Protocol for diffusion magnetic resonance imaging and tractography in ex vivo mouse models.

Overview

1. Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
2. Idaho College of Osteopathic Medicine, Meridian, Idaho 83642, USA
3. Department of Biological Sciences, Delaware State University, Dover, DE 19901, USA
4. Department of Anatomy, Physiology & Pharmacology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA

Abstract

Diffusion magnetic resonance imaging (dMRI) is a powerful tool to investigate brain structure and connectivity. We present a protocol for quantitative analyses of microstructural properties and white matter pathways via tractography using ex vivo dMRI in mouse models. We describe steps for tissue preparation, postmortem brain scanning, diffusion modeling, and tractography. We detail procedures to track white matter trajectories across development and disease states.

For complete details on the use and execution of this protocol, please refer to Cottam et al.1

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

Code

The paper links to its data, not to its authors' code: see the Data section.

Materials availability

DSI Studio is free for academic users under Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). DSI Studio is available for download at https://dsi-studio.labsolver.org/download.html.

The version used for our protocol is “Chen” 2024, and it is currently at version “Hou” 2025. For a Commercial License, refer to the DSI Studio website for commercial licensing and application.

TrackVis and Diffusion Toolkit are free for users after registration (https://trackvis.org/dtk/).

Bruker materials can be obtained at https://www.bruker.com/en/products-and-solutions/preclinical-imaging/mri.html.

Bruker Biospec 9.4 T MRI information can be found at https://www.bruker.com/en/products-and-solutions/preclinical-imaging/mri/biospec.html.

Bruker Paravision Software information can be found at https://www.bruker.com/en/products-and-solutions/preclinical-imaging/paravision-360.html.

Bruker Coil availability and information can be found at https://www.bruker.com/en/products-and-solutions/preclinical-imaging/mri/mri-rf-coils.html.

Additional information can be found at https://www.bruker.com/en/products-and-solutions/preclinical-imaging/mri/mri-rf-coils/mri-rf-coils-technical-details.html.

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

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

• doi:10.5061/dryad.8pk0p2nzt, at Dryad; found in “Data and code availability”
• doi:10.5061/dryad.9w0vt4bg9, at Dryad; found in “Data and code availability”

Data and code availability

Diffusion MR scans and R scripts are available as Dryad datasets.

Cottam N, Ofori K, Stoll K, Madison B, Rogge J, Hekmatyar K, Sun J, Charvet CJ. (2025). Data from: From circuits to lifespan: Translating mouse and human timelines with neuroimaging based tractography [Dataset]. Dryad. https://doi.org/10.5061/dryad.8pk0p2nzt.

Charvet C (2022). Tracing pathways from high-resolution tractography, transcription, and temporal dimensions [Dataset]. Dryad. https://doi.org/10.5061/dryad.9w0vt4bg9.

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 3 keywords, 3 funders, 30 references.

Cite

This paper

Cottam, N. C., Stoll, K. T., Sun, J., & Charvet, C. J. (2026). Protocol for diffusion magnetic resonance imaging and tractography in ex vivo mouse models. STAR protocols, 7(3), 104667. https://doi.org/10.1016/j.xpro.2026.104667

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