X

Forgot your Password

If you have forgotten your password, please enter your account email below and we will reset your password and email you the new password.

X

Login to SciCrunch

X

Register an Account

Delete Saved Search

Are you sure you want to delete this saved search?

NO

NIF LinkOut Portal

FILTERS

Scan-rescan reliability of subcortical brain volumes derived from automated segmentation.

Authors:
Morey RA, Selgrade ES, Wagner HR, Huettel SA, Wang L, McCarthy G
Affiliation:
Journal:
Human brain mapping

Abstract

Large-scale longitudinal studies of regional brain volume require reliable quantification using automated segmentation and labeling. However, repeated MR scanning of the same subject, even if using the same scanner and acquisition parameters, does not result in identical images due to small changes in image orientation, changes in prescan parameters, and magnetic field instability. These differences may lead to appreciable changes in estimates of volume for different structures. This study examined scan-rescan reliability of automated segmentation algorithms for measuring several subcortical regions, using both within-day and across-day comparison sessions in a group of 23 normal participants. We found that the reliability of volume measures including percent volume difference, percent volume overlap (Dice's coefficient), and intraclass correlation coefficient (ICC), varied substantially across brain regions. Low reliability was observed in some structures such as the amygdala (ICC = 0.6), with higher reliability (ICC = 0.9) for other structures such as the thalamus and caudate. Patterns of reliability across regions were similar for automated segmentation with FSL/FIRST and FreeSurfer (longitudinal stream). Reliability was associated with the volume of the structure, the ratio of volume to surface area for the structure, the magnitude of the interscan interval, and the method of segmentation. Sample size estimates for detecting changes in brain volume for a range of likely effect sizes also differed by region. Thus, longitudinal research requires a careful analysis of sample size and choice of segmentation method combined with a consideration of the brain structure(s) of interest and the magnitude of the anticipated effects.

  1. Welcome

    Welcome to NIF. Explore available research resources: data, tools and materials, from across the web

  2. Community Resources

    Search for resources specially selected for NIF community

  3. More Resources

    Search across hundreds of additional biomedical databases

  4. Literature

    Search Pub Med abstracts and full text from PubMed Central

  5. Insert your Query

    Enter your search terms here and hit return. Search results for the selected tab will be returned.

  6. Join the Community

    Click here to login or register and join this community.

  7. Categories

    Narrow your search by selecting a category. For additional help in searching, view our tutorials.

  8. Query Info

    Displays the total number of search results. Provides additional information on search terms, e.g., automated query expansions, and any included categories or facets. Expansions, filters and facets can be removed by clicking on the X. Clicking on the + restores them.

  9. Search Results

    Displays individual records and a brief description. Click on the icons below each record to explore additional display options.

X