Test-retest reliability of myelin imaging in the human spinal cord: Measurement errors versus region- and aging-induced variations

Simon Lévy, Marie Claude Guertin, Ali Khatibi, Aviv Mezer, Kristina Martinu, Jen I. Chen, Nikola Stikov, Pierre Rainville, Julien Cohen-Adad

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article numbere0189944
JournalPLoS ONE
Volume13
Issue number1
DOIs
StatePublished - Jan 2018

All Science Journal Classification (ASJC) codes

  • General

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