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Nat Commun. 2017 Nov 7;8(1):1349. doi: 10.1038/s41467-017-01285-x.

The challenge of mapping the human connectome based on diffusion tractography.

Author information

1
Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany. k.maier-hein@dkfz.de.
2
Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany.
3
Sherbrooke Connectivity Imaging Lab (SCIL), Université de Sherbrooke, Sherbrooke, QC J1K 0A5, QC, Canada.
4
Department of Intelligent Systems Engineering, School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA.
5
Krembil Research Institute, University Health Network, Toronto, Canada, M5G 2C4.
6
Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
7
IMT-Institute for Advanced Studies, Lucca, 55100, Italy.
8
Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
9
University of Toronto Institute of Medical Science, Toronto, Canada, M5S 1A8.
10
Institute of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, 310023, Zhejiang, China.
11
United Imaging Healthcare Co., Shanghai, 201807, China.
12
Shanghai Advanced Research Institute, Shanghai, 201210, China.
13
Laboratory of Mathematics in Imaging, Harvard Medical School, Boston, MA, 02215, USA.
14
Center for Research in Mathematics, Guanajuato, 36023, Mexico.
15
PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, 3508, The Netherlands.
16
Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK.
17
Department of Radiology, University Medical Center Utrecht, Utrecht, 3508, The Netherlands.
18
Centre de recherche institut universitaire de geriatrie de Montreal (CRIUGM), Université de Montréal, Montreal, QC, Canada, H3W 1W5.
19
Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale (LIB), 75013, Paris, France.
20
Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada, H4J 1C5.
21
Neuroimaging Unit, Institute of Bioimaging and Molecular Physiology (IBFM), National Research Council (CNR), Policlinico Magna Graecia, Germaneto, 88100, CZ, Italy.
22
Institute of Neurology, University Magna Graecia, Germaneto, 88100, CZ, Italy.
23
Institute for Learning & Brain Sciences and Department of Speech & Hearing Sciences, University of Washington, Seattle, WA, 98195, USA.
24
Departments of Medical Biophysics & Medical Imaging, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond St N, London, ON, Canada, N6A 5C1.
25
Synaptive Medical Inc., MaRS Discovery District, 101 College Street, Suite 200, Toronto, ON, Canada, M5V 3B1.
26
Signal Processing Lab (LTS5), Ecole Polytechnique Federale de Lausanne, Lausanne, 1015, Switzerland.
27
Biomedical Image Technologies (BIT), ETSI Telecom., U. Politécnica de Madrid and CIBER-BBN, Madrid, 28040, Spain.
28
Department of Radiology, University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, 1011, Switzerland.
29
Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, 08540, USA.
30
Imaging Genetics Center, Stevens Neuro Imaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, 90033, USA.
31
NatBrainLab, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
32
Groupe d'imagerie Neurofonctionnelle-Institut des Maladies Neurodégénératives (GIN-IMN), UMR5293 CNRS, CEA, University of Bordeaux, Bordeaux, 33000, France.
33
Centre national de la recherche scientifique (CNRS), Institute for Research in IT and Random Systems (IRISA), UMR 6074 VISAGES Project-Team, Rennes, 35042, France.
34
Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, 2650, Denmark.
35
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, 2800, Denmark.
36
Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany.
37
Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg, 20246, Germany.
38
University Hospital Basel, Radiology & Nuclear Medicine Clinic, Basel, 4031, Switzerland.
39
Sherbrooke Connectivity Imaging Lab (SCIL), Université de Sherbrooke, Sherbrooke, QC J1K 0A5, QC, Canada. m.descoteaux@usherbrooke.ca.

Abstract

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

PMID:
29116093
PMCID:
PMC5677006
DOI:
10.1038/s41467-017-01285-x
[Indexed for MEDLINE]
Free PMC Article

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