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Magnetic Resonance Imaging (MRI) motion artifacts can corrupt structural images. This study generates synthetic structural MRI from diffusion MRI, enabling robust analysis even with corrupted data, crucial for vulnerable populations.

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Area of Science:

  • Neuroimaging
  • Medical Physics

Background:

  • Motion artifacts in Magnetic Resonance Imaging (MRI) frequently compromise the integrity of structural and diffusion MRI analyses.
  • While diffusion imaging can be corrected for motion, structural images (T1w, T2w) are more susceptible, leading to significant data loss in pipelines.
  • Corruption of structural images is a major obstacle for diffusion imaging analysis, particularly in studies involving children or individuals with cognitive impairments.

Purpose of the Study:

  • To develop a method for generating synthetic structural MRI (T1w and T2w) from diffusion MRI data.
  • To enable diffusion-image processing pipelines when structural images are missing or corrupted.
  • To provide a tool that aids in the analysis of neuroimaging datasets affected by common structural image corruption.

Main Methods:

  • The proposed technique integrates multi-tissue constrained spherical deconvolution with the Bloch equations.
  • This approach simulates MRI intensities based on scanner parameters and MR tissue properties, effectively generating synthetic structural images from diffusion MRI.
  • The method was validated on 32 scans across different scanners, protocols, and pathologies.

Main Results:

  • Generated synthetic T1w and T2w images were visually convincing and showed comparable tissue contrast to acquired structural images.
  • The synthetic images were of sufficient quality to drive Freesurfer-based tractographic analysis.
  • Probabilistic tractography results using synthetic versus real structural images showed high similarity (Dice 0.88-0.95) and minimal differences in mean fractional anisotropy (0.00-0.02).

Conclusions:

  • The developed technique successfully generates high-quality synthetic structural MRI from diffusion MRI.
  • This method offers a viable solution for processing neuroimaging data with corrupted structural images, preserving analytical integrity.
  • The availability of executables aims to support the research community in overcoming challenges posed by motion artifacts in MRI studies.