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

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  • 1Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia.

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Summary

Fixel-based analysis (FBA) shows high reproducibility and reliability across MRI scanners, supporting its use in multi-site studies. The TRAMFIX dataset aids future research on harmonization strategies for brain white matter analysis.

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diffusion MRIfixel-based analysisreliabilityreproducibility

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Area of Science:

  • Neuroimaging
  • Diffusion MRI
  • White Matter Analysis

Background:

  • Fixel-based analysis (FBA) is a powerful tool for examining white matter microstructure using diffusion-weighted imaging (DWI).
  • Assessing the reproducibility and reliability of FBA metrics across different MRI scanners is crucial for multi-site studies but remains largely unexplored.

Purpose of the Study:

  • To evaluate the reproducibility and reliability of fixel-based measures (fibre density, fibre cross-section, fibre density and cross-section) across multiple 3T MRI scanners.
  • To compare the reliability of FBA metrics with traditional diffusion tensor imaging (DTI) metrics.
  • To introduce the TRAMFIX dataset for future research on multi-site FBA.

Main Methods:

  • A multisite dataset (TRAMFIX) was created with 10 healthy adults scanned on four 3T MRI scanners using a harmonized multi-shell DWI protocol.
  • Fixel-based measures (FD, FC, FDC) and DTI metrics (FA, MD) were extracted using site-specific and pooled processing pipelines.
  • Reproducibility and reliability were assessed using within-subject coefficients of variation (CVws) and intraclass correlation coefficients (ICC) at whole-brain, tract, and fixel/voxel levels.

Main Results:

  • Fixel-based metrics demonstrated high reproducibility (CVws: 0.51%-1.57%) and reliability (ICC: 0.782-0.994) at the whole-brain level.
  • Tract-averaged FBA measures showed high reliability, particularly FC and FDC, though some FD measures had lower ICC (<0.8).
  • Fixel-level analysis revealed spatial patterns of reliability, with lower ICC in subcortical/cerebellar regions and higher CVws at cortical boundaries, comparable or better than DTI metrics.

Conclusions:

  • Fixel-based analysis metrics exhibit robust reproducibility and reliability, making them suitable for multi-site neuroimaging studies.
  • The TRAMFIX dataset provides a valuable resource for investigating scanner and protocol effects on FBA measures.
  • Further research into harmonization strategies is recommended for optimal data pooling across sites and scanners.