Maximum Spherical Mean Value (mSMV) Filtering for Whole Brain Quantitative Susceptibility Mapping

Alexandra G Roberts, Dominick Romano, Mert Sisman, Alexey V. Dimov, Pascal Spincemaille, Thanh D. Nguyen, Ilhami Kovanlikaya, Susan Gauthier, Yi Wang

Abstract:

Purpose: To develop a tissue field filtering algorithm, called maximum Spherical Mean Value
(mSMV), for reducing shadow artifacts in quantitative susceptibility mapping (QSM) of the brain
without requiring brain tissue erosion.
Theory and Methods: Residual background field is a major source of shadow artifacts in QSM.
The mSMV algorithm filters large field values near the border, where the maximum value of
the harmonic background field is located. The effectiveness of mSMV for artifact removal was
evaluated by comparing with existing QSM algorithms in numerical brain simulation as well as
using in vivo human data acquired from 11 healthy volunteers and 93 patients.
Results: Numerical simulation showed that mSMV reduces shadow artifacts and improves QSM
accuracy. Better shadow reduction, as demonstrated by lower QSM variation in the gray matter
and higher QSM image quality score, was also observed in healthy subjects and in patients with
hemorrhages, stroke and multiple sclerosis.
Conclusion: The mSMV algorithm allows QSM maps that are substantially equivalent to those
obtained using SMV-filtered dipole inversion without eroding the volume of interest.