Comparative mouse brain tractography of diffusion magnetic resonance imaging

Area of Science:

• Neuroimaging
• Neuroscience
• Biomedical Engineering

Background:

• Diffusion magnetic resonance imaging (dMRI) tractography visualizes white matter tracts.
• Various methods exist for modeling diffusion-weighted data for tractography.

Purpose of the Study:

• To compare deterministic and probabilistic tractography for analyzing white and grey matter pathways in ex vivo mouse brains.
• To assess the impact of different tractography parameters and approaches on neuroimaging results.

Main Methods:

• Applied deterministic and probabilistic tractography algorithms to ex vivo mouse brain data.
• Utilized various regions of interest and seeding strategies.
• Investigated parameter sensitivity including streamline number, step size, and curvature.
• Examined tractography in a mouse model deficient for fibroblast growth factor 17.

Main Results:

• Probabilistic tractography proved more robust than deterministic methods for visualizing both white and grey matter pathways.
• Demonstrated the sensitivity of probabilistic tractography to various parameters and seeding methods.
• Projection maps enabled topographical assessment of corticothalamic pathways.
• Tractography approaches influenced the assessment of tract changes in the FGF17-deficient mouse model.

Conclusions:

• Probabilistic tractography is a powerful tool for visualizing brain pathways.
• This method can quantitatively elucidate phenotypes in mouse models of neurodevelopmental and neurodegenerative disorders.