Format

Send to

Choose Destination
See comment in PubMed Commons below
Hum Brain Mapp. 2013 Nov;34(11):3000-9. doi: 10.1002/hbm.22120. Epub 2012 Jul 17.

Sample size estimates for well-powered cross-sectional cortical thickness studies.

Author information

1
Brain Research Institute, Florey Neuroscience Institutes, Melbourne Brain Centre, Austin Hospital, Heidelberg, Victoria, Australia; Department of Medicine, The University of Melbourne, Victoria, Australia.

Abstract

INTRODUCTION:

Cortical thickness mapping is a widely used method for the analysis of neuroanatomical differences between subject groups. We applied power analysis methods over a range of image processing parameters to derive a model that allows researchers to calculate the number of subjects required to ensure a well-powered cross-sectional cortical thickness study.

METHODS:

0.9-mm isotropic T1 -weighted 3D MPRAGE MRI scans from 98 controls (53 females, age 29.1 ± 9.7 years) were processed using Freesurfer 5.0. Power analyses were carried out using vertex-wise variance estimates from the coregistered cortical thickness maps, systematically varying processing parameters. A genetic programming approach was used to derive a model describing the relationship between sample size and processing parameters. The model was validated on four Alzheimer's Disease Neuroimaging Initiative control datasets (mean 126.5 subjects/site, age 76.6 ± 5.0 years).

RESULTS:

Approximately 50 subjects per group are required to detect a 0.25-mm thickness difference; less than 10 subjects per group are required for differences of 1 mm (two-sided test, 10 mm smoothing, α = 0.05). Sample size estimates were heterogeneous over the cortical surface. The model yielded sample size predictions within 2-6% of that determined experimentally using independent data from four other datasets. Fitting parameters of the model to data from each site reduced the estimation error to less than 2%.

CONCLUSIONS:

The derived model provides a simple tool for researchers to calculate how many subjects should be included in a well-powered cortical thickness analysis.

KEYWORDS:

MRI; cortical thickness; morphometry; neuroimaging; power analysis; study design

PMID:
22807270
PMCID:
PMC3500581
DOI:
10.1002/hbm.22120
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Wiley Icon for PubMed Central
    Loading ...
    Support Center