REGIONAL WHITE MATTER VOLUME DIFFERENCES IN NONDEMENTED AGING AND ALZHEIMER’S DISEASE

By David H. Salat, Douglas N. Greve, J. Pacheco, Brian T. Quinn, Karl G. Helmer, Randy L. Buckner, Bruce Fischl. NeuroImage, 2008

312 citations recorded by the source corpus.

Accumulating evidence suggests that altered cerebral white matter (WM) influences normal aging, and further that WM degeneration may modulate the clinical expression of Alzheimer’s disease (AD). Here we conducted a study of differences in WM volume across the adult age span and in AD employing a newly developed, automated method for regional parcellation of the subcortical WM that uses curvature landmarks and gray matter (GM)/WM surface boundary information. This procedure measures the volume of gyral WM, utilizing a distance constraint to limit the measurements from extending into the centrum semiovale. Regional estimates were first established to be reliable across two scan sessions in 20 young healthy individuals. Next, the method was applied to a large clinically-characterized sample of 299 individuals including 73 normal older adults and 91 age-matched participants with very mild to mild AD. The majority of measured regions showed a decline in volume with increasing age, with strong effects found in bilateral fusiform, lateral orbitofrontal, superior frontal, medial orbital frontal, inferior temporal, and middle temporal WM. The association between WM volume and age was quadratic in many regions suggesting that WM volume loss accelerates in advanced aging. A number of WM regions were further reduced in AD with parahippocampal, entorhinal, inferior parietal and rostral middle frontal WM showing the strongest AD-associated reductions. There were minimal sex effects after correction for intracranial volume, and there were associations between ventricular volume and regional WM volumes in the older adults and AD that were not apparent in the younger adults. Certain results, such as the loss of WM in the fusiform region with aging, were unexpected and provide novel insight into patterns of age associated neural and cognitive decline. Overall, these results demonstrate the utility of automated regional WM measures in revealing the distinct patterns of age and AD associated volume loss that may contribute to cognitive decline.

Subfields: Cognitive Neuroscience, Psychiatry and Mental health, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/1170ab6ccf133ae5775d093703d6bd808cdae72a

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Citations in the corpus

Open Access Series of Imaging Studies (OASIS): Longitudinal MRI Data in Nondemented and Demented Older Adults (2010, methodology): “Portions of the clinical, demographic, and longitudinal image data obtained from subjects in this release have been used in previous publications (Dickerson et al., 2008; Fotenos, Mintun, Snyder, Morris, & Buckner, 2008; He, Chen, & Evans, 2008; Salat et al., 2009; Dickerson et al., 2009; Buckner et”
Structural Brain Changes in Aging: Courses, Causes and Cognitive Consequences (2010, result): “Course Cerebellum GM mainly linearly related, while WM are best characterized by a nonlinear function of prolonged volume increase and accelerated decrease in high age Effects There is agreement across studies that CSF compartments increase in volume with age [22, 24, 30, 32, 43, 45, 74-76], and som”
Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. (2010, methodology): “WM voxels within a distance of 5 mm from the cortical surface was labeled according to the label of the nearest cortical vertex (Fjell et al. 2008; Salat, Greve, et al. 2009) yielding 33 bilateral gyral WM segmentations, each corresponding to a cortical area.”
Brain maturation in adolescence and young adulthood: regional age-related changes in cortical thickness and white matter volume and microstructure. (2010, methodology): “Based on the preceding cortical parcellation, regional WM volume was calculated by a newly developed algorithm (Fjell et al. 2008; Salat et al. 2009).”
The Effects of FreeSurfer Version, Workstation Type, and Macintosh Operating System Version on Anatomical Volume and Cortical Thickness Measurements (2012, background): “[13] reported within-scanner reliabilities of white matter structures on the order of 5% (signed differences) with some exceptions as large as 29.”
The Lifespan Human Connectome Project in Aging: An overview (2018, unknown): “, 2001), non-demented aging (Head et al., 2004; Salat et al., 2009), ‘normal’ aging (Gideon et al.”
Multi-compartment microscopic diffusion imaging (2016, background): “A distance constraint halted the label propagation after 5 mm, thus producing an anatomical parcellation of the gyral white matter (Salat et al., 2009).”
FreeSurfer (2012, background): “…basis of neuroanatomical variability and change (Kremen et al., 2010; Panizzon et al., 2009), as well as healthy development (Isaacs et al., 2008; Martinussen et al., 2005) and aging (Fjell et al., 2005, 2006; Salat et al., 2004, 2005a, 2005b, 2009; Walhovd et al., 2004, 2005a, 2005b, 2006).”