English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly

Liem, F., Merillat, S., Bezzola, L., Hirsiger, S., Philipp, M., Madhyastha, T., et al. (2015). Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly. NeuroImage, 108, 95-109. doi:10.1016/j.neuroimage.2014.12.035.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-780D-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-791E-5
Genre: Journal Article

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Liem, Franz1, 2, Author              
Merillat, Susan2, 3, Author
Bezzola, Ladina2, 3, Author
Hirsiger, Sarah2, 3, Author
Philipp, Michel4, Author
Madhyastha, Tara5, Author
Jancke, Lutz1, 2, 3, 6, Author
Affiliations:
1Division of Neuropsychology, Department of Psychology, University of Zurich, Switzerland, ou_persistent22              
2University Research Priority Program “Dynamics of Healthy Aging”, University of Zurich, Switzerland, ou_persistent22              
3International Normal Aging and Plasticity Imaging Center, University of Zurich, Switzerland, ou_persistent22              
4Department of Psychological Methods, Evaluation, and Statistics, University of Zurich, Switzerland, ou_persistent22              
5Department of Radiology, University of Washington, Seattle, WA, USA, ou_persistent22              
6Department of Special Education, King Abdulaziz University, Jeddah, Saudi Arabia, ou_persistent22              

Content

show
hide
Free keywords: Surface-based morphometry; Cortical thickness; Cortical surface area; Cortical volume; Subcortical volume
 Abstract: FreeSurfer is a tool to quantify cortical and subcortical brain anatomy automatically and noninvasively. Previous studies have reported reliability and statistical power analyses in relatively small samples or only selected one aspect of brain anatomy. Here, we investigated reliability and statistical power of cortical thickness, surface area, volume, and the volume of subcortical structures in a large sample (N = 189) of healthy elderly subjects (64 + years). Reliability (intraclass correlation coefficient) of cortical and subcortical parameters is generally high (cortical: ICCs > 0.87, subcortical: ICCs > 0.95). Surface-based smoothing increases reliability of cortical thickness maps, while it decreases reliability of cortical surface area and volume. Nevertheless, statistical power of all measures benefits from smoothing. When aiming to detect a 10% difference between groups, the number of subjects required to test effects with sufficient power over the entire cortex varies between cortical measures (cortical thickness: N = 39, surface area: N = 21, volume: N = 81; 10 mm smoothing, power = 0.8, α = 0.05). For subcortical regions this number is between 16 and 76 subjects, depending on the region. We also demonstrate the advantage of within-subject designs over between-subject designs. Furthermore, we publicly provide a tool that allows researchers to perform a priori power analysis and sensitivity analysis to help evaluate previously published studies and to design future studies with sufficient statistical power.

Details

show
hide
Language(s): eng - English
 Dates: 2014-12-112014-12-192015-03
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: BibTex Citekey: pmid25534113
DOI: 10.1016/j.neuroimage.2014.12.035
PMID: 25534113
Other: Epub 2014
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: NeuroImage
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 108 Sequence Number: - Start / End Page: 95 - 109 Identifier: ISSN: 1053-8119
CoNE: /journals/resource/954922650166