An improved asymmetric susceptibility tensor imaging model with frequency offset correction

Abstract

Purpose To improve susceptibility tensor imaging (STI) reconstruction using the asymmetric STI model with the correction of non‐bulk‐magnetic‐susceptibility (NBMS) effects. Method A frequency offset term was introduced into the asymmetric STI model to account for the bias between measured MRI frequency signals and conventional susceptibility tensor models because of NBMS contributions. Experiments were conducted to compare the proposed model with conventional STI, conventional STI with the proposed frequency offset correction, and asymmetric STI on simulation, ex vivo mouse brain, and in vivo human brain data. Results In the simulation where NBMS contributions are head rotation‐invariant, the proposed method achieves the lowest errors in mean magnetic susceptibility (MMS) and magnetic susceptibility anisotropy (MSA) and is more robust to noise in the estimation of principal eigenvector (PEV). When considering the head orientation dependency of NBMS contributions, the proposed method shows advantages in estimating MSA and PEV. On the mouse and human brain data, the proposed method produces more reliable MSA maps and more consistent white matter fiber directions when referring to those from DTI than the compared STI methods. Conclusion The proposed method can reduce the effects of NBMS‐related frequency shifts on the susceptibility tensors in the brain white matter. This study inspires STI reconstruction from the perspective of better modeling the sources of frequency shifts.

Incorporating the effect of white matter microstructure in the estimation of magnetic susceptibility in ex vivo mouse brain

“…Our simulations reveal that a predominant source of anisotropy in the STI tensor arises instead from the mesoscopic frequency from WM microstructure with only scalar susceptibility, that is, microstructural anisotropy. In fact, the apparent anisotropy was the same order of magnitude as the mean susceptibility, and in line with experimental findings for STI 16,27,28 . We also compared our maps to known STI tractography studies, 16,27,28 and found results strikingly similar to previous studies, including their characteristic deviation from standard DTI tractography.…”

“…STI represents a natural extension of QSM to include macroscopic tensor anisotropy while still neglecting mesoscopic frequency shifts. Numerous studies have applied the STI model as a demonstration of WM susceptibility anisotropy 16,27,28 . However, microstructurally related frequency shifts in WM produce a large bias in STI 20 .…”

“…Numerous studies have applied the STI model as a demonstration of WM susceptibility anisotropy. 16,27,28 However, microstructurally related frequency shifts in WM produce a large bias in STI. 20 This was corroborated in a recent work 28 incorporating orientation dependent WM frequency offsets in STI fitting, resulting in a large decrease in susceptibility anisotropy on human brain.…”

“…16,27,28 However, microstructurally related frequency shifts in WM produce a large bias in STI. 20 This was corroborated in a recent work 28 incorporating orientation dependent WM frequency offsets in STI fitting, resulting in a large decrease in susceptibility anisotropy on human brain. However, the susceptibility and fODF dependence in these local frequency offsets, which was demonstrated here (Figure 4) and in previous work, 21 was not included.…”

“…We further simulate the frequency shift acquired at multiple sample directions, where frequency shifts from WM susceptibility anisotropy are turned on or off. By applying STI, 16,27,28 we investigate the fitted tensor susceptibility originating exclusively from unaccounted mesoscopic frequency shifts from the WM microstructure with only scalar susceptibility. This reveals a major bias in the apparent susceptibility tensor from microscopic structural anisotropy, which turns out to be much greater than the effect from actual susceptibility anisotropy (microscopic and macroscopic).…”