It appears no script is enabled within your browser. Please enable JavaScript to use this site.
Skip header and navigation
Home
View Selections:
0
Items
Help
Print
Allometric scaling of brain regions to intra-cranial volume: An epidemiological MRI study.
https://arctichealth.org/en/permalink/ahliterature289829
Source
Hum Brain Mapp. 2017 01; 38(1):151-164
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Intramural
Date
01-2017
More detail
Author
Laura W de Jong
Jean-Sébastien Vidal
Lars E Forsberg
Alex P Zijdenbos
Thaddeus Haight
Sigurdur Sigurdsson
Vilmundur Gudnason
Mark A van Buchem
Lenore J Launer
Author Affiliation
Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Source
Hum Brain Mapp. 2017 01; 38(1):151-164
Date
01-2017
Language
English
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Intramural
Keywords
Aged
Aged, 80 and over
Aging
Algorithms
Alzheimer Disease - diagnostic imaging - epidemiology
Brain - diagnostic imaging - pathology
Brain Mapping
Community Health Planning
Coronary Artery Disease - diagnostic imaging - epidemiology - pathology
Female
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Male
Netherlands - epidemiology
Reproducibility of Results
Sex Factors
Abstract
There is growing evidence that sub-structures of the brain scale allometrically to total brain size, that is, in a non-proportional and non-linear way. Here, scaling of different volumes of interest (VOI) to intra-cranial volume (ICV) was examined. It was assessed whether scaling was allometric or isometric and whether scaling coefficients significantly differed from each other. We also tested to what extent allometric scaling of VOI was introduced by the automated segmentation technique. Furthermore, reproducibility of allometric scaling was studied different age groups and study populations. Study samples included samples of cognitively healthy adults from the community-based Age Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik Study) (N?=?3,883), the Coronary Artery Risk Development in Young Adults Study (CARDIA) (N =709), and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N?=?180). Data encompassed participants with different age, ethnicity, risk factor profile, and ICV and VOI obtained with different automated MRI segmentation techniques. Our analysis showed that (1) allometric scaling is a trait of all parts of the brain, (2) scaling of neo-cortical white matter, neo-cortical gray matter, and deep gray matter structures including the cerebellum are significantly different from each other, and (3) allometric scaling of brain structures cannot solely be explained by age-associated atrophy, sex, ethnicity, or a systematic bias from study-specific segmentation algorithm, but appears to be a true feature of brain geometry. Hum Brain Mapp 38:151-164, 2017. © 2016 Wiley Periodicals, Inc.
Notes
Cites: Hum Brain Mapp. 2011 Apr;32(4):641-53 PMID 20572207
Cites: Am J Epidemiol. 2007 May 1;165(9):1076-87 PMID 17351290
Cites: Brain Behav Evol. 1985;27(1):28-40 PMID 3836731
Cites: Acad Radiol. 2008 Mar;15(3):300-13 PMID 18280928
Cites: Hum Brain Mapp. 2006 Apr;27(4):314-24 PMID 16124013
Cites: Neuroimage. 2010 Dec;53(4):1244-55 PMID 20600995
Cites: Med Image Comput Comput Assist Interv. 2008;11(Pt 1):620-7 PMID 18979798
Cites: Psychiatry Res. 2011 Aug 30;193(2):113-22 PMID 21684724
Cites: Neuroreport. 2002 Dec 3;13(17):2371-4 PMID 12488829
Cites: Neuroimage. 2008 Aug 15;42(2):535-47 PMID 18599317
Cites: J Comput Assist Tomogr. 1998 Sep-Oct;22(5):827-37 PMID 9754125
Cites: Cereb Cortex. 1994 Jul-Aug;4(4):331-43 PMID 7950307
Cites: J Theor Biol. 1982 Mar 7;95(1):37-41 PMID 7087496
Cites: IEEE Trans Med Imaging. 2003 Mar;22(3):414-23 PMID 12760558
Cites: Cereb Cortex. 2008 Sep;18(9):2181-91 PMID 18234686
Cites: Neurosci Lett. 2011 Apr 8;493(1-2):8-13 PMID 21296128
Cites: IEEE Trans Med Imaging. 2002 Oct;21(10):1280-91 PMID 12585710
Cites: Front Aging Neurosci. 2014 Oct 07;6:264 PMID 25339897
Cites: J Clin Epidemiol. 1988;41(11):1105-16 PMID 3204420
Cites: Neuroimage. 2002 Feb;15(2):422-34 PMID 11798276
Cites: Neuroimage. 2012 Feb 15;59(4):3862-70 PMID 22119006
Cites: Brain Behav Evol. 1988;32(1):17-26 PMID 3056571
Cites: Neuroimage. 2012 Nov 15;63(3):1257-72 PMID 22877579
Cites: Neuroimage. 1999 Feb;9(2):179-94 PMID 9931268
Cites: Nat Neurosci. 1999 Oct;2(10):859-61 PMID 10491602
Cites: Brain. 1997 Apr;120 ( Pt 4):701-22 PMID 9153131
Cites: Comput Med Imaging Graph. 1994 Jan-Feb;18(1):11-23 PMID 8156533
Cites: Front Neurosci. 2014 Nov 06;8:356 PMID 25414635
PubMed ID
27557999
View in PubMed
Less detail
Permalink