BUAN

BUAN analyzes tractography-derived tractometry data to quantify white matter bundle anatomy and shape, enabling detection of localized group differences and mapping bundle-shape similarity using a bundle adjacency metric.

Key Features:

• Large-scale tractometry: Performs tractometry analyses on tractography datasets to study white matter bundles at scale.
• Tractography and anatomical integration: Integrates tractographic data and anatomical information for bundle-specific analyses.
• Shape-aware analysis: Incorporates the shape of white matter bundles into statistical and comparative analyses.
• Bundle adjacency metric: Computes a novel bundle adjacency metric to compare and quantify shape similarity between bundles.
• Similarity network generation: Generates networks that map similarities in bundle shapes for downstream analysis.
• Automated quality control support: Leverages shape-similarity networks to assist automated quality control in tractometric studies.
• Localized difference detection: Identifies significant group differences at specific locations along white matter bundles.

Scientific Applications:

• Group-difference analysis: Detecting localized group differences in white matter bundles across populations.
• Brain connectivity and tractometry studies: Enabling large-scale investigations of brain connectivity using tractometry.
• Quality control in tractometry: Automating quality control workflows for tractographic and tractometric datasets.
• Clinical research example: Applied to data from the Parkinson's Progression Markers Initiative (PPMI) for Parkinson's disease research.
• Neuroscience research: Supporting investigations of brain structure and function in fundamental neuroscience studies.

Methodology:

Uses tractography and tractometry, integrates tractographic data with anatomical information, incorporates bundle shape, computes a bundle adjacency metric to quantify shape similarity, and generates networks of bundle-shape similarity; has been applied to Parkinson's Progression Markers Initiative data.