Interpreting tissue architecture plays an important role in gaining a better understanding of healthy tissue development and disease. Novel molecular detection and imaging techniques make it possible to locate many different types of objects, such as cells and/or mRNAs, and map their location across the tissue space. In this review, we present several methods that provide quantification and statistical verification of observed patterns in the tissue architecture. We categorize these methods into three main groups: Spatial statistics on a single type of object, two types of objects, and multiple types of objects. We discuss the methods in relation to four hypotheses regarding the methods' capability to distinguish random and non-random distributions of objects across a tissue sample, and present a number of openly available tools where these methods are provided. We also discuss other spatial statistics methods compatible with other types of input data.

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Highlights Possible favorable factors for glioma infiltration were investigated with MRI, TEM and DTI analysis. The infiltration of white matter bundles (WMB) displayed regional differences in three gliomaś subgroups. Regional differences within the same WMB were detected by morphological (TEM) and DTI analysis. HIF regions, common to all gliomas subgroups, displayed a smaller fiber diameter, lower FA and higher RD. Morphological features and diffusion parameters of the VMB may be linked to preferential locations of gliomas.