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A Prospective Multi-Institutional Study of the Reproducibility of fMRI: A Preliminary Report from the Biomedical Informatics Research Network
Institution:
 Surgical Planning Laboratory, Brigham and Women’s Hospital, Computational Radiology Laboratory, Brigham and Women’s Hospital
Publisher:
 Med Image Comput Comput Assist Interv. MICCAI 2004
Publication Date:
 Sep-2004
Volume Number:
 7
Issue Number:
 Pt 2
Pages:
 769-776
Citation:
 Int Conf Med Image Comput Comput Assist Interv. 2004;7(Pt 2):769-776.
Keywords:
 Reproducibility of fMRI
Appears in Collections:
SPL, CRL, NAC
Sponsors:
 NCRR P41 RR13218
NIH R01 LM007861-01
NIH R03HS013234-01
NIH CA89449-01
NIH R21MH67054
Generated Citation:
 Zou K.H., Greve D.N., Wang M., Pieper S.D., Warfield S.K., White N.S., Vangel M.G., Kikinis R., Wells III W.M., FIRST BIRN . A Prospective Multi-Institutional Study of the Reproducibility of fMRI: A Preliminary Report from the Biomedical Informatics Research Network. Int Conf Med Image Comput Comput Assist Interv. 2004;7(Pt 2):769-776.
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Functional magnetic resonance imaging (fMRI) has significantly contributed to understanding both normal and diseased human brains. Variability often exists in the magnitude, spatial distribution, and statistical significance of the resulting fMRI maps due to differences in equipment and other site-specific differences. In addition, because of costly imaging, demanding tasks, and analytical burden, understanding the effect of these differences may help develop an efficient pooling and comparison mechanism. Prospective multi-institutional repeated fMRI data were acquired recently in the first phase of the extensive Functional Imaging Research of Schizophrenia Testbed study, sponsored by the Biomedical Informatics Research Network (BIRN) in the US. Five “human phantoms,” who were right-handed healthy males, were included in the study.These subjects repeatedly performed the same sensory-motor task over 10 of the 11 study sites on 2 separate visits per site. The effects of factors such as subject, study site, field strength, vendor, K-space, visit, and repeated run on the fMRI reproducibility were evaluated. Over 4 repeated runs per visit at each site, at a given binarizing activation threshold, we first calculated a three-dimensional (3D) brain activation map via an intial expectation and maximization (EM) algorithm. Site-to-site differences were then assessed based on a second-level hiearchical EM. Against the estimated gold standard of the 3D activation map, activation percentage, sensitivity, specificity, and receiver operating characteristic curves were then estimated using voxel counts. A statistical regression model was used to assess the significance of accuracy predictors with p-values generated in order to explain those factors contributing towards the variability in repeated brain activation maps.

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