We investigated the test-retest reliability of bundle- and voxel-/fixel-level microstructural metrics with fixel-based analysis, neurite orientation dispersion and density imaging, and diffusion tensor imaging. For the bundle-level analyses, TractSeg was used to automatically segment 72 fiber bundles of the brain. Our results indicate that most of the metrics, especially those measured with fixel-based analysis, are highly robust and show excellent test-retest reliability both in local and bundle-level analyses. In general, the reproducibility was higher in the white matter in contrast to gray matter and for acquisitions with multi-shell compared to single-shell data.
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