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.

Several MRI measures have been proposed as in vivo biomarkers of myelin content, each with a concrete application ranging from plasticity to pathology. Despite the broad availability of these myelin-sensitive MRI modalities, specificity and sensitivity have been a matter of discussion. Debate about which MRI measure is the most suitable one for quantifying myelin is still ongoing. In this study, we performed a systematic review of published quantitative validation studies, and used meta-analysis tools to clarify how different these measures are when compared to the underlying histology, controlling for the study sample size and using interactive visualization tools. A first qualitative selection of 58 studies proposed 35 different measures to characterize myelin content. However, a quantitative analysis showed that most of these measures have a limited coefficient of determination and provide little information to inform future studies, because of the large prediction intervals and high heterogeneity. These results indicate that most measures are statistically equivalent regarding their relationship with histology and that future work should take inter-study variability into consideration.

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Magnetic resonance imaging (MRI) has revolutionized the way we look at the human body. However, conventional MR scanners are not measurement devices. They produce digital images represented by "shades of grey", and the intensity of the shades depends on the way the images are acquired. This is why it is difficult to compare images acquired at different clinical sites, limiting the diagnostic, prognostic, and scientific potential of the technology. Quantitative MRI (qMRI) aims to overcome this problem by assigning units to MR images, ensuring that the values represent a measurable quantity that can be reproduced within and across sites. While the vision for quantitative MRI is to overcome site-dependent variations, this is still a challenge due to variability in the hardware and software used by MR vendors to produce quantitative MRI maps.