：
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