Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/10610
Title: Selection of the control group for VBM analysis: influence of covariates, matching and sample size.
Authors: Pell, Gaby S;Briellmann, Regula S;Chan, Chow Huat Patrick;Pardoe, Heath R;Abbott, David F;Jackson, Graeme D
Affiliation: Brain Research Institute, Neuroscience Building, Austin Health, Victoria, Australia.
Issue Date: 7-Mar-2008
Citation: Neuroimage 2008; 41(4): 1324-35
Abstract: Variability in the control group plays a crucial role in voxel-based morphometry (VBM) detection of structural abnormalities. Two common methods of minimising this variance are inclusion of covariates and matching of control and patient groups. We address two major questions: What are the optimal covariates in the VBM design? When a large pool of controls are available, is it better to choose a subset of matched control subjects at the expense of numbers, or include all available controls? We used regression analysis in a group of 176 controls to determine the contribution of gender, age, and total intracranial volume (TIV) to volume variation. We then used different matching and covariate strategies to determine the optimal design for VBM detection of abnormality in epilepsy patients with hippocampal sclerosis. In the regression analysis, focal gender effects disappeared with inclusion of TIV as an additional regressor. Age had a small but unique contribution to focal volume changes. In the VBM analysis of HS patients, detection of abnormalities was strongly influenced by choice of covariates. The optimal combination was different for grey and white matter (for grey matter: TIV; for temporal lobe white matter: TIV, age and gender). A control group size of 70-90 subjects allowed optimal detection of volume loss in the hippocampus and thalamus. At these group sizes, matched control groups did not consistently prove superior to deliberately "unmatched" groups of the same size. The optimal detection of volume loss was obtained with all available control subjects.
Internal ID Number: 18467131
URI: http://ahro.austin.org.au/austinjspui/handle/1/10610
DOI: 10.1016/j.neuroimage.2008.02.050
URL: http://www.ncbi.nlm.nih.gov/pubmed/18467131
Type: Journal Article
Subjects: Adolescent
Adult
Aged
Aging.physiology
Analysis of Variance
Brain.anatomy & histology.physiology
Data Interpretation, Statistical
Epilepsy.genetics.pathology.physiopathology
Female
Hippocampus.pathology.physiopathology
Humans
Image Processing, Computer-Assisted.methods
Magnetic Resonance Imaging
Male
Middle Aged
Regression Analysis
Sample Size
Sclerosis
Sex Characteristics
Appears in Collections:Journal articles

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