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Global Cerebral Atrophy Detected by Routine Imaging: Relationship with Age, Hippocampal Atrophy, and White Matter Hyperintensities
Author(s) -
AlJanabi Omar M.,
Panuganti Pradeep,
Abner Erin L.,
Bahrani Ahmed A.,
Murphy Ronan,
Bardach Shoshana H.,
CabanHolt Allison,
Nelson Peter T.,
Gold Brian T.,
Smith Charles D.,
Wilcock Donna M.,
Jicha Gregory A.
Publication year - 2018
Publication title -
journal of neuroimaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.822
H-Index - 64
eISSN - 1552-6569
pISSN - 1051-2284
DOI - 10.1111/jon.12494
Subject(s) - hyperintensity , medicine , atrophy , logistic regression , dementia , cognitive decline , cerebral atrophy , neuroimaging , temporal lobe , white matter , population , magnetic resonance imaging , disease , cardiology , radiology , psychiatry , epilepsy , environmental health
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.