Introduction

T1 is emerging as a quantitative biomarker of liver fibrosis^1,2. Fibrosis is the histological change most predictive of chronic liver disease progression to cirrhosis and primary liver cancer³. Early detection and quantitative staging of liver fibrosis would allow for targeted interventions.

T1 mapping using variable flip angle (VFA) spoiled gradient echo (SGRE) acquisitions is commonly used for applications where short acquisition times, volumetric coverage, and motion robustness are important^4,5. However, VFA methods are confounded by fat and B1 inhomogeneities⁶. The effects of fat can be addressed through chemical-shift-encoded MRI (CSE-MRI)^7,8; however, standard B1-correction requires separate B1-calibration⁹. The additional calibration increases scan time, risks inter-acquisition patient motion, and requires post-acquisition image registration. Therefore, the purpose of this work is to present a novel SGRE-based method for simultaneous B1- and fat-corrected T1 mapping for volumetric evaluation of the entire liver in a single breath-hold.

Theory

A previously presented B1 mapping method¹⁰ uses two consecutive non-selective RF pulses of equal magnitude, but orthogonal phase, to encode the transmitted flip angle into the phase of the MR signal. Our acquisition adapts this method for slab-selection using bipolar slab-select gradients and time-reversed RF waveforms, and combines it with multi-echo CSE-MRI and multi-pass VFA⁵ to jointly estimate PDFF, R2*, B1, and T1 in a single breath-hold (Figure 1).

The signal model for the proposed acquisition was derived using Bloch equation simulations in MATLAB assuming instantaneous RF excitation, perfect spoiling of transverse magnetization at the end of each TR, and a 6-peak spectral model of fat^11,12. In passes 2 and 3, an optimal RF spoiling increment¹³ was chosen as $$$116^{\circ}$$$ (Figure 2A).

After initialization with a graph-cut algorithm¹⁵, parameter estimations were performed by nonlinear least-squares¹⁴:\begin{equation}\pmb{\widehat{\theta}}=\text{arg}\min\limits_{\pmb{\theta}}\,[\sum_{p=1}^{3}\sum_{n=1}^{N_p}|s_{p,n}(\pmb{\theta})-s_{meas,p,n}|^2]\\for\,\pmb{\theta}=\{\beta_W,\beta_F,T1_W,T1_F,M_0,\phi_1,\phi_{2,W},\phi_{2,F},PDFF,R_{2,W}^*,R_{2,F}^*,\psi\}\tag{1}\end{equation}where $$$s_{p,n}$$$ is the derived signal and $$$s_{meas,p,n}$$$ is the acquired/measured signal. In this notation, $$$p$$$ is the pass index, $$$n$$$ the echo index, and $$$N_p$$$ the number of echoes acquired in pass $$$p$$$. Unknown parameters ($$$\pmb{\theta}$$$) include B1 transmission efficiency ($$$\beta$$$), T1, signal amplitude ($$$M_0$$$), an initial phase in pass 1 ($$$\phi_1$$$), an initial phase common between passes 2 and 3 ($$$\phi_{2}$$$), PDFF, R2*, and B0 off-resonance ($$$\psi$$$). Subscripts W/F denote that the term is modeled and estimated independently for water/fat, respectively (Figure 2B).

Methods

We evaluated the proposed method at 1.5T (Signa Artist, GE Healthcare). Two protocols were used in this study (Figure 1). Protocol 1 was designed for phantom experiments performed without parallel imaging acceleration. Protocol 2 was designed for in vivo liver imaging, with total scan time reduced to a 19-second breath-hold using parallel imaging acceleration and partial Fourier acquisition.

Phantom Experiments
An agar gel phantom was fabricated using peanut oil and NiCl_2⁻ to modulate PDFF and T1_W, respectively. The 15-vial phantom consisted of 3 sets (PDFF=0,10,20%) of 5 vials (T1_W=200,400,600,800,1000ms). 2D spin-echo inversion-recovery (IR-SE) data (TR=4000ms,TI=50,103,212,436,897,1846,3800ms) were acquired to determine reference T1 values.

Bias and precision were determined with linear regression and Bland-Altman analysis from independent repeated measurements in the constructed phantom. Protocol 1 was acquired 40 times, Protocol 2 was acquired 10 times, and a product 2D single-slice T1 mapping application (SMART1MAP, GE Healthcare) was acquired 10 times.

In Vivo Evaluations
The proposed method was tested in 5 healthy volunteers using Protocol 2. SMART1MAP was acquired as an in vivo reference for T1 and multi-TE-TR MR Spectroscopy (STEAM)¹⁶ was acquired as a reference for PDFF.

Results

Phantom Experiments
The proposed T1_W shows excellent agreement with the IR-SE T1W reference (slope=1.01, R²=1.00, RMSE=22ms) with an average bias of -5.2±23ms using Protocol 1 in the agar gel phantom (Figure 3B). In a comparison of in vivo protocols in phantom data, Protocol 2 exhibited improved repeatability with an 11.2% reduction in coefficient of variation (CV) compared to SMART1MAP (Figure 4).

In Vivo Evaluations
Figure 5 shows that T1_W maps in 5 healthy volunteers showed good agreement with the vendor provided SMART1MAP. Measured PDFF was in close agreement with MRS-STEAM results.

Discussion

In this work we have presented a novel method for simultaneous B1- and fat-corrected T1_W estimation that can provide full liver coverage in a single breath-hold. Accuracy was demonstrated in phantoms and in vivo feasibility in healthy volunteers.

Currently, this method has only been evaluated at 1.5T. While B1 inhomogeneity is a confounder at 1.5T, the magnitude of B1 errors increases with field strength¹⁷. Future work is needed to optimize the method for 3.0T acquisitions.

B1 inhomogeneity and fat are known confounders of T1 estimation. Our proposed method accounts for both confounders through simultaneous estimation of T1, B1, PDFF and R2*. The proposed method demonstrates good linear agreement with reference T1 measurements, with both low bias and high precision, and can achieve full-volume liver coverage in a single breath-hold.

Acknowledgements

We wish to acknowledge support from the NIH (R01 DK088925, UL1TR002373), UW Department of Radiology, UW Institute for Clinical and Translational Research, and the Clinical and Translational Science Award of the NCATS/NIH. Further, we wish to acknowledge GE Healthcare who provides research support to the University of Wisconsin. Finally, Dr. Reeder is a Romnes Faculty Fellow, and has received an award provided by the University of Wisconsin-Madison Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation.

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