|
|||||
|
|
Reliability of neuroanatomical measurements in a multisite longitudinal study of youth at risk for psychosis |
|
| Authors: | Tyrone D. Cannon Frank Sun Sarah Jacobson McEwen Xenophon Papademetris George He Theo G.M. van Erp Aron Jacobson Carrie E. Bearden Elaine Walker Xiaoping Hu Lei Zhou Larry J. Seidman Heidi W. Thermenos Barbara Cornblatt Doreen M. Olvet Diana Perkins Aysenil Belger Kristin Cadenhead Ming Tsuang Heline Mirzakhanian Jean Addington Richard Frayne Scott W. Woods Thomas H. McGlashan R. Todd Constable Maolin Qiu Daniel H. Mathalon Paul Thompson Arthur W. Toga |
| Affiliation: | 1. Department of Psychology, Yale University, New Haven, CT;2. Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA;3. Departments of Diagnostic Radiology and Biomedical Engineering, Yale University, New Haven, CT;4. Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA;5. Department of Psychiatry, Emory University, Atlanta, Georgia;6. Biomedical Imaging Technology Center, Emory University, Atlanta, Georgia;7. Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA;8. Department of Psychiatry, Zucker Hillside Hospital, Great Neck, NY;9. Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, NC;10. Department of Psychiatry, University of California, San Diego, San Diego, CA;11. Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada;12. Department of Radiology, University of Calgary, Calgary, Alberta, Canada;13. Department of Psychiatry, Yale University, New Haven, CT;14. Department of Psychiatry, University of California, San Francisco, San Francisco, CA;15. Department of Neurology, University of California, Los Angeles, Los Angeles, CA |
| Abstract: | Multisite longitudinal neuroimaging designs are used to identify differential brain structural change associated with onset or progression of disease. The reliability of neuroanatomical measurements over time and across sites is a crucial aspect of power in such studies. Prior work has found that while within‐site reliabilities of neuroanatomical measurements are excellent, between‐site reliability is generally more modest. Factors that may increase between‐site reliability include standardization of scanner platform and sequence parameters and correction for between‐scanner variations in gradient nonlinearities. Factors that may improve both between‐ and within‐site reliability include use of registration algorithms that account for individual differences in cortical patterning and shape. In this study 8 healthy volunteers were scanned twice on successive days at 8 sites participating in the North American Prodrome Longitudinal Study (NAPLS). All sites employed 3 Tesla scanners and standardized acquisition parameters. Site accounted for 2 to 30% of the total variance in neuroanatomical measurements. However, site‐related variations were trivial (<1%) among sites using the same scanner model and 12‐channel coil or when correcting for between‐scanner differences in gradient nonlinearity and scaling. Adjusting for individual differences in sulcal‐gyral geometries yielded measurements with greater reliabilities than those obtained using an automated approach. Neuroimaging can be performed across multiple sites at the same level of reliability as at a single site, achieving within‐ and between‐site reliabilities of 0.95 or greater for gray matter density in the majority of voxels in the prefrontal and temporal cortical surfaces as well as for the volumes of most subcortical structures. Hum Brain Mapp 35:2424–2434, 2014. © 2013 Wiley Periodicals, Inc . |
| Keywords: | magnetic resonance imaging neuroanatomy reproducibility of results computer‐assisted image processing cerebral cortex thalamus hippocampus amygdala |