Synopsis
MR-based Quantitative Susceptibility Mapping (QSM)
techniques have multiple potential applications in brain and body imaging.
QSM techniques generally rely on the removal of
background field effects to obtain a local B0 map, followed by dipole
inversion to estimate the underlying susceptibility distribution.
However, concomitant gradients introduce
significant unanticipated phase shifts in the acquired data that manifest as
errors in the measured B0 field map.
Our results demonstrate that CG phase
corrections and/or the use of a background field removal algorithm that removes
this background field component are necessary for accurate QSM.Purpose
MR-based Quantitative Susceptibility Mapping (QSM)
techniques have multiple potential applications in brain [1] and body imaging [2]. QSM techniques generally rely on the removal
of background field effects to obtain a “local” B
0 map, followed by “dipole
inversion” to estimate the underlying susceptibility distribution. Common background
field removal techniques are based on the assumption that this field is
harmonic inside the region of interest. However,
concomitant gradients (CG) introduce significant unanticipated phase shifts in
the acquired data that manifest as errors in the measured B
0 field map
[3]. It is unknown whether CG-related B
0 errors are harmonic, which
may violate assumptions made by some background field removal techniques. Therefore,
the purpose of this work was to characterize the effects of CGs on QSM by
assessing the ability of background field removal techniques to address
CG-related field map errors.
Theory
Li
and Leigh [4] demonstrated that the field map induced by regions with
homogeneous magnetic susceptibility is a harmonic function (i.e. the Laplacian is
zero $$$\triangledown^2 B(x,y,z,t) = 0$$$).
However, the effects of CG phase errors were not considered in their analysis.
In
the presence of CGs, the net magnetization becomes a non-linear function of the
magnetization, contrary to the assumption of [4]. A full expression for the Laplacian
of the field map with CG terms can be calculated analytically. For simplicity,
here we consider the case with only an x-gradient
$$$\left(G_x(t)\right)$$$ present.
The magnetization becomes $$$B(t)=G_x(t)z\hat{x}+B_0+G_x(t)x\hat{z}$$$,
where the first term is due to CGs. The Laplacian of this expression is
$$\triangledown^2 B(x,y,z,t)=\frac{G_x(t)^2}{\sqrt{\left(B_0+G_x(t)\right)^2+\left(G_x(t)z\right)^2}}.$$
This
is nonzero since we assumed $$$\left(G_x(t)\right)$$$ is non-zero and the integral of a positive
function will always be nonzero. Consequently,
the field map will have a nonzero Laplacian and cannot be a harmonic function. Using simulations (below), we confirmed this conclusion
numerically and tested previously proposed background field removal algorithms
in the presence of CG phase shifts.
Simulations
We conducted two simulations of a pulse sequence
(Fig. 1) with two echoes, TE1=3.38 ms and TE2=22ms, and FOV=35 x 35 x 40 cm (X
x Y x Z cm) on a pure water signal. One simulation was performed with the
effects of CGs and the other without.
Next,
the Laplacian of the measured field map was calculated numerically with and
without the effects of CGs. Finally, three
background field removal techniques were tested in the presence of CGs,
including the Projection onto Dipole Fields (PDF) [5,6], Sophisticated Harmonic
Artifact Reduction for Phase data [1], and Regularization Enabled SHARP (RESHARP)
[7]. Since the simulated field map does not include inhomogeneities (e.g. magnet
imperfections, shims, or susceptibility sources) the estimated background field
map should be 0 Hz.
Results
CGs
create a large error in the field map (Fig. 2). This error is quadratic in nature and in
this case is largest along the z-direction [3].
The Laplacian
of the estimated field map, using data without CG errors, was zero as
expected. However, including CG errors
resulted in a small non-zero Laplacian of the estimated field map (6.1e-6 (Hz/m2)
at isocenter and the second echo time). This confirms that the field map is not
harmonic when CG terms are considered.
The impact of this non-zero Laplacian is characterized by
applying background field removal algorithms. As shown in Fig. 2, the PDF
algorithm does not remove the effects of CGs on the background field map.
However, SHARP significantly reduces these errors and the RESHARP algorithm effectively
removes them.
Discussion & Conclusions
CGs
create significant errors in the measured field map. For the sequence shown in Fig. 1 the error was
as high as 150 Hz and would be expected to have significant impact on estimated
susceptibility maps. Smaller FOVs would
decrease the magnitude of this error, but other pulse sequence parameters may
increase the error.
We demonstrated analytically and numerically
that the effect of the CGs creates a nonzero Laplacian of the field map such
that it is not harmonic. Three background field removal algorithms were tested
in the presence of CG shifts. PDF was unable to remove large errors in the
field map since these errors are not in the subspace spanned by dipole fields. SHARP
and RESHARP were able to reduce the CG effects since the Laplacian is small enough
that the spherical mean value property holds, approximately. However, these errors are dependent on
gradients strengths, echo train lengths, and flow compensated gradients. Our results demonstrate that CG phase
corrections [3] and/or the use of a background field removal algorithm that removes
this background field component are necessary for accurate QSM.
Acknowledgements
The authors wish to acknowledge support form the
NIH (UL1TR00427, R01 DK083380, R01 DK088925, R01 DK100651, and K24 DK102595),
GE Healthcare, and the National Cancer Institute of the National Institutes of
Health under Award Number T32CA009206.References
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