Analysis of different phase unwrapping methods to optimize quantitative susceptibility mapping in the abdomen

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

χ

, with the magnetic field of a unit dipole,

d

d (r) = \frac{1}{4 π} \frac{3 \cos^{2} θ ‐ 1}{{|r^{'} ‐ r|}^{3}}

where

r

is the location of observation,

r^{'}

is the location of the source, and

θ

is the angle between

r^{'} ‐ r

and

B_{0}

.…”

Section: Methodsmentioning

confidence: 99%

“…61 The magnetization field may contain phase wraps, necessitating the use of phase-unwrapping methods. 62 The magnetization field is modeled as the convolution of a susceptibility distribution, , with the magnetic field of a unit dipole, d:…”

Section: Theorymentioning

confidence: 99%

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

Yan

Spincemaille

Nguyen

et al. 2021

“…An accurate and inherently non‐wrapped field‐map is particularly important for quantitative susceptibility mapping. Field‐map errors and wraps are expected to translate in strong susceptibility artifacts 16 . Since QSM is based on the field‐map estimate, errors in the field‐map estimation propagate into the susceptibility maps as demonstrated in Figures 4 and 5.…”

Section: Discussionmentioning

confidence: 99%

“…Field-map errors and wraps are expected to translate in strong susceptibility artifacts. 16 Since QSM is based on the field-map estimate, errors in the field-map estimation propagate into the susceptibility maps as demonstrated in Figures 4 and 5. Using the proposed method, an erroneous algorithmic step in the QSM processing pipeline can be circumvented.…”

Section: F I G U R Ementioning

confidence: 99%

“…The first QSM step, the magnetic field‐mapping, therefore connects QSM to the sub‐domain of chemical shift encoding‐based water–fat separation, which also can be reformulated as a field‐map estimation problem 5,11,15 . Field‐mapping in the body can be challenging for mainly two reasons: (a) the presence of large background fields possibly due to concave geometry of the anatomy or air inclusions in the field of view (FOV), 16 and (b) the presence of signal voids in regions of low signal‐to‐noise ratio (SNR) due to MR invisible or short‐

T_{2}

tissues, for example, bone 17 . Field‐mapping in water–fat regions relies on optimizing a least‐squares optimization problem due to the nonlinearity of the field‐map term 5,18,19 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping

Boehm

Diefenbach

Makowski

et al. 2020

Quantitative mapping of renal oxygen consumption using pseudo‐continuous arterial spin labeling and quantitative susceptibility mapping in humans

Jung,

Ahn,

Park

2024

PurposeTo propose a new method for quantitatively mapping the renal metabolic rate of oxygen (RMRO2) and to evaluate the proposed method using a caffeine challenge.Theory and MethodsPseudo‐continuous arterial spin labeling (pCASL) and QSM sequences were used to obtain MR images in the kidney. Six healthy volunteers were scanned on caffeine and control days. The pCASL and QSM images were registered using DICOM information and rigid translation. The Fick principle was applied to estimate RMRO2. The results on caffeine and control days were compared to evaluate the capability of the proposed method to estimate renal oxygen consumption. A paired t‐test was used to assess the statistical significance.ResultsEstimated renal blood flow (RBF), QSM, and RMRO2 maps were consistent with those reported in the literature. RMRO2 values were higher than the cerebral metabolic rate of oxygen (CMRO2) and were significantly reduced on the caffeine days compared to the control days, consistent with findings from non‐MRI literature.ConclusionThe feasibility of measuring renal oxygen consumption using pCASL and QSM images was demonstrated. To the best of our knowledge, this work provides quantitative maps of renal oxygen consumption in humans for the first time. The results were consistent with the literature, including the statistically significant reduction in renal oxygen consumption with caffeine challenge. These findings suggest the potential utility of our technique in measuring renal oxygen consumption noninvasively, especially for patients with complications associated with contrast agents.