An interactive meta-analysis of MRI biomarkers of myelin

  1. Matteo Mancini  Is a corresponding author
  2. Agah Karakuzu
  3. Julien Cohen-Adad
  4. Mara Cercignani
  5. Thomas E Nichols
  6. Nikola Stikov
  1. University of Sussex, United Kingdom
  2. Polytechnique Montreal, Canada
  3. University of Oxford, United Kingdom

Abstract

Several MRI measures have been proposed as in vivo biomarkers of myelin, each with applications ranging from plasticity to pathology. Despite the availability of these myelin-sensitive modalities, specificity and sensitivity have been a matter of discussion. Debate about which MRI measure is the most suitable for quantifying myelin is still ongoing. In this study, we performed a systematic review of published quantitative validation studies to clarify how different these measures are when compared to the underlying histology. We analysed the results from 43 studies applying meta-analysis tools, controlling for study sample size and using interactive visualization (https://neurolibre.github.io/myelin-meta-analysis). We report the overall estimates and the prediction intervals for the coefficient of determination and find that MT and relaxometry-based measures exhibit the highest correlations with myelin content. We also show which measures are, and which measures are not statistically different regarding their relationship with histology.

Data availability

All the data collected from the selected studies for this meta-analysis are provided in the spreadsheet file Source data 1

Article and author information

Author details

  1. Matteo Mancini

    Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom
    For correspondence
    ingmatteomancini@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7194-4568
  2. Agah Karakuzu

    NeuroPoly Lab, Polytechnique Montreal, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Julien Cohen-Adad

    NeuroPoly Lab, Polytechnique Montreal, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Mara Cercignani

    Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Thomas E Nichols

    University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Nikola Stikov

    NeuroPoly Lab, Polytechnique Montreal, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8480-5230

Funding

Wellcome Trust (213722/Z/18/Z)

  • Matteo Mancini

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Saad Jbabdi, University of Oxford, United Kingdom

Publication history

  1. Received: July 28, 2020
  2. Accepted: October 20, 2020
  3. Accepted Manuscript published: October 21, 2020 (version 1)
  4. Version of Record published: November 6, 2020 (version 2)

Copyright

© 2020, Mancini et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Matteo Mancini
  2. Agah Karakuzu
  3. Julien Cohen-Adad
  4. Mara Cercignani
  5. Thomas E Nichols
  6. Nikola Stikov
(2020)
An interactive meta-analysis of MRI biomarkers of myelin
eLife 9:e61523.
https://doi.org/10.7554/eLife.61523

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