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Myelin quantification with MRI: a systematic review of accuracy and reproducibility


van der Weijden, Chris W J; García, David Vállez; Borra, Ronald J H; Thurner, Patrick; Meilof, Jan F; van Laar, Peter-Jan; Dierckx, Rudi A J O; Gutmann, Ingomar W; de Vries, Erik F J (2020). Myelin quantification with MRI: a systematic review of accuracy and reproducibility. NeuroImage, 226:117561.

Abstract

OBJECTIVES: Currently, multiple sclerosis is treated with anti-inflammatory therapies, but these treatments lack efficacy in progressive disease. New treatment strategies aim to repair myelin damage and efficacy evaluation of such new therapies would benefit from validated myelin imaging techniques. Several MRI methods for quantification of myelin density are available now. This systematic review aims to analyse the performance of these MRI methods.
METHODS: Studies comparing myelin quantification by MRI with histology, the current gold standard, or assessing reproducibility were retrieved from PubMed/MEDLINE and Embase (until December 2019). Included studies assessed both myelin histology and MRI quantitatively. Correlation or variance measurements were extracted from the studies. Non-parametric tests were used to analyse differences in study methodologies.
RESULTS: The search yielded 1348 unique articles. Twenty-two animal studies and 13 human studies correlated myelin MRI with histology. Eighteen clinical studies analysed the reproducibility. Overall bias risk was low or unclear. All MRI methods performed comparably, with a mean correlation between MRI and histology of R$^{2}$=0.54 (SD=0.30) for animal studies, and R$^{2}$=0.54 (SD=0.18) for human studies. Reproducibility for the MRI methods was good (ICC=0.75-0.93, R$^{2}$=0.90-0.98, COV=1.3-27%), except for MTR (ICC=0.05-0.51).
CONCLUSIONS: Overall, MRI-based myelin imaging methods show a fairly good correlation with histology and a good reproducibility. However, the amount of validation data is too limited and the variability in performance between studies is too large to select the optimal MRI method for myelin quantification yet.

Abstract

OBJECTIVES: Currently, multiple sclerosis is treated with anti-inflammatory therapies, but these treatments lack efficacy in progressive disease. New treatment strategies aim to repair myelin damage and efficacy evaluation of such new therapies would benefit from validated myelin imaging techniques. Several MRI methods for quantification of myelin density are available now. This systematic review aims to analyse the performance of these MRI methods.
METHODS: Studies comparing myelin quantification by MRI with histology, the current gold standard, or assessing reproducibility were retrieved from PubMed/MEDLINE and Embase (until December 2019). Included studies assessed both myelin histology and MRI quantitatively. Correlation or variance measurements were extracted from the studies. Non-parametric tests were used to analyse differences in study methodologies.
RESULTS: The search yielded 1348 unique articles. Twenty-two animal studies and 13 human studies correlated myelin MRI with histology. Eighteen clinical studies analysed the reproducibility. Overall bias risk was low or unclear. All MRI methods performed comparably, with a mean correlation between MRI and histology of R$^{2}$=0.54 (SD=0.30) for animal studies, and R$^{2}$=0.54 (SD=0.18) for human studies. Reproducibility for the MRI methods was good (ICC=0.75-0.93, R$^{2}$=0.90-0.98, COV=1.3-27%), except for MTR (ICC=0.05-0.51).
CONCLUSIONS: Overall, MRI-based myelin imaging methods show a fairly good correlation with histology and a good reproducibility. However, the amount of validation data is too limited and the variability in performance between studies is too large to select the optimal MRI method for myelin quantification yet.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Neuroradiology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Neurology
Life Sciences > Cognitive Neuroscience
Language:English
Date:12 November 2020
Deposited On:09 Dec 2020 16:52
Last Modified:24 May 2024 01:44
Publisher:Elsevier
ISSN:1053-8119
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.neuroimage.2020.117561
PubMed ID:33189927
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)