title: Brain morphometry reproducibility in multi-center 3T MRI studies: a comparison of cross-sectional and longitudinal segmentations.
abstract: Large-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.
authors.affiliation: Center for Mind Brain Sciences, University of Trento, Trento, Italy. Electronic address: jorge.jovicich@unitn.it.
authors.forename: Jorge
authors.initials: J
authors.lastname: Jovicich
authors.forename: Moira
authors.initials: M
authors.lastname: Marizzoni
authors.forename: Roser
authors.initials: R
authors.lastname: Sala-Llonch
authors.forename: Beatriz
authors.initials: B
authors.lastname: Bosch
authors.forename: David
authors.initials: D
authors.lastname: Bartrés-Faz
authors.forename: Jennifer
authors.initials: J
authors.lastname: Arnold
authors.forename: Jens
authors.initials: J
authors.lastname: Benninghoff
authors.forename: Jens
authors.initials: J
authors.lastname: Wiltfang
authors.forename: Luca
authors.initials: L
authors.lastname: Roccatagliata
authors.forename: Flavio
authors.initials: F
authors.lastname: Nobili
authors.forename: Tilman
authors.initials: T
authors.lastname: Hensch
authors.forename: Anja
authors.initials: A
authors.lastname: Tränkner
authors.forename: Peter
authors.initials: P
authors.lastname: Schönknecht
authors.forename: Melanie
authors.initials: M
authors.lastname: Leroy
authors.forename: Renaud
authors.initials: R
authors.lastname: Lopes
authors.forename: Régis
authors.initials: R
authors.lastname: Bordet
authors.forename: Valérie
authors.initials: V
authors.lastname: Chanoine
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Ranjeva
authors.forename: Mira
authors.initials: M
authors.lastname: Didic
authors.forename: Hélène
authors.initials: H
authors.lastname: Gros-Dagnac
authors.forename: Pierre
authors.initials: P
authors.lastname: Payoux
authors.forename: Giada
authors.initials: G
authors.lastname: Zoccatelli
authors.forename: Franco
authors.initials: F
authors.lastname: Alessandrini
authors.forename: Alberto
authors.initials: A
authors.lastname: Beltramello
authors.forename: Núria
authors.initials: N
authors.lastname: Bargalló
authors.forename: Olivier
authors.initials: O
authors.lastname: Blin
authors.forename: Giovanni B
authors.initials: GB
authors.lastname: Frisoni
mesh_terms: D000375:Aging / Q000473:pathology*; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003430:Cross-Sectional Studies; D005060:Europe; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Brain morphometry; Multi-center; Multi-site MRI; Reliability; Reproducibility; Structural MRI