Test‐retest reliability of the default mode network in a multi‐centric fMRI study of healthy elderly: Effects of data‐driven physiological noise correction techniques期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

Test‐retest reliability of the default mode network in a multi‐centric fMRI study of healthy elderly: Effects of data‐driven physiological noise correction techniques

Authors:	Rocco Marchitelli Ludovico Minati Moira Marizzoni Beatriz Bosch David Bartrés‐Faz Bernhard W. Müller Jens Wiltfang Ute Fiedler Luca Roccatagliata Agnese Picco Flavio Nobili Oliver Blin Stephanie Bombois Renaud Lopes Régis Bordet Julien Sein Jean‐Philippe Ranjeva Mira Didic Hélène Gros‐Dagnac Pierre Payoux Giada Zoccatelli Franco Alessandrini Alberto Beltramello Núria Bargalló Antonio Ferretti Massimo Caulo Marco Aiello Carlo Cavaliere Andrea Soricelli Lucilla Parnetti Roberto Tarducci Piero Floridi Magda Tsolaki Manos Constantinidis Antonios Drevelegas Paolo Maria Rossini Camillo Marra Peter Schönknecht Tilman Hensch Karl‐Titus Hoffmann Joost P. Kuijer Pieter Jelle Visser Frederik Barkhof Jorge Jovicich

Affiliation:	1. Center for Mind/Brain Sciences (CIMEC), University of Trento, Rovereto, Italy;2. Scientific Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy;3. LENITEM Laboratory of Epidemiology, Neuroimaging, & Telemedicine—IRCCS San Giovanni Di Dio‐FBF, Brescia, Italy;4. Alzheimer's Disease and Other Cognitive Disorders Unit, Department of Neurology, Hospital Clínic, and IDIBAPS, Barcelona, Spain;5. Department of Psychiatry and Clinical Psychobiology, Universitat De Barcelona and IDIBAPS, Barcelona, Spain;6. LVR‐Clinic for Psychiatry and Psychotherapy, Institutes and Clinics of the University Duisburg‐Essen, Essen, Germany;7. Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg August University, G?ttingen, Germany;8. Department of Neuroradiology, IRCSS San Martino University Hospital and IST, Genoa, Italy;9. Department of Health Sciences, University of Genoa, Genoa, Italy;10. Department of Neuroscience, Ophthalmology, Genetics and Mother–Child Health (DINOGMI), University of Genoa, Genoa, Italy;11. Pharmacology, Assistance Publique — H?pitaux De Marseille, Aix‐Marseille University—CNRS, UMR, Marseille, France;12. University of Lille, INSERM, CHU Lille, U1171 ‐ Degenerative and Vascular Cognitive Disorders, Lille, France;13. CRMBM–CEMEREM, UMR 7339, Aix Marseille Université—CNRS, Marseille, France;14. APHM, CHU Timone, Service De Neurologie Et Neuropsychologie, Marseille, France;15. Aix‐Marseille Université, INSERM INS UMR_S 1106, Marseille, France;16. INSERM, Imagerie Cérébrale Et Handicaps Neurologiques, UMR 825, Toulouse, France;17. Université De Toulouse, UPS, Imagerie Cérébrale Et Handicaps Neurologiques, UMR 825, CHU Purpan, Place Du Dr Baylac, Toulouse Cedex 9, France;18. Department of Neuroradiology, General Hospital, Verona, Italy;19. Department of Neuroradiology and Magnetic Resonace Image Core Facility, Hospital Clínic De Barcelona, IDIBAPS, Barcelona, Spain;20. Department of Neuroscience Imaging and Clinical Sciences, University “G. d'Annunzio” of Chieti, Italy;21. Institute for Advanced Biomedical Technologies (ITAB), University “G. d'Annunzio” of Chieti, Italy;22. IRCCS SDN, Naples, Italy;23. University of Naples Parthenope, Naples, Italy;24. Section of Neurology, Centre for Memory Disturbances, University of Perugia, Perugia, Italy;25. Perugia General Hospital, Medical Physics Unit, Perugia, Italy;26. Perugia General Hospital, Neuroradiology Unit, Perugia, Italy;27. 3rd Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece;28. Interbalkan Medical Center of Thessaloniki, Thessaloniki, Greece;29. Department of Radiology, Aristotle University of Thessaloniki, Thessaloniki, Greece;30. Department of Geriatrics, Neuroscience & Orthopaedics, Catholic University, Policlinic Gemelli, Rome, Italy;31. IRCSS S.Raffaele Pisana, Rome, Italy;32. Center for Neuropsychological Research, Catholic University, Rome, Italy;33. Department of Psychiatry, University Hospital Leipzig, Leipzig, Germany;34. Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany;35. Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, the Netherlands;36. Alzheimer Centre and Department of Neurology, Vrije Universiteit University Medical Center, Amsterdam, the Netherlands;37. Department of Psychiatry and Neuropsychology, Alzheimer Center Limburg, University of Maastricht, Maastricht, the Netherlands

Abstract:	Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within‐site test‐retest reliability and the across‐site reproducibility consistency of DMN‐derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue‐based regression, PESTICA and FSL‐FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z‐scores and, albeit less markedly, the cluster‐size in the DMN; in particular, FSL‐FIX tended to increase the DMN z‐scores compared to others. Within‐site test‐retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5–11% for DMN z‐scores and cluster‐size reliability. DMN pattern overlap was in the range 60–65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL‐FIX and Tissue‐based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC = 0.67) for the DMN z‐scores relative to NPC. Overall these findings support the use of rPNC methods like tissue‐based or FSL‐FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114–2132, 2016. © 2016 Wiley Periodicals, Inc.

Keywords:	task‐free fMRI resting‐state networks default mode network physiological noise correction multisite test‐retest reliability independent component analysis

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