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

Code ↔ Paper

5 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 5 matches · 3 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › DWI data processing ↔ dwi_scripts/script_TH_step01_preproc.sh, lines 50–124 · score 0.84 · bias field correction, FSL, MRtrix, eddy, ANTs, volumes
  2. [2] § Methods › DWI data processing ↔ dwi_scripts/script_TH_step02_preproc_RF.sh, the whole file · a weak match · score 0.80 · bias field correction, Brain masks, MRtrix, ANTs, upsampling, preprocessed
  3. [3] § Methods › MRI data acquisition ↔ dwi_scripts/script_TH_step01_preproc.sh, lines 50–124 · score 0.69 · PA directions, harmonization protocol, AP, volumes, EPI, shell
  4. [4] § Methods › DWI data processing ↔ dwi_scripts/msmt_csd_mtnorm_siteRF.sh, the whole file · a weak match · score 0.62 · MSMT CSD, CSF, RFs, preprocessing, FOD, DWI
  5. [5] § Methods › DWI data processing ↔ dwi_scripts/msmt_csd_mtnorm_globalRF.sh, the whole file · a weak match · score 0.62 · MSMT CSD, CSF, RFs, preprocessing, FOD, DWI

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Shell · 124 lines · 6.7 KB · no license · 2 matches

  1. #!/bin/bash
  3. # Author: Remika Mito
  4. # Date: 9 May 2025
  5. # Description: This script performs the preprocessing steps for Travelling Heads data.
  6. # This script should be run within a slurm script to run in batch all the protocols for a given site.
  7. # Note that this script is updated from the previous version to include additional considerations when running preproc
  9. # load modules
  10. module load MRtrix/3.0.4
  11. module load FSL/6.0.7.12
  12. module load CUDA
  13. module load ANTs/2.4.4
  15. # check arguments are provided
  16. if [ "$#" -ne 3 ]; then
  17. echo "Usage: script_TH_step01_preproc.sh [ID] [SITE] [PROTOCOL]"
  18. exit 1
  19. fi
  21. # example usage
  22. # sbatch script_TH_step01_preproc.sh P01 MBI freedwi
  23. # Note the protocol options are: harmdwi freedwi mddw aepdwi didwi sandi ukb ukb_cmrr ukb_product (use lowercase and this exact usage)
  25. # specify inputs & outputs
  26. ID=$1
  27. SITE=$2
  28. PROTOCOL=$3
  29. OUTDIR=/data/gpfs/projects/punim2175/T-HEADS/mif/${ID}/${SITE}/DWI_${PROTOCOL}
  30. FSLDIR=/apps/easybuild-2022/easybuild/software/Core/FSL/6.0.7.12/
  32. ### Step 1: Run denoising step ###
  33. # Note: denoising should be performed before we concatenate any images & extract relevant b-shells!
  34. # where there is one input ${PROTOCOL}.mif
  35. if [ -f $OUTDIR/${PROTOCOL}.mif ] ; then
  36. dwidenoise $OUTDIR/${PROTOCOL}.mif $OUTDIR/${PROTOCOL}_denoised.mif
  37. # where there are AP and PA sets - denoise individually then concatenate
  38. elif [ -f $OUTDIR/${PROTOCOL}_AP.mif ] && [ -f $OUTDIR/${PROTOCOL}_PA.mif ] && [ ! -f $OUTDIR/${PROTOCOL}.mif ]; then
  39. #mrcat $OUTDIR/${PROTOCOL}_AP.mif $OUTDIR/${PROTOCOL}_PA.mif -axis 3 $OUTDIR/${PROTOCOL}_all.mif
  40. dwidenoise $OUTDIR/${PROTOCOL}_AP.mif $OUTDIR/${PROTOCOL}_AP_denoised.mif
  41. dwidenoise $OUTDIR/${PROTOCOL}_PA.mif $OUTDIR/${PROTOCOL}_PA_denoised.mif
  42. mrcat $OUTDIR/${PROTOCOL}_AP_denoised.mif $OUTDIR/${PROTOCOL}_PA_denoised.mif -axis 3 $OUTDIR/${PROTOCOL}_denoised.mif
  43. # for HCP data
  44. elif [ "$PROTOCOL" == "hcpdwi" ] ; then
  45. dwidenoise $OUTDIR/${PROTOCOL}_99dir_AP.mif $OUTDIR/${PROTOCOL}_AP_denoised.mif
  46. dwidenoise $OUTDIR/${PROTOCOL}_98dir_AP.mif $OUTDIR/${PROTOCOL}_PA_denoised.mif
  47. mrcat $OUTDIR/${PROTOCOL}_AP_denoised.mif $OUTDIR/${PROTOCOL}_PA_denoised.mif -axis 3 $OUTDIR/${PROTOCOL}_denoised.mif
  48. fi
  50. ### Step 2: Run unringing ###
  51. mrdegibbs $OUTDIR/${PROTOCOL}_denoised.mif $OUTDIR/${PROTOCOL}_denoised_unringed.mif -axes 0,1
  53. ### Step 3: Check predwi and make b0_pair ###
  54. # for harmonisation protocol, leading b0s should be extracted - note this should be done on denoised data!
  55. if [ "$PROTOCOL" == "harmdwi" ] || [ "$PROTOCOL" == "aepdwi" ]; then
  56. # Extract b0s for each image (denoised), then concatenate
  57. mrconvert $OUTDIR/${PROTOCOL}_AP_denoised.mif -coord 3 0:1:2 $OUTDIR/${PROTOCOL}_AP_b0.mif
  58. mrconvert $OUTDIR/${PROTOCOL}_PA_denoised.mif -coord 3 0:1:2 $OUTDIR/${PROTOCOL}_PA_b0.mif
  59. mrcat ${OUTDIR}/${PROTOCOL}_AP_b0.mif ${OUTDIR}/${PROTOCOL}_PA_b0.mif $OUTDIR/${PROTOCOL}_b0_pair.mif
  60. # where there are 2 b0s (AP and PA blips)
  61. elif [ -f $OUTDIR/${PROTOCOL}_predwi_AP.mif ] && [ -f $OUTDIR/${PROTOCOL}_predwi_PA.mif ] ; then
  62. # if the blips have more than 1 volume (di and sandi) - note, I don't need to do this!! can use all b0s
  63. if [ ` mrinfo $OUTDIR/${PROTOCOL}_predwi_AP.mif -ndim ` == 4 ] ; then
  64. mrconvert $OUTDIR/${PROTOCOL}_predwi_AP.mif -coord 3 0 $OUTDIR/${PROTOCOL}_predwi_AP_b0.mif
  65. mrconvert $OUTDIR/${PROTOCOL}_predwi_PA.mif -coord 3 0 -axes 0,1,2 $OUTDIR/${PROTOCOL}_predwi_PA_b0.mif
  66. mrcat ${OUTDIR}/${PROTOCOL}_predwi_AP_b0.mif ${OUTDIR}/${PROTOCOL}_predwi_PA_b0.mif ${OUTDIR}/${PROTOCOL}_b0_pair.mif -axis 3
  67. # if the blips are 3D (freedwi, mddw,
  68. elif [ ` mrinfo $OUTDIR/${PROTOCOL}_predwi_AP.mif -ndim ` == 3 ] ; then
  69. mrcat ${OUTDIR}/${PROTOCOL}_predwi_AP.mif ${OUTDIR}/${PROTOCOL}_predwi_PA.mif ${OUTDIR}/${PROTOCOL}_b0_pair.mif -axis 3
  70. fi
  71. # where there is 1 blip (PA only - ukb)
  72. elif [ -f $OUTDIR/${PROTOCOL}_predwi_PA.mif ] && [ ! -f $OUTDIR/${PROTOCOL}_predwi_AP.mif ] ; then
  73. if [ "$PROTOCOL" == "ukb" ] || [ "$PROTOCOL" == "ukb_cmrr" ] || [ "$PROTOCOL" == "ukb_product" ]; then
  74. mrconvert ${OUTDIR}/${PROTOCOL}_predwi_PA.mif -coord 3 0 -axes 0,1,2 $OUTDIR/${PROTOCOL}_PA_b0.mif
  75. mrconvert ${OUTDIR}/${PROTOCOL}.mif -coord 3 0 -axes 0,1,2 ${OUTDIR}/${PROTOCOL}_AP_b0.mif
  76. mrcat ${OUTDIR}/${PROTOCOL}_AP_b0.mif ${OUTDIR}/${PROTOCOL}_PA_b0.mif ${OUTDIR}/${PROTOCOL}_b0_pair.mif -axis 3
  77. else
  78. echo "Check predwi exists for both AP & PA: $PROTOCOL"
  79. exit 1
  80. fi
  81. fi
  83. ### Step 4: Run preproc ###
  84. # For data with b0 pairs (freedwi, mddw, DI, SANDI)
  85. if [ "$PROTOCOL" == "freedwi" ] || [ "$PROTOCOL" == "mddw" ] || [ "$PROTOCOL" == "didwi" ] ; then
  86. echo "Running preprocessing for ${PROTOCOL} with b0 pairs..."
  87. dwifslpreproc ${OUTDIR}/${PROTOCOL}_denoised_unringed.mif $OUTDIR/dwi_denoised_unringed_preproc.mif -rpe_pair -se_epi $OUTDIR/${PROTOCOL}_b0_pair.mif -pe_dir ap -eddyqc_text $OUTDIR/eddylogs
  89. elif [ "$PROTOCOL" == "sandi" ]; then
  90. echo "Running preprocessing for ${PROTOCOL} with b0 pairs..."
  91. dwifslpreproc ${OUTDIR}/${PROTOCOL}_denoised_unringed.mif $OUTDIR/dwi_denoised_unringed_preproc.mif -rpe_pair -se_epi $OUTDIR/${PROTOCOL}_b0_pair.mif -pe_dir ap -eddyqc_text $OUTDIR/eddylogs -eddy_options " --slm=linear" -eddy_options " --data_is_shelled"
  93. # For data with one b0 blip (ukb)
  94. elif [ "$PROTOCOL" == "ukb" ] || [ "$PROTOCOL" == "ukb_cmrr" ] || [ "$PROTOCOL" == "ukb_product" ]; then
  95. echo "Running preprocessing for ${PROTOCOL} with one b0 blip..."
  96. dwifslpreproc ${OUTDIR}/${PROTOCOL}_denoised_unringed.mif $OUTDIR/dwi_denoised_unringed_preproc.mif -rpe_pair -se_epi $OUTDIR/${PROTOCOL}_b0_pair.mif -pe_dir ap -eddyqc_text $OUTDIR/eddylogs
  98. # For data with AP and PA directions (harmonisation & AEP)
  99. elif [ "$PROTOCOL" == "harmdwi" ] || [ "$PROTOCOL" == "aepdwi" ] || [ "$PROTOCOL" == "aepdwi_nii" ]; then
  100. echo "Running preprocessing for ${PROTOCOL} with AP and PA directions..."
  101. dwifslpreproc $OUTDIR/${PROTOCOL}_denoised_unringed.mif $OUTDIR/dwi_denoised_unringed_preproc.mif -rpe_header -eddyqc_text $OUTDIR/eddylogs -se_epi $OUTDIR/${PROTOCOL}_b0_pair.mif
  103. # For data with full AP and PA sets (HCP-lifespan)
  104. elif [ "$PROTOCOL" == "hcpdwi" ]; then
  105. echo "Running preprocessing for ${PROTOCOL} with full AP and PA sets..."
  106. dwifslpreproc $OUTDIR/${PROTOCOL}_denoised_unringed.mif $OUTDIR/dwi_denoised_unringed_preproc.mif -rpe_all -pe_dir ap -eddyqc_text $OUTDIR/eddylogs -se_epi $OUTDIR/${PROTOCOL}_b0_pair.mif
  108. # Else if protocol not working
  109. else
  110. echo "Unsupported protocol: $PROTOCOL"
  111. exit 1
  112. fi
  114. ### Step 5: Run bias field correction ###
  115. if [ -f $OUTDIR/dwi_denoised_unringed_preproc.mif ] ; then
  116. dwibiascorrect ants $OUTDIR/dwi_denoised_unringed_preproc.mif $OUTDIR/dwi_denoised_unringed_preproc_unbiased.mif
  117. elif [ ! -f $OUTDIR/dwi_denoised_unringed_preproc.mif ] ; then
  118. echo "Preprocessed image not found. Skipping bias field correction."
  119. fi
  122. module unload MRtrix/3.0.4
  123. module unload FSL/6.0.7.12
  124. module unload CUDA

script_TH_step01_preproc.sh at commit 0fda3e2, no license · at the source

Overview

Authors: Remika Mito1,2, Sila Genc3,4,5, Jocelyn Halim1, Joseph Yuan-Mou Yang4,5,6, Jacques-Donald Tournier7, Michael Kean3,6,8, Chris Kokkinos9, Richard McIntyre10, Maria A Di Biase1,11, Robert E Smith2,9, Andrew Zalesky1,12
ORCID iDs: Remika Mito, Sila Genc, Jocelyn Halim, Joseph Yuan-Mou Yang, Jacques-Donald Tournier, Maria A Di Biase, Robert E Smith, Andrew Zalesky
  1. Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia
  2. Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
  3. Developmental Imaging, Clinical Sciences, Murdoch Children’s Research Institute, Parkville, VIC, Australia
  4. Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children’s Hospital, Parkville, VIC, Australia
  5. Neuroscience Research, Murdoch Children’s Research Institute, Parkville, VIC, Australia
  6. Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia
  7. Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
  8. Department of Medical Imaging, The Royal Children’s Hospital, Parkville, VIC, Australia
  9. Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia
  10. Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
  11. Department of Anatomy and Physiology, The University of Melbourne, Melbourne, VIC, Australia
  12. Department of Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia
Institutions: The University of Melbourne (Australia); Florey Institute of Neuroscience and Mental Health (Australia); Royal Children's Hospital (Australia); Murdoch Children's Research Institute (Australia); King's College London (United Kingdom); Monash University (Australia)
Journal: Imaging neuroscience (Cambridge, Mass.), volume 4, article IMAG.a.1153
Dates: received 19 August 2025; accepted 4 February 2026; published online 10 March 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1162/imag.a.1153 · PMID 41821830 · PMCID PMC12977090 · OpenAlex W7128537133
Open access: diamond, a free copy (OpenAlex)
Status: code verified
Categories: structural MRI / diffusion (modality), human (organism), methods / tools (subfield)
Methods: Connectivity, Statistics, Smoothing, state filtering, decompositions, fMRI & imaging
Keywords: diffusion MRI, fixel-based analysis, reproducibility, reliability
Topic: Advanced Neuroimaging Techniques and Applications (Radiology, Nuclear Medicine and Imaging, Medicine), according to OpenAlex
Funding: University of Melbourne Establishment Grant; Royal Children’s Hospital Foundation (RCHF 2022-1402); National Institute for Health Research (NIHR); Wellcome/EPSRC Centre for Medical Engineering (WT203148/Z/16/Z); ARC Discovery Early Career Researcher Award; Melbourne Children’s Clinician-Scientist Fellowship; Rebecca L. Cooper Foundation Fellowship; Australian Research Council (DE240101035); Australian Research Council Future Fellowship; Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London; NIHR Clinical Research Facility; National Imaging Facility; The Kids’ Cancer Project (TKCP) Col Reynolds Fellowship
Citations: cited by 2 papers (Europe PMC); 89 references in the paper

Abstract

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 (TRavelling Across Melbourne for FIXel-based analysis): a multisite dataset of traveling participants (n = 10 healthy adults) scanned across four 3T MRI scanners using a harmonised multi-shell diffusion-weighted imaging (DWI) protocol. DWI data were processed using two pipelines that can be adopted when performing multi-site FBA studies (site-specific vs. pooled processing). We extracted fixel-based measures of fibre density (FD), fibre cross-section (FC), and fibre density and cross-section (FDC) from the harmonized 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 harmonization 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 harmonization of fixel-based analysis measures.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above, with 5 matches between paragraphs and lines of code.

remikamito/TRAMFIX

License: none: the authors keep all their rights
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 0fda3e2734bb5582dd0127f357b095144adc1bd4, 20 January 2026
Languages: Shell (5), Jupyter (3)
Size: 76 files, 8 scripts
Software Heritage: not archived
Found in: “Data and Code Availability”
Holds: README, 3 notebooks
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: MRtrix3 (5 files), Matplotlib (3 files), pandas (3 files), seaborn (3 files), ANTs (2 files), FSL (2 files), NumPy (2 files), Pingouin (2 files), statsmodels (2 files), SciPy (1 file)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
9 files
At the source: github.com/remikamito/TRAMFIX

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 8 scripts, each with its path and the digest of its content;
  • 5 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data and Code Availability

The TRAMFIX dataset is available to the community as a resource. Data have been uploaded to OpenNeuro (https://openneuro.org/datasets/ds006935). The code used to process DWI data, and to perform statistical analyses is available on GitHub (https://github.com/remikamito/TRAMFIX).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 11 authors, 4 keywords, 13 funders, 85 references.

Cite

This paper

Mito, R., Genc, S., Halim, J., Yang, J. Y.-M., Tournier, J.-D., Kean, M., Kokkinos, C., McIntyre, R., Di Biase, M. A., Smith, R. E., & Zalesky, A. (2026). TRAMFIX: TRavelling Across Melbourne for FIXel-based analysis (a reproducibility and reliability study). Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1153. https://doi.org/10.1162/imag.a.1153

BibTeX

@article{mito2026tramfix,
author = {Mito, Remika and Genc, Sila and Halim, Jocelyn and Yang, Joseph Yuan-Mou and Tournier, Jacques-Donald and Kean, Michael and Kokkinos, Chris and McIntyre, Richard and Di Biase, Maria A and Smith, Robert E and Zalesky, Andrew},
title = {{TRAMFIX: TRavelling Across Melbourne for FIXel-based analysis (a reproducibility and reliability study)}},
journal = {Imaging neuroscience (Cambridge, Mass.)},
year = {2026},
month = mar,
volume = {4},
pages = {IMAG.a.1153},
publisher = {MIT Press},
issn = {2837-6056},
doi = {10.1162/imag.a.1153},
url = {https://doi.org/10.1162/imag.a.1153},
pmid = {41821830},
pmcid = {PMC12977090}
}

RIS

TY - JOUR
AU - Mito, Remika
AU - Genc, Sila
AU - Halim, Jocelyn
AU - Yang, Joseph Yuan-Mou
AU - Tournier, Jacques-Donald
AU - Kean, Michael
AU - Kokkinos, Chris
AU - McIntyre, Richard
AU - Di Biase, Maria A
AU - Smith, Robert E
AU - Zalesky, Andrew
TI - TRAMFIX: TRavelling Across Melbourne for FIXel-based analysis (a reproducibility and reliability study)
T2 - Imaging neuroscience (Cambridge, Mass.)
J2 - Imaging Neurosci (Camb)
PY - 2026
DA - 2026/03/10
VL - 4
SP - IMAG.a.1153
SN - 2837-6056
PB - MIT Press
DO - 10.1162/imag.a.1153
UR - https://doi.org/10.1162/imag.a.1153
LA - en
ER -

CSL-JSON

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