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Maximum spherical mean value filtering for whole-brain QSM.

Alexandra G Roberts1,2, Dominick J Romano2,3, Mert Şişman1,2

  • 1Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA.

Magnetic Resonance in Medicine
|January 3, 2024
PubMed
Summary

A new maximum spherical mean value (mSMV) algorithm reduces brain QSM shadow artifacts without tissue erosion. This method improves QSM accuracy and image quality in simulations and human studies.

Keywords:
artifactsbackground field removalbrainquantitative susceptibility mappingshadowspherical mean value

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Area of Science:

  • Medical imaging
  • Biophysics
  • Neuroscience

Background:

  • Background field is a primary cause of shadow artifacts in Quantitative Susceptibility Mapping (QSM).
  • Existing QSM algorithms may require brain-tissue erosion to mitigate these artifacts.

Purpose of the Study:

  • To introduce the maximum spherical mean value (mSMV) algorithm for QSM.
  • To reduce shadow artifacts in brain QSM without eroding tissue volume.

Main Methods:

  • Developed the mSMV algorithm to filter large field-magnitude values near the border.
  • Evaluated mSMV effectiveness using numerical brain simulations.
  • Assessed mSMV performance with in vivo human data from healthy volunteers and patients.

Main Results:

  • mSMV effectively reduced shadow artifacts and enhanced QSM accuracy in simulations.
  • Observed improved shadow reduction in healthy subjects and patients with various neurological conditions.
  • Demonstrated lower QSM variation in gray matter and higher image quality scores with mSMV.

Conclusions:

  • The mSMV algorithm provides QSM maps comparable to SMV-filtered dipole inversion.
  • mSMV successfully reduces artifacts without compromising the volume of interest.