Jorge Jovicich1,
Moira Marizzoni2, Roser Sala-Llonch3, Nuria Bargall3,
David Bartrs-Faz3, Jennifer Arnold4, Jens Benninghoff4,
Jens Wiltfang4, Luca Roccatagliata5, Flavio Nobili5,
Christian Zeeh6, Peter Schonknecht6, Giada Zoccatelli7,
Franco Alessandrini7, Alberto Beltramello7, Hlne
Gros-Dagnac8, Pierre Payoux8, Valrie Chanoine9,
10, Jean-Philippe Ranjeva9, 10, Mira Didic9,
10, Melanie Leroy11, Regis Bordet11, Giovanni
Frisoni2
1University
of Trento, Center for Mind/Brain Sciences, Mattarello, Trento, Italy; 2IRCCS
San Giovanni di Dio Fatebenefratelli, LENITEM Lab of Epidem., Neuroim. &
Telem, Brescia, Lombardia, Italy; 3Dept. Psychiatry and Clinical
Psychobiology, Faculty of Medicine University of Barcelona, Barcelona, Spain;
4Department of Psychiatry
and nuclear medicine, Universitaet Duisburg-Essen, Essen, Germany; 5Dept
of Neuroscience, Ophthalmology and Genetics, University of Genoa, Genoa,
Lombardia, Italy; 6Dept of Psychiatry and Dept of Neuroradiology,
University of Leipzig, Leipzig, Germany; 7Dept of Neuroradiology,
Verona General Hospital, Verona, Italy; 8U825 - Plateau Technique
IRM, INSERM / Universit Paul Sabatier, Toulouse, France; 9Hpital
La Timone CIC UPCET, Marseille, France; 10Centre de Resonance
Magnetique Biologique et Medicale , Aix Marseille Universit , Marseille, France;
11Universit Lille UL2, Lille, France
The success in finding clinically useful MRI-derived biomarkers is highly dependent on data acquisition and analysis strategies. In this brain morphometry study we show for the first time the across-session test-retest reproducibility advantages of the fully automated longitudinal FreeSurfer segmentation protocol relative to the cross-sectional analysis, when tested in a consortia using different 3T MRI scanners (Siemens, Philips, GE) acquiring standard 3D MPRAGE data, with 7 out of 8 sites using parallel imaging acquisition (about 5 min acquisition per volume) and no data averaging.
Keywords