Shape of cerebral hemispheres: structural and spatial complexity. Quantitative analysis of skeletonized MR images

Abstract

For quantitative characterization of the complexity of the spatial configuration of anatomical structures, including cerebral hemispheres, fractal analysis is the most often used method, in addition to which, other methods of image analysis are quite promising, including quantitative analysis of skeletonized images. The purpose of the study was to determine the features of the structural and spatial complexity of the cerebral hemispheres shape using quantitative analysis of skeletonized magnetic resonance images of the cerebral hemispheres. Magnetic resonance brain images of 100 conditionally healthy individuals (who did not have structural changes in the brain) of both sexes (56 women, 44 men) aged 18-86 years (average age 41.72±1.58 years) were studied, 5 tomographic sections (4 coronal sections and 1 axial section) were selected from the set of tomographic images of each brain. During preprocessing, image segmentation was performed to obtain a binary silhouette image, after which silhouette skeletonizing was carried out. Quantitative analysis of skeletonized images included determination of the following parameters: branches, junctions, end-point voxels, junction voxels, slab voxels, triple points, quadruple points, average branch length, maximum branch length. We divided quantitative parameters of skeletonized images into two groups. The first group included branches, junctions, end-point voxels, junction voxels, slab voxels, triple points, quadruple points. These parameters were related to each other and to the values of the fractal dimension by positive correlations. The second group of parameters included average branch length, maximum branch length. These parameters were positively correlated, but they had negative correlations with most of the parameters of the first group and with fractal dimension values. Quantitative parameters and fractal dimension turned out to be better parameters for characterizing the spatial and structural complexity of the cerebral hemispheres shape than traditional morphometric parameters (area, perimeter and their derivatives). It was found that the values of most of the investigated quantitative parameters decreased with age; coronal sections were the most representative for characterizing age-related changes. Quantitative assessment of the brain shape, including spatial and structural complexity, can become an informative tool for the diagnosis of some nervous diseases and the differentiation of pathological and normal age-related changes.