Evidence map›Paper›PMID 28766853›Full record

ArticleHuman brain mapping2017

AxTract: Toward microstructure informed tractography.

Gabriel Girard, Alessandro Daducci, Laurent Petit, Jean-Philippe Thiran, Kevin Whittingstall, Rachid Deriche, Demian Wassermann, Maxime Descoteaux

Abstract read
In one paragraph

Article in Human brain mapping, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–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

36 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Toward nonparametric diffusion-Magnetic resonance in medicine · 2021
    Article
  19. Article
  20. Article
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

8 authors.

Gabriel GirardSherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, Université de Sherbrooke, Sherbrooke, Canada.ORCID 0000-0002-5781-3104
Alessandro DaducciSignal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Laurent PetitGroupe d'Imagie Neurofonctionnelle, Institut des Maladies Neurodégénératives - UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France.ORCID 0000-0003-2499-5367
Jean-Philippe ThiranSignal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Kevin WhittingstallDepartment of Diagnostic Radiology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, Canada.
Rachid DericheProject Team Athena, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur, Sophia Antipolis, France.
Demian WassermannProject Team Athena, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur, Sophia Antipolis, France.
Maxime DescoteauxSherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science, Université de Sherbrooke, Sherbrooke, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffusion-weighted (DW) magnetic resonance imaging (MRI) tractography has become the tool of choice to probe the human brain's white matter in vivo. However, tractography algorithms produce a large number of erroneous streamlines (false positives), largely due to complex ambiguous tissue configurations. Moreover, the relationship between the resulting streamlines and the underlying white matter microstructure characteristics remains poorly understood. In this work, we introduce a new approach to simultaneously reconstruct white matter fascicles and characterize the apparent distribution of axon diameters within fascicles. To achieve this, our method, AxTract, takes full advantage of the recent development DW-MRI microstructure acquisition, modeling, and reconstruction techniques. This enables AxTract to separate parallel fascicles with different microstructure characteristics, hence reducing ambiguities in areas of complex tissue configuration. We report a decrease in the incidence of erroneous streamlines compared to the conventional deterministic tractography algorithms on simulated data. We also report an average increase in streamline density over 15 known fascicles of the 34 healthy subjects. Our results suggest that microstructure information improves tractography in crossing areas of the white matter. Moreover, AxTract provides additional microstructure information along the fascicle that can be studied alongside other streamline-based indices. Overall, AxTract provides the means to distinguish and follow white matter fascicles using their microstructure characteristics, bringing new insights into the white matter organization. This is a step forward in microstructure informed tractography, paving the way to a new generation of algorithms able to deal with intricate configurations of white matter fibers and providing quantitative brain connectivity analysis. Hum Brain Mapp 38:5485-5500, 2017. © 2017 Wiley Periodicals, Inc.

Indexed as

AlgorithmsAxonsBrainCell SizeComputer SimulationDiffusion Magnetic Resonance ImagingHumansImage Processing, Computer-AssistedModels, NeurologicalNerve Fibers, MyelinatedWhite MatterActiveAxaxon diameter indexdiffusion MRImicrostructuremulti-shell acquisitionwhite matter tractography

Identifiers

PMID28766853
PMCPMC6866984

What OpenQuestion holds

Textmetadata
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.