Year 2020, Volume , Issue 18, Pages 599 - 606 2020-04-15

Comparison Global Brain Volume Ratios on Alzheimer’s Disease Using 3D T1 Weighted MR Images

Muhammet Üsame ÖZİÇ [1] , Seral ÖZŞEN [2]

Alzheimer's Disease is a cause of dementia that starts with the loss of cognitive functions. The degeneration that starts in memory-related areas in the brain spreads to other regions as the disease progresses. Volumetric losses occurring in the brain can be monitored with high resolution 3D T1-weighted magnetic resonance images. The interpretation of these images is carried out by radiologists in hospitals. However, since the voxel intensity transitions of the brain regions are not clear in magnetic resonance images, computer-aided numerical methods are needed. These methods can perform pre-processing, post-processing, segmentation and volume calculation on magnetic resonance images. In this study, gray matter, white matter, cerebrospinal fluid, total intracranial volume, parenchyma, and lateral ventricle global volumes were calculated on 70 Alzheimer Patients 70 Normal Control 3D T1-weighted magnetic resonance images taken from Open Access Series of Imaging Studies database. SPM8 and MRIcro programs, ALVIN and VBM8 libraries were used. Since the numerical methods used are found in different programs and libraries, a model is proposed which combinations should be used. Volumetric results are relative due to the different head sizes in each person. Therefore, the problem of relativity should be eliminated by proportioning each volume value with another volume value. Twenty different metrics of the brain were obtained by summing and dividing the six global volume regions obtained in different combinations. Using these values, it was determined whether there was a statistically significant difference between the two groups by independent samples t-test. The performance of the numerical methods used and the statistical results of twenty metrics obtained from global brain volumes were discussed. After measurements and evaluations, it was observed that the ratio of cerebrospinal fluid volume to gray matter volume was an important marker in the differential diagnosis of the disease.
Alzheimer, Volume, Ratios, SPM8, VBM8
  • Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38(1), 95-113.
  • Ashburner, J., Barnes, G., Chen, C., Daunizeau, J., Flandin, G., Friston, K., . . . Litvak, V. (2008). SPM8 manual. Functional Imaging Laboratory, Institute of Neurology, 41.
  • Association, A. s. (2019). 2019 Alzheimer's disease facts and figures. Alzheimer's & Dementia, 15(3), 321-387.
  • Bigler, E. D. (2015). Structural image analysis of the brain in neuropsychology using magnetic resonance imaging (MRI) techniques. Neuropsychology Review, 25(3), 224-249.
  • Derneği, T. A. (2020). Türkiye'de 600bin aile Alzheimer Hastalığı ile Mücadele Ediyor. Retrieved from
  • Dubois, B., Hampel, H., Feldman, H. H., Scheltens, P., Aisen, P., Andrieu, S., . . . Blennow, K. (2016). Preclinical Alzheimer's disease: definition, natural history, and diagnostic criteria. Alzheimer's & Dementia, 12(3), 292-323.
  • Fischl, B. (2012). FreeSurfer. Neuroimage, 62(2), 774-781.
  • Frisoni, G., Testa, C., Zorzan, A., Sabattoli, F., Beltramello, A., Soininen, H., & Laakso, M. (2002). Detection of grey matter loss in mild Alzheimer's disease with voxel based morphometry. Journal of Neurology, Neurosurgery & Psychiatry, 73(6), 657-664.
  • Frisoni, G. B., Fox, N. C., Jack, C. R., Scheltens, P., & Thompson, P. M. (2010). The clinical use of structural MRI in Alzheimer disease. Nature Reviews Neurology, 6(2), 67-77.
  • Ge, Y., Grossman, R. I., Babb, J. S., Rabin, M. L., Mannon, L. J., & Kolson, D. L. (2002). Age-related total gray matter and white matter changes in normal adult brain. Part I: volumetric MR imaging analysis. American Journal of Neuroradiology, 23(8), 1327-1333.
  • Goto, M., Abe, O., Aoki, S., Hayashi, N., Miyati, T., Takao, H., . . . Mori, H. (2013). Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects. Neuroradiology, 55(7), 869-875.
  • Guo, X., Wang, Z., Li, K., Li, Z., Qi, Z., Jin, Z., . . . Chen, K. (2010). Voxel-based assessment of gray and white matter volumes in Alzheimer's disease. Neuroscience letters, 468(2), 146-150.
  • Holland, D., Brewer, J. B., Hagler, D. J., Fennema-Notestine, C., Dale, A. M., Weiner, M., . . . Jagust, W. (2009). Subregional neuroanatomical change as a biomarker for Alzheimer's disease. Proceedings of the National Academy of Sciences, 106(49), 20954-20959.
  • Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W., & Smith, S. M. (2012). Fsl. Neuroimage, 62(2), 782-790. Keller, S. S., & Roberts, N. (2009). Measurement of brain volume using MRI: software, techniques, choices and prerequisites. J Anthropol Sci, 87, 127-151.
  • Kempton, M. J., Underwood, T. S., Brunton, S., Stylios, F., Schmechtig, A., Ettinger, U., . . . Frangou, S. (2011). A comprehensive testing protocol for MRI neuroanatomical segmentation techniques: evaluation of a novel lateral ventricle segmentation method. Neuroimage, 58(4), 1051-1059.
  • Klein, A., Andersson, J., Ardekani, B. A., Ashburner, J., Avants, B., Chiang, M.-C., . . . Hellier, P. (2009). Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. Neuroimage, 46(3), 786-802.
  • Kurth, F., Luders, E., & Gaser, C. (2010). VBM8 toolbox manual. Jena: University of Jena.
  • Marcus, D. S., Wang, T. H., Parker, J., Csernansky, J. G., Morris, J. C., & Buckner, R. L. (2007). Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. Journal of cognitive neuroscience, 19(9), 1498-1507.
  • Mechelli, A., Price, C. J., Friston, K. J., & Ashburner, J. (2005). Voxel-based morphometry of the human brain: methods and applications. Current medical imaging reviews, 1(2), 105-113.
  • MRIcro. (2020). Retrieved from
  • Orellana, C., Ferreira, D., Muehlboeck, J.-S., Mecocci, P., Vellas, B., Tsolaki, M., . . . Simmons, A. (2016). Measuring global brain atrophy with the brain volume/cerebrospinal fluid index: normative values, cut-offs and clinical associations. Neurodegenerative Diseases, 16(1-2), 77-86.
  • Öziç, M., Ü. (2018). 3B Alzheimer MR Görütnülerinin Sınıflandırılmasında Yeni Yaklaşımlar. (Doktora Tezi), Selçuk Üniversitesi,
  • Penny, W. D., Friston, K. J., Ashburner, J. T., Kiebel, S. J., & Nichols, T. E. (2011). Statistical parametric mapping: the analysis of functional brain images: Elsevier.
  • Petrella, J. R., Coleman, R. E., & Doraiswamy, P. M. (2003). Neuroimaging and early diagnosis of Alzheimer disease: a look to the future 1. Radiology, 226(2), 315-336.
  • Petropoulos, H., Sibbitt Jr, W. L., & Brooks, W. M. (1999). Automated T2 quantitation in neuropsychiatric lupus erythematosus: a marker of active disease. Journal of Magnetic Resonance Imaging, 9(1), 39-43.
  • Rababa'h, Q. (2014). Intracranial volume Segmentation. (Master Thesis in Medicine), Örebro University,
  • Ridgway, G. (2020). Miscellaneous useful MATLAB scripts for SPM/VBM. Retrieved from
  • Salat, D. H., Greve, D. N., Pacheco, J. L., Quinn, B. T., Helmer, K. G., Buckner, R. L., & Fischl, B. (2009). Regional white matter volume differences in nondemented aging and Alzheimer's disease. Neuroimage, 44(4), 1247-1258.
  • Schuff, N., Woerner, N., Boreta, L., Kornfield, T., Shaw, L., Trojanowski, J., . . . Initiative, D. N. (2009). MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers. Brain, 132(4), 1067-1077.
  • Selekler, K. (2010). Alois Alzheimer ve Alzheimer Hastalığı. Türk Geriatri Dergisi, 13(3), 9-14.
  • Talaraich, J., & Tournoux, P. (1988). Co-planar stereotaxic atlas of the human brain. George Thieme, Stuttgard.
  • Vemuri, P., & Jack, C. R. (2010). Role of structural MRI in Alzheimer's disease. Alzheimer's research & therapy, 2(4), 23.
  • Villarreal, G., Hamilton, D. A., Petropoulos, H., Driscoll, I., Rowland, L. M., Griego, J. A., . . . Brooks, W. M. (2002). Reduced hippocampal volume and total white matter volume in posttraumatic stress disorder. Biological psychiatry, 52(2), 119-125.
  • Youn, Y. C., & Hsiung, G.-Y. R. (2015). A Voxel Based Morphometric Analysis of Longitudinal Cortical Gray Matter Changes in Progranulin Mutation Carriers At-Risk for Frontotemporal Dementia: Preliminary Study. Dementia and Neurocognitive Disorders, 14(4), 163-167.
Primary Language en
Subjects Engineering
Journal Section Articles

Orcid: 0000-0002-3037-2687
Author: Muhammet Üsame ÖZİÇ (Primary Author)
Institution: Necmettin Erbakan University
Country: Turkey

Orcid: 0000-0001-5332-8665
Author: Seral ÖZŞEN
Institution: Konya Technical University
Country: Turkey


Publication Date : April 15, 2020

APA Özi̇ç, M , Özşen, S . (2020). Comparison Global Brain Volume Ratios on Alzheimer’s Disease Using 3D T1 Weighted MR Images . Avrupa Bilim ve Teknoloji Dergisi , (18) , 599-606 . DOI: 10.31590/ejosat.697446