Evidence map›Paper›PMID 31179595›Full record

SynthesisJournal of magnetic resonance imaging : JMRI2020

Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challenge.

Vishwesh Nath, Kurt G Schilling, Prasanna Parvathaneni, Yuankai Huo, Justin A Blaber, Allison E Hainline, Muhamed Barakovic, David Romascano, Jonathan Rafael-Patino, Matteo Frigo and 33 more

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of magnetic resonance imaging : JMRI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts.Proceedings of SPIE--the International Society for Optical Engineering · 2026
    Article
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  10. Review
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  13. Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  14. Article
  15. Review
  16. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

43 authors.

Vishwesh NathComputer Science, Vanderbilt University, Nashville, Tennessee, USA.ORCID 0000-0002-6840-6205
Kurt G SchillingBiomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.
Prasanna ParvathaneniElectrical Engineering, Vanderbilt University, Nashville, Tennessee, USA.
Yuankai HuoElectrical Engineering, Vanderbilt University, Nashville, Tennessee, USA.
Justin A BlaberElectrical Engineering, Vanderbilt University, Nashville, Tennessee, USA.
Allison E HainlineBiostatistics, Vanderbilt University, Nashville, Tennessee, USA.
Muhamed BarakovicSignal Processing Lab (LTS5), EPFL, Switzerland.
David RomascanoSignal Processing Lab (LTS5), EPFL, Switzerland.
Jonathan Rafael-PatinoSignal Processing Lab (LTS5), EPFL, Switzerland.
Matteo FrigoSignal Processing Lab (LTS5), EPFL, Switzerland.
Gabriel GirardSignal Processing Lab (LTS5), EPFL, Switzerland.
Jean-Philippe ThiranSignal Processing Lab (LTS5), EPFL, Switzerland.
Alessandro DaducciComputer Science Department, University of Verona, Italy.
Matt RoweMint Labs Inc., Boston, Massachusetts, USA.
Paulo RodriguesMint Labs Inc., Boston, Massachusetts, USA.
Vesna PrčkovskaMint Labs Inc., Boston, Massachusetts, USA.
Dogu B AydoganKeck School of Medicine, University of Southern California (NICR), Los Angeles, California, USA.
Wei SunKeck School of Medicine, University of Southern California (NICR), Los Angeles, California, USA.
Yonggang ShiKeck School of Medicine, University of Southern California (NICR), Los Angeles, California, USA.
William A ParkerCenter for Biomedical Image Computing and Analytics, Dept. of Radiology, Perelman School of Medicine, University of Pennsylvania (UPENN), Philadelphia, Pennsylvania, USA.
Abdol A Ould IsmailCenter for Biomedical Image Computing and Analytics, Dept. of Radiology, Perelman School of Medicine, University of Pennsylvania (UPENN), Philadelphia, Pennsylvania, USA.
Ragini VermaCenter for Biomedical Image Computing and Analytics, Dept. of Radiology, Perelman School of Medicine, University of Pennsylvania (UPENN), Philadelphia, Pennsylvania, USA.
Ryan P CabeenLaboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
Arthur W TogaLaboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
Allen T NewtonVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jakob WasserthalMedical Image Computing Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Peter NeherMedical Image Computing Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Klaus Maier-HeinMedical Image Computing Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Giovanni SaviniDepartment of Physics, University of Milan, Milan, Italy.
Fulvia PalesiBrain Connectivity Center, C. Mondino National Neurological Institute (EFG), Pavia, Italy.
Enrico KadenCentre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
Ye WuInstitution of Information Processing and Automation, Zhejiang University of Technology (ZUT), Hangzhou, China.
Jianzhong HeInstitution of Information Processing and Automation, Zhejiang University of Technology (ZUT), Hangzhou, China.
Yuanjing FengInstitution of Information Processing and Automation, Zhejiang University of Technology (ZUT), Hangzhou, China.
Michael PaquetteSherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada.
Francois RheaultSherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada.
Jasmeen SidhuSherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada.
Catherine LebelDepartment of Radiology, University of Calgary, Canada.
Alexander LeemansImage Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands.
Maxime DescoteauxSherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, Canada.
Tim B DyrbyDanish Research Centre for Magnetic Resonance, Copenhagen University Hospital, Hvidovre, Denmark.
Hakmook KangBiostatistics, Vanderbilt University, Nashville, Tennessee, USA.
Bennett A LandmanComputer Science, Vanderbilt University, Nashville, Tennessee, USA.

Funding

VANDERBILT UNIVERSITY CTSA FOR PEDIATRIC RESEARCHUL1RR024975 · NCRR · VANDERBILT UNIVERSITY · PI BERNARD, GORDON RAPHAEL · 2007 to 2011
$45.7M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Postdoctoral Training in Biomedical MRI and MRST32EB001628 · NIBIB · VANDERBILT UNIVERSITY MEDICAL CENTER · PI John C Gore · 2003 to 2026
$7.0M
Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRIR01EB017230 · NIBIB · VANDERBILT UNIVERSITY · PI LANDMAN, BENNETT A. · 2015 to 2024
$5.1M
Connectomics meets neuro-oncology: mapping the brain for treatment planningR01NS096606 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI BREM, STEVEN, VERMA, RAGINI · 2016 to 2020
$2.7M
NCATS NIH HHS UL1 TR000445NCRR NIH HHS UL1 RR024975NCRR NIH HHS UL1 RR024975-01NIBIB NIH HHS R01 EB017230NIBIB NIH HHS T32 EB001628NINDS NIH HHS R01 NS096606
6 · The paper itself

Abstract

backgroundFiber tracking with diffusion-weighted MRI has become an essential tool for estimating in vivo brain white matter architecture. Fiber tracking results are sensitive to the choice of processing method and tracking criteria. PURPOSE: To assess the variability for an algorithm in group studies reproducibility is of critical context. However, reproducibility does not assess the validity of the brain connections. Phantom studies provide concrete quantitative comparisons of methods relative to absolute ground truths, yet do no capture variabilities because of in vivo physiological factors. The ISMRM 2017 TraCED challenge was created to fulfill the gap. STUDY TYPE: A systematic review of algorithms and tract reproducibility studies. SUBJECTS: Single healthy volunteers. FIELD STRENGTH/SEQUENCE: 3.0T, two different scanners by the same manufacturer. The multishell acquisition included b-values of 1000, 2000, and 3000 s/mm ASSESSMENT: Nine international groups submitted 46 tractography algorithm entries each consisting 16 tracts per scan. The algorithms were assessed using intraclass correlation (ICC) and the Dice similarity measure. STATISTICAL TESTS: Containment analysis was performed to assess if the submitted algorithms had containment within tracts of larger volume submissions. This also serves the purpose to detect if spurious submissions had been made.

resultsThe top five submissions had high ICC and Dice >0.88. Reproducibility was high within the top five submissions when assessed across sessions or across scanners: 0.87-0.97. Containment analysis shows that the top five submissions are contained within larger volume submissions. From the total of 16 tracts as an outcome relatively the number of tracts with high, moderate, and low reproducibility were 8, 4, and 4. DATA

conclusionThe different methods clearly result in fundamentally different tract structures at the more conservative specificity choices. Data and challenge infrastructure remain available for continued analysis and provide a platform for comparison. LEVEL OF EVIDENCE: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:234-249.

Indexed as

BrainDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingHumansReference ValuesReproducibility of ResultschallengeDW-MRIHARDIin vivoreproducibilitytractography

Identifiers

PMID31179595
PMCPMC6900461

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.