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Abstract #4476

Accelerating CEST MRI using Data-Driven Z-Spectral Compressed Sensing

Haipeng Xu1, Tao Gong2, and Lin Chen1
1Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, School of Electronic Science and Engineering, National Model Microelectronics College, Xiamen University, Xiamen, China, 2Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China

Synopsis

Keywords: CEST / APT / NOE, CEST & MT

Motivation: CEST MRI requires the collection of multiple saturated images with different saturation offsets, resulting in prolonged scan times, which hinders its clinical applications.

Goal(s): we aim to reduce the scan time of CEST MRI by recovering the undersampled Z-spectrum to full-sampling counterpart using data-driven Z-spectral compressed sensing method.

Approach: The modified U-Net was employed for Z-spectral recovery. Training data were generated using Bloch equation. Numerical simulations and in vivo experiments on rat brains were conducted to validate the proposed method.

Results: The results demonstrate that our method outperformed conventional interpolation methods, and threefold undersampling rate can be achieved without discernible degradation in quantification.

Impact: The proposed method can efficiently reduce the scan time of CEST MRI, potentially facilitating its clinical applications.

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Keywords