Whole brain fiber-based comparison (FBC)-A tool for diffusion tensor imaging-based cohort studies

Area of Science:

• Neuroimaging
• Diffusion Tensor Imaging (DTI)
• Computational Neuroscience

Background:

• Comparing diffusion tensor imaging (DTI) scans across subject groups is challenging.
• Existing methods may require hypotheses or manual intervention.
• Identifying subtle group differences in white matter tracts is crucial for understanding neurological disorders.

Purpose of the Study:

• To present a novel, hypothesis-free fiber-based method for comparing DTI scans across subject groups.
• To establish spatial correspondence between individual brains using fiber geometry.
• To facilitate exploratory analysis in neurological population studies.

Main Methods:

• Preprocessing and fiber reconstruction using tractography in native space.
• Sampling diffusion parameters along individual fibers.
• Establishing spatial correspondence via fiber geometric similarity to a template set.
• Statistical comparison of diffusion parameters between groups for each template fiber.

Main Results:

• The method successfully identified group differences at single fiber resolution.
• Results were compatible with previous findings and the Tract-Based Spatial Statistics (TBSS) method.
• Demonstrated utility in distinguishing between healthy subjects and amyotrophic lateral sclerosis (ALS) patients.

Conclusions:

• The proposed fiber-based DTI comparison method is effective for exploratory neurological studies.
• It offers an automated, hypothesis-free approach to identify affected brain regions.
• This method advances the analysis of white matter integrity in disease populations.