TRAMFIX: TRavelling Across Melbourne for FIXel-based analysis (a reproducibility and reliability study)

Fixel-based analysis (FBA) has gained substantial interest for its ability to probe fibre-specific changes in the brain’s white matter from diffusion-weighted imaging data. However, the reproducibility and reliability of fixel-based measures across different scanners remains largely unknown. In this work, we present TRAMFIX: a multisite dataset of travelling participants (n=10 healthy adults) scanned across four 3T MRI scanners using a harmonised multi-shell DWI protocol. DWI data were processed using two pipelines that can be adopted when performing multi-site FBA studies (site-specific versus pooled processing). We extracted fixel-based measures of fibre density (FD), fibre cross-section (FC), and fibre density and cross-section (FDC), from the harmonised protocol. While the primary goal was to assess reproducibility and reliability of FBA metrics, we additionally computed diffusion tensor imaging (DTI)-based fractional anisotropy (FA) and mean diffusivity (MD) for the purposes of comparison with previous studies. Within-subject coefficients of variation (CVws) and intraclass correlation coefficients (ICC) of FBA and DTI measures were computed at multiple resolutions of computation and analysis: (i) the whole-brain averaged level, (ii) tract-level, and (iii) fixel- or voxel-level. Fixel-based metrics demonstrated high reproducibility and reliability at the whole-brain level (CVws ranging between 0.51% to 1.57% and ICC between 0.782 and 0.994). While reproducibility and reliability remained high for tract-averaged FBA measures (particularly the FC and FDC metrics), some tracts exhibited lower ICC values < 0.8 for the FD measure. When examining fixel-level reliability and reproducibility clear spatial patterns emerged, with lower ICC across subcortical and cerebellar regions, and higher CVws at the cortical boundaries. FBA metrics demonstrated comparable, if not slightly better, reliability than tensor-based metrics derived from a subset of the same data. Our findings provide support for the reproducibility and reliability of fixel-based measures, highlighting their potential for use in multi-site FBA studies. Future work examining protocol-related differences, as well as appropriate harmonisation strategies when pooling data across sites and scanners, will be valuable. To facilitate this, we provide the TRAMFIX dataset as a resource for investigating reproducibility, reliability, and harmonisation of fixel-based analysis measures.