Omar M Al-Janabi1,2, Pradeep Panuganti3, Erin L Abner1,4, Ahmed A Bahrani1,5, Ronan Murphy1,3, Shoshana H Bardach1,6, Allison Caban-Holt1,2, Peter T Nelson1,7, Brian T Gold1,8, Charles D Smith1,3, Donna M Wilcock1,9, Gregory A Jicha1,2,3. 1. Sanders-Brown Center on Aging, Lexington, KY. 2. Departments of Behavioral Science, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY. 3. Neurology, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY. 4. Epidemiology and Biostatistics, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY. 5. Biomedical Engineering, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY. 6. Gerontology, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY. 7. Pathology, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY. 8. Neuroscience, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY. 9. Physiology, University of Kentucky Colleges of Medicine, Public Health and Engineering, Lexington, KY.
Abstract
BACKGROUND AND PURPOSE: Interpreting the clinical significance of moderate-to-severe global cerebral atrophy (GCA) is a conundrum for many clinicians, who visually interpret brain imaging studies in routine clinical practice. GCA may be attributed to normal aging, Alzheimer's disease (AD), or cerebrovascular disease (CVD). Understanding the relationships of GCA with aging, AD, and CVD is important for accurate diagnosis and treatment decisions for cognitive complaints. METHODS: To elucidate the relative associations of age, moderate-to-severe white matter hyperintensities (WMHs), and moderate-to-severe medial temporal lobe atrophy (MTA), with moderate-to-severe GCA, we visually rated clinical brain imaging studies of 325 participants from a community based sample. Logistic regression analysis was conducted to assess the relations of GCA with age, WMH, and MTA. RESULTS: The mean age was 76.2 (±9.6) years, 40.6% were male, and the mean educational attainment was 15.1 (±3.7) years. Logistic regression results demonstrated that while a 1-year increase in age was associated with GCA (OR = 1.04; P = .04), MTA (OR = 3.7; P < .001), and WMH (OR = 8.80; P < .001) were strongly associated with GCA in our study population. Partial correlation analysis showed that the variance of GCA explained by age is less than the variance attributed to MTA and WMH (r = .13, .21, and .43, respectively). CONCLUSIONS: Moderate-to-severe GCA is most likely to occur in the presence of AD or CVD and should not be solely attributed to age when evaluating clinical imaging findings in the workup of cognitive complaints. Developing optimal diagnostic and treatment strategies for cognitive decline in the setting of GCA requires an understanding of its risk factors in the aging population.
BACKGROUND AND PURPOSE: Interpreting the clinical significance of moderate-to-severe global cerebral atrophy (GCA) is a conundrum for many clinicians, who visually interpret brain imaging studies in routine clinical practice. GCA may be attributed to normal aging, Alzheimer's disease (AD), or cerebrovascular disease (CVD). Understanding the relationships of GCA with aging, AD, and CVD is important for accurate diagnosis and treatment decisions for cognitive complaints. METHODS: To elucidate the relative associations of age, moderate-to-severe white matter hyperintensities (WMHs), and moderate-to-severe medial temporal lobe atrophy (MTA), with moderate-to-severe GCA, we visually rated clinical brain imaging studies of 325 participants from a community based sample. Logistic regression analysis was conducted to assess the relations of GCA with age, WMH, and MTA. RESULTS: The mean age was 76.2 (±9.6) years, 40.6% were male, and the mean educational attainment was 15.1 (±3.7) years. Logistic regression results demonstrated that while a 1-year increase in age was associated with GCA (OR = 1.04; P = .04), MTA (OR = 3.7; P < .001), and WMH (OR = 8.80; P < .001) were strongly associated with GCA in our study population. Partial correlation analysis showed that the variance of GCA explained by age is less than the variance attributed to MTA and WMH (r = .13, .21, and .43, respectively). CONCLUSIONS: Moderate-to-severe GCA is most likely to occur in the presence of AD or CVD and should not be solely attributed to age when evaluating clinical imaging findings in the workup of cognitive complaints. Developing optimal diagnostic and treatment strategies for cognitive decline in the setting of GCA requires an understanding of its risk factors in the aging population.
Authors: Susan M Resnick; Dzung L Pham; Michael A Kraut; Alan B Zonderman; Christos Davatzikos Journal: J Neurosci Date: 2003-04-15 Impact factor: 6.167
Authors: Thomas Gattringer; Christian Enzinger; Stefan Ropele; Faton Gorani; Katja Elisabeth Petrovic; Reinhold Schmidt; Franz Fazekas Journal: Dement Geriatr Cogn Disord Date: 2012-02-24 Impact factor: 2.959
Authors: Frederick A Schmitt; Peter T Nelson; Erin Abner; Stephen Scheff; Gregory A Jicha; Charles Smith; Gregory Cooper; Marta Mendiondo; Deborah D Danner; Linda J Van Eldik; Allison Caban-Holt; Mark A Lovell; Richard J Kryscio Journal: Curr Alzheimer Res Date: 2012-07 Impact factor: 3.498
Authors: C DeCarli; D G Murphy; M Tranh; C L Grady; J V Haxby; J A Gillette; J A Salerno; A Gonzales-Aviles; B Horwitz; S I Rapoport Journal: Neurology Date: 1995-11 Impact factor: 9.910
Authors: Domenico Inzitari; Giovanni Pracucci; Anna Poggesi; Giovanna Carlucci; Frederik Barkhof; Hugues Chabriat; Timo Erkinjuntti; Franz Fazekas; José M Ferro; Michael Hennerici; Peter Langhorne; John O'Brien; Philip Scheltens; Marieke C Visser; Lars-Olof Wahlund; Gunhild Waldemar; Anders Wallin; Leonardo Pantoni Journal: BMJ Date: 2009-07-06
Authors: Man Qu; William Robert Kwapong; Chenlei Peng; Yungang Cao; Fan Lu; Meixiao Shen; Zhao Han Journal: Brain Behav Date: 2019-12-25 Impact factor: 2.708