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Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge

G. Girard, J. Rafael-Patiño, R. Truffet, DB. Aydogan, N. Adluru, VA. Nair, V. Prabhakaran, BB. Bendlin, AL. Alexander, S. Bosticardo, I. Gabusi, M. Ocampo-Pineda, M. Battocchio, Z. Piskorova, P. Bontempi, S. Schiavi, A. Daducci, A. Stafiej, D....

. 2023 ; 277 (-) : 120231. [pub] 20230616

Language English Country United States

Document type Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't

Persistent link   https://www.medvik.cz/link/bmc24001266

Grant support
U54 AI117924 NIAID NIH HHS - United States
R01 AG037639 NIA NIH HHS - United States
R01 NS111022 NINDS NIH HHS - United States
R01 AI138647 NIAID NIH HHS - United States
R01 MH125479 NIMH NIH HHS - United States
R01 EB028774 NIBIB NIH HHS - United States
P50 HD105353 NICHD NIH HHS - United States
R01 NS102665 NINDS NIH HHS - United States
UF1 AG051216 NIA NIH HHS - United States
U54 HD090256 NICHD NIH HHS - United States
P50 AG033514 NIA NIH HHS - United States
P41 EB017183 NIBIB NIH HHS - United States
R01 NS092870 NINDS NIH HHS - United States
R34 DA050258 NIDA NIH HHS - United States
R01 EB017230 NIBIB NIH HHS - United States
R01 NS117568 NINDS NIH HHS - United States
R01 NS124920 NINDS NIH HHS - United States
K01 EB032898 NIBIB NIH HHS - United States
R01 EB022883 NIBIB NIH HHS - United States
R01 AG027161 NIA NIH HHS - United States
P01 AI132132 NIAID NIH HHS - United States
RF1 AG059312 NIA NIH HHS - United States
R01 NS123378 NINDS NIH HHS - United States
R01 NS105646 NINDS NIH HHS - United States
R21 NS126806 NINDS NIH HHS - United States
R01 NS082436 NINDS NIH HHS - United States

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

A 1 Virtanen Institute for Molecular Sciences University of Eastern Finland Kuopio Finland

AGH University of Science and Technology Kraków Poland

Athena Project Team Centre Inria d'Université Côte d'Azur France

Brain Mapping Lab Department of Biomedical Dental Sciences and Morphological and Functional Images University of Messina Messina Italy

Brno Faculty of Electrical Engineering and Communication Department of mathematics University of Technology Brno Czech Republic

Center for Advanced Imaging Innovation and Research Department of Radiology NYU Langone Health New York NY United States

Center for Complex Network Intelligence Tsinghua University Beijing China

CIBM Center for Biomedical Imaging Switzerland

Computer Science Department Centro de Investigación en Matemáticas A C Guanajuato México

Department of Advanced Biomedical Sciences University of Naples Federico 2 Naples Italy

Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs Lyngby Denmark

Department of Biomedical Engineering The University of Melbourne Parkville Victoria Australia

Department of Biomedical Engineering Tsinghua University Beijing China

Department of Electrical and Computer Engineering Vanderbilt University Nashville TN United States

Department of Medical Physics University of Wisconsin Madison Madison WI United States

Department of Medicine University of Wisconsin Madison Madison WI United States

Department of Neuroscience and Biomedical Engineering Aalto University Espoo Finland

Department of Neuroscience Rehabilitation Ophthalmology Genetics Maternal and Child Health University of Genoa Genoa Italy

Department of Neurosurgery Perlmutter Cancer Center Neuroscience Institute Kimmel Center for Stem Cell Biology NYU Langone Health New York NY United States

Department of Psychiatry Helsinki University Hospital Helsinki Finland

Department of Psychiatry University of Wisconsin Madison Madison WI United States

Department of Psychological and Brain Sciences Indiana University Bloomington IN United States

Department of Radiology and Biomedical Research Imaging Center The University of North Carolina at Chapel Hill Chapel Hill NC United States

Department of Radiology and Radiological Sciences Vanderbilt University Medical Center Nashville TN United States

Department of Radiology Stanford University Stanford CA United States

Department of Radiology University of Wisconsin Madison Madison WI United States

Diffusion Imaging and Connectivity Estimation Lab Department of Computer Science University of Verona Verona Italy

Institut de Biologie de Valrose Université Côte d'Azur Nice France

Instituto de Neurobiología Universidad Nacional Autónoma de México Juriquilla Querétaro México

Laboratorio de Procesado de Imagen ETSI Telecomunicación Universidad de Valladolid Valladolid Spain

McGill University Montréal QC Canada

Melbourne Neuropsychiatry Centre Department of Psychiatry The University of Melbourne and Melbourne Health Parkville Victoria Australia

Radiology Department Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne Switzerland

Sano Centre for Computational Personalised Medicine Kraków Poland

School of Biomedical Engineering The University of Sydney Sydney Australia

School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

Sherbrooke Connectivity Imaging Laboratory Department of Computer Science University of Sherbrooke Sherbrooke QC Canada

Signal Processing Laboratory Lausanne Switzerland

Translational Imaging in Neurology Department of Biomedical Engineering University Hospital Basel and University of Basel Basel Switzerland

Univ Rennes Inria CNRS Inserm IRISA UMR 6074 Empenn ERL U 1228 Rennes France

Waisman Center University of Wisconsin Madison Madison WI United States

References provided by Crossref.org

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$a Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge / $c G. Girard, J. Rafael-Patiño, R. Truffet, DB. Aydogan, N. Adluru, VA. Nair, V. Prabhakaran, BB. Bendlin, AL. Alexander, S. Bosticardo, I. Gabusi, M. Ocampo-Pineda, M. Battocchio, Z. Piskorova, P. Bontempi, S. Schiavi, A. Daducci, A. Stafiej, D. Ciupek, F. Bogusz, T. Pieciak, M. Frigo, S. Sedlar, S. Deslauriers-Gauthier, I. Kojčić, M. Zucchelli, H. Laghrissi, Y. Ji, R. Deriche, KG. Schilling, BA. Landman, A. Cacciola, GA. Basile, S. Bertino, N. Newlin, P. Kanakaraj, F. Rheault, P. Filipiak, TM. Shepherd, YC. Lin, DG. Placantonakis, FE. Boada, SH. Baete, E. Hernández-Gutiérrez, A. Ramírez-Manzanares, R. Coronado-Leija, P. Stack-Sánchez, L. Concha, M. Descoteaux, S. Mansour L, C. Seguin, A. Zalesky, K. Marshall, EJ. Canales-Rodríguez, Y. Wu, S. Ahmad, PT. Yap, A. Théberge, F. Gagnon, F. Massi, E. Fischi-Gomez, R. Gardier, JLV. Haro, M. Pizzolato, E. Caruyer, JP. Thiran
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$a Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.
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$a Bosticardo, Sara $u Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy; Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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$a Gabusi, Ilaria $u Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy; Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
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$a Battocchio, Matteo $u Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy; Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, University of Sherbrooke, Sherbrooke, QC, Canada
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$a Piskorova, Zuzana $u Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy; Brno Faculty of Electrical Engineering and Communication, Department of mathematics, University of Technology, Brno, Czech Republic
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$a Daducci, Alessandro $u Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
700    1_
$a Stafiej, Aleksandra $u AGH University of Science and Technology, Kraków, Poland
700    1_
$a Ciupek, Dominika $u Sano Centre for Computational Personalised Medicine, Kraków, Poland
700    1_
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700    1_
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700    1_
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700    1_
$a Sedlar, Sara $u Athena Project Team, Centre Inria d'Université Côte d'Azur, France
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700    1_
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700    1_
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700    1_
$a Basile, Gianpaolo Antonio $u Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
700    1_
$a Bertino, Salvatore $u Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
700    1_
$a Newlin, Nancy $u Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
700    1_
$a Kanakaraj, Praitayini $u Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
700    1_
$a Rheault, Francois $u Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
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$a Filipiak, Patryk $u Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, NYU Langone Health, New York, NY, United States
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$a Lin, Ying-Chia $u Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, NYU Langone Health, New York, NY, United States
700    1_
$a Placantonakis, Dimitris G $u Department of Neurosurgery, Perlmutter Cancer Center, Neuroscience Institute, Kimmel Center for Stem Cell Biology, NYU Langone Health, New York, NY, United States
700    1_
$a Boada, Fernando E $u Department of Radiology, Stanford University, Stanford, CA, United States
700    1_
$a Baete, Steven H $u Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, NYU Langone Health, New York, NY, United States
700    1_
$a Hernández-Gutiérrez, Erick $u Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, University of Sherbrooke, Sherbrooke, QC, Canada
700    1_
$a Ramírez-Manzanares, Alonso $u Computer Science Department, Centro de Investigación en Matemáticas A.C, Guanajuato, México
700    1_
$a Coronado-Leija, Ricardo $u Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, NYU Langone Health, New York, NY, United States
700    1_
$a Stack-Sánchez, Pablo $u Computer Science Department, Centro de Investigación en Matemáticas A.C, Guanajuato, México
700    1_
$a Concha, Luis $u Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
700    1_
$a Descoteaux, Maxime $u Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, University of Sherbrooke, Sherbrooke, QC, Canada
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700    1_
$a Seguin, Caio $u Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, Victoria, Australia; School of Biomedical Engineering, The University of Sydney, Sydney, Australia; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States
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$a Zalesky, Andrew $u Department of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, Australia; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, Victoria, Australia
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$a Canales-Rodríguez, Erick J $u Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
700    1_
$a Wu, Ye $u Department of Radiology and Biomedical Research Imaging Center (BRIC), The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States; School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China
700    1_
$a Ahmad, Sahar $u Department of Radiology and Biomedical Research Imaging Center (BRIC), The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
700    1_
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$a Caruyer, Emmanuel $u Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U-1228, Rennes, France
700    1_
$a Thiran, Jean-Philippe $u CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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