Longitudinal visualization tools for advanced characterization of multiple sclerosis lesions using diffusion MRI and...

Area of Science:

• Neuroimaging
• White Matter Microstructure
• Brain Network Organization

Background:

• White matter microstructure organization is crucial for functional brain networks.
• Pathological changes, like in multiple sclerosis (MS), disrupt this relationship across scales.
• Analyzing complex, multi-metric imaging data longitudinally presents significant challenges.

Purpose of the Study:

• To introduce novel visualization tools for integrating multi-metric, multi-time point neuroimaging data.
• To enable the investigation of white matter structure-function relationships at multiple scales.
• To characterize microstructural heterogeneity and support hypothesis generation in MS research.

Main Methods:

• Development of five complementary visualization tools.
• Integration of fixel-based multi-tensor, magnetization transfer, and isotropic volume fraction data.
• Preservation of spatial organization of white matter tracts and tissue compartments across longitudinal datasets.

Main Results:

• The framework allows for patient-level network disruption analysis.
• It enables investigation of tract-specific vulnerability and regional variations.
• Descriptive characterization of microstructural heterogeneity in MS patients over five scanning periods was achieved.

Conclusions:

• The visualization framework facilitates exploratory investigation of microstructural heterogeneity at multiple scales.
• It provides research tools for hypothesis generation regarding white matter structure-function relationships in pathology.
• Potential applications exist for understanding tissue-level microstructural changes across patients, bundles, and lesions.