Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

• DOI: 10.1016/j.neuroimage.2021.118502
• Publication Date: 2021-08-22T05:22:19Z
• Authors: Kurt G. Schilling; François Rheault; Laurent Petit; Colin B. Hansen; Vishwesh Nath; Fang-Cheng Yeh; Gabriel Girard; Muhamed Barakovic; Jonathan Rafael-P...; Thomas Yu; Elda Fischi-Gomez; Marco Pizzolato; Mario Ocampo-Pineda; Simona Schiavi; Erick J. Canales-...; Alessandro Daducci; Cristina Granziera; Giorgio Innocenti; Jean-Philippe Thiran; Laura Mancini; Stephen Wastling; Sirio Cocozza; Maria Petracca; Giuseppe Pontillo; Matteo Mancini; Sjoerd B. Vos; Vejay N. Vakharia; John S. Duncan; Helena Melero; Lidia Manzanedo; Emilio Sanz-Morales; Ángel Peña-Melián; Fernando Calamante; Arnaud Attyé; Ryan P. Cabeen; Laura Korobova; Arthur W. Toga; Anupa Ambili Vija...; Drew Parker; Ragini Verma; Ahmed Radwan; Stefan Sunaert; Louise Emsell; Alberto De Luca; Alexander Leemans; Claude J. Bajada; Hamied Haroon; Hojjatollah Azadb...; Maxime Chamberland; Sila Genc; Chantal M.W. Tax; Ping-Hong Yeh; Rujirutana Srikan...; Colin D. Mcknight; Joseph Yuan-Mou Yang; Jian Chen; Claire E. Kelly; Chun-Hung Yeh; Jerome Cochereau; Jerome J. Maller; Thomas Welton; Fabien Almairac; Kiran K Seunarine; Chris A. Clark; Fan Zhang; Nikos Makris; Alexandra Golby; Yogesh Rathi; Lauren J. O'Donnell; Yihao Xia; Dogu Baran Aydogan; Yonggang Shi; Francisco Guerrei...; Mathijs Raemaekers; Shaun Warrington; Stijn Michielse; Alonso Ramírez-Ma...; Luis Concha; Ramón Aranda; Mariano Rivera Meraz; Garikoitz Lerma-U...; Lucas Roitman; Lucius S. Fekonja; Navona Calarco; Michael Joseph; Hajer Nakua; Aristotle N. Voin...; Philippe Karan; Gabrielle Grenier; Jon Haitz Legarreta; Nagesh Adluru; Veena A. Nair; Vivek Prabhakaran; Andrew L. Alexander; Koji Kamagata; Yuya Saito; Wataru Uchida; Christina Andica; Masahiro Abe; Roza G. Bayrak; Claudia A.M. Gand...; Egidio D'Angelo; Fulvia Palesi; Giovanni Savini; Nicolò Rolandi; Pamela Guevara; Josselin Houenou; Narciso López-López; Jean-François Mangin; Cyril Poupon; Claudio Román; Andrea Vázquez; Chiara Maffei; Mavilde Arantes; José Paulo Andrade; Susana Maria Silva; Vince D. Calhoun; Eduardo Caverzasi; Simone Sacco; Michael Lauricella; Franco Pestilli; Daniel Bullock; Yang Zhan; Edith Brignoni-Perez; Catherine Lebel; Jess E Reynolds; Igor Nestrasil; René Labounek; Christophe Lenglet; Amy Paulson; Stefania Aulicka; Sarah R. Heilbronner; Katja Heuer; Bramsh Qamar Chandio; Javier Guaje; Wei Tang; Eleftherios Garyf...; Rajikha Raja; Adam W. Anderson; Bennett A. Landman; Maxime Descoteaux
• Keywords: Radiology, Nuclear Medicine and Imaging; Artificial intelligence; principal eigenvector measurements; [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging; Image Processing; corpus-callosum; tractography; Fiber pathway; FRACTIONAL ANISOTROPY; Medical and Health Sciences; in-vivo; Computer-Assisted; Segmentation; 0302 clinical medicine; Fiber Tractography; Neural Pathways; Image Processing, Computer-Assisted; Bundle segmentation; Dissection; Fiber pathways; Tractography; White matter; IN-VIVO; Dissection; Radiology, Nuclear Medicine & Medical Imaging; White matter; MEAN DIFFUSIVITY; Bundle segmentation; White Matter; 004; 3. Good health; Algorithm; Diffusion Tensor Imaging; dissection; 2490 Neurociencias; Biomedical Imaging; mean diffusivity; Medicine; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; bundle segmentation; Radiology; white matter; Life Sciences & Biomedicine; Tractography; fractional anisotropy; Algorithms; Human; RC321-571; Magnetic Resonance Imaging Applications in Medicine; Composite material; FIBER PATHWAYS; fiber pathways; Neuroimaging; Neurosciences. Biological psychiatry. Neuropsychiatry; ta3112; Diffusion MRI; ANATOMICAL ACCURACY; Neural Pathway; 03 medical and health sciences; Magnetic resonance imaging; TENSOR IMAGING TRACTOGRAPHY; 616; Health Sciences; Humans; Neurology & Neurosurgery; Science & Technology; Fiber bundle; [SCCO.NEUR]Cognitive science/Neuroscience; Psychology and Cognitive Sciences; Neurosciences; ARCUATE FASCICULUS; Computer science; CORPUS-CALLOSUM; Materials science; diffusion mri; PRINCIPAL EIGENVECTOR MEASUREMENTS; Fiber pathways; Bundle; Diffusion Magnetic Resonance Imaging; anatomical accuracy; Pediatrics, Perinatology and Child Health; arcuate fasciculus; tensor imaging tractography; Neurosciences & Neurology; DIFFUSION MRI; Neuropsicología; Development and Disorders of Fetal Brain

AbstractWhite matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathwaysin vivoin 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.