Adèle LC Mackowiak1,2,3, Tom Hilbert3,4, Giulia MC Rossi1,3, Tobias Kober3,4, and Jessica AM Bastiaansen1
1Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 2Department of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 3Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 4LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Synopsis
The Signal Profile
Asymmetries for Robust multi-Compartment Quantification (SPARCQ) framework was
recently developed and used to quantify water and fat content in tissues.
Applying SPARCQ on bSSFP signal profiles obtained from phase-cycled acquisitions
provided reliable fat fractions with a total scan time of 20:21min at low
resolution. In this study, SPARCQ was accelerated and optimized for water-fat
separation using numerical simulations and in vivo experiments to obtain
a clinically acceptable protocol. Images and fat-fraction maps of knees at an
isotropic resolution of (1.25mm)3 were obtained with a scan time of
7:12min.
Introduction
Phase-cycled
balanced Steady-State Free-Precession (bSSFP) acquisitions can be used to
sample bSSFP profiles, the steady-state magnetization as function of the RF
phase angle. The recently developed “Signal Profile Asymmetries for Robust
multi-Compartment Quantification” (SPARCQ)[1] framework enabled quantification
of fat and water content using asymmetries[2] in bSSFP profiles. In prior work[1], 37 low-resolution scans
were performed to sample the profile in 20min. This work
aims at accelerating the SPARCQ framework and improving signal encoding to
maximize the accuracy of fat-water separation with an improved resolution.Methods
TR
optimization to maximize SPARCQ sensitivity for fat-water separation
In bSSFP,
the magnetization vector precesses during the repetition time TR and accumulates
a precession angle $$$\Phi$$$ depending
on the off-resonance frequency $$$f$$$: $$\Phi=2\pi f\text{TR}$$
Depending on TR, water ($$$f=0$$$Hz) and fat ($$$f=-440$$$Hz) signals may have the
same $$$\Phi$$$ and thus overlap (Figure
1A). The bSSFP signals of water and fat as a function of $$$\Phi$$$ display a periodic
behaviour[3] (Figure 1AB) and their precession angle $$$\Phi$$$ as function of TR is
wrapped into the range $$$[0;2\pi]$$$. Water and fat peaks accordingly wrap
into the corresponding frequency range $$$[0;1/\text{TR}]$$$, with respective relative
frequencies $$$f_{W,\textit{rel}}$$$ and $$$f_{F,\textit{rel}}$$$ such that: $$f_{rel}=\Phi_{[0;2 \pi]}/ 2\pi\text{TR}$$ The
relative distance between the wrapped peaks was calculated as $$$\Delta f_{peak}=f_{F,\textit{rel}} – f_{W,\textit{rel}}$$$. The optimal TR was
defined as the shortest TR which maximizes $$$\Delta f_{peak}$$$.
To
determine the effect of TR on fat-fraction quantification, spectra containing
water and fat resonances with varying fat fractions FF were generated, then Bloch
simulations[4] were performed to obtain bSSFP profiles, with TR $$$\in [3;11]$$$ms and T1/T2 = 5. Fat fractions were extracted from the frequency spectra fitted by the SPARCQ prototype framework[1]. The difference between simulated and estimated fat fraction was calculated.
Minimization
of phase-cycled acquisitions
Simulations: The
effect of reducing the amount of phase-cycles $$$N_{\phi}$$$ on SPARCQ fat-fraction estimation was tested numerically. bSSFP profiles were
simulated[4] using $$$f \in [-600;200]$$$ Hz, T1/T2 = 5, FF $$$\in [0;1]$$$ and
TR = 3.41ms. After noise addition (with signal-to-noise ratio SNR $$$\in [1;100]$$$),
the fat fraction was estimated with SPARCQ. The error between
simulated and estimated fat fraction was calculated for $$$N_{\phi} \in [2;37]$$$.
In
vivo imaging:
The effect of $$$N_{\phi}$$$ reduction on fat quantification was tested in knee images of three volunteers. Phase-cycled bSSFP acquisitions were performed at a 3T
clinical scanner (MAGNETOM, Prismafit, Siemens Healthcare, Erlangen,
Germany). 72 phase-cycled scans were acquired with 5°
RF phase increments and sub-sampled into 36 subsets of length $$$N_{\phi} \in [2;37]$$$.
Fat fractions were estimated in each subset. 25-pixel-wide regions of interest
(ROI) were selected in bone marrow, muscle, and sub-cutaneous fat compartments.
Within each ROI, the mean and standard deviation of the fat fraction were computed and compared to the fully sampled acquisition. A reference,
low-resolution, non-accelerated protocol[1] was compared to the proposed protocol
in one volunteer. The proposed protocol incorporated parallel imaging (GRAPPA[5]) to further enhance the
acceleration. Sequence parameters are summarized in Figure 5D.Results
The
maximum relative distance between fat and water signals occurs when $$$\Delta \Phi = k\pi$$$, $$$k \in ℕ$$$ (Figure
1C) and TR = 3.41ms. Similarly, the quantification
error follows a periodic pattern (Figure 2). Regions where fat-fraction
quantification fails correspond to TR values yielding a similar precession angle for water and fat, i.e. where the profiles are nearly identical.
A SNR ≥ 30 resulted in a consistent estimation when $$$N_{\phi}$$$ is reduced (Figure 3). Relatively
small errors were observed for 16 ≤ $$$N_{\phi}$$$ ≤ 37 (Figure 3). This was corroborated in
vivo, where a consistent standard deviation within each ROI was observed when $$$N_{\phi}$$$ is reduced to 16 (Figure 4).
Comparing the long low-resolution protocol with the short high-resolution
protocol shows that fat fractions were the same (Figure 5). Due to a misclassification
of the fat peak, a signal void can be observed in the patella for both
acquisitions (Figure 5). Discussion
The SPARCQ framework for water-fat separation is TR
sensitive and optimal TRs can be chosen from the analysis of the bSSFP profiles
by maximizing the relative distance $$$\Delta f_{peak}$$$. This is an important consideration for the use of
slab-selective RF excitation pulses, or for changing the magnetic field
strength.
Agreement between numerical simulations and in vivo
experiments indicates that a simple reduction to 16 phase cycles provides sufficient
data for SPARCQ to resolve water and fat. Further acceleration could be achieved
with compressed sensing[6,7].
With SPARCQ a frequency spectrum is obtained in each
voxel that is independent from field inhomogeneities[1]. However, the current
SPARCQ framework assigns water or fat depending on which peak is closest to
on-resonance (Figure 5C). This caused the misclassification of bone
marrow in the patella as water (Figure 5). Using the peak shape, in
conjunction with its location, may be more suitable to classify fat and is
currently being investigated.Conclusion
The SPARCQ framework to separate and quantify
water and fat was optimized in terms of TR and accelerated to a total
acquisition time of 7:12min with an isotropic resolution of (1.25mm)3.
Simulations and in vivo experiments demonstrated the accuracy of fat-fraction
quantification with the proposed accelerated SPARCQ framework.Acknowledgements
This study was supported by funding from the Swiss National Science Foundation (grant number PZ00P3_167871), the Emma Muschamp foundation, and the Swiss Heart foundation.References
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