Purpose To implement a statistical framework for assessing the precision of several quantitative MRI metrics sensitive to myelin in the human spinal cord: T1, Magnetization Transfer Ratio (MTR), saturation imposed by an off-resonance pulse (MTsat) and Macromolecular Tissue Volume (MTV). Methods Thirty-three healthy subjects within two age groups (young, elderly) were scanned at 3T. Among them, 16 underwent the protocol twice to assess repeatability. Statistical reliability indexes such as the Minimal Detectable Change (MDC) were compared across metrics quantified within different cervical levels and white matter (WM) sub-regions. The differences between pathways and age groups were quantified and interpreted in context of the test-retest repeatability of the measurements. Results The MDC was respectively 105.7ms, 2.77%, 0.37% and 4.08% for T1, MTR, MTsat and MTV when quantified over all WM, while the standard-deviation across subjects was 70.5ms, 1.34%, 0.20% and 2.44%. Even though particular WM regions did exhibit significant differences, these differences were on the same order as test-retest errors. No significant difference was found between age groups for all metrics. Conclusion While T1-based metrics (T1 and MTV) exhibited better reliability than MT-based measurements (MTR and MTsat), the observed differences between subjects or WM regions were comparable to (and often smaller than) the MDC. This makes it difficult to determine if observed changes are due to variations in myelin content, or simply due to measurement error. Measurement error remains a challenge in spinal cord myelin imaging, but this study provides statistical guidelines to standardize the field and make it possible to conduct large-scale multi-center studies.
Bibliographical noteFunding Information:
This study was funded by the Canada Research Chair in Quantitative Magnetic Resonance Imaging (JCA), the Canadian Institutes of Health Research [CIHR FDN-143263] (JCA), the Canadian Institutes of Health Research [CIHR MOP-130341] (JCA and PR), the Fonds de Recherche du Québec—Santé [FRQS-28826] (JCA), the Fonds de Recherche du Québec—Nature et Technologies [2015-PR-182754] (JCA), the Natural Sciences and Engineering Research Council of Canada [NSERC-435897-2013] (JCA), the Natural Sciences and Engineering Research Council of Canada [NSERC 2016-06774] (NS), the Quebec BioImaging Network (JCA) and the Montreal Heart Institute Foundation (NS). Those funds were used for MRI data acquisition, computer and software resources and authors’ funding. The authors would like to sincerely thank Robert Brown for the helpful discussions.
© 2018 Lévy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.