Rong Guo^{1,2}, Yudu Li^{1,2}, Yibo Zhao^{1,2}, Tianyao Wang^{3}, Yao Li^{4}, Brad Sutton^{1,2,5}, and Zhi-Pei Liang^{1,2}

^{1}Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ^{2}Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ^{3}Radiology Department, Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China, ^{4}School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ^{5}Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

The feasibility of high-resolution
metabolic imaging using water-unsuppressed MRSI has been recently demonstrated
in clinical settings using SPICE. This work utilizes the unsuppressed water
spectroscopic signals for distortion-free mapping of water diffusion
coefficients, thus adding a new feature to SPICE for multi-modal brain mapping.
Experimental results demonstrated that simultaneous distortion-free diffusion
imaging at 1.0×1.0×2.0 mm^{3} resolution and metabolic imaging at
2.0×3.0×3.0 mm^{3} nominal resolution were successfully obtained in a
total 8-min scan.

$$\rho_i(\mathbf{x},t)=\rho_r(\mathbf{x},t)\cdot \sum_{n_i=-N_i/2}^{N_i/2}{c_{n_i}(\mathbf{x})e^{i2{\pi}n_i{\Delta}ft}}$$

where $$$i$$$ denotes a specific diffusion frame, $$$c_{n_i}(x)$$$ the GS coefficients and $$$N_i$$$ the model order. Reconstruction of $$$\rho_i(x,t)$$$ from the sparse data (denoted as $$$d_i$$$) can be done by solving the following optimization problem:

$$\widehat{c}_i={\mathrm{arg}}{\mathrm{min}}_{c_i}\left \| d_i-{\Omega}FBS(G(\rho_r)c_i))) \right \|_2^2 + R(c_i)$$

where $$$c_i$$$ and $$$\rho_r$$$ are the vector forms of {$$$c_{n_i}(x)$$$} and $$$\rho_r(x,t)$$$, $$$\Omega,F,B,S,G,R$$$ operators representing k-space sampling, Fourier transform, field inhomogeneity, coil sensitivity, GS modeling and regularization, respectively. With $$$\widehat{c}_i$$$ being determined, reconstructed diffusion signals $$$\widehat{\rho}_i(x,t)$$$ could be synthesized using the GS model and the SPICE signals.

To correct the errors caused by the physiological motion, first, we identified the corrupted TRs and corresponding data using the navigator signals. Then, the corrupted (k, t)-space data were discarded and interpolated using the uncorrupted data through GS-based reconstruction with stronger constraints. The final reconstruction results were generated from the corrected data.

The generation of metabolite maps from the SPICE frame followed the existing methods

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Figure
1. (a) Pulse sequence diagram of the proposed method. A diffusion preparation
module was incorporated into the SPICE sequence for simultaneous diffusion and
metabolic imaging. (b) Sampling pattern of (k, t)-space. Both SPICE frame and
diffusion frames were sparsely sampled using spatiotemporal CAIPIRINHA
trajectories.

Figure
2. Diffusion weighted images and ADC maps of the NIST diffusion phantom. (a)
water image of the SPICE frame as the anatomical reference; (b) diffusion
images acquired using traditional EPI sequence; (c) diffusion images acquired using the proposed sequence with fully sampled (k, t)-space;
(d) diffusion images reconstructed from the sparse (k, t)-space data
retrospectively sampled from the full data.

Figure
3. A representative set of results obtained from a healthy subject. (a) First
TE images of the SPICE frame and diffusion frames (b = 0, 500, 1000 s/mm^{2}).
(b) Diffusion weighted images of different TEs (TE = 2, 18, 34, 50 ms, b = 500
s/mm^{2}). (c) ADC maps obtained using the proposed method and the
traditional EPI method.

Figure
4. A representative set of diffusion imaging and MRSI results obtained from a
healthy subject. Diffusion images (including TRACE image with b = 1000 s/mm^{2}
and ADC map, at 1.0×1.0×2.0 mm^{3}), and metabolite maps (including
NAA, Cr, and Cho maps, at 2.0×3.0×3.0 mm^{3}) were simultaneously
obtained in the single 8-min scan.

Figure
5. Representative diffusion images (including TRACE image and ADC map) and
metabolite maps (including NAA, Cr, and Cho maps) obtained from a tumor patient
using the proposed method. T1-weighted image with contrast enhancement is shown
as anatomical reference.

DOI: https://doi.org/10.58530/2022/3544