Marschallinger Robert, Tur Carmen, Marschallinger Hannes, Sellner Johann
Department of Geoinformatics, University of Salzburg, Schillerstr 30, 5020 Salzburg, Austria.
Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Ignaz-Harrer Str. 79, 5020 Salzburg, Austria.
Brain Sci. 2021 Jan 12;11(1):90. doi: 10.3390/brainsci11010090.
One significant characteristic of Multiple Sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is the evolution of highly variable patterns of white matter lesions. Based on geostatistical metrics, the MS-Lesion Pattern Discrimination Plot reduces complex three- and four-dimensional configurations of MS-White Matter Lesions to a well-arranged and standardized two-dimensional plot that facilitates follow-up, cross-sectional and medication impact analysis. Here, we present a script that generates the MS-Lesion Pattern Discrimination Plot, using the widespread statistical computing environment R. Input data to the script are Nifti-1 or Analyze-7.5 files with individual MS-White Matter Lesion masks in Montreal Normal Brain geometry. The MS-Lesion Pattern Discrimination Plot, variogram plots and associated fitting statistics are output to the R console and exported to standard graphics and text files. Besides reviewing relevant geostatistical basics and commenting on implementation details for smooth customization and extension, the paper guides through generating MS-Lesion Pattern Discrimination Plots using publicly available synthetic MS-Lesion patterns. The paper is accompanied by the R script , a small sample data set and associated graphics for comparison.
多发性硬化症(MS)是一种中枢神经系统的慢性炎症性脱髓鞘疾病,其一个显著特征是白质病变模式高度可变。基于地理统计指标,MS病变模式判别图将MS白质病变复杂的三维和四维构型简化为一个排列整齐且标准化的二维图,便于进行随访、横断面和药物影响分析。在此,我们展示一个使用广泛应用的统计计算环境R生成MS病变模式判别图的脚本。该脚本的输入数据是具有蒙特利尔正常脑几何结构中单个MS白质病变掩码的Nifti-1或Analyze-7.5文件。MS病变模式判别图、变异函数图及相关拟合统计量输出到R控制台,并导出为标准图形和文本文件。除了回顾相关地理统计基础知识并对实现细节进行注释以实现顺畅定制和扩展外,本文还指导如何使用公开可用的合成MS病变模式生成MS病变模式判别图。本文还附带了R脚本、一个小样本数据集及相关图形以供比较。