SPATIAL AND STRUCTURAL COMPLEXITY OF CEREBRAL HEMISPHERES IN MALE AND FEMALE BRAIN: FRACTAL AND QUANTITATIVE ANALYSES OF MRI BRAIN SCANS
DOI:
https://doi.org/10.31051/1852.8023.v15.n3.43151Keywords:
cerebrum, fractal dimension, gender, neuroimagingAbstract
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.
Downloads
References
Brennan D, Wu T, Fan J. 2021. Morphometrical brain markers of sex difference. Cerebral Cortex. 31(8):3641–3649.
De Luca A, Arrigoni F, Romaniello R, Triulzi FM, Peruzzo D, Bertoldo A. 2016. Automatic localization of cerebral cortical malformations using fractal analysis. Physics in Medicine and Biology. 61(16):6025–6040.
Di Ieva A, Esteban FJ, Grizzi F, Klonowski W, Martín-Landrove M. 2015. Fractals in the neurosciences, Part II: Clinical applications and future perspectives. The Neuroscientist. 21(1):30-43.
Farahibozorg S, Hashemi-Golpayegani SM, Ashburner J. 2015. Age- and sex-related variations in the brain white matter fractal dimension throughout adulthood: an MRI study. Clinical Neuroradiology. 25(1):19–32.
Goñi J, Sporns O, Cheng H, Aznárez-Sanado M, Wang Y, Josa S, Arrondo G, Mathews VP, Hummer TA, Kronenberger WG, Avena-Koenigsberger A, Saykin AJ, Pastor MA. 2013. Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility. NeuroImage. 83:646-657.
Ha TH, Yoon U, Lee KJ, Shin YW, Lee JM, Kim IY, Ha KS, Kim SI, Kwon JS. 2005. Fractal dimension of cerebral cortical surface in schizophrenia and obsessive-compulsive disorder. Neuroscience Letters. 384(1-2):172-176.
Hofman MA. 1991. The fractal geometry of convoluted brains. Journal of Hirnforschung. 32(1):103-111.
Im K, Lee JM, Yoon U, Shin YW, Hong SB, Kim IY, Kwon JS, Kim SI. 2006. Fractal dimension in human cortical surface: multiple regression analysis with cortical thickness, sulcal depth, and folding area. Human Brain Mapping. 27(12):994-1003.
Jelinek HF, Fernandez E. 1998. Neurons and fractals: how reliable and useful are calculations of fractal dimensions? Journal of Neuroscience Methods. 81(1-2):9-18.
Jiang S, Pan Z, Feng Z, Guan Y, Ren M, Ding Z, Chen S, Gong H, Luo Q, Li A. 2020. Skeleton optimization of neuronal morphology based on three-dimensional shape restrictions. BMC Bioinformatics. 21(1):395.
Kalmanti E, Maris TG. 2007. Fractal dimension as an index of brain cortical changes throughout life. In vivo. 21(4):641–646.
King RD, George AT, Jeon T, Hynan LS, Youn TS, Kennedy DN, Dickerson B; Alzheimer’s Disease Neuroimaging Initiative. 2009. Characterization of atrophic changes in the cerebral cortex using fractal dimensional analysis. Brain Imaging and Behavior. 3(2):154-166.
Király A, Szabó N, Tóth E, Csete G, Faragó P, Kocsis K, Must A, Vécsei L, Kincses ZT. 2016. Male brain ages faster: the age and gender dependence of subcortical volumes. Brain Imaging and Behavior. 10(3):901–910.
Kiselev VG, Hahn KR, Auer DP. 2003. Is the brain cortex a fractal? NeuroImage. 20(3):1765-1774.
Lee JM, Yoon U, Kim JJ, Kim IY, Lee DS, Kwon JS, Kim SI. 2004. Analysis of the hemispheric asymmetry using fractal dimension of a skeletonized cerebral surface. IEEE Transactions on Biomedical Engineering. 51(8):1494-1498.
Li S, Quan T, Xu C, Huang Q, Kang H, Chen Y, Li A, Fu L, Luo Q, Gong H, Zeng S. 2019. Optimization of traced neuron skeleton using Lasso-based model. Frontiers in Neuroanatomy. 13:18.
Madan CR, Kensinger EA. 2016. Cortical complexity as a measure of age-related brain atrophy. NeuroImage. 134:617-629.
Mandelbrot BB. 1982. The fractal geometry of nature. San Francisco: W.H. Freeman and Company.
Maryenko NI, Stepanenko OY. 2022a. Fractal dimension of skeletonized MR images as a measure of cerebral hemispheres spatial complexity. Reports of Morphology. 28(2):40-47.
Maryenko NI, Stepanenko OY. 2022b. Shape of cerebral hemispheres: structural and spatial complexity. Quantitative analysis of skeletonized MR images. Reports of Morphology. 28(3):62-73.
Maryenko N, Stepanenko O. 2023. Quantitative characterization of age-related atrophic changes in cerebral hemispheres: A novel “contour smoothing” fractal analysis method. Translational Research in Anatomy. 33:100263.
Milosević NT, Ristanović D. 2006. Fractality of dendritic arborization of spinal cord neurons. Neurosci Lett. 396(3):172-176.
Podgórski P, Bladowska J, Sasiadek M, Zimny A. 2021. Novel volumetric and surface-based magnetic resonance indices of the aging brain - does male and female brain age in the same way? Frontiers in Neurology. 12:645729.
Savic I, Arver S. 2011. Sex dimorphism of the brain in male-to-female transsexuals. Cerebral Cortex (New York, N.Y. : 1991). 21(11):2525–2533.
Schneider CA, Rasband WS, Eliceiri KW. 2012. NIH Image to ImageJ: 25 years of image analysis. Nature Methods. 9(7):671-675.
Zhang L, Liu JZ, Dean D, Sahgal V, Yue GH. 2006. A three-dimensional fractal analysis method for quantifying white matter structure in human brain. Journal of neuroscience methods, 150(2):242-253.
Zhang L, Dean D, Liu JZ, Sahgal V, Wang X, Yue GH. 2007. Quantifying degeneration of white matter in normal aging using fractal dimension. Neurobiology of Aging. 28(10):1543-1555.
Zhang L, Butler AJ, Sun CK, Sahgal V, Wittenberg GF, Yue GH. 2008. Fractal dimension assessment of brain white matter structural complexity post-stroke in relation to upper-extremity motor function. Brain Research. 1228:229-240.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Nataliia Maryenko, Oleksandr Stepanenko
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. Use restricted to non commercial purposes.
Once the manuscript has been accepted for publications, authors will sign a Copyright Transfer Agreement to let the “Asociación Argentina de Anatomía Clínica” (Argentine Association of Clinical Anatomy) to edit, publish and disseminate the contribution.
