Removal of evidential motion-contaminated and poorly fitted image data improves IVIM diffusion MRI parameter

Olivier Chevallier1,2, Nan Zhou3, Jian He3

  • 11 Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, New Territories, Hong Kong SAR.

Insights

Improving intravoxel incoherent motion (IVIM) diffusion MRI reproducibility in liver parenchyma is crucial. Removing motion-contaminated or poorly fitted data significantly enhances IVIM parameter scan-rescan consistency.

Area of Science:

  • Medical Imaging
  • Radiology
  • Biophysics

Background:

  • Intravoxel incoherent motion (IVIM) diffusion MRI is valuable for liver parenchyma assessment.
  • Previous studies reported unsatisfactory scan-rescan reproducibility of IVIM parameters.
  • Data quality, including motion and fitting artifacts, is a potential source of variability.

Purpose of the Study:

  • To evaluate the reproducibility of IVIM MRI parameters in the liver parenchyma.
  • To assess the impact of excluding motion-contaminated and poorly fitted data on IVIM parameter reproducibility.
  • To determine the repeatability and reproducibility of key IVIM metrics.

Main Methods:

  • Eighteen healthy volunteers underwent repeated liver diffusion-weighted MRI scans at 3 Tesla.
  • Respiratory-triggered echo-planar imaging with 16 b-values (0-800 s/mm²) was used.
  • Image data were rigorously screened for artifacts and poor signal-to-noise ratio curves; segment-unconstrained least square fitting was applied.

Main Results:

  • A high success rate (89%) was achieved after excluding inadequate datasets, with 14 volunteers included.
  • Excellent repeatability for slow diffusion coefficient (Dslow) (CV 2.86%) and perfusion fraction (PF) (CV 3.81%).
  • Improved reproducibility for Dslow (CV 2.48%) and PF (CV 4.91%) after data curation, while Dfast remained less reproducible.

Conclusions:

  • Exclusion of motion-contaminated and poorly fitted image data significantly improves IVIM parameter reproducibility in liver parenchyma.
  • This data curation strategy enhances the reliability of IVIM MRI for clinical applications.
  • Further optimization may be needed for fast diffusion (Dfast) parameter estimation.

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