Evidence map›Paper›PMID 31877372›Full record

ArticleNeuroImage2020

Tractography in the presence of multiple sclerosis lesions.

Ilona Lipp, Greg D Parker, Emma C Tallantyre, Alex Goodall, Steluta Grama, Eleonora Patitucci, Phoebe Heveron, Valentina Tomassini, Derek K Jones

Open access · hybridAbstract read
In one paragraph

Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
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

27 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Article
  3. Modeling a Shared Reality of Tractography through Varied Structural Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Tractometry of Human Visual White Matter Pathways in Health and Disease.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Graph theoretical approach to brain remodeling in multiple sclerosis.Network neuroscience (Cambridge, Mass.) · 2023
    Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. Review
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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

9 authors at 3 institutions in 4 countries.

Ilona LippDivision of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, UK; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. Electronic address: lippi@cbs.mpg.de.
Greg D ParkerCardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, UK; Experimental MRI Centre (EMRIC), Cardiff University School of Biosciences, Cardiff, UK.
Emma C TallantyreDivision of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK; Helen Durham Centre for Neuroinflammation, University Hospital of Wales, Cardiff, UK.
Alex GoodallCardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, UK; Department of Medical Physics, Leeds Teaching Hospitals NHS Trust, Leeds, UK; Department of Medical Imaging and Medical Physics, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield UK.
Steluta GramaCardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, UK.
Eleonora PatitucciCardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, UK.
Phoebe HeveronDivision of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK.
Valentina TomassiniDivision of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, UK; Helen Durham Centre for Neuroinflammation, University Hospital of Wales, Cardiff, UK; Institute for Advanced Biomedical Technologies (ITAB), University of Chieti-Pescara, Chieti, Italy.
Derek K JonesCardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, UK; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
Cardiff University · GBAustralian Catholic University · AUSheffield Teaching Hospitals NHS Foundation Trust · GB

Funding

Wellcome Trust 096646Wellcome Trust 096646/Z/11/ZWellcome Trust 104943Wellcome Trust 104943/Z/14/Z
6 · The paper itself

Abstract

Accurate anatomical localisation of specific white matter tracts and the quantification of their tract-specific microstructural damage in conditions such as multiple sclerosis (MS) can contribute to a better understanding of symptomatology, disease evolution and intervention effects. Diffusion MRI-based tractography is being used increasingly to segment white matter tracts as regions-of-interest for subsequent quantitative analysis. Since MS lesions can interrupt the tractography algorithm's tract reconstruction, clinical studies frequently resort to atlas-based approaches, which are convenient but ignorant to individual variability in tract size and shape. Here, we revisit the problem of individual tractography in MS, comparing tractography algorithms using: (i) The diffusion tensor framework; (ii) constrained spherical deconvolution (CSD); and (iii) damped Richardson-Lucy (dRL) deconvolution. Firstly, using simulated and in vivo data from 29 MS patients and 19 healthy controls, we show that the three tracking algorithms respond differentially to MS pathology. While the tensor-based approach is unable to deal with crossing fibres, CSD produces spurious streamlines, in particular in tissue with high fibre loss and low diffusion anisotropy. With dRL, streamlines are increasingly interrupted in pathological tissue. Secondly, we demonstrate that despite the effects of lesions on the fibre orientation reconstruction algorithms, fibre tracking algorithms are still able to segment tracts that pass through areas with a high prevalence of lesions. Combining dRL-based tractography with an automated tract segmentation tool on data from 131 MS patients, the cortico-spinal tracts and arcuate fasciculi could be reconstructed in more than 90% of individuals. Comparing tract-specific microstructural parameters (fractional anisotropy, radial diffusivity and magnetisation transfer ratio) in individually segmented tracts to those from a tract probability map, we show that there is no systematic disease-related bias in the individually reconstructed tracts, suggesting that lesions and otherwise damaged parts are not systematically omitted during tractography. Thirdly, we demonstrate modest anatomical correspondence between the individual and tract probability-based approach, with a spatial overlap between 35 and 55%. Correlations between tract-averaged microstructural parameters in individually segmented tracts and the probability-map approach ranged between r=.53 (p<.001) for radial diffusivity in the right cortico-spinal tract and r=.97 (p<.001) for magnetisation transfer ratio in the arcuate fasciculi. Our results show that MS white matter lesions impact fibre orientation reconstructions but this does not appear to hinder the ability to anatomically reconstruct white matter tracts in MS. Individual tract segmentation in MS is feasible on a large scale and could prove a powerful tool for investigating diagnostic and prognostic markers.

Indexed as

AdultComputer SimulationDiffusion Tensor ImagingFemaleHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedMaleMiddle AgedMultiple SclerosisWhite MatterBrain MRIDiffusion tensor imagingMultiple sclerosis lesionsSpherical harmonic deconvolutionTractography

Identifiers

PMID31877372
PMCPMC7613131
OpenAlexW2997387327

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.