SPATIAL AND STRUCTURAL COMPLEXITY OF CEREBRAL HEMISPHERES IN MALE AND FEMALE BRAIN: FRACTAL AND QUANTITATIVE ANALYSES OF MRI BRAIN SCANS
Abstract
Objectives: The aim of the present study was to compare the features of the structural complexity of the cerebral hemispheres in men and women using fractal analysis of outlined and skeletonized images, as well as quantitative analysis of digital skeletons of the cerebral hemispheres. Material and Methods: Magnetic resonance imaging brain scans of 100 individuals aged 18-86 years (44 males and 56 females) were investigated. Five tomographic sections of each brain were selected for morphometric study (4 coronal and 1 axial sections). The sections were preprocessed, and outlined and skeletonized images were obtained. Fractal analysis was conducted using the two-dimensional box counting method, and fractal dimensions of outlined and skeletonized images were determined. Additionally, quantitative analysis of skeletonized images was performed, determining the following parameters: branches, junctions, end-point voxels, junction voxels, slab voxels, triple points, quadruple points, average branch length, and maximum branch length. Results: We observed that both variants of fractal dimension in males and females did not show significant differences, although most quantitative parameters in males were larger than those in females. Conclusions: The spatial and structural complexity of the cerebral hemispheres, as characterized by fractal dimensions, is almost indistinguishable between males and females. However, in some individual tomographic sections, the male brain may exhibit a slightly higher number of end-point voxels, corresponding to the gyri of the cerebral hemispheres. The obtained data can be used in clinical practice for diagnostic purposes (e.g., for detecting malformations) and for theoretical studies in neuroanatomy.
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Malformations of cortical development (MCDs) encompass a variety of brain disorders affecting the normal development and organization of the brain cortex. The relatively low incidence and the extreme heterogeneity of these disorders hamper the application of classical group level approaches for the detection of lesions. Here, we present a geometrical descriptor for a voxel level analysis based on fractal geometry, then define two similarity measures to detect the lesions at single subject level. The pipeline was applied to 15 normal children and nine pediatric patients affected by MCDs following two criteria, maximum accuracy (WACC) and minimization of false positives (FPR), and proved that our lesion detection algorithm is able to detect and locate abnormalities of the brain cortex with high specificity (WACC = 85%, FPR = 96%), sensitivity (WACC = 83%, FPR = 63%) and accuracy (WACC = 85%, FPR = 90%). The combination of global and local features proves to be effective, making the algorithm suitable for the detection of both focal and diffused malformations. Compared to other existing algorithms, this method shows higher accuracy and sensitivity.
To observe age- and sex-related differences in the complexity of the global and hemispheric white matter (WM) throughout adulthood by means of fractal dimension (FD).
A box-counting algorithm was used to extract FD from the WM magnetic resonance images of 209 healthy adults from three structural layers, including general (gFD), skeleton (sFD), and boundaries (bFD). Model selection algorithms and statistical analyses, respectively, were used to examine the patterns and significance of the changes.
gFD and sFD showed inverse U-shape patterns with aging, with a slighter slope of increase from young to mid-age and a steeper decrease to the old. bFD was less affected by age. Sex differences were evident, specifically in gFD and sFD, with men showing higher FDs. Age × sex interaction was significant mainly in the hemispheric analysis, with men undergoing sharper age-related changes. After adjusting for the volume effect, age-related results remained approximately the same, but sex differences changed in most of the features, with women indicating higher values, specifically in the left hemisphere and boundaries. Right hemisphere was still more complex in men.
This study is the first that investigates the WM FD spanning adulthood, treating age both as a continuous and categorical variable. We found positive correlations between FD and volume, and our results show similarities with those investigating small-world properties of the brain networks, as well as those of functional complexity and WM integrity. These suggest that FD could yield a highly compact description of the structural changes and also might inform us about functional and cognitive variations.
Many major neuropsychiatric pathologies, some of which appear in adolescence, show differentiated prevalence, onset, and symptomatology across the biological sexes. Therefore, mapping differences in brain structure between males and females during this critical developmental period may provide information about the neural mechanisms underlying the dimorphism of these pathologies. Utilizing a large dataset collected through the Adolescent Brain Cognitive Development study, we investigated the differences of adolescent (9-10 years old) male and female brains (n = 8325) by using a linear Support-Vector Machine Classifier to predict sex based on morphometry and image intensity values of structural brain imaging data. The classifier correctly classified the sex of 86% individuals with the insula, the precentral and postcentral gyri, and the pericallosal sulcus as the most discernable features. These results demonstrate the existence of complex, yet robustly observable morphometrical brain markers of sex difference.
- Di Ieva
- A Esteban
- F J Grizzi
- F Klonowski
- W Martín-Landrove
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