Mapping reliability in multicenter MRI: Voxel-based morphometry and cortical thickness
Multicenter structural MRI studies can have greater statistical power than single‐center studies. However, across‐center differences in contrast sensitivity, spatial uniformity, etc., may lead to tissue classification or image registration differences that could reduce or wholly offset the enhanced...
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Published in | Human brain mapping Vol. 31; no. 12; pp. 1967 - 1982 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Hoboken
Wiley Subscription Services, Inc., A Wiley Company
01.12.2010
Wiley-Liss |
Subjects | |
Online Access | Get full text |
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Summary: | Multicenter structural MRI studies can have greater statistical power than single‐center studies. However, across‐center differences in contrast sensitivity, spatial uniformity, etc., may lead to tissue classification or image registration differences that could reduce or wholly offset the enhanced statistical power of multicenter data. Prior work has validated volumetric multicenter MRI, but robust methods for assessing reliability and power of multisite analyses with voxel‐based morphometry (VBM) and cortical thickness measurement (CORT) are not yet available. We developed quantitative methods to investigate the reproducibility of VBM and CORT to detect group differences and estimate heritability when MRI scans from different scanners running different acquisition protocols in a multicenter setup are included. The method produces brain maps displaying information such as lowest detectable effect size (or heritability) and effective number of subjects in the multicenter study. We applied the method to a five‐site multicenter calibration study using scanners from four different manufacturers, running different acquisition protocols. The reliability maps showed an overall good comparability between the sites, providing a reasonable gain in sensitivity in most parts of the brain. In large parts of the cerebrum and cortex scan pooling improved heritability estimates, with “effective‐N” values upto the theoretical maximum. For some areas, “optimal‐pool” maps indicated that leaving out a site would give better results. The reliability maps also reveal which brain regions are in any case difficult to measure reliably (e.g., around the thalamus). These tools will facilitate the design and analysis of multisite VBM and CORT studies for detecting group differences and estimating heritability. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc. |
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Bibliography: | Dutch Organization for Medical Research NWO ZON-MW VIDI Program - No. 917.46.370 US National Institute of Mental Health - No. MH052857 istex:23FB8921E6A186112703C0107DE36D78182E4232 ark:/67375/WNG-LN3CDM6L-R ArticleID:HBM20991 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 1065-9471 1097-0193 1097-0193 |
DOI: | 10.1002/hbm.20991 |