Introduction: Alzheimer’s disease is a chronic neurodegenerative disease that is being diagnosed more and more commonly in neurology clinics. Physicians are familiar to see brain atrophy definition in the MRI reports of these patients. To aid physicians in the diagnosis, we aimed to find a novel radiological diagnostic index for Alzheimer’s disease by making MRI-based specific measurements. Materials and Methods: Fifty-three patients diagnosed with typical Alzheimer’s disease and fifty-five healthy control cases were enrolled in our study. Demographic data containing age, gender, and medical history were recorded. Non-contrast 1.5T brain magnetic resonance images of all participants were collected. Measurements of the prefrontal and precentral sulcus cortical gray matter thickness, as well as the area of the pons, were done by a radiologist. The cortical thickness to the pontine area ratio was calculated and compared between the two groups. Finally, a ROC curve analysis was done to find a certain index value. Results: In the patient group, prefrontal and precentral gray matter thicknesses were significantly lower than in the control group. Also, the ROC curve analysis revealed a crucial ratio of prefrontal gray matter thickness to the pontine area. This novel radiological index ratio distinguished Alzheimer's disease atrophy from healthy variances with a sensitivity of 21% and a specificity of 97%. Conclusion: The radiological ratios that we found in our study can not be caught by the human eye. Calculating and reporting our suggested index ratio in brain MRI reports may provide additional information for physicians diagnosing Alzheimer's disease.
Published in | International Journal of Psychological and Brain Sciences (Volume 9, Issue 1) |
DOI | 10.11648/j.ijpbs.20240901.11 |
Page(s) | 1-7 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Alzheimer’s Disease, Alzheimer Dementia, Brain Imaging, Dementia, Novel Diagnostic Index, Prefrontal Cortex to Pons Ratio
[1] | Gurvit H, Emre M, Tinaz S, Bilgic B, Hanagasi H, Sahin H, Gurol E, Kvaloy JT, Harmanci H. The prevalence of dementia in an urban Turkish population. Am J Alzheimers Dis Other Demen. 2008 Mar; 23 (1): 67-76. |
[2] | Şentürk İA, Başar HM, Soykök GU, et al. Prevalence of Dementia and Mild Cognitive Impairment in a Rural Area of Sivas, Turkey. Cureus. 2021; 13 (2): e13069. |
[3] | 2021 Alzheimer's disease facts and figures. Alzheimers Dement. 2021 Mar; 17 (3): 327-406. |
[4] | Perl DP. Neuropathology of Alzheimer's disease. Mt Sinai J Med. 2010; 77 (1): 32-42. |
[5] | James BD, Leurgans SE, Hebert LE, Scherr PA, Yaffe K, Bennett DA. Contribution of Alzheimer disease to mortality in the United States. Neurology. 2014; 82 (12): 1045-1050. |
[6] | Stokes AC, Weiss J, Lundberg DJ, et al. Estimates of the Association of Dementia With US Mortality Levels Using Linked Survey and Mortality Records. JAMA Neurol. 2020; 77 (12): 1543–1550. |
[7] | Hooker D. Early human fetal behavior, with a preliminary note on double simultaneous fetal stimulation. Res Publ Assoc Res Nerv Ment Dis. 1954; 33: 98-113. |
[8] | Miller JL, Sonies BC, Macedonia C. Emergence of oropharyngeal, laryngeal and swallowing activity in the developing fetal upper aerodigestive tract: an ultrasound evaluation. Early Hum Dev. 2003; Feb; 71 (1): 61-87. |
[9] | Erman AB, Kejner AE, Hogikyan ND, Feldman EL. Disorders of cranial nerves IX and X. Semin Neurol. 2009; 29 (1): 85-92. |
[10] | Nicholls JG, Paton JF. Brainstem: neural networks vital for life. Philos Trans R Soc Lond B Biol Sci. 2009; 364 (1529): 2447-2451. |
[11] | Wilks T, Gerber RJ, Erdie-Lalena C. Developmental milestones: cognitive development. Pediatr Rev. 2010; Sep; 31 (9): 364-7. |
[12] | Corey-Bloom J. The ABC of Alzheimer's disease: cognitive changes and their management in Alzheimer's disease and related dementias. Int Psychogeriatr. 2002; 14 Suppl 1: 51-75. |
[13] | Larson EB, Kukull WA, Katzman RL. Cognitive impairment: dementia and Alzheimer's disease. Annu Rev Public Health. 1992; 13: 431-49. |
[14] | Stout JC, Bondi MW, Jernigan TL, Archibald SL, Delis DC, Salmon DP. Regional cerebral volume loss associated with verbal learning and memory in dementia of the Alzheimer type. Neuropsychology. 1999; Apr; 13 (2): 188-97. |
[15] | Harper L, Bouwman F, Burton EJ, et al. Patterns of atrophy in pathologically confirmed dementias: a voxelwise analysis. Journal of Neurology, Neurosurgery & Psychiatry. 2017; 88: 908-916. |
[16] | Logue MW, Posner H, Green RC, Moline M, Cupples LA, Lunetta KL, Zou H, Hurt SW, Farrer LA, Decarli C. MIRAGE Study Group. Magnetic resonance imaging-measured atrophy and its relationship to cognitive functioning in vascular dementia and Alzheimer's disease patients. Alzheimers Dement. 2011; Sep; 7 (5): 493-500. |
[17] | Persson K, Eldholm RS, Barca ML, Cavallin L, Ferreira D, Knapskog AB, Selbæk G, Brækhus A, Saltvedt I, Westman E, Engedal K. MRI-assessed atrophy subtypes in Alzheimer's disease and the cognitive reserve hypothesis. PLoS One. 2017; Oct 16; 12 (10): e0186595. |
[18] | Khadhraoui, E., Müller, S. J., Hansen, N. et al. Manual and automated analysis of atrophy patterns in dementia with Lewy bodies on MRI. BMC Neurol 2022; 22, 114. |
[19] | E. J. Burton, R. Barber, E. B. Mukaetova-Ladinska, J. Robson, R. H. Perry, E. Jaros, R. N. Kalaria, J. T. O’Brien. Medial temporal lobe atrophy on MRI differentiates Alzheimer's disease from dementia with Lewy bodies and vascular cognitive impairment: a prospective study with pathological verification of diagnosis. Brain. 2009; Volume 132, Issue 1, January: 195–203. |
[20] | Bang OY, Lee PH, Kim SY, et al. Pontine atrophy precedes cerebellar degeneration in spinocerebellar ataxia 7: MRI-based volumetric analysis. Journal of Neurology, Neurosurgery & Psychiatry. 2004; 75: 1452-1456. |
[21] | Mascalchi, M. MRI CNS Atrophy Pattern and the Etiologies of Progressive Ataxias. Tomography. 2022; 8, 423-437. |
[22] | Scahill RI, Schott JM, Stevens JM, Rossor MN, Fox NC. Mapping the evolution of regional atrophy in Alzheimer's disease: unbiased analysis of fluid-registered serial MRI. Proc Natl Acad Sci U S A. 2002; 99 (7): 4703-4707. |
[23] | Sabuncu MR, Desikan RS, Sepulcre J, et al. The Dynamics of Cortical and Hippocampal Atrophy in Alzheimer Disease. Arch Neurol. 2011; 68 (8): 1040–1048. |
[24] | Wu, BS., Zhang, YR., Li, HQ. et al. Cortical structure and the risk for Alzheimer’s disease: a bidirectional Mendelian randomization study. Transl Psychiatry. 2021; 11, 476. |
APA Style
Arslan, G. (2024). Cortical Gray Matter Thickness to Pons Ratio: A Novel Diagnostic Index for Alzheimer’s Disease. International Journal of Psychological and Brain Sciences, 9(1), 1-7. https://doi.org/10.11648/j.ijpbs.20240901.11
ACS Style
Arslan, G. Cortical Gray Matter Thickness to Pons Ratio: A Novel Diagnostic Index for Alzheimer’s Disease. Int. J. Psychol. Brain Sci. 2024, 9(1), 1-7. doi: 10.11648/j.ijpbs.20240901.11
AMA Style
Arslan G. Cortical Gray Matter Thickness to Pons Ratio: A Novel Diagnostic Index for Alzheimer’s Disease. Int J Psychol Brain Sci. 2024;9(1):1-7. doi: 10.11648/j.ijpbs.20240901.11
@article{10.11648/j.ijpbs.20240901.11, author = {Guven Arslan}, title = {Cortical Gray Matter Thickness to Pons Ratio: A Novel Diagnostic Index for Alzheimer’s Disease}, journal = {International Journal of Psychological and Brain Sciences}, volume = {9}, number = {1}, pages = {1-7}, doi = {10.11648/j.ijpbs.20240901.11}, url = {https://doi.org/10.11648/j.ijpbs.20240901.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijpbs.20240901.11}, abstract = {Introduction: Alzheimer’s disease is a chronic neurodegenerative disease that is being diagnosed more and more commonly in neurology clinics. Physicians are familiar to see brain atrophy definition in the MRI reports of these patients. To aid physicians in the diagnosis, we aimed to find a novel radiological diagnostic index for Alzheimer’s disease by making MRI-based specific measurements. Materials and Methods: Fifty-three patients diagnosed with typical Alzheimer’s disease and fifty-five healthy control cases were enrolled in our study. Demographic data containing age, gender, and medical history were recorded. Non-contrast 1.5T brain magnetic resonance images of all participants were collected. Measurements of the prefrontal and precentral sulcus cortical gray matter thickness, as well as the area of the pons, were done by a radiologist. The cortical thickness to the pontine area ratio was calculated and compared between the two groups. Finally, a ROC curve analysis was done to find a certain index value. Results: In the patient group, prefrontal and precentral gray matter thicknesses were significantly lower than in the control group. Also, the ROC curve analysis revealed a crucial ratio of prefrontal gray matter thickness to the pontine area. This novel radiological index ratio distinguished Alzheimer's disease atrophy from healthy variances with a sensitivity of 21% and a specificity of 97%. Conclusion: The radiological ratios that we found in our study can not be caught by the human eye. Calculating and reporting our suggested index ratio in brain MRI reports may provide additional information for physicians diagnosing Alzheimer's disease. }, year = {2024} }
TY - JOUR T1 - Cortical Gray Matter Thickness to Pons Ratio: A Novel Diagnostic Index for Alzheimer’s Disease AU - Guven Arslan Y1 - 2024/01/08 PY - 2024 N1 - https://doi.org/10.11648/j.ijpbs.20240901.11 DO - 10.11648/j.ijpbs.20240901.11 T2 - International Journal of Psychological and Brain Sciences JF - International Journal of Psychological and Brain Sciences JO - International Journal of Psychological and Brain Sciences SP - 1 EP - 7 PB - Science Publishing Group SN - 2575-1573 UR - https://doi.org/10.11648/j.ijpbs.20240901.11 AB - Introduction: Alzheimer’s disease is a chronic neurodegenerative disease that is being diagnosed more and more commonly in neurology clinics. Physicians are familiar to see brain atrophy definition in the MRI reports of these patients. To aid physicians in the diagnosis, we aimed to find a novel radiological diagnostic index for Alzheimer’s disease by making MRI-based specific measurements. Materials and Methods: Fifty-three patients diagnosed with typical Alzheimer’s disease and fifty-five healthy control cases were enrolled in our study. Demographic data containing age, gender, and medical history were recorded. Non-contrast 1.5T brain magnetic resonance images of all participants were collected. Measurements of the prefrontal and precentral sulcus cortical gray matter thickness, as well as the area of the pons, were done by a radiologist. The cortical thickness to the pontine area ratio was calculated and compared between the two groups. Finally, a ROC curve analysis was done to find a certain index value. Results: In the patient group, prefrontal and precentral gray matter thicknesses were significantly lower than in the control group. Also, the ROC curve analysis revealed a crucial ratio of prefrontal gray matter thickness to the pontine area. This novel radiological index ratio distinguished Alzheimer's disease atrophy from healthy variances with a sensitivity of 21% and a specificity of 97%. Conclusion: The radiological ratios that we found in our study can not be caught by the human eye. Calculating and reporting our suggested index ratio in brain MRI reports may provide additional information for physicians diagnosing Alzheimer's disease. VL - 9 IS - 1 ER -