Work

A software ecosystem for brain tractometry processing, analysis, and insight

Year: 2025

Type: article

Abstract: 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.

Source: PLoS Computational Biology

DOI: 10.1371/journal.pcbi.1013323

Authors: John Kruper, Adam Richie-Halford, Joanna Qiao, Asa Gilmore, Kelly Chang, Mareike Grotheer, Ethan Roy, Sendy Caffarra, Teresa Gomez, Sam Chou, Matthew Cieslak, Serge Koudoro, Eleftherios Garyfallidis, Theodore D. Satterthwaite, Jason D. Yeatman, Ariel Rokem

Institutions: University of Washington, Stanford Medicine, Stanford University, Philipps University of Marburg, Justus-Liebig-Universität Gießen, University of Modena and Reggio Emilia, University of Pennsylvania, Indiana University Bloomington, Indiana University

Language: English

Topic: Advanced Neuroimaging Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: gold

Estimated APC paid: $3,043

Funders: National Science Foundation, Alfred P. Sloan Foundation, Gordon and Betty Moore Foundation, Chan Zuckerberg Initiative, Bundesministerium für Forschung und Technologie, National Institute of Mental Health, National Eye Institute, National Institute of Biomedical Imaging and Bioengineering, National Science Foundation Graduate Research Fellowship Program

Awards: G1136693386, G1148347952, G1318417280, A data science toolbox for analysis of Human Connectome Project diffusion MRI, G3415959687, G3933175036, HDR: I-DIRSE-FW: Accelerating the Engineering Design and Manufacturing Life-Cycle with Data Science, G6955144958, G8297988257, CRCNS: A computational approach to map visual cortex organization in the human brain, Community-supported open-source software for computational neuroanatomy

OpenAlex ID: W4413138599

FWCI: 5.82

Cites: 123

Cited by: 11

Related to: 10