Frequency Of Brain Atrophy Diagnosed on Computed Tomography
Frequency of Brain Atrophy Diagnosed on Computed Tomography
Keywords:Brain Atrophy, Alzheimer disease, Age Related Atrophy, Trauma, Computed Tomography
Brain atrophy is the loss of connections between neurons. It can be due to old age, trauma, ischemic stroke, multiple sclerosis, post infective and neurodegenerative diseases. Objective: To determine the frequency of brain atrophy on Computed Tomography. Methods: A cross sectional study conducted in Medcare international hospital, Gujranwala and DHQ, Kasur. The data was collected using convenient sampling technique from February 2022 to May 2022 after written consent. A sample size of 60 was calculated using mean from previous published studies. The age considered was maximum of 100 and minimum of 20 years. The study included all the patients who had focal and generalized brain atrophy. The equipment used for the evaluation was Toshiba Aquilion 64 slices CT scanner. Results: The mean age of patients was 79.88 ± 9.22 having minimum age of 57y and maximum age of 91y. The male patients were more frequent as 34(56.7%) and females as 26(43.3%). The brain atrophy was categorized as focal 14(23.3%) and generalized atrophy 46(76.7%). The patients of brain atrophy had history of smoking 30(39%), alcohol use 13(16.9%) and diabetes mellitus 15(19.5%) and the common symptoms include memory problems 25(33.3%), poor judgment 13(17.3%) and loss of language 11(14.7%). The most common cause of brain atrophy evaluated was due to old age 42(70%) following post traumatic 9(15%) and Alzheimer 4(6. 7%). Conclusion: In conclusion, brain atrophy can be due to old age, trauma and Alzheimer disease. The common symptoms include memory problems and loss of language.
Martins NRB, Angelica A, Chakravarthy K, Svidinenko Y, Boehm FJ, Opris I, et al. Human Brain/Cloud Interface. Front Neuroscience. 2019 Mar; 13:112. doi: 10.3389/fnins.2019.00112.
Suarez AM, Martinez ME, Mendoza LR. Brain and learning. International Journal of Social Sciences and Humanities. 2019; 3(2):128-35.doi.org/10.29332/ijssh.v3n2.302
Eickhoff SB, Yeo BTT, Genon S. Imaging-based parcellations of the human brain. Nature Reviews Neuroscience. 2018 Nov; 19(11):672-686. doi: 10.1038/s41583-018-0071-7.
Pașca SP. The rise of three-dimensional human brain cultures. Nature. 2018 Jan; 553(7689):437-445. doi: 10.1038/nature25032.
Sedmak G, Judaš M. The total number of white matter interstitial neurons in the human brain. Journal of Anatomy. 2019 Sep; 235(3):626-636. doi: 10.1111/joa.13018.
Ushizima D, Chen Y, Alegro M, Ovando D, Eser R, Lee W, et al. Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation. NeuroImage. 2022 Mar; 248:118790. doi: 10.1016/j.neuroimage.2021.118790. Epub 2021 Dec 20.
Tsiakas K, Abujelala M, Makedon F. Task engagement as personalization feedback for socially-assistive robots and cognitive training. Technologies. 2018 May; 6(2):49. doi.org/10.3390/technologies6020049
Andravizou A, Dardiotis E, Artemiadis A, Sokratous M, Siokas V, Tsouris Z, et al. Brain atrophy in multiple sclerosis: mechanisms, clinical relevance and treatment options. Auto Immun Highlights. 2019 Aug; 10(1):7. doi: 10.1186/s13317-019-0117-5.
Moran C, Beare R, Wang W, Callisaya M, Srikanth V; Alzheimer's Disease Neuroimaging Initiative (ADNI). Type 2 diabetes mellitus, brain atrophy, and cognitive decline. Neurology. 2019 Feb; 92(8):e823-e830. doi: 10.1212/WNL.0000000000006955.
10. Moran C, Münch G, Forbes JM, Beare R, Blizzard L, Venn AJ, et al.Type 2 diabetes, skin autofluorescence, and brain atrophy. Diabetes. 2015 Jan;64(1):279-83. doi: 10.2337/db14-0506.
Graham NS, Sharp DJ. Understanding neurodegeneration after traumatic brain injury: from mechanisms to clinical trials in dementia. Journal of Neurology, Neurosurgery & Psychiatry. 2019 Nov; 90(11):1221-1233. doi: 10.1136/jnnp-2017-317557.
Azevedo CJ, Cen SY, Jaberzadeh A, Zheng L, Hauser SL, Pelletier D. Contribution of normal aging to brain atrophy in MS. Neurology-Neuroimmunology Neuroinflammation. 2019 Sep; 6(6):e616. doi: 10.1212/NXI.0000000000000616.
Callisaya ML, Beare R, Moran C, Phan T, Wang W, Srikanth VK. Type 2 diabetes mellitus, brain atrophy and cognitive decline in older people: a longitudinal study. Diabetologia. 2019 Mar; 62(3):448-458. doi: 10.1007/s00125-018-4778-9. 2019;62(3):448-58.
Helfrich RF, Mander BA, Jagust WJ, Knight RT, Walker MP. Old brains come uncoupled in sleep: slow wave-spindle synchrony, brain atrophy, and forgetting. Neuron. 2018 Jan; 97(1):221-230.e4. doi: 10.1016/j.neuron.2017.11.020.
Tian Q, Resnick SM, Davatzikos C, Erus G, Simonsick EM, Studenski SA, et al. A prospective study of focal brain atrophy, mobility and fitness. Journal of internal medicine. 2019 Jul; 286(1):88-100. doi: 10.1111/joim.12894.
Moccia M, Prados F, Filippi M, Rocca MA, Valsasina P, Brownlee WJ, et al. Longitudinal spinal cord atrophy in multiple sclerosis using the generalized boundary shift integral. Annals of Neurology. 2019 Nov; 86(5):704-713. doi: 10.1002/ana.25571.
Erten-Lyons D, Dodge HH, Woltjer R, Silbert LC, Howieson DB, Kramer P, et al. Neuropathologic basis of age-associated brain atrophy. JAMA neurology. 2013 May; 70(5):616-22. doi: 10.1001/jamaneurol.2013.1957.
Obelieniene D, Bauzaite S, Kulakiene I, Keleras E, Eitmonaite I, Rastenyte D. Diagnostic challenges in multiple system atrophy. Neuropsychiatric Disease and Treatment. 2018 Jan; 14:179-184. doi: 10.2147/NDT.S146080.
Van Elderen S, De Roos A, De Craen A, Westendorp R, Blauw G, Jukema J, et al. Progression of brain atrophy and cognitive decline in diabetes mellitus: a 3-year follow-up. Neurology. 2010 Sep; 75(11):997-1002. doi: 10.1212/WNL.0b013e3181f25f06.
Ghione E, Bergsland N, Dwyer MG, Hagemeier J, Jakimovski D, Paunkoski I, et al. Aging and brain atrophy in multiple sclerosis. Journal of Neuroimaging. 2019 Jul; 29(4):527-535. doi: 10.1111/jon.12625.
牛田知佳. Assessment of brain atrophy in elderly subjects with diabetes mellitus by computed tomography: 名古屋大学; 2003.
Ushida C, Umegaki H, Hattori A, Mogi N, Aoki S, Iguchi A. Assessment of brain atrophy in elderly subjects with diabetes mellitus by computed tomography. Geriatrics & Gerontology International. 2001 Dec;1(1‐2):33-7.
Zahid AB, Mikheev A, Yang AI, Samadani U, Rusinek H. Calculation of brain atrophy using computed tomography and a new atrophy measurement tool. InMedical Imaging 2015: Image Processing. 2015 Mar; 9413: 751-759. SPIE.
Chrzan R, Gleń A, Bryll A, Urbanik A. Computed tomography assessment of brain atrophy in centenarians. International Journal of Environmental Research and Public Health. 2019 Sep ; 16(19):3659. doi: 10.3390/ijerph16193659.
Zahid AB, Mikheev A, Srivatsa N, Babb J, Samadani U, Rusinek H. Accelerated brain atrophy on serial computed tomography: Potential marker of the progression of alzheimer's disease. Journal of computer assisted tomography. 2016 Oct; 40(5):827-32. doi: 10.1097/RCT.0000000000000435.
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