| Literature DB >> 34433094 |
Kurt G Schilling1, François Rheault2, Laurent Petit3, Colin B Hansen4, Vishwesh Nath4, Fang-Cheng Yeh5, Gabriel Girard6, Muhamed Barakovic7, Jonathan Rafael-Patino8, Thomas Yu8, Elda Fischi-Gomez8, Marco Pizzolato9, Mario Ocampo-Pineda10, Simona Schiavi10, Erick J Canales-Rodríguez8, Alessandro Daducci10, Cristina Granziera7, Giorgio Innocenti11, Jean-Philippe Thiran8, Laura Mancini12, Stephen Wastling12, Sirio Cocozza13, Maria Petracca14, Giuseppe Pontillo13, Matteo Mancini15, Sjoerd B Vos16, Vejay N Vakharia17, John S Duncan18, Helena Melero19, Lidia Manzanedo20, Emilio Sanz-Morales21, Ángel Peña-Melián22, Fernando Calamante23, Arnaud Attyé24, Ryan P Cabeen25, Laura Korobova26, Arthur W Toga25, Anupa Ambili Vijayakumari27, Drew Parker27, Ragini Verma27, Ahmed Radwan28, Stefan Sunaert28, Louise Emsell28, Alberto De Luca29, Alexander Leemans29, Claude J Bajada30, Hamied Haroon31, Hojjatollah Azadbakht32, Maxime Chamberland33, Sila Genc33, Chantal M W Tax33, Ping-Hong Yeh34, Rujirutana Srikanchana34, Colin D Mcknight35, Joseph Yuan-Mou Yang36, Jian Chen37, Claire E Kelly38, Chun-Hung Yeh39, Jerome Cochereau40, Jerome J Maller41, Thomas Welton42, Fabien Almairac43, Kiran K Seunarine44, Chris A Clark44, Fan Zhang45, Nikos Makris45, Alexandra Golby45, Yogesh Rathi45, Lauren J O'Donnell45, Yihao Xia46, Dogu Baran Aydogan47, Yonggang Shi46, Francisco Guerreiro Fernandes48, Mathijs Raemaekers48, Shaun Warrington49, Stijn Michielse50, Alonso Ramírez-Manzanares51, Luis Concha52, Ramón Aranda53, Mariano Rivera Meraz51, Garikoitz Lerma-Usabiaga54, Lucas Roitman54, Lucius S Fekonja55, Navona Calarco56, Michael Joseph56, Hajer Nakua56, Aristotle N Voineskos56, Philippe Karan2, Gabrielle Grenier2, Jon Haitz Legarreta2, Nagesh Adluru57, Veena A Nair57, Vivek Prabhakaran57, Andrew L Alexander57, Koji Kamagata58, Yuya Saito58, Wataru Uchida58, Christina Andica58, Masahiro Abe58, Roza G Bayrak4, Claudia A M Gandini Wheeler-Kingshott59, Egidio D'Angelo60, Fulvia Palesi60, Giovanni Savini61, Nicolò Rolandi60, Pamela Guevara62, Josselin Houenou63, Narciso López-López62, Jean-François Mangin63, Cyril Poupon63, Claudio Román62, Andrea Vázquez62, Chiara Maffei64, Mavilde Arantes65, José Paulo Andrade65, Susana Maria Silva65, Vince D Calhoun66, Eduardo Caverzasi67, Simone Sacco67, Michael Lauricella68, Franco Pestilli69, Daniel Bullock69, Yang Zhan70, Edith Brignoni-Perez71, Catherine Lebel72, Jess E Reynolds72, Igor Nestrasil73, René Labounek73, Christophe Lenglet74, Amy Paulson73, Stefania Aulicka75, Sarah R Heilbronner76, Katja Heuer77, Bramsh Qamar Chandio78, Javier Guaje78, Wei Tang79, Eleftherios Garyfallidis78, Rajikha Raja80, Adam W Anderson81, Bennett A Landman4, Maxime Descoteaux2.
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.Entities:
Keywords: Bundle segmentation; Dissection; Fiber pathways; Tractography; White matter
Mesh:
Year: 2021 PMID: 34433094 PMCID: PMC8855321 DOI: 10.1016/j.neuroimage.2021.118502
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 7.400