Armstrong R A
Vision Sciences, Aston University, Birmingham, UK.
J Microsc. 2006 Mar;221(Pt 3):153-8. doi: 10.1111/j.1365-2818.2006.01559.x.
This article reviews the statistical methods that have been used to study the planar distribution, and especially clustering, of objects in histological sections of brain tissue. The objective of these studies is usually quantitative description, comparison between patients or correlation between histological features. Objects of interest such as neurones, glial cells, blood vessels or pathological features such as protein deposits appear as sectional profiles in a two-dimensional section. These objects may not be randomly distributed within the section but exhibit a spatial pattern, a departure from randomness either towards regularity or clustering. The methods described include simple tests of whether the planar distribution of a histological feature departs significantly from randomness using randomized points, lines or sample fields and more complex methods that employ grids or transects of contiguous fields, and which can detect the intensity of aggregation and the sizes, distribution and spacing of clusters. The usefulness of these methods in understanding the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Creutzfeldt-Jakob disease is discussed.
本文回顾了用于研究脑组织组织学切片中物体的平面分布,尤其是聚类的统计方法。这些研究的目的通常是定量描述、患者之间的比较或组织学特征之间的相关性。诸如神经元、胶质细胞、血管等感兴趣的物体或诸如蛋白质沉积物等病理特征在二维切片中表现为截面轮廓。这些物体在切片内可能不是随机分布的,而是呈现出一种空间模式,即偏离随机性,趋向于规则性或聚类。所描述的方法包括使用随机点、线或样本区域对组织学特征的平面分布是否显著偏离随机性进行简单测试,以及采用网格或连续区域样带的更复杂方法,这些方法可以检测聚集强度以及簇的大小、分布和间距。还讨论了这些方法在理解诸如阿尔茨海默病和克雅氏病等神经退行性疾病发病机制方面的作用。