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Test-retest reliability of multi-parametric maps (MPM) of brain microstructure
Norman Aye1, Nico Lehmann2, Jörn Kaufmann3
1Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104 Magdeburg, Germany.
Neuroimage
|April 29, 2022
Summary
Multiparameter mapping (MPM) offers reliable in vivo brain microstructure assessment. This study confirms moderate to good reliability for MPMs, crucial for longitudinal neuroimaging research.
Area of Science:
- Neuroimaging
- Quantitative MRI
Background:
- Multiparameter mapping (MPM) is a quantitative MRI protocol for in vivo brain microstructure analysis.
- Reliability data is essential for designing efficient and replicable studies in development, aging, and neuroplasticity research.
Purpose of the Study:
- To assess the longitudinal reliability of MPM parameters.
- To investigate the impact of spatial smoothing on reliability.
- To inform the design of longitudinal intervention studies.
Main Methods:
- MPM protocol acquired twice in 31 healthy young adults over 4 weeks.
- Assessed within-subject coefficient of variation (WCV), between-subject coefficient of variation (BCV), and intraclass correlation coefficient (ICC).
- Evaluated reliability at voxel and ROI levels for MTsat, PD, R1, and R2*.
Main Results:
- Voxelwise ICC reliability for MPMs was moderate to good (e.g., cortex MT: 0.789).
- Optimal reproducibility was achieved with Gaussian smoothing kernels of 2–4 mm FWHM.
- Within- and between-subject variability contributions to ICC were disentangled.
Conclusions:
- MPM demonstrates good longitudinal reliability, supporting its use in neuroimaging.
- Spatial smoothing optimizes reproducibility, aiding in the analysis of neuroimaging data.
- Findings are relevant for longitudinal studies on development, aging, and neuroplasticity.
