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On the generalizabi...
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De Luca, AlbertoUniv Med Ctr Utrecht, Netherlands; Univ Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
(author)
On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types : Chronicles of the MEMENTO challenge
- Article/chapterEnglish2021
Publisher, publication year, extent ...
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Elsevier BV,2021
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electronicrdacarrier
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LIBRIS-ID:oai:DiVA.org:liu-179831
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https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-179831URI
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https://doi.org/10.1016/j.neuroimage.2021.118367DOI
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https://lup.lub.lu.se/record/3d9f4686-5cdd-423c-8ffc-b9f5eb692e4fURI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
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Funding Agencies|European Research Council (ERC) under the European UnionEuropean Research Council (ERC) [694665]; French government, through the 3IA Cote DAzur Investments in the Future project [ANR-19-P3IA-0002]; EPSRCUK Research & Innovation (UKRI)Engineering & Physical Sciences Research Council (EPSRC) [EP/N018702/1, MR/T020296/1, ISLRA-2009]; European Space AgencyEuropean Space AgencyEuropean Commission; Belgian Science Policy Office-ProdexBelgian Federal Science Policy Office; Research Foundation Flanders (FWO Vlaanderen)FWO [12M3119N, G0D7216N]; Wellcome Trust Investigator AwardWellcome Trust [096646/Z/11/Z]; Wellcome Trust Strategic AwardWellcome Trust [104943/Z/14/Z]; Polish National Agency for Academic ExchangePolish National Agency for Academic Exchange (NAWA) [PN/BEK/2019/1/00421]; Ministry of Science and Higher Education (Poland)Ministry of Science and Higher Education, Poland [692/STYP/13/2018]; AGH Science and Technology, Poland [16.16.120.773]; Linkoping University (LiU) Center for Industrial Information Technology (CENIIT); LiU Cancer [VINNOVA/ITEA3 17021 IMPACT]; Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [RMX18-0056]; "la Caixa" FoundationLa Caixa Foundation [100010434]; European UnionEuropean Commission [847648, LCF/BQ/PI20/11760029]; Ministerio de Ciencia e Innovacion" of SpainSpanish Government [RTI2018-094569-B-I00]; National Institute for Biomedical Imaging [5R01EB027585-02]
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Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural organization of brain tissue. Depending on the specific acquisition settings, the dMRI signal encodes specific properties of the underlying diffusion process. In the last two decades, several signal representations have been proposed to fit the dMRI signal and decode such properties. Most methods, however, are tested and developed on a limited amount of data, and their applicability to other acquisition schemes remains unknown. With this work, we aimed to shed light on the generalizability of existing dMRI signal representations to different diffusion encoding parameters and brain tissue types. To this end, we organized a community challenge - named MEMENTO, making available the same datasets for fair comparisons across algorithms and techniques. We considered two state-of-the-art diffusion datasets, including single-diffusion-encoding (SDE) spin-echo data from a human brain with over 3820 unique diffusion weightings (the MASSIVE dataset), and double (oscillating) diffusion encoding data (DDE/DODE) of a mouse brain including over 2520 unique data points. A subset of the data sampled in 5 different voxels was openly distributed, and the challenge participants were asked to predict the remaining part of the data. After one year, eight participant teams submitted a total of 80 signal fits. For each submission, we evaluated the mean squared error, the variance of the prediction error and the Bayesian information criteria. The received submissions predicted either multi-shell SDE data (37%) or DODE data (22%), followed by cartesian SDE data (19%) and DDE (18%). Most submissions predicted the signals measured with SDE remarkably well, with the exception of low and very strong diffusion weightings. The prediction of DDE and DODE data seemed more challenging, likely because none of the submissions explicitly accounted for diffusion time and frequency. Next to the choice of the model, decisions on fit procedure and hyperparameters play a major role in the prediction performance, highlighting the importance of optimizing and reporting such choices. This work is a community effort to highlight strength and limitations of the field at representing dMRI acquired with trending encoding schemes, gaining insights into how different models generalize to different tissue types and fiber configurations over a large range of diffusion encodings.
Subject headings and genre
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Ianus, AndradaChampalimaud Ctr Unknown, Portugal
(author)
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Leemans, AlexanderUniv Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
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Palombo, MarcoUCL, England,University College London
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Shemesh, NoamChampalimaud Ctr Unknown, Portugal
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Zhang, HuiUCL, England,University College London
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Alexander, Daniel C.UCL, England,University College London
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Nilsson, MarkusLund University,Lunds universitet,Diagnostisk radiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,LUCC: Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,Diagnostic Radiology, (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,LUCC: Lund University Cancer Centre,Other Strong Research Environments(Swepub:lu)med-mun
(author)
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Froeling, MartijnUniv Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
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Biessels, Geert-JanUniv Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
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Zucchelli, MauroUniv Cote dAzur, France,University of Côte d'Azur
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Frigo, MatteoUniv Cote dAzur, France,University of Côte d'Azur
(author)
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Albay, EnesUniv Cote dAzur, France; Istanbul Tech Univ, Turkey,University of Côte d'Azur,Istanbul Technical University
(author)
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Sedlar, SaraUniv Cote dAzur, France,University of Côte d'Azur
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Alimi, AbibUniv Cote dAzur, France,University of Côte d'Azur
(author)
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Deslauriers-Gauthier, SamuelUniv Cote dAzur, France,University of Côte d'Azur
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Deriche, RachidUniv Cote dAzur, France,University of Côte d'Azur
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Fick, RutgerTRIBVN Healthcare, France
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Afzali, MaryamCardiff Univ, Wales
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Pieciak, TomaszAGH Univ Sci & Technol, Poland; Univ Valladolid, Spain,University of Valladolid,AGH University of Science and Technology
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Bogusz, FabianAGH Univ Sci & Technol, Poland,AGH University of Science and Technology
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Aja-Fernandez, SantiagoUniv Valladolid, Spain,University of Valladolid
(author)
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Özarslan, EvrenLinköping University,Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV(Swepub:liu)evroz77
(author)
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Jones, Derek K.Cardiff Univ, Wales
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Chen, HaozeNorth Univ China, Peoples R China
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Jin, MingwuUniv Texas Arlington, TX 76019 USA,University of Texas at Arlington
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Zhang, ZhijieNorth Univ China, Peoples R China
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Wang, FengxiangNorth Univ China, Peoples R China
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Nath, VishweshNVIDIA Corp, MD USA
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Parvathaneni, PrasannaNIH, MD 20892 USA,National Institutes of Health, United States
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Morez, JanUniv Antwerp, Belgium,University of Antwerp
(author)
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Sijbers, JanUniv Antwerp, Belgium,University of Antwerp
(author)
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Jeurissen, BenUniv Antwerp, Belgium,University of Antwerp
(author)
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Fadnavis, ShreyasIndiana Univ, IN 47405 USA,Indiana University
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Endres, StefanUniv Bremen, Germany,University of Bremen
(author)
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Rokem, ArielUniv Washington, WA 98195 USA; Univ Washington, WA 98195 USA,University of Washington
(author)
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Garyfallidis, EleftheriosIndiana Univ, IN 47405 USA,Indiana University
(author)
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Sanchez, IrinaQMENTA Inc, MA USA
(author)
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Prchkovska, VesnaQMENTA Inc, MA USA
(author)
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Rodrigues, PauloQMENTA Inc, MA USA
(author)
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Landman, Bennet A.Vanderbilt Univ, TN 37235 USA
(author)
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Schilling, Kurt G.Vanderbilt Univ, TN 37235 USA; Vanderbilt Univ, TN 37232 USA,Vanderbilt University
(author)
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Univ Med Ctr Utrecht, Netherlands; Univ Med Ctr Utrecht, NetherlandsUniversity Medical Center Utrecht
(creator_code:org_t)
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In:NeuroImage: Elsevier BV2401053-81191095-9572
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- By the author/editor
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De Luca, Alberto
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Ianus, Andrada
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Leemans, Alexand ...
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Palombo, Marco
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Shemesh, Noam
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Zhang, Hui
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show more...
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Alexander, Danie ...
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Nilsson, Markus
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Froeling, Martij ...
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Biessels, Geert- ...
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Zucchelli, Mauro
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Frigo, Matteo
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Albay, Enes
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Sedlar, Sara
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Alimi, Abib
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Deslauriers-Gaut ...
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Deriche, Rachid
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Fick, Rutger
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Afzali, Maryam
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Pieciak, Tomasz
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Bogusz, Fabian
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Aja-Fernandez, S ...
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Özarslan, Evren
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Jones, Derek K.
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Chen, Haoze
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Jin, Mingwu
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Zhang, Zhijie
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Wang, Fengxiang
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Nath, Vishwesh
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Parvathaneni, Pr ...
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Morez, Jan
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Sijbers, Jan
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Jeurissen, Ben
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Fadnavis, Shreya ...
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Endres, Stefan
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Rokem, Ariel
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Garyfallidis, El ...
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Sanchez, Irina
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Prchkovska, Vesn ...
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Rodrigues, Paulo
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Landman, Bennet ...
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Schilling, Kurt ...
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NeuroImage
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Linköping University
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