Borys Damian, Kijonka Marek, Psiuk-Maksymowicz Krzysztof, Gorczewski Kamil, Zarudzki Lukasz, Sokol Maria, Swierniak Andrzej
Faculty of Automatic Control, Electronics and Computer Science, Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland.
Biotechnology Center, Silesian University of Technology, Gliwice, Poland.
Front Neuroinform. 2021 Oct 6;15:684759. doi: 10.3389/fninf.2021.684759. eCollection 2021.
The application of magnetic resonance imaging (MRI) to acquire detailed descriptions of the brain morphology is a driving force in brain mapping research. Most atlases are based on parametric statistics, however, the empirical results indicate that the population brain tissue distributions do not exhibit exactly a Gaussian shape. Our aim was to verify the population voxel-wise distribution of three main tissue classes: gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), and to construct the brain templates for the Polish (Upper Silesian) healthy population with the associated non-parametric tissue probability maps (TPMs) taking into account the sex and age influence. The voxel-wise distributions of these tissues were analyzed using the Shapiro-Wilk test. The non-parametric atlases were generated from 96 brains of the ethnically homogeneous, neurologically healthy, and radiologically verified group examined in a 3-Tesla MRI system. The standard parametric tissue proportion maps were also calculated for the sake of comparison. The maps were compared using the Wilcoxon signed-rank test and Kolmogorov-Smirnov test. The volumetric results segmented with the parametric and non-parametric templates were also analyzed. The results confirmed that in each brain structure (regardless of the studied sub-population) the data distribution is skewed and apparently not Gaussian. The determined non-parametric and parametric templates were statistically compared, and significant differences were found between the maps obtained using both measures (the maps of GM, WM, and CSF). The impacts of applying the parametric and non-parametric TPMs on the segmentation process were also compared. The GM volumes are significantly greater when using the non-parametric atlas in the segmentation procedure, while the CSF volumes are smaller. To determine the population atlases the parametric measures are uncritically and widely used. However, our findings suggest that the mean and parametric measures of such skewed distribution may not be the most appropriate summary statistic to find the best spatial representations of the structures in a standard space. The non-parametric methodology is more relevant and universal than the parametric approach in constructing the MRI brain atlases.
应用磁共振成像（MRI）获取大脑形态的详细描述是脑图谱研究的驱动力。然而，大多数图谱基于参数统计，而实证结果表明总体脑组织分布并非完全呈高斯形状。我们的目的是验证三种主要组织类型：灰质（GM）、白质（WM）和脑脊液（CSF）的总体体素分布，并构建考虑性别和年龄影响的波兰（上西里西亚）健康人群的脑模板以及相关的非参数组织概率图（TPM）。使用夏皮罗-威尔克检验分析这些组织的体素分布。非参数图谱由在3特斯拉MRI系统中检查的96例种族同质、神经健康且经放射学验证的人群的大脑生成。为了进行比较，还计算了标准参数组织比例图。使用威尔科克森符号秩检验和柯尔莫哥洛夫-斯米尔诺夫检验对这些图谱进行比较。还分析了用参数和非参数模板分割得到的体积结果。结果证实，在每个脑结构中（无论所研究的亚人群如何），数据分布都是偏态的，显然不是高斯分布。对确定的非参数和参数模板进行了统计学比较，发现在使用两种测量方法获得的图谱（GM、WM和CSF的图谱）之间存在显著差异。还比较了应用参数和非参数TPM对分割过程的影响。在分割过程中使用非参数图谱时，GM体积显著更大，而CSF体积更小。为了确定总体图谱，参数测量方法被不加批判地广泛使用。然而，我们的研究结果表明，对于这种偏态分布，均值和参数测量可能不是找到标准空间中结构最佳空间表示的最合适汇总统计量。在构建MRI脑图谱时，非参数方法比参数方法更相关、更通用。
