Measuring the degree of spatial correlation between histological features in thin sections of brain tissue

Abstract

Histological features visible in thin sections of brain tissue, such as neuronal perikarya, blood vessels, or pathological lesions may exhibit a degree of spatial association or correlation. In neurodegenerative disorders such as AD, Pick's disease, and CJD, information on whether different types of pathological lesion are spatially correlated may be useful in elucidating disease pathogenesis. In the present article the statistical methods available for studying spatial association in histological sections are reviewed. These include tests of interspecific association between two or more histological features using chi2 contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, the use of correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

Spatial patterns of the tau pathology in progressive supranuclear palsy

“…The frequencies of the different types of spatial pattern were compared between cortical and subcortical regions using chi-square ( 2 ) contingency table tests. Spatial correlations between histological features were tested for each region by calculating Pearson's correlation coefficient ('r') between the densities measured parallel to the tissue boundary for each region [39].…”

Classic β-Amyloid Deposits Cluster Around Large Diameter Blood Vessels Rather than Capillaries in Sporadic Alzheimers Disease

“…Regularly spaced clusters are indicated by a V/M peak, the location of the peak corresponding to the mean dimension of the clusters. To determine whether the spatial distribution of the Aβ deposits is related to blood vessels, the degree of correlation between the density of Aβ deposits and the frequency of contacts with the blood vessel profiles was tested at each field size using Pearson's correlation coefficient (Armstrong, 2003).…”

Quantitative pathological changes in the cerebellum of multiple system atrophy

“…whether the feature was distributed randomly, regularly, or in clusters, was determined using the variance/mean (V/M) method described previously [1,2,5,6]. Third, spatial correlations between histological features along the folia were tested in each case using Pear son's correlation coefficient ('r') [4]. Fourth, to study pathological variation among cases, the data were analysed using principal components analysis (PCA) [11].…”