A software ecosystem for brain tractometry processing, analysis, and insight
Tractometry uses diffusion-weighted magnetic resonance imaging (dMRI) to assess physical properties of brain connections. Here, we present an integrative ecosystem of software that performs all steps of tractometry: post-processing of dMRI data, delineation of major white matter pathways, and modeling of the tissue properties within them. This ecosystem also provides a set of interoperable and extensible tools for visualization and interpretation of the results that extract insights from these measurements. These include novel machine learning and statistical analysis methods adapted to the characteristic structure of tract-based data. We benchmark the performance of these statistical analysis methods in different datasets and analysis tasks, including hypothesis testing on group differences and predictive analysis of subject age. We also demonstrate that computational advances implemented in the software offer orders of magnitude of acceleration. Taken together, these open-source software tools-freely available at https://tractometry.org-provide a transformative environment for the analysis of dMRI data.
Authors
- Sendy Caffarra (ORCID: https://orcid.org/0000-0003-3667-5061)
- John Kruper (ORCID: https://orcid.org/0000-0003-0081-391X)
- Ariel Rokem (ORCID: https://orcid.org/0000-0003-0679-1985)
- Matthew Cieslak (ORCID: https://orcid.org/0000-0002-1931-4734)
- Jason D. Yeatman (ORCID: https://orcid.org/0000-0002-2686-1293)
- Adam Richie-Halford (ORCID: https://orcid.org/0000-0001-9276-9084)
- Joanna Qiao
- Sam Chou
- Ethan Roy (ORCID: https://orcid.org/0000-0002-4956-2237)
- Teresa García Gómez (ORCID: https://orcid.org/0000-0003-0251-2432)
- Mareike Grotheer (ORCID: https://orcid.org/0000-0002-8653-1157)
- Eleftherios Garyfallidis (ORCID: https://orcid.org/0000-0002-3991-2774)
- Kelly Chang (ORCID: https://orcid.org/0000-0001-5385-2782)
- Serge Koudoro
- Asa Gilmore
- Theodore D Satthertwaite
Institutions
- University of Modena and Reggio Emilia (IT)
- Philipps University of Marburg (DE)
- University of Washington (US)
- Indiana University Bloomington (US)
- Stanford Medicine (US)
- Phillips University (US)
- University of Pennsylvania (US)
- Stanford University (US)
Publication Details
- Journal
- PLoS Computational Biology
- Published
- 2025-08-14
- DOI
- https://doi.org/10.1371/journal.pcbi.1013323
- Citations
- 4
- Primary Topic
- Advanced Neuroimaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- National Science Foundation
- Alfred P. Sloan Foundation
- Gordon and Betty Moore Foundation
- Chan Zuckerberg Initiative