Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors
The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we asses...
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| Published in | NeuroImage Vol. 218; p. 116932 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Inc
01.09.2020
Elsevier BV Elsevier Limited Elsevier |
| Subjects | |
| Online Access | Get full text |
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| Abstract | The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.
Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1–90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.
Significant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman’s r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80).
Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.
•Differences in MRI site/vendor had a limited effect on volume reproducibility.•Differences in MRI site/vendor had an extensive effect on spatial accuracy.•Reliability is good for larger amygdalar and hippocampal structures.•Automated volumetry is reliable in multicenter MRI studies. |
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| AbstractList | Background: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults. Methods: Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1–90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. Results: Significant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman’s r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80). Conclusion: Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials. BackgroundThe amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.MethodsSixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1–90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.ResultsSignificant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman’s r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80).ConclusionOur results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials. The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults. Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. Significant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm (for amygdalar nuclei) and 300 mm (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80). Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials. The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults. Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1–90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. Significant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman’s r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80). Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials. •Differences in MRI site/vendor had a limited effect on volume reproducibility.•Differences in MRI site/vendor had an extensive effect on spatial accuracy.•Reliability is good for larger amygdalar and hippocampal structures.•Automated volumetry is reliable in multicenter MRI studies. Background: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.Methods: Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.Results: Significant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80).Conclusion: Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials. The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.BACKGROUNDThe amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.METHODSSixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.Significant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80).RESULTSSignificant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80).Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.CONCLUSIONOur results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials. |
| ArticleNumber | 116932 |
| Author | Richardson, Jill C. Marizzoni, Moira Picco, Agnese Bartres-Faz, David Drevelegas, Antonios Müller, Bernhard W. Floridi, Piero Schonknecht, Peter Marra, Camillo Nobili, Flavio Payoux, Pierre Schott, Björn H. Ranjeva, Jean-Philippe Jovicich, Jorge Hensch, Tilman Barkhof, Frederik Tsolaki, Magda Blin, Olivier Pizzini, Francesca B. Quattrini, Giulia Bordet, Regis Didic, Mira Gros-Dagnac, Hélène Sein, Julien Tarducci, Roberto Frisoni, Giovanni B. Caulo, Massimo Ferretti, Antonio Kuijer, Joost P. Rossini, Paolo M. Salvatore, Marco Roccatagliata, Luca Hoffmann, Karl-Titus Visser, Pieter J. Soricelli, Andrea Pievani, Michela Aiello, Marco Fiedler, Ute Parnetti, Lucilla Lopes, Renaud Bargalló, Núria Wiltfang, Jens Constantinides, Manos Beltramello, Alberto |
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Gemelli, IRCCS, Rome, Italy – sequence: 25 givenname: Bernhard W. surname: Müller fullname: Müller, Bernhard W. organization: LVR-Hospital Essen, Department for Psychiatry and Psychotherapy, Faculty of Medicine, University of Duisburg-Essen, Germany – sequence: 26 givenname: Flavio surname: Nobili fullname: Nobili, Flavio organization: Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy – sequence: 27 givenname: Lucilla surname: Parnetti fullname: Parnetti, Lucilla organization: Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy – sequence: 28 givenname: Pierre surname: Payoux fullname: Payoux, Pierre organization: ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France – sequence: 29 givenname: Agnese surname: Picco fullname: Picco, Agnese organization: Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy – sequence: 30 givenname: Jean-Philippe surname: Ranjeva fullname: Ranjeva, Jean-Philippe organization: CRMBM-CEMEREM, UMR 7339, Aix-Marseille University, CNRS, Marseille, France – sequence: 31 givenname: Luca surname: Roccatagliata fullname: Roccatagliata, Luca organization: IRCCS, Ospedale Policlinico San Martino, Genova, Italy – sequence: 32 givenname: Paolo M. surname: Rossini fullname: Rossini, Paolo M. organization: Dept. Neuroscience & Rehabilitation, IRCCS San Raffaele-Pisana, Rome, Italy – sequence: 33 givenname: Marco surname: Salvatore fullname: Salvatore, Marco organization: IRCCS SDN, Napoli, Italy – sequence: 34 givenname: Peter surname: Schonknecht fullname: Schonknecht, Peter organization: Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany – sequence: 35 givenname: Björn H. surname: Schott fullname: Schott, Björn H. organization: Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Göttingen, Germany – sequence: 36 givenname: Julien orcidid: 0000-0003-1767-5330 surname: Sein fullname: Sein, Julien organization: CRMBM-CEMEREM, UMR 7339, Aix-Marseille University, CNRS, Marseille, France – sequence: 37 givenname: Andrea surname: Soricelli fullname: Soricelli, Andrea organization: IRCCS SDN, Napoli, Italy – sequence: 38 givenname: Roberto orcidid: 0000-0003-3539-7856 surname: Tarducci fullname: Tarducci, Roberto organization: Perugia General Hospital, Medical Physics Unit, Perugia, Italy – sequence: 39 givenname: Magda surname: Tsolaki fullname: Tsolaki, Magda organization: Aristotle University of Thessaloniki, Thessaloniki, Greece – sequence: 40 givenname: Pieter J. surname: Visser fullname: Visser, Pieter J. organization: Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, Netherlands – sequence: 41 givenname: Jens surname: Wiltfang fullname: Wiltfang, Jens organization: Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Göttingen, Germany – sequence: 42 givenname: Jill C. surname: Richardson fullname: Richardson, Jill C. organization: Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom – sequence: 43 givenname: Giovanni B. surname: Frisoni fullname: Frisoni, Giovanni B. organization: Laboratory of Alzheimer’s Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy – sequence: 44 givenname: Moira orcidid: 0000-0003-3749-2988 surname: Marizzoni fullname: Marizzoni, Moira organization: Laboratory of Alzheimer’s Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy |
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| ContentType | Journal Article |
| Contributor | Marizzoni, Moira Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig VU University Medical Center Amsterdam Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire Lille (CHRU Lille) Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - AP-HM] (CEMEREM) ; Centre de résonance magnétique biologique et médicale (CRMBM) ; Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE) University "G. d'Annunzio" of Chieti-Pescara [Chieti] Universität Duisburg-Essen = University of Duisburg-Essen [Essen] Laboratory of Alzheimer’s Neuroimaging and Epidemiology (LANE) ; Saint John of God Clinical Research Centre Aristotle |
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| Copyright | 2020 The Authors Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved. 2020. The Authors Attribution |
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| DOI | 10.1016/j.neuroimage.2020.116932 |
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| DocumentTitleAlternate | Test-retest reliability of automated volumetry across different MRI sites and vendors |
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| Keywords | Reliability analysis Hippocampal subfields FreeSurfer Amygdalar nuclei Multicenter MRI study |
| Language | English |
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| SubjectTerms | [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging Adult Aged ALZHEIMERS-DISEASE Amygdala Amygdala - anatomy & histology Amygdalar nuclei Amygdalar nuclei; FreeSurfer; Hippocampal subfields; Multicenter MRI study; Reliability analysis Amygdalar nuclei; Hippocampal subfields; Multicenter MRI study; FreeSurfer; Reliability analysis anatomy & histology [Amygdala] anatomy & histology [Hippocampus] Automation Behavior Bioengineering BORDERLINE PERSONALITY-DISORDER Cognition ELDERLY-PATIENTS Female FreeSurfer FUNCTIONAL-ORGANIZATION Hippocampal subfields Hippocampus Hippocampus - anatomy & histology HUMAN BRAIN Humans Image processing Image Processing, Computer-Assisted Image Processing, Computer-Assisted - methods Image Processing, Computer-Assisted - standards Imaging info:eu-repo/classification/ddc/616.8 Life Sciences Magnetic Resonance Imaging Magnetic Resonance Imaging - methods Magnetic Resonance Imaging - standards Male MANUAL SEGMENTATION Medical imaging Medizin Memory MESH: Adult MESH: Aged MESH: Amygdala / anatomy & histology MESH: Female MESH: Hippocampus / anatomy & histology MESH: Humans MESH: Image Processing, Computer-Assisted / methods MESH: Image Processing, Computer-Assisted / standards MESH: Magnetic Resonance Imaging / methods MESH: Magnetic Resonance Imaging / standards MESH: Male MESH: Middle Aged MESH: Neuroimaging / methods MESH: Neuroimaging / standards MESH: Reproducibility of Results MESH: Software methods [Image Processing, Computer-Assisted] methods [Magnetic Resonance Imaging] methods [Neuroimaging] METHODS FREESURFER Middle Aged Multicenter MRI study Neuroimaging Neuroimaging - methods Neuroimaging - standards Neurosciences. Biological psychiatry. Neuropsychiatry Nuclei RC321-571 Regulation Reliability analysis Reproducibility of Results SAMPLE-SIZE CALCULATIONS Segmentation Software standards [Image Processing, Computer-Assisted] standards [Magnetic Resonance Imaging] standards [Neuroimaging] STRUCTURAL DIFFERENCES Studies SURFACE-BASED ANALYSIS |
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| Title | Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors |
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