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Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?
Schilling, Kurt G; Rheault, François; Petit, Laurent; Hansen, Colin B; Nath, Vishwesh; Yeh, Fang-Cheng; Girard, Gabriel; Barakovic, Muhamed; Rafael-Patino, Jonathan; Yu, Thomas; Fischi-Gomez, Elda; Pizzolato, Marco; Ocampo-Pineda, Mario; Schiavi, Simona; Canales-Rodríguez, Erick J; Daducci, Alessandro; Granziera, Cristina; Innocenti, Giorgio; Thiran, Jean-Philippe; Mancini, Laura; Wastling, Stephen; Cocozza, Sirio; Petracca, Maria; Pontillo, Giuseppe; Mancini, Matteo; Vos, Sjoerd B; Vakharia, Vejay N; Duncan, John S; Melero, Helena; Manzanedo, Lidia; Sanz-Morales, Emilio; Peña-Melián, Ángel; Calamante, Fernando; Attyé, Arnaud; Cabeen, Ryan P; Korobova, Laura; Toga, Arthur W; Vijayakumari, Anupa Ambili; Parker, Drew; Verma, Ragini; Radwan, Ahmed; Sunaert, Stefan; Emsell, Louise; De Luca, Alberto; Leemans, Alexander; Bajada, Claude J; Haroon, Hamied; Azadbakht, Hojjatollah; Chamberland, Maxime; Genc, Sila.
Afiliação
  • Schilling KG; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States. Electronic address: kurt.g.schilling.1@vumc.org.
  • Rheault F; SCIL, Université de Sherbrooke, Québec, Canada.
  • Petit L; Groupe dImagerie Neurofonctionnelle, Institut Des Maladies Neurodegeneratives, CNRS, CEA University of Bordeaux, Bordeaux, France.
  • Hansen CB; Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States.
  • Nath V; Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States.
  • Yeh FC; Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, United States.
  • Girard G; CIBM Center for BioMedical Imaging, Lausanne, Switzerland.
  • Barakovic M; Translational Imaging in Neurology (ThINK), Department of Medicine and Biomedical Engineering, University Hospital and University of Basel, Basel, Switzerland.
  • Rafael-Patino J; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Yu T; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Fischi-Gomez E; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Pizzolato M; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.
  • Ocampo-Pineda M; Department of Computer Science, University of Verona, Italy.
  • Schiavi S; Department of Computer Science, University of Verona, Italy.
  • Canales-Rodríguez EJ; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Daducci A; Department of Computer Science, University of Verona, Italy.
  • Granziera C; Translational Imaging in Neurology (ThINK), Department of Medicine and Biomedical Engineering, University Hospital and University of Basel, Basel, Switzerland.
  • Innocenti G; Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
  • Thiran JP; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Mancini L; Lysholm Department of Neuroradiology, National Hospital for Neurology & Neurosurgery, UCL Hospitals NHS Foundation Trust, London, United Kingdom.
  • Wastling S; Lysholm Department of Neuroradiology, National Hospital for Neurology & Neurosurgery, UCL Hospitals NHS Foundation Trust, London, United Kingdom.
  • Cocozza S; Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy.
  • Petracca M; Department of Neurosciences and Reproductive and Odontostomatological Sciences, University "Federico II", Naples, Italy.
  • Pontillo G; Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy.
  • Mancini M; Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom.
  • Vos SB; Centre for Medical Image Computing, University College London, London, United Kingdom.
  • Vakharia VN; Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom.
  • Duncan JS; Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom.
  • Melero H; Departamento de Psicobiología y Metodología en Ciencias del Comportamiento - Universidad Complutense de Madrid, Spain Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain.
  • Manzanedo L; Facultad de Ciencias de la Salud, Universidad Rey Juan Carlos, Madrid, Spain.
  • Sanz-Morales E; Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain.
  • Peña-Melián Á; Departamento de Anatomía, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain.
  • Calamante F; Sydney Imaging and School of Biomedical Engineering, The University of Sydney, Sydney, Australia.
  • Attyé A; School of Biomedical Engineering, The University of Sydney, Sydney, Australia.
  • Cabeen RP; Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
  • Korobova L; Center for Integrative Connectomics, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
  • Toga AW; Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
  • Vijayakumari AA; Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
  • Parker D; Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
  • Verma R; Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
  • Radwan A; KU Leuven, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium.
  • Sunaert S; KU Leuven, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium.
  • Emsell L; KU Leuven, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium.
  • De Luca A; PROVIDI Lab, UMC Utrecht, The Netherlands.
  • Leemans A; PROVIDI Lab, UMC Utrecht, The Netherlands.
  • Bajada CJ; Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, University of Malta, Malta.
  • Haroon H; Division of Neuroscience & Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.
  • Azadbakht H; AINOSTICS Limited, London, United Kingdom.
  • Chamberland M; Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom.
  • Genc S; Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom.
Neuroimage ; 243: 118502, 2021 11.
Article em En | MEDLINE | ID: mdl-34433094
ABSTRACT
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Dissecação / Imagem de Tensor de Difusão / Substância Branca Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Dissecação / Imagem de Tensor de Difusão / Substância Branca Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2021 Tipo de documento: Article