Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects
Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by...
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| Published in | NeuroImage (Orlando, Fla.) Vol. 101; pp. 390 - 403 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Inc
01.11.2014
Elsevier Limited |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2×2×2mm3, b=700s/mm2, 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test–retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test–retest reproducibility. White matter b0 SNR reproducibility was on average 7±1% with no significant MRI site effects. Whole brain analysis resulted in no significant test–retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2–4% range for FA and AD and 2–6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.
•We implement a multi-site 3T MRI protocol for brain DTI on 10 EU sites.•We acquire across-session test–retest data on 50 healthy elderly subjects.•We use full brain TBSS and ROI analysis to calculate FA, MD, RD and AD.•Reproducibility errors are in the 2–6% range.•Reproducibility errors tended to be lower in sites with shorter acquisitions. |
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| AbstractList | Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2×2×2mm3, b=700s/mm2, 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test–retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test–retest reproducibility. White matter b0 SNR reproducibility was on average 7±1% with no significant MRI site effects. Whole brain analysis resulted in no significant test–retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2–4% range for FA and AD and 2–6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.
•We implement a multi-site 3T MRI protocol for brain DTI on 10 EU sites.•We acquire across-session test–retest data on 50 healthy elderly subjects.•We use full brain TBSS and ROI analysis to calculate FA, MD, RD and AD.•Reproducibility errors are in the 2–6% range.•Reproducibility errors tended to be lower in sites with shorter acquisitions. Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (222mm3, b=700s/mm2, 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 plus or minus 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios. Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios. Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2x2x2mm3, b=700s/mm2, 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7±1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios. Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios. |
| Author | Marizzoni, Moira Benninghoff, Jens Picco, Agnese Alessandrini, Franco Bosch, Beatriz Arnold, Jennifer Drevelegas, Antonios Floridi, Piero Nobili, Flavio Marra, Camillo Payoux, Pierre Chanoine, Valérie Ranjeva, Jean-Philippe Otto, Josephin Jovicich, Jorge Reiss-Zimmermann, Martin Tsolaki, Magda Bordet, Régis Didic, Mira Gros-Dagnac, Hélène Tarducci, Roberto Frisoni, Giovanni B. Constantinidis, Manos Galluzzi, Samantha Blin, Oliver Ferretti, Antonio Caulo, Massimo Ragucci, Monica Zoccatelli, Giada Roccatagliata, Luca Hoffmann, Karl-Titus Soricelli, Andrea Salvadori, Nicola Aiello, Marco Rossini, Paolo Maria Bartrés-Faz, David Bombois, Stephanie Lopes, Renaud Bargalló, Núria Wiltfang, Jens Beltramello, Alberto |
| Author_xml | – sequence: 1 givenname: Jorge orcidid: 0000-0001-9504-7503 surname: Jovicich fullname: Jovicich, Jorge email: jorge.jovicich@unitn.it organization: Center for Mind/Brain Sciences (CIMEC), University of Trento, Rovereto, Italy – sequence: 2 givenname: Moira surname: Marizzoni fullname: Marizzoni, Moira organization: LENITEM Laboratory of Epidemiology, Neuroimaging, & Telemedicine — IRCCS San Giovanni di Dio-FBF, Brescia, Italy – sequence: 3 givenname: Beatriz surname: Bosch fullname: Bosch, Beatriz organization: Alzheimer's Disease and Other Cognitive Disorders Unit, Department of Neurology, Hospital Clínic, and IDIBAPS, Barcelona, Spain – sequence: 4 givenname: David surname: Bartrés-Faz fullname: Bartrés-Faz, David organization: Department of Psychiatry and Clinical Psychobiology, Universitat de Barcelona and IDIBAPS, Barcelona, Spain – sequence: 5 givenname: Jennifer surname: Arnold fullname: Arnold, Jennifer organization: LVR-Clinic for Psychiatry and Psychotherapy, Institutes and Clinics of the University Duisburg-Essen, Essen, Germany – sequence: 6 givenname: Jens surname: Benninghoff fullname: Benninghoff, Jens organization: LVR-Clinic for Psychiatry and Psychotherapy, Institutes and Clinics of the University Duisburg-Essen, Essen, Germany – sequence: 7 givenname: Jens surname: Wiltfang fullname: Wiltfang, Jens organization: LVR-Clinic for Psychiatry and Psychotherapy, Institutes and Clinics of the University Duisburg-Essen, Essen, Germany – sequence: 8 givenname: Luca surname: Roccatagliata fullname: Roccatagliata, Luca organization: Department of Neuroradiology, IRCSS San Martino University Hospital and IST, Genoa, Italy – sequence: 9 givenname: Agnese surname: Picco fullname: Picco, Agnese organization: Department of Neuroscience, Ophthalmology, Genetics and Mother–Child Health (DINOGMI), University of Genoa, Genoa, Italy – sequence: 10 givenname: Flavio surname: Nobili fullname: Nobili, Flavio organization: Department of Neuroscience, Ophthalmology, Genetics and Mother–Child Health (DINOGMI), University of Genoa, Genoa, Italy – sequence: 11 givenname: Oliver surname: Blin fullname: Blin, Oliver organization: Pharmacology, Assistance Publique — Hôpitaux de Marseille, Aix-Marseille University — CNRS, UMR 7289, Marseille, France – sequence: 12 givenname: Stephanie surname: Bombois fullname: Bombois, Stephanie organization: Department of Neurology, EA1046, Lille University, Lille, France – sequence: 13 givenname: Renaud surname: Lopes fullname: Lopes, Renaud organization: Department of Neuroradiology, EA1046, Lille University, Lille, France – sequence: 14 givenname: Régis surname: Bordet fullname: Bordet, Régis organization: Department of Pharmacology, EA1046, Lille University, Lille, France – sequence: 15 givenname: Valérie surname: Chanoine fullname: Chanoine, Valérie organization: CRMBM–CEMEREM, UMR 7339, Aix Marseille Université — CNRS, Marseille, France – sequence: 16 givenname: Jean-Philippe surname: Ranjeva fullname: Ranjeva, Jean-Philippe organization: CRMBM–CEMEREM, UMR 7339, Aix Marseille Université — CNRS, Marseille, France – sequence: 17 givenname: Mira surname: Didic fullname: Didic, Mira organization: APHM, CHU Timone, Service de Neurologie et Neuropsychologie, Marseille, France – sequence: 18 givenname: Hélène surname: Gros-Dagnac fullname: Gros-Dagnac, Hélène organization: INSERM, Imagerie cérébrale et handicaps neurologiques, UMR 825, Toulouse, France – sequence: 19 givenname: Pierre surname: Payoux fullname: Payoux, Pierre organization: INSERM, Imagerie cérébrale et handicaps neurologiques, UMR 825, Toulouse, France – sequence: 20 givenname: Giada surname: Zoccatelli fullname: Zoccatelli, Giada organization: Department of Neuroradiology, General Hospital, Verona, Italy – sequence: 21 givenname: Franco surname: Alessandrini fullname: Alessandrini, Franco organization: Department of Neuroradiology, General Hospital, Verona, Italy – sequence: 22 givenname: Alberto surname: Beltramello fullname: Beltramello, Alberto organization: Department of Neuroradiology, General Hospital, Verona, Italy – sequence: 23 givenname: Núria surname: Bargalló fullname: Bargalló, Núria organization: Department of Neuroradiology and Magnetic Resonace Image core Facility, Hospital Clínic de Barcelona, IDIBAPS, Barcelona, Spain – sequence: 24 givenname: Antonio surname: Ferretti fullname: Ferretti, Antonio organization: Department of Neuroscience Imaging and Clinical Sciences, University “G. d'Annunzio” of Chieti, Italy – sequence: 25 givenname: Massimo surname: Caulo fullname: Caulo, Massimo organization: Department of Neuroscience Imaging and Clinical Sciences, University “G. d'Annunzio” of Chieti, Italy – sequence: 26 givenname: Marco surname: Aiello fullname: Aiello, Marco organization: IRCCS SDN, Naples, Italy – sequence: 27 givenname: Monica surname: Ragucci fullname: Ragucci, Monica organization: IRCCS SDN, Naples, Italy – sequence: 28 givenname: Andrea surname: Soricelli fullname: Soricelli, Andrea organization: IRCCS SDN, Naples, Italy – sequence: 29 givenname: Nicola surname: Salvadori fullname: Salvadori, Nicola organization: Section of Neurology, Centre for Memory Disturbances, University of Perugia, Perugia, Italy – sequence: 30 givenname: Roberto surname: Tarducci fullname: Tarducci, Roberto organization: Medical Physics Unit, Perugia General Hospital, Perugia, Italy – sequence: 31 givenname: Piero surname: Floridi fullname: Floridi, Piero organization: Neuroradiology Unit, Perugia General Hospital, Perugia, Italy – sequence: 32 givenname: Magda surname: Tsolaki fullname: Tsolaki, Magda organization: 3rd Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece – sequence: 33 givenname: Manos surname: Constantinidis fullname: Constantinidis, Manos organization: Interbalkan Medical Center of Thessaloniki, Thessaloniki, Greece – sequence: 34 givenname: Antonios surname: Drevelegas fullname: Drevelegas, Antonios organization: Interbalkan Medical Center of Thessaloniki, Thessaloniki, Greece – sequence: 35 givenname: Paolo Maria surname: Rossini fullname: Rossini, Paolo Maria organization: Dept. Geriatrics, Neuroscience & Orthopaedics, Catholic University, Policlinic Gemelli, Rome, Italy – sequence: 36 givenname: Camillo surname: Marra fullname: Marra, Camillo organization: Center for Neuropsychological Research, Catholic University, Rome, Italy – sequence: 37 givenname: Josephin surname: Otto fullname: Otto, Josephin organization: Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany – sequence: 38 givenname: Martin surname: Reiss-Zimmermann fullname: Reiss-Zimmermann, Martin organization: Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany – sequence: 39 givenname: Karl-Titus surname: Hoffmann fullname: Hoffmann, Karl-Titus organization: Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany – sequence: 40 givenname: Samantha surname: Galluzzi fullname: Galluzzi, Samantha organization: LENITEM Laboratory of Epidemiology, Neuroimaging, & Telemedicine — IRCCS San Giovanni di Dio-FBF, Brescia, Italy – sequence: 41 givenname: Giovanni B. surname: Frisoni fullname: Frisoni, Giovanni B. organization: LENITEM Laboratory of Epidemiology, Neuroimaging, & Telemedicine — IRCCS San Giovanni di Dio-FBF, Brescia, Italy |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25026156$$D View this record in MEDLINE/PubMed |
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| Title | Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects |
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