Determining and visualizing uncertainty in estimates of fiber orientation from diffusion tensor MRI

Area of Science:

• Neuroimaging
• Biomedical Engineering
• Medical Physics

Background:

• Diffusion tensor MRI (DT-MRI) is crucial for determining tissue structure orientation.
• Current methods approximate white matter fasciculi orientation using diffusion tensor eigenvectors.
• Quantifying in vivo uncertainty in eigenvector estimation for DT-MRI tractography remains a challenge.

Purpose of the Study:

• To develop and present a method for quantifying confidence intervals in fiber orientation from in vivo DT-MRI data.
• To introduce the concept of 'cone of uncertainty' mapping for simultaneous visualization of orientation and its uncertainty.
• To investigate the relationship between orientation uncertainty and tissue anisotropy in white matter.

Main Methods:

• Employed the bootstrap method to determine confidence intervals for fiber orientation estimates.
• Utilized DT-MRI data for in vivo analysis.
• Constructed 'cone of uncertainty' maps to represent orientation variability.

Main Results:

• Successfully determined confidence intervals for fiber orientation in DT-MRI data.
• Developed 'cone of uncertainty' maps enabling simultaneous visualization of orientation and uncertainty.
• Provided a framework to examine the correlation between orientation uncertainty and tissue anisotropy.

Conclusions:

• The proposed bootstrap method effectively quantifies in vivo fiber orientation uncertainty in DT-MRI.
• The 'cone of uncertainty' maps offer a valuable tool for enhanced white matter tractography and analysis.
• This approach advances the understanding of DT-MRI data reliability and its relationship with tissue properties.