An improved asymmetric susceptibility tensor imaging model with frequency offset correction. Issue 2 (27th October 2022)

• Record Type: Journal Article
• Authors: Feng, Ruimin; Cao, Steven; Zhuang, Jie; Zhao, Jiayi; Guan, Xiaojun; Zhang, Yuyao; Liu, Chunlei; Wei, Hongjiang
• Is Part Of: Magnetic resonance in medicine. Volume 89:Issue 2(2023)
• Page Start: 828
• Page End: 844
• Publication Date: 2022-10-27
• Subjects: asymmetric susceptibility tensor -- frequency model -- frequency offset correction -- STI; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.29494
• Languages: English
• ISSNs: 0740-3194

Abstract

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.