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Area of Science:

  • Magnetic Resonance Imaging
  • Biophysics
  • Neuroimaging

Background:

  • Diffusion MRI is crucial for non-invasively characterizing brain tissue microstructure.
  • Diffusion-weighted steady-state free precession (DW-SSFP) is used for post-mortem MRI due to tissue properties.
  • Current DW-SSFP signal interpretation is limited, hindering its microstructural characterization potential.

Purpose of the Study:

  • To establish new representations for interpreting DW-SSFP signals.
  • To investigate the impact of parameters and gradient waveforms on DW-SSFP diffusion sensitivity.
  • To enable incorporation of biophysical models into DW-SSFP analysis.

Main Methods:

  • Utilized Extended Phase Graphs (EPG) to derive two DW-SSFP signal representations: conventional b-values and encoding power-spectra.
  • Introduced a Gaussian phase approximation for time-dependent diffusion estimation.
  • Validated models using free diffusion and microscopic restriction simulations (cylinders).

Main Results:

  • Developed novel representations for DW-SSFP signal interpretation, distinguishing time-independent and time-dependent diffusion regimes.
  • Demonstrated excellent agreement between proposed models and analytical/simulation methods.
  • Successfully derived Tensor and Neurite Orientation Dispersion and Density Imaging (NODDI) estimates from post-mortem human brain data.

Conclusions:

  • The new DW-SSFP representations enhance understanding of diffusion sensitivity and parameter impact.
  • The approach facilitates integrating biophysical models for more accurate microstructural analysis.
  • DW-SSFP shows significant potential for ultra-high field microstructural imaging, particularly in post-mortem applications.