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Publication Detail
Test-retest reliability of multi-parametric maps (MPM) of brain microstructure
  • Publication Type:
    Journal article
  • Authors:
    Aye N, Lehmann N, Kaufmann J, Heinze HJ, Düzel E, Taubert M, Ziegler G
  • Publisher:
    Elsevier BV
  • Publication date:
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  • Volume:
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  • Country:
    United States
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  • Keywords:
    HMRI, Multiparameter mapping (MPM), Quantitative MRI, Reproducibility, Scan-rescan reliability
  • Notes:
    Copyright © 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Multiparameter mapping (MPM) is a quantitative MRI protocol that is promising for studying microstructural brain changes in vivo with high specificity. Reliability values are an important prior knowledge for efficient study design and facilitating replicable findings in development, aging and neuroplasticity research. To explore longitudinal reliability of MPM we acquired the protocol in 31 healthy young subjects twice over a rescan interval of 4 weeks. We assessed the within-subject coefficient of variation (WCV), the between-subject coefficient of variation (BCV), and the intraclass correlation coefficient (ICC). Using these metrics, we investigated the reliability of (semi-) quantitative magnetization transfer saturation (MTsat), proton density (PD), transversal relaxation (R2*) and longitudinal relaxation (R1). To increase relevance for explorative studies in development and training-induced plasticity, we assess reliability both on local voxel- as well as ROI-level. Finally, we disentangle contributions and interplay of within- and between-subject variability to ICC and assess the optimal degree of spatial smoothing applied to the data. We reveal evidence that voxelwise ICC reliability of MPMs is moderate to good with median values in cortex (subcortical GM): MT: 0.789 (0.447) PD: 0.553 (0.264) R1: 0.555 (0.369) R2*: 0.624 (0.477). The Gaussian smoothing kernel of 2 to 4 mm FWHM resulted in optimal reproducibility. We discuss these findings in the context of longitudinal intervention studies and the application to research designs in neuroimaging field.
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