Effects of Age and Sex on The Cerebellum and The Ventral Pons Volume - MRI Study

Year 2020, Volume: 1 Issue: 2, 45 - 51, 29.09.2020

Rabia Taşdemir İsmihan İlknur Uysal Süleyman Savaş Durduran

Abstract

Magnetic resonance image (MRI) has much importance in terms of searching ageing and gender effects on brain growing and structure.
In the study, it is aimed to find out age and gender differences on cerebellium and ventral pons volumes. It is totally studied on nine cross-section images from MRI; these: three at transvers plane (top, middle, and bottom), three at frontal plane (front, middle, back), and three at sagittal plane (right, middle, left). T1 transvers, frontal and sagittal MRI was taken from 100 adult people (43 men- 57 women), which in not observed pathological symptom, which come to Afyonkarahisar State Hospital Imaging Center with various reasons. The admitted both gender was separated age groups as young (13 men-10 women), average (12 men-24 women) and aged (18 men- 23 women) in order to understand effects of ageing. Areas of cerebellum and ventral pons formation were calculated by transfering choosed images to NETCAD software. The volumes were calculated in Excel program by using the values obtained from MRI and analysed by SPSS.
It was not found significant differences between genders in the ventral pons volumes. It was determined a significant size in men’s right and left hemisphere volumes at transvers and frontal planes. It was determined a significant size in women’s vermis volumes at sagittal plane. Also a significant reducing was observed in right hemisphere volumes, in frontal plane right – left hemisphere volumes owing to ageing and, so it was found that the reducing was much more in men. Becoming smaller was not observed in vermis volumes and vental pons volumes related to ageing. Although significant becoming smaller in vermis volumes, it was determined much more becoming smaller in men. When comparing the results of the current study and the previous studies, reattainment of the similar results indicated that NETCAD is suitable to be used in volume calculating with MRI.

Keywords

Cerebellum,, Ventral Pons,, MRI,, Volumetry,, NETCAD.

References

• 1. Persson N, Wu J, Zhang Q, et al. Age and sex related differences in subcortical brain iron concentrations among healthy adults. Neuroimage. 2015;122:385-398. doi:10.1016/j.neuroimage.2015.07.050
• 2. Szabo CA, Lancester JL, Xiong J, Cook C, Fox P. MR imaging volumetry of subcortical structures and cerebellar hemispheres in normal persons, Am J. Neuroradiol, 2003;24, 644-7.
• 3. Mormina E, Petracca M, Bommarito G, Piaggio N, Cocozza S, Inglese M. Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging. World J Radiol. 2017;9(10):371-388. doi:10.4329/wjr.v9.i10.371
• 4. Webb EA, Elliott L, Carlin D, et al. Quantitative Brain MRI in Congenital Adrenal Hyperplasia: In Vivo Assessment of the Cognitive and Structural Impact of Steroid Hormones. J Clin Endocrinol Metab. 2018;103(4):1330-1341. doi:10.1210/jc.2017-01481
• 5. Serrano NL, De Diego V, Cuadras D, et al. A quantitative assessment of the evolution of cerebellar syndrome in children with phosphomannomutase-deficiency (PMM2-CDG). Orphanet J Rare Dis. 2017;12(1):155. doi:10.1186/s13023-017-0707-0
• 6. Ber R, Hoffman D, Hoffman C, et al. Volume of Structures in the Fetal Brain Measured with a New Semiautomated Method. AJNR Am J Neuroradiol. 2017;38(11):2193-2198. doi:10.3174/ajnr.A5349
• 7. Szots M, Blaabjerg M, Orsi G, et al. Global brain atrophy and metabolic dysfunction in LGI1 encephalitis: A prospective multimodal MRI study. J Neurol Sci. 2017;376:159-165. doi:10.1016/j.jns.2017.03.020
• 8. Rosini F, Pretegiani E, Mignarri A, et al. The role of dentate nuclei in human oculomotor control: insights from cerebrotendinous xanthomatosis. J Physiol. 2017;595(11):3607-3620. doi:10.1113/JP273670
• 9. Murshed KA. Volume analysis in normal adult human brains: evaluation by magnetic resonance imaging. PHD Thesis. 2003
• 10. Sumiyoshi A, Nonaka H, Kawashima R. Sexual differentiation of the adolescent rat brain: A longitudinal voxel-based morphometry study. Neurosci Lett. 2017;642:168-173. doi:10.1016/j.neulet.2016.12.023
• 11. Ashburner J, Friston KJ. Unified segmentation. Neuroimage. 2005;26(3):839-851. doi:10.1016/j.neuroimage.2005.02.018
• 12. Lindig T, Kotikalapudi R, Schweikardt D, et al. Evaluation of multimodal segmentation based on 3D T1-, T2- and FLAIR-weighted images - the difficulty of choosing. Neuroimage. 2018;170:210-221. doi:10.1016/j.neuroimage.2017.02.016
• 13. Wyciszkiewicz A, Pawlak MA, Krawiec K. Cerebellar Volume in Children With Attention-Deficit Hyperactivity Disorder (ADHD). J Child Neurol. 2017;32(2):215-221. doi:10.1177/0883073816678550
• 14. D'Ambrosio A, Pagani E, Riccitelli GC, et al. Cerebellar contribution to motor and cognitive performance in multiple sclerosis: An MRI sub-regional volumetric analysis. Mult Scler. 2017;23(9):1194-1203. doi:10.1177/1352458516674567
• 15. Vurdem ÜE, Acer N, Ertekin T, Savranlar A, Inci MF. Analysis of the volumes of the posterior cranial fossa, cerebellum, and herniated tonsils using the stereological methods in patients with Chiari type I malformation. Scientific World Journal. 2012;2012:616934. doi:10.1100/2012/616934
• 16. Zanigni S, Calandra-Buonaura G, Manners DN, et al. Accuracy of MR markers for differentiating Progressive Supranuclear Palsy from Parkinson's disease. Neuroimage Clin. 2016;11:736-742. doi:10.1016/j.nicl.2016.05.016
• 17. Womer FY, Tang Y, Harms MP, et al. Sexual dimorphism of the cerebellar vermis in schizophrenia. Schizophr Res. 2016;176(2-3):164-170. doi:10.1016/j.schres.2016.06.028
• 18. Meyer CE, Kurth F, Lepore S, et al. In vivo magnetic resonance images reveal neuroanatomical sex differences through the application of voxel-based morphometry in C57BL/6 mice. Neuroimage. 2017;163:197-205. doi:10.1016/j.neuroimage.2017.09.027
• 19. Yu T, Korgaonkar MS, Grieve SM. Gray Matter Atrophy in the Cerebellum-Evidence of Increased Vulnerability of the Crus and Vermis with Advancing Age. Cerebellum. 2017;16(2):388-397. doi:10.1007/s12311-016-0813-x
• 20. Yamada K, Watanabe M, Suzuki K, Suzuki Y. Cerebellar Volumes Associate with Behavioral Phenotypes in Prader-Willi Syndrome [published online ahead of print. Cerebellum. 2020;10.1007/s12311-020-01163-1. doi:10.1007/s12311-020-01163-1
• 21. Straub S, Mangesius S, Emmerich J, et al. Toward quantitative neuroimaging biomarkers for Friedreich's ataxia at 7 Tesla: Susceptibility mapping, diffusion imaging, R2and R1 relaxometry. J Neurosci Res. 2020;10.1002/jnr.24701. doi:10.1002/jnr.24701
• 22. Chen WT, Chou KH, Lee PL, et al. Comparison of gray matter volume between migraine and "strict-criteria" tension-type headache. J Headache Pain. 2018;19(1):4. doi:10.1186/s10194-018-0834-6
• 23. Vňuková M, Ptáček R, Raboch J, Stefano GB. Decreased Central Nervous System Grey Matter Volume (GMV) in Smokers Affects Cognitive Abilities: A Systematic Review. Med Sci Monit. 2017;23:1907-1915. doi:10.12659/msm.901870