Reliability of brain volumes from multicenter MRI acquisition: A calibration study

Multicenter studies can provide additional information over single center studies because of their increased statistical power. Because similar acquisition protocols are being used internationally for structural magnetic resonance imaging (MRI) studies of the human brain, volumetric MRI data studies seem suitable for this purpose. Possible systematic differences between sites should be avoided, however, particularly when subtle differences in tissue volume are being searched for, such as in neuropsychiatric diseases. In this calibration study, the brains of six healthy volunteers were (re)scanned with MR scanners from four different manufacturers at five different sites, using the local acquisition protocols. The images were segmented at a central reference site. The intraclass correlation coefficient (ICC) was determined for the whole brain, gray and white matter, cerebellum, and lateral and third ventricle volumes. When required, the processing algorithms were calibrated for each site. Calibration of the histogram analysis was needed for segmentation of total brain volume at one site and for gray and white matter volume at all sites. No (additional) calibration was needed for cerebellum and ventricle volumes. The ICCs were ≥0.96 for total brain, ≥0.92 for cerebellum, ≥0.96 for lateral ventricle, ≥0.21 for third ventricle, ≥0.84 for gray matter, and ≥0.78 for white matter volume. Calibration of segmentation procedures allows morphologic MRI data acquired at different research sites to be combined reliably in multicenter studies. Hum. Brain Mapping 22:312–320, 2004. © 2004 Wiley‐Liss, Inc.

[1]  J J Bartko,et al.  ON THE METHODS AND THEORY OF RELIABILITY , 1976, The Journal of nervous and mental disease.

[2]  M. Torrens Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268 , 1990 .

[3]  U Klose,et al.  Reliability and exactness of MRI‐based volumetry: A phantom study , 1996, Journal of magnetic resonance imaging : JMRI.

[4]  Guy Marchal,et al.  Multi-modality image registration by maximization of mutual information , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

[5]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[6]  F. Barkhof,et al.  Interscanner variation in brain MRI lesion load measurements in MS: Implications for clinical trials , 1997, Neurology.

[7]  K. Blennow,et al.  A population study of apoE genotype at the age of 85: relation to dementia, cerebrovascular disease, and mortality , 1998, Journal of neurology, neurosurgery, and psychiatry.

[8]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[9]  P S Tofts,et al.  Standardisation and optimisation of magnetic resonance techniques for multicentre studies. , 1998, Journal of neurology, neurosurgery, and psychiatry.

[10]  M Filippi,et al.  Interscanner variation in brain MR lesion load measurements in multiple sclerosis using conventional spin-echo, rapid relaxation-enhanced, and fast-FLAIR sequences. , 1999, AJNR. American journal of neuroradiology.

[11]  R. Murray,et al.  Meta-analysis of regional brain volumes in schizophrenia. , 2000, The American journal of psychiatry.

[12]  G Ratcliff,et al.  Cognitive correlates of human brain aging: a quantitative magnetic resonance imaging investigation. , 2001, The Journal of neuropsychiatry and clinical neurosciences.

[13]  R. Kahn,et al.  Automated Separation of Gray and White Matter from MR Images of the Human Brain , 2001, NeuroImage.

[14]  R. S. Kahn,et al.  Automatic Segmentation of the Ventricular System from MR Images of the Human Brain , 2001, NeuroImage.

[15]  G H Glover,et al.  Effects of Image Orientation on the Comparability of Pediatric Brain Volumes Using Three-Dimensional MR Data , 2001, Journal of computer assisted tomography.

[16]  R. Kahn,et al.  Volume changes in gray matter in patients with schizophrenia. , 2002, The American journal of psychiatry.

[17]  Hilleke E. Hulshoff Pol,et al.  Brain volumes as predictor of outcome in recent-onset schizophrenia: a multi-center MRI study , 2003, Schizophrenia Research.