Correlation Between Corpus Callosum Shape and Craniometric Measurements According to Mri Data

Authors

DOI:

https://doi.org/10.18662/brain/12.3/216

Keywords:

brain, corpus callosum shape, corpus callosum trunk bulge height, morphometry, individual variability, neurocranium

Abstract

The correlation between the cranial height and the height of the corpus callosum trunk bulge, and the relationship between the corpus callosum shape and the cranial shape have not been studied. The purpose of the article was to determine the individual variability of the corpus callosum height and shape of adults, and their dependence on the cranial height and shape. The material was two samples from a series of MR scans of the head of men and women of the second period of adulthood (19 variations in each group) without the central nervous system pathology. Magnetic resonance tomographic scanner Magnetom C was used for obtaining MRI images. Morphometric study was conducted using RadiAnt Dicom Viewer software on MR scans performed in the sagittal area in T1- and T2-weighted images modes. According to the findings, the height of the corpus callosum trunk bulge of men is on average – 26.1 ± 2.8 mm, women – 25.2 ± 2.6 mm, and the neurocranium height – 150.4 ± 6.9 mm and 140.2 ± 4.2 mm, respectively. Wherein the aspect ratio of the neurocranium height to the corpus callosum trunk bulge height in men is 5.8 ± 0.7, in women – 5.6 ± 0.5. The aspect ratio of the corpus callosum longitudinal size along the constricting chord to its trunk bulge height in men is on average 2.8 ± 0.3, in women – 2.7 ± 0.3. The absence of correlation between the cranial height and the corpus callosum trunk bulge height, and the absence of correlation between the corpus callosum shape and cranial shape in people of the second period of adulthood have been concluded.

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Published

2021-08-23

How to Cite

Boiagina, O., Stepanenko, O., & Lebedieva, A. (2021). Correlation Between Corpus Callosum Shape and Craniometric Measurements According to Mri Data. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 12(3), 01-10. https://doi.org/10.18662/brain/12.3/216

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