Diffusion tensor imaging in anisotropic tissues: application of reduced gradient vector schemes in peripheral nerves

Area of Science:

• Medical Imaging
• Neuroimaging
• Diffusion Tensor Imaging

Background:

• Peripheral nerves exhibit a monodirectional structure, unlike the brain, suggesting simpler Diffusion Tensor Imaging (DTI) schemes may suffice.
• This study explores the diagnostic value of reduced gradient vector schemes for peripheral nerve DTI.

Purpose of the Study:

• To investigate the diagnostic utility of reduced gradient vector schemes in peripheral nerve DTI.
• To assess if simplified DTI protocols can achieve diagnostic accuracy comparable to standard DTI.

Main Methods:

• Three-Tesla magnetic resonance neurography of the tibial nerve using 20-vector DTI (DTI20) in healthy volunteers and patients with type 2 diabetes.
• Reduced DTI datasets with two or three vectors were created to calculate key DTI parameters.
• Analysis involved assessing diagnostic accuracy using receiver operating characteristic curves (ROC-AUC) and evaluating the influence of nerve angulation and intraneural connective tissue.

Main Results:

• Simplified DTI datasets achieved excellent diagnostic accuracy (ROC-AUC 0.847-0.868), comparable to the full DTI20.
• Reduced models generally yielded lower absolute DTI scalar values (FA, ADC, axial diffusivity, radial diffusivity).
• Intraneural connective tissue negatively correlated with FA and ADC; nerve angulation had minimal impact on FA accuracy.

Conclusions:

• Peripheral nerve DTI metrics can be accurately approximated using only three predefined gradient vectors.
• This simplified approach offers similar diagnostic performance to standard DTI with substantial scan time reduction.
• The simplified model facilitates the adoption of advanced techniques like multi-b-value DTI in clinical practice.