Multiecho complex total field inversion method (mcTFI) for improved signal modeling in quantitative susceptibility mapping

Abstract

Purpose: Typical quantitative susceptibility mapping (QSM) reconstruction steps consist of first estimating the magnetization field from the gradient-echo images, and then reconstructing the susceptibility map from the estimated field. The errors from the field-estimation steps may propagate into the final QSM map, and the noise in the estimated field map may no longer be zero-mean Gaussian noise, thus, causing streaking artifacts in the resulting QSM. A multiecho complex total field inversion (mcTFI) method was developed to compute the susceptibility map directly from the multiecho gradient echo images using an improved signal model that retains the Gaussian noise property in the complex domain. It showed improvements in QSM reconstruction over the conventional field-to-source inversion. Methods: The proposed mcTFI method was compared with the nonlinear total field inversion (nTFI) method in a numerical brain with hemorrhage and calcification, the numerical brains provided by the QSM Challenge 2.0, 18 brains with intracerebral hemorrhage scanned at 3T, and 6 healthy brains scanned at 7T. Results: Compared with nTFI, the proposed mcTFI showed more accurate QSM reconstruction around the lesions in the numerical simulations. The mcTFI reconstructed QSM also showed the best image quality with the least artifacts in the brains with intracerebral hemorrhage scanned at 3T and healthy brains scanned at 7T. Conclusion:The proposed multiecho complex total field inversion improved QSM reconstruction over traditional field-to-source inversion through better signal modeling. K E Y W O R D Sbrain imaging, nonlinear total field inversion, quantitative susceptibility mapping

Preconditioned water‐fat total field inversion: Application to spine quantitative susceptibility mapping

“…A previous method ,called mcTFI, which directly estimates susceptibility from multi-echo data in the brain could reduce streaking artifacts, while the depiction of strong susceptibility sources was improved without the need for the MERIT method. 34 The proposed wfTFI shows the same reduction in streaking artifacts as shown in Figure 3 close to the air in the bowel and in all depicted spine regions in the F I G U R E 8 Results of water-fat imaging (first row), clinical T1w TSE, T2w IP, T2w water, CT, and QSM (second row) results in a male patient diagnosed with prostate cancer and mainly osteoblastic bone metastases along the displayed thoracolumbar spine. The osteoblastic components in the vertebrae T12-L5 according to CT show T1-and T2-hypointense correlates that are in good agreement with the results of the wfTFI QSM method cerebrospinal fluid region.…”

“…However, this method can lead to an artifactual distortion of regions with strong susceptibility sources 34 and the method itself requires appropriate optimization. A previous method ,called mcTFI, which directly estimates susceptibility from multi‐echo data in the brain could reduce streaking artifacts, while the depiction of strong susceptibility sources was improved without the need for the MERIT method 34 . The proposed wfTFI shows the same reduction in streaking artifacts as shown in Figure 3 close to the air in the bowel and in all depicted spine regions in the cerebrospinal fluid region.…”

“…To further reduce streaking artifacts, the use of MERIT was proposed to alleviate remaining artifacts 31 . However, this method can lead to an artifactual distortion of regions with strong susceptibility sources 34 and the method itself requires appropriate optimization. A previous method ,called mcTFI, which directly estimates susceptibility from multi‐echo data in the brain could reduce streaking artifacts, while the depiction of strong susceptibility sources was improved without the need for the MERIT method 34 .…”

“…Voxels with high model mismatch are weighted down to reduce the influence of outliers in otherwise normally distributed data. However, MERIT can be subject to heuristic optimization and it can deteriorate the depiction of strong susceptibility sources 34 …”

“…However, MERIT can be subject to heuristic optimization and it can deteriorate the depiction of strong susceptibility sources. 34 A recently proposed TFI method that directly estimates the susceptibility map from complex multi-echo gradient echo data (mcTFI) 34 combines the advantages of a nonlinear QSM model and a total field inversion method by reducing noise amplification and BFR artifacts. Additionally, mcTFI is able to reduce streaking artifacts without the use of the MERIT method.…”