Skip Navigation Links.
Collapse <span class="m110 colortj mt20 fontw700">Volume 12 (2024)</span>Volume 12 (2024)
Collapse <span class="m110 colortj mt20 fontw700">Volume 11 (2023)</span>Volume 11 (2023)
Collapse <span class="m110 colortj mt20 fontw700">Volume 10 (2022)</span>Volume 10 (2022)
Collapse <span class="m110 colortj mt20 fontw700">Volume 9 (2021)</span>Volume 9 (2021)
Collapse <span class="m110 colortj mt20 fontw700">Volume 8 (2020)</span>Volume 8 (2020)
Collapse <span class="m110 colortj mt20 fontw700">Volume 7 (2019)</span>Volume 7 (2019)
Collapse <span class="m110 colortj mt20 fontw700">Volume 6 (2018)</span>Volume 6 (2018)
Collapse <span class="m110 colortj mt20 fontw700">Volume 5 (2017)</span>Volume 5 (2017)
Collapse <span class="m110 colortj mt20 fontw700">Volume 4 (2016)</span>Volume 4 (2016)
Collapse <span class="m110 colortj mt20 fontw700">Volume 3 (2015)</span>Volume 3 (2015)
Collapse <span class="m110 colortj mt20 fontw700">Volume 2 (2014)</span>Volume 2 (2014)
Collapse <span class="m110 colortj mt20 fontw700">Volume 1 (2013)</span>Volume 1 (2013)
American Journal of Public Health Research. 2019, 7(4), 157-160
DOI: 10.12691/AJPHR-7-4-5
Original Research

Morphometric Assessment of Aging Impact in Cranial/Ventricles’ Volumes and CT/MRI Imaging Systems Parameters

Emad M. Mukhtar Alasar1, Mohammed A. Ali Omer2, 3, and Ghada A. E. Sakin1

1Department of Radiotherapy & Nuclear Medicine, College of Medical Radiologic Science, Sudan University of Science and Technology, Khartoum-Sudan

2Department of Radiology, College of Applied Medical Science, King Khalid University, Abha-KSA

3Department of Radiologic Technology Department, College of Applied Medical Science, Qassim University, Buraidah-KSA

Pub. Date: July 29, 2019

Cite this paper

Emad M. Mukhtar Alasar, Mohammed A. Ali Omer and Ghada A. E. Sakin. Morphometric Assessment of Aging Impact in Cranial/Ventricles’ Volumes and CT/MRI Imaging Systems Parameters. American Journal of Public Health Research. 2019; 7(4):157-160. doi: 10.12691/AJPHR-7-4-5

Abstract

A retrospective study aims to assess aging impact in cranial/ventricles volumes and the effect in signal intensity of imaging modalities (CT & MRI). The analysis of collected data using Excel and SPSS showed that: aging has less significant (R2 =0.4) impact on ventricle volume generally and the correlation best fitted to equation: Volume = 1.46 age - 40.742. The impact of aging in ventricles volume was significant (p = 0.05) increment after 69 years with prominent effect among male relative to female; and steady before the age of 69 years old. Aging had less significant decreasing impact (R2 = 0.3) in signal intensity (T1, T2) of white and gray matter and having prominent high signal intensity of white mater relative to gray mater. The age showed high significant (R2 = 0.8) reducing impact in white matter HU that fitted to equations of the following forms: HU = 0.53 age + 9.6864; while there is an increasing impact in gray matter HU that fitted to: HU = -0.26 age + 40.093.

Keywords

volumetric, cranium, ventricle, ageing-impact

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]  Standring, Susan; Ellis, Harold; Wigley, Caroline/ Gray's anatomy: the anatomical basis of clinical practice. 39th. edition. Edinburgh; New York: Elsevier Churchill Livingstone, 2005.
 
[2]  Kathryn A. Booth and Terri D. Wyman. Anatomy, physiology, and pathophysiology for allied health. McGraw-Hill Companies, New York 2008.
 
[3]  Chiang, A., Priya, R., Ramaswami, M., Vijayraghavan, K., Rodrigues, V. “Neuronal activity and Wnt signaling act through Gsk3-beta to regulate axonal integrity in mature Drosophila olfactory sensory neurons”. Development, 136(8):1273-82. 2009.
 
[4]  Shenton ME, Dickey CC, Frumin M, McCarley RW. “A review of MRI findings in schizophrenia”. Schizophre-nia Res, 49: 1-52. 2001.
 
[5]  Nestor, P. G., Kubicki, M., Nakamura, M., Niznikiewicz, M., McCarley, R. W., & Shenton, M. E. “Comparing prefrontal gray and white matter contributions to intelligence and decision making in schizophrenia and healthy controls”. Neuropsychology, 24(1), 121-129. 2010.
 
[6]  Whitwell JL, Jack CR, Parisi JE, Knopman DS, Boeve BF, Petersen RC, Ferman TJ, Dickson DW, Josephs K. A. “Rates of cerebral atrophy differ in different degenerative pathologies”. Brain, Vol.130, P: 1148-1158. 2007.
 
[7]  Simic G, Kostović I, Winblad B, Bogdanović N. “Volume and number of neurons of the human hippocampal formation in normal aging and Alzheimer's disease”. J Comp Neurol;379(4): 482-94. 1997.
 
[8]  Resnick SM, Pham DL, Kraut MA, Zonderman AB, Davatzikos C. “Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain”. J Neurosci; 23(8):3295-301. 2003.
 
[9]  Coffey, C.E., Lucke, J.F., Saxton, J.A., Ratcliff, G., Unitas, L.J., Billig, B., Bryan, R.N., “Sex differences in brain aging: a quantitative magnetic resonance imaging study”. Archives of Neurology 55, 169-179. 1998.
 
[10]  Rania Ahmed Mohammed F. Almoula, Carloine E. Ayad, Abdurrahman Abdullah Saad Alsayyari, Abdulaziz A. Ahmed and Mohammed Ahmed Ali Omer. “Morphometric of hepatic duct angulation & relative pathologies incidence among Sudanese population”. International Journal of Development Research, 08(06): 20854-20858. 2018.
 
[11]  Mohammed A. Ali Omer, Emad M. Mukhtar Alasar, Mohamed E. M.Gar-elnabi, Ghada A. E. Sakin, Yahia M. Bushara. “Measurement of Cranial and Brain Ventricle Volumes Relative to Pathologies”. International Journal of Science and Research (IJSR), Vol. 3(5): 987-991. 2014.
 
[12]  Anders M. Fjell and Kristine B. Walhovd. “Structural Brain Changes in Aging: Courses, Causes and Cognitive Consequences”. Reviews in the Neurosciences 21, 187-221. 2010.
 
[13]  Anders M. Fjell and Kristine B. Walhovd (2010) Structural Brain Changes in Aging: Courses, Causes and Cognitive Consequences. Reviews in the Neurosciences 21, 187-221.
 
[14]  Salat, D.H., Lee, S.Y., van der Kouwe, A.J., Greve, D.N., Fischl, B., Rosas, H.D., “Age associated alterations in cortical gray and white matter signal intensity and gray to white matter contrast”. Neuroimage 48, 21-28. 2009.
 
[15]  Westlye, L.T., Walhovd, K.B., Dale, A.M., Espeseth, T., Reinvang, I., Raz, N., Agartz, I., Greve, D.N., Fischl, B., Fjell, A.M., “Increased sensitivity to effects of normal aging and Alzheimer's disease on cortical thickness by adjustment for local variability in gray/white contrast: a multi-sample MRI study. Neuroimage 47, 1545-1557. 2009.
 
[16]  Devi R. Ramya and G.S. Anandhamala. “Recent Trends in Medical Imaging Modalities and Challenges for Diagnosing Breast Cancer”. Biomedical & Pharmacology Journal, 11(3): 1649-1658. 2018.
 
[17]  Govaert, G. A., IJpma, F. F., McNally, M., McNally, E., Reininga, I. H., & Glaudemans, A. W. “Accuracy of diagnostic imaging modalities for peripheral post-traumatic osteomyelitis - a systematic review of the recent literature”. European Journal of Nuclear Medicine and Molecular Imaging, 44(8), 1393-1407. 2017.
 
[18]  Manjunath K. Y. “Estimation of cranial volume an over view of methodologies”. J. Anat. Soc. India., 51 (1): 85-91. 2002.
 
[19]  Ruffman T., Henry J. D., Livingstone V., Phillips L. H. “A meta-analytic review of emotion recognition and aging: implications for neuropsychological models of aging”. Neurosci. Biobehav. Rev. 32, 863-881. 2008.
 
[20]  Scheibe S., Carstensen L. L. “Emotional aging: recent findings and future trends”. J. Gerontol. B Psychol. Sci. Soc. Sci. 65B, 135-144. 2010.
 
[21]  Bijaylakshmi Parija, Niranjan Sahu, Shakti Rath, Rabindra N. Padhy. “Age-related Changes in Ventricular System of Brain in Normal Individuals Assessed by Computed Tomography Scans”. Siriraj Med J 2014; 66:225-230. 2014.
 
[22]  Sasank Chilamkurthy, Pooja Rao, Georgios Maragkos, Ajith Thomas. “Morphology of the Brain: Changes in Ventricular and Cranial Vault Volumes in 15000 subjects with Aging and Hydrocephalus”. Qure.ai, Beth Israel Deaconess Medical Center March 11, 2019.
 
[23]  Magnaldi S., M. Ukmar, A. Vasciaveo, R. Longo and R. S. Pozzi-Mucelli. “Contrast between white and grey matter: MRI appearance with ageing”. European Radiology, 3(6): 513-519. 1993.
 
[24]  Lars T. Westlye, Kristine B. Walhovd, Anders M. Dale, Atle Bjørnerud, Paulina Due-Tønnessen, Andreas Engvig, Håkon Grydeland, Christian K. Tamnes, Ylva Østby, Anders M. Fjell. “Differentiating maturational and aging-related changes of the cerebral cortex by use of thickness and signal intensity”. NeuroImage 52, 172-185. 2010.
 
[25]  Kim Dennis M., Stavra A. Xanthakos, Larry A. Tupler, Daniel P. Barboriak, H. Cecil Charles, James R. MacFall, K. Ranga Rama Krishnan. “MR signalintensity of gray mattery white matter contrast and intracranialfat: effects of age and sex”. Psychiatry Research Neuroimaging, 114,149-161. 2002.
 
[26]  Christian Langkammer, Nikolaus Krebs, Walter Goessler, Eva Scheurer, Kathrin Yen, Franz Fazekas, Stefan Ropele. “Susceptibility induced gray–white matter MRI contrast in the human brain”. NeuroImage, 59: 1413-1419. 2012.