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Abstract #1692

B1 Correction of MRSI Data Using Unsuppressed Water Signals

Yibo Zhao1, Yudu Li1,2,3, Rong Guo1,4, Wen Jin1,5, Brad Sutton1,2,3, Ziyu Meng6, Chang Xu6, Wenqi Zhang6, Yao Li6, and Zhi-Pei Liang1,5
1Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States, 2Department of Bioengineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States, 3National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Champaign, IL, United States, 4Siemens Medical Solutions USA, Inc., St. Louis, MO, United States, 5Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States, 6School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

Synopsis

Keywords: Quantitative Imaging, Quantitative Imaging, System Imperfections: Measurement & Correction

Motivation: B1 inhomogeneities hinders biological interpretation of MRSI results. By correcting B1 effects, quantitative estimation of metabolite concentrations can be obtained from MRSI data.

Goal(s): To develop a practical method for B1-correction of MRSI using the companion unsuppressed water signals.

Approach: We used a non-water-suppressed MRSI data acquisition scheme with variable-flip-angle frames to encode B1 information. B1 effects were estimated with physics-based and data-driven priors and corrected from metabolite maps, producing quantitative concentration estimations.

Results: Results from phantom, healthy subjects and tumor patients demonstrated the feasibility of B1-corrected quantitative MRSI. Metabolite concentrations obtained from the proposed method aligned with the ground truth and literature.

Impact: The proposed method enables quantitative metabolite concentration estimation, which is robust even in pathological tissues. This method is expected to enhance the accuracy, robustness and reproducibility of MRSI technologies.

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Abstract

Keywords