• Jorge Jovicich, Moira Marizzoni, Roser Sala-Llonch, Beatriz Bosch, David Bartrés-Faz, Jennifer Arnold, Jens Benninghoff, Jens Wiltfang, Luca Roccatagliata, Flavio Nobili, Tilman Hensch, Anja Tränkner, Peter Schönknecht, Melanie Leroy, Renaud Lopes, Régis Bordet, Valérie Chanoine, Jean-Philippe Ranjeva, Mira Didic, Hélène Gros-Dagnac, Pierre Payoux, Giada Zoccatelli, Franco Alessandrini, Alberto Beltramello, Núria Bargalló, Olivier Blin, Giovanni B Frisoni, and PharmaCog Consortium.
• Center for Mind Brain Sciences, University of Trento, Trento, Italy. Electronic address: jorge.jovicich@unitn.it.
• Neuroimage. 2013 Dec 1; 83: 472-84.

AbstractLarge-scale longitudinal multi-site MRI brain morphometry studies are becoming increasingly crucial to characterize both normal and clinical population groups using fully automated segmentation tools. The test-retest reproducibility of morphometry data acquired across multiple scanning sessions, and for different MR vendors, is an important reliability indicator since it defines the sensitivity of a protocol to detect longitudinal effects in a consortium. There is very limited knowledge about how across-session reliability of morphometry estimates might be affected by different 3T MRI systems. Moreover, there is a need for optimal acquisition and analysis protocols in order to reduce sample sizes. A recent study has shown that the longitudinal FreeSurfer segmentation offers improved within session test-retest reproducibility relative to the cross-sectional segmentation at one 3T site using a nonstandard multi-echo MPRAGE sequence. In this study we implement a multi-site 3T MRI morphometry protocol based on vendor provided T1 structural sequences from different vendors (3D MPRAGE on Siemens and Philips, 3D IR-SPGR on GE) implemented in 8 sites located in 4 European countries. The protocols used mild acceleration factors (1.5-2) when possible. We acquired across-session test-retest structural data of a group of healthy elderly subjects (5 subjects per site) and compared the across-session reproducibility of two full-brain automated segmentation methods based on either longitudinal or cross-sectional FreeSurfer processing. The segmentations include cortical thickness, intracranial, ventricle and subcortical volumes. Reproducibility is evaluated as absolute changes relative to the mean (%), Dice coefficient for volume overlap and intraclass correlation coefficients across two sessions. We found that this acquisition and analysis protocol gives comparable reproducibility results to previous studies that used longer acquisitions without acceleration. We also show that the longitudinal processing is systematically more reliable across sites regardless of MRI system differences. The reproducibility errors of the longitudinal segmentations are on average approximately half of those obtained with the cross sectional analysis for all volume segmentations and for entorhinal cortical thickness. No significant differences in reliability are found between the segmentation methods for the other cortical thickness estimates. The average of two MPRAGE volumes acquired within each test-retest session did not systematically improve the across-session reproducibility of morphometry estimates. Our results extend those from previous studies that showed improved reliability of the longitudinal analysis at single sites and/or with non-standard acquisition methods. The multi-site acquisition and analysis protocol presented here is promising for clinical applications since it allows for smaller sample sizes per MRI site or shorter trials in studies evaluating the role of potential biomarkers to predict disease progression or treatment effects. Copyright © 2013 Elsevier Inc. All rights reserved.

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