An interactive meta-analysis of MRI biomarkers of myelin

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.

Myelin development in cerebral gray and white matter during adolescence and late childhood

“…To date, a number of quantitative or semi-quantitative MRI methods have been proposed to characterize brain myelination. Detailed overviews of these techniques can be found in recent reviews ( Heath et al, 2018 ; Piredda et al, 2020 ; Mancini et al, 2020 ). However, only a few approaches based on the MT saturation index ( Helms et al, 2008 ), T1/T2 signal ratio ( Glasser and Van Essen, 2011 ), and 3D myelin water fraction ( Deoni et al, 2008 ) mapping appeared capable of producing whole-brain coverage, reasonable spatial resolution, and sufficient sensitivity to myelin to identify subtle regional distinction in myelination of cortical GM.…”

“…The technical demands for cortical myelin mapping include sufficiently high spatial resolution (typically < 1.3 mm 3 isotropic voxel size), high signal-to-noise ratio enabling reliable performance of brain segmentation and registration algorithms ( Fischl et al, 2002 ; Avants et al, 2011 ), and a reasonable scan time allowing serial studies in large cohorts of participants. At the current state of development, MPF mapping using the single-point method with synthetic reference normalization ( Yarnykh, 2012 ) fully meets the above technical requirements and provides additional advantages of high specificity to myelin ( Mancini et al, 2020 ), quantitative myelin content measurements ( Underhill et al, 2011 ), and high reproducibility ( Yarnykh et al, 2020 ). Our results demonstrate that high-resolution MPF maps enable generation of high-quality templates with excellent delineation of fine neuroanatomical structures ( Fig.…”

Investigating the relationship between multi-scale perfusion and white matter microstructural integrity in patients with relapsing-remitting MS

“…Given this, future work will focus on comparing SAGE perfusion estimates to more specific myelin measures (e.g., magnetization transfer, myelin water imaging). 30 Additionally, SAGE-DSC as implemented here does not have full brain coverage due to the inclusion of the SE; future studies will implement simultaneous multi-slice approaches to ensure whole brain SAGE-DSC coverage. Additionally, cortical lesions can go undetected due to their small size, which may affect the true perfusion values in our data.…”

Charting human subcortical maturation across the adult lifespan within vivo7 T MRI

“…While iron accumulation and myelin degradation are part of normal aging processes, increased accumulation and myelin degradation are part of multiple neurodegenerative disorders including Parkinson's and Huntington's disease (Andersen, Johnsen, & Moos, 2014;Collingwood & Davidson, 2014;Ward et al, 2014;Zecca et al, 2004). An accurate description of the distributions of iron and myelin across the lifespan in health provides a frame of reference against which pathological iron accumulation and myelin degradation can be contrasted, and can prove useful in the development of biomarkers for disease (Guan, Xu, & Zhang, 2017;Mancini et al, 2020;Martin, Wieler, & Gee, 2008;Schenck & Zimmerman, 2004;Zecca et al, 2004). (Keuken et al, 2014;Lau et al, 2020;Pauli, Nili, & Tyszka, 2018;Trutti et al, 2021;Ye et al, 2021) due to improvements in MRI resolution and contrasts.…”

“…Iron deposition (Daugherty & Raz, 2013;Hallgren & Sourander, 1958;Raz & Rodrigue, 2006;Ward, Zucca, Duyn, Crichton, & Zecca, 2014;Zecca et al, 2004) and decreased myelination (Raz & Rodrigue, 2006;Shen et al, 2008) are part of normal aging processes, but excessive iron accumulation and myelin degradation are prominent in diseases including Parkinson's and Alzheimer's disease (e.g. Mancini et al, 2020;Zecca et al, 2004). A description of normal age-related changes in iron and myelin content can therefore provide a frame of reference to contrast pathological iron accumulation and myelin degradation, and to refine methods for the early detection of pathological alterations using MRI measures as biomarkers.…”