Diffusion phase-imaging in anisotropic media using non-linear gradients for diffusion encoding.

Area of Science:

• Magnetic Resonance Imaging
• Biophysics
• Medical Physics

Background:

• Classical diffusion MRI uses linear gradients, encoding diffusion information in signal magnitude.
• Spin ensembles in linear gradients result in zero net phase change due to opposing molecular motion.
• This limits the information obtainable from phase in conventional diffusion MRI.

Purpose of the Study:

• To investigate the phase evolution of water molecules in anisotropic media using quadratic gradient fields.
• To explore the potential of quadratic gradients for novel diffusion MRI contrast mechanisms.
• To validate theoretical predictions with experimental diffusion MRI data.

Main Methods:

• Utilized Monte Carlo simulations to model spin dynamics in quadratic gradient fields.
• Conducted diffusion MRI experiments on anisotropic fiber phantoms and isotropic agar phantoms.
• Developed an analytic model to predict phase changes based on anisotropy and diffusion weighting.

Main Results:

• Simulations confirmed phase change dependence on anisotropy and diffusion weighting.
• Experimental results showed time-dependent phase changes in anisotropic phantoms.
• Negligible phase changes were observed in isotropic phantoms, consistent with theoretical predictions.

Conclusions:

• Quadratic gradient fields in diffusion MRI can induce measurable phase changes in anisotropic media.
• This phase information is sensitive to tissue microstructure and diffusion properties.
• The findings suggest a new avenue for diffusion MRI by leveraging phase evolution.