Automatic whole brain tract-based analysis using predefined tracts in a diffusion spectrum imaging template and an...

Area of Science:

• Neuroimaging
• Diffusion MRI analysis
• White matter tractography

Background:

• Automated analysis of cerebral white matter tracts is crucial for understanding neurological conditions.
• Existing template-based methods struggle with comprehensive tract atlases and accurate registration.

Purpose of the Study:

• To develop and validate a novel tract-based automatic analysis (TBAA) method for diffusion MRI.
• To enhance the accuracy and reduce variability in white matter tract integrity assessment.

Main Methods:

• Developed TBAA using a comprehensive atlas of 76 white matter tracts reconstructed from diffusion spectrum imaging (DSI) data.
• Implemented an advanced two-step registration strategy combining T1-weighted and diffusion-weighted imaging data.
• Transformed tract coordinates from a DSI template to individual subject datasets for stepwise microstructural property sampling.

Main Results:

• TBAA demonstrated high geometric agreement with manual tract segmentation and significantly lower measurement variability.
• The method successfully identified altered white matter microstructural properties in patients with schizophrenia.
• Fifteen major tract bundles showed significant differences in patients, even after controlling for the family-wise error rate.

Conclusions:

• The proposed TBAA method offers a robust and accurate approach for automated white matter tract analysis.
• TBAA is particularly suitable for large-scale cohort studies investigating brain-wise white matter integrity.
• This method has the potential to advance the understanding of neurological disorders affecting white matter.