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Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset
KG. Schilling, F. Rheault, L. Petit, CB. Hansen, V. Nath, FC. Yeh, G. Girard, M. Barakovic, J. Rafael-Patino, T. Yu, E. Fischi-Gomez, M. Pizzolato, M. Ocampo-Pineda, S. Schiavi, EJ. Canales-Rodríguez, A. Daducci, C. Granziera, G. Innocenti, JP....
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články, Research Support, N.I.H., Extramural, práce podpořená grantem, Research Support, U.S. Gov't, Non-P.H.S.
Grantová podpora
K24 MH116366
NIMH NIH HHS - United States
T32 EB001628
NIBIB NIH HHS - United States
R01 EB017230
NIBIB NIH HHS - United States
T32 MH103213
NIMH NIH HHS - United States
213722/Z/18/Z
Wellcome Trust - United Kingdom
P41 EB015898
NIBIB NIH HHS - United States
P30 NS076408
NINDS NIH HHS - United States
R01 MH119222
NIMH NIH HHS - United States
MR/N013913/1
Medical Research Council - United Kingdom
U54 HD090256
NICHD NIH HHS - United States
R01 MH111917
NIMH NIH HHS - United States
215944/Z/19/Z
Wellcome Trust - United Kingdom
P41 EB015922
NIBIB NIH HHS - United States
P41 EB027061
NIBIB NIH HHS - United States
R01 EB029272
NIBIB NIH HHS - United States
P41 RR013218
NCRR NIH HHS - United States
UL1 RR024975
NCRR NIH HHS - United States
Wellcome Trust - United Kingdom
T32 MH019908
NIMH NIH HHS - United States
P41 EB015902
NIBIB NIH HHS - United States
NLK
Directory of Open Access Journals
od 2020
ProQuest Central
od 1998-05-01 do Před 2 měsíci
Health & Medicine (ProQuest)
od 2002-08-01 do Před 2 měsíci
Psychology Database (ProQuest)
od 2002-08-01 do Před 2 měsíci
ROAD: Directory of Open Access Scholarly Resources
- MeSH
- algoritmy MeSH
- bílá hmota diagnostické zobrazování MeSH
- disekce metody MeSH
- lidé MeSH
- nervové dráhy diagnostické zobrazování MeSH
- počítačové zpracování obrazu metody MeSH
- zobrazování difuzních tenzorů metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.
AINOSTICS Limited London United Kingdom
Brain MRI 3T Research Center IRCCS Mondino Foundation Pavia Italy
Brigham and Women's Hospital and Harvard Medical School Boston Massachusetts USA
Cardiff University Brain Research Imaging Centre Cardiff University Cardiff United Kingdom
Center for Research and Interdisciplinarity INSERM U1284 Université de Paris Paris France
Centre for Medical Image Computing University College London London United Kingdom
Centro de Investigación en Matemáticas A C Guanajuato Mexico
CIBM Center for BioMedical Imaging Lausanne Switzerland
Departamento de Anatomía Facultad de Medicina Universidad Complutense de Madrid Madrid Spain
Department of Advanced Biomedical Sciences University Federico 2 Naples Italy
Department of Brain and Behavioral Sciences University of Pavia Italy
Department of Clinical and Experimental Epilepsy University College London London United Kingdom
Department of Computer Science Indiana University Bloomington IN USA
Department of Computer Science University of Verona Italy
Department of Intelligent Systems Engineering Indiana University Bloomington IN USA
Department of Neurological Surgery University of Pittsburgh Pittsburgh PA United States
Department of Neuroscience Karolinska Institutet Stockholm Sweden
Department of Neuroscience University of Minnesota Minneapolis MN USA
Department of Neurosurgery Charité Universitätsmedizin Berlin Berlin Germany
Department of Neurosurgery School for Mental Health and Neuroscience Maastricht University
Department of Physiology and Biochemistry Faculty of Medicine and Surgery University of Malta Malta
Department of Psychology Stanford University Stanford California USA
Department of Psychology The University of Texas at Austin TX 78731 USA
Department of Radiology Juntendo University Graduate School of Medicine Tokyo Japan
Department of Radiology University of Calgary 2500 University Drive NW Calgary AB Canada T2N 1N4
Department of Radiology University of Pennsylvania Philadelphia PA United States
Developmental Imaging and Biophysics Section UCL GOS Institute of Child Health London
Developmental Imaging Murdoch Children's Research Institute Melbourne Australia
Epilepsy Society MRI Unit Chalfont St Peter United Kingdom
Facultad de Ciencias de la Salud Universidad Rey Juan Carlos Madrid Spain
KU Leuven Department of Imaging and Pathology Translational MRI B 3000 Leuven Belgium
Laboratorio de Análisis de Imagen Médica y Biometría Universidad Rey Juan Carlos Madrid Spain
MRI Clinical Science Specialist General Electric Healthcare Australia
National Intrepid Center of Excellence Walter Reed National Military Medical Center Bethesda MD USA
National Neuroscience Institute Singapore
Neurology Department UCSF Weill Institute for Neurosciences University of California San Francisco
Neurosurgery department Hôpital Pasteur University Hospital of Nice Côte d'Azur University France
Poitiers University Hospital France
PROVIDI Lab UMC Utrecht The Netherlands
School of Biomedical Engineering The University of Sydney Sydney Australia
SCIL Université de Sherbrooke Québec Canada
Signal Processing Lab École Polytechnique Fédérale de Lausanne Lausanne Switzerland
Sir Peter Mansfield Imaging Centre School of Medicine University of Nottingham UK
Sydney Imaging and School of Biomedical Engineering The University of Sydney Sydney Australia
UMC Utrecht Brain Center Department of Neurology and Neurosurgery Utrecht the Netherlands
Universidad de Concepción Faculty of Engineering Concepción Chile
Universidad Nacional Autonoma de Mexico Institute of Neurobiology Mexico City Mexico
Université Paris Saclay CEA CNRS Neurospin Gif sur Yvette France
University of Arkansas for Medical Sciences Little Rock AR USA
University of Wisconsin Madison Madison WI USA
Victorian Infant Brain Studies Murdoch Children's Research Institute Melbourne Australia
Citace poskytuje Crossref.org
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- $a Schilling, Kurt G $u Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States. Electronic address: kurt.g.schilling.1@vumc.org
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- $a White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.
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