Intracranial volume in computed axial tomography images as a biomarker of brain aging
Keywords:
biomarkers, aging, computed tomography, volumetry.Abstract
Introduction: The determination of volumes of multiple brain structures is of great importance in the field of neurosciences, not only with the objective of measuring or detecting structural alterations, but due to the need to make an early diagnosis of diseases that affect the nervous system.Objective: To describe the differences between absolute and standardized brain volumetry by intracranial volume as well as the elaboration of percentile tables that characterize this volumetry.
Methods: A descriptive, cross-sectional study of a series of cases was developed in 320 subjects with normal neurocognitive functions and neuropsychiatric examination, aged between 30 and 79 years, who underwent single-slice simple skull computed tomography. A general multivariate linear model was applied; intracranial volume was weighted, to rule out the influence of the size of the subjects' heads on the results. The digital processing of the images was carried out through the use of use of an image segmentation method based on the analysis of homogeneous textures and interpolation.
Results: The predominant age group was 50-59 years (14.1%). The highest absolute intracranial volumes were present in men, and once Nordenskjold's residual correction was performed, they were higher in women. A high correlation was obtained between total brain volume and intracranial volume.
Conclusions: The volumetric parameters obtained are significantly correlated with intracranial volume.
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References
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3. Hernández- Cortés Katherine S, Mesa- Pujals Adrián A, García- Gómez Odalis, Montoya Pedrón A. Brain morphometry in adult: volumetric visualization as a tool in image processing. Rev Mex Neurocienc. 2021; 22(3):101-11. DOI: 10.24875/rmn.20000074
4. Spalletta G, Piras F, Gili T. Brain Morphometry, Neuromethods. En: Hiroshi M. Morphometry in Normal Aging. New Jersey: Human Press; 2018. p. 165-70. DOI: 10.1007/978-1-4939-7647-8
5. Bonilla Santos J, Zea Romero EY, Cala Martínez DY, González Hernández A. Marcadores cognitivos, Biológicos, Anatómicos y Conductuales del Deterioro Cognitivo Leve y la Enfermedad de Alzheimer. Una revisión sistemática. Rev Ecuat Neurol. 2021; 30(2):57-67. DOI: 10.46997/revecuatneurol30200057
6. Harris SE, Cox S R, Bell S, Marioni RE, Prins BP, Pattie A, et al. Neurology-related protein biomarkers are associated with cognitive ability and brain volume in older age. Nature Communications. 2020; 11:800. DOI: 10.1038/s41467-019-14161-7
7. Ballarini T, van Lent D M, Brunner J, Schröder A, Wolfsgruber S, Altenstein S, et al. Mediterranean diet, Alzheimer disease biomarkers, and brain atrophy in old age. Neurology. 2021; 96(24):e2920-e2932. DOI: 10.1212/WNL.0000000000012067
8. Rouviere H, Delmas A. Anatomía Humana Descriptiva, Topográfica y Funcional. 11.ª ed. Francia: Masson; 2005.
9. Mohanty A, Mahapatra S, Bhanja U. Traffic congestion detection in a city using clustering techniques in VANETs. Indones. J Electr Eng Comput Sci. 2019; 13(2):884-91. DOI: 10.11591/ijeecs.v13.i3.pp884-891 10
10. Heurtier A. Texture feature extraction methods: A survey. IEEE Access. 2019; 7:8975-9000. DOI: 10.1109/ACCESS.2018.2890743
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13. Kollem S, Reddy KR, Rao DS. A review of image denoising and segmentation methods based on medical images. Int J Mach Learn Comput. 2019; 9(3):288-95. DOI: 10.18178/ijmlc.2019.9.3.800.
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15. Nordenskjöld R, Malmberg F, Larsson EM, Simmons A, Ahlström H, Johansson L, et al. Intracranial volume normalization methods: considerations when investigating gender differences in regional brain volume. Psychiatry Research: Neuroimaging. 2015; 231(3):227-35. DOI: 10.1016/j.pscychresns.2014.11.011
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17. Van Loenhoud AC, Groot C, Vogel JW, Van Der Flier WM, Ossenkoppele RR. Is intracraneal volume a suitable proxy for brain reserve? Alzheimer´s research & therapy. 2018; 10(1):1-12. DOI:10.1186/s13195-018-0408-5
18. Caspi Y, Brouwer RM, Schnack HG, van de Nieuwenhuijzen ME, Cahn W, Kahn RS, et al. Changes in the intracranial volume from early adulthood to the sixth decade of life: A longitudinal study. NeuroImage. 2020; 220:116842. DOI: 10.1186/s13195-018-0408-5
19. MacLullich AMJ, Ferguson KJ, Deary IJ, Seckl JR, Starr JM, Wardlaw JM. Intracranial capacity and brain volumes are associated with cognition in healthy elderly men. Neurology. 2002; 59(2):169-74. DOI: 10.1212/wnl.59.2.169
20. Klasson N, Olsson E, Eckerstrom C, Malmgren H, Wallin A. Estimated intracraneal volume from Free Surfer is biased by total brain volume. European Radiology Experimental. 2018; 2(1):1-6. DOI: 10.1186/s41747-018-0055-4
21. Bigler ED, Tate DF. Brain volume, intracranial volume, and dementia. Investigative radiology. 2001; 36(9):539-46. DOI: 10.1097/00004424-200109000-00006
22. Farokhian F, Yang C, Beheshti I, Matsuda H, Wu S. Age-related gray and white matter changes in normal adult brains. Aging and disease. 2017; 8(6):899. DOI: 10.1097/00004424-200109000-00006
23. Klein M, Walters RK, Demontis D, Stein JL, Hibar DP, Adams HH, et al. Genetic markers of ADHD-related variations in intracranial volume. American Journal of Psychiatry. 2019; 176(3):228-38. DOI: 10.1176/appi.ajp.2018.18020149
Published
2023-12-21
How to Cite
1.
Hernández Cortés KS, Sagaró del Campo NM, Montoya Pedrón A. Intracranial volume in computed axial tomography images as a biomarker of brain aging. Rev Cubana Med Milit [Internet]. 2023 Dec. 21 [cited 2025 Apr. 4];53(1):e024018273. Available from: https://revmedmilitar.sld.cu/index.php/mil/article/view/18273
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