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Simultaneous metabolic and functional imaging of the brain using SPICE
Author(s) -
Guo Rong,
Zhao Yibo,
Li Yudu,
Li Yao,
Liang ZhiPei
Publication year - 2019
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.27865
Subject(s) - magnetic resonance spectroscopic imaging , computer science , artificial intelligence , image resolution , iterative reconstruction , computer vision , pattern recognition (psychology) , temporal resolution , nuclear magnetic resonance , magnetic resonance imaging , physics , medicine , radiology , optics
Purpose To enable simultaneous high‐resolution mapping of brain function and metabolism. Methods An encoding scheme was designed for interleaved acquisition of functional MRI (fMRI) data in echo volume imaging trajectories and MR spectroscopic imaging (MRSI) data in echo‐planar spectroscopic imaging trajectories. The scheme eliminates water and lipid suppression and utilizes free induction decay signals to encode both functional and metabolic information with ultrashort TE, short TR, and sparse sampling ofk , t ‐space. A subspace‐based image reconstruction method was introduced for processing both the fMRI and MRSI data. The complementary information in the fMRI and MRSI data sets was also utilized to improve image reconstruction in the presence of intrascan head motion, field drift, and tissue susceptibility changes. Results In‐vivo experimental results were obtained from healthy human subjects in resting‐state fMRI/MRSI experiments. In these experiments, the proposed method was able to simultaneously acquire metabolic and functional information from the brain in high resolution. For scans of 6.5 minutes, we achieved 3.0 × 3.0 × 1.8 mm 3 spatial resolution for fMRI, 1.9 × 2.5 × 3.0 mm 3 nominal spatial resolution for MRSI, and 1.9 × 1.9 × 1.8 mm 3 nominal spatial resolution for quantitative susceptibility maps. Conclusion This work demonstrates the feasibility of simultaneous high‐resolution mapping of brain function and metabolism with improved spatial resolution and synergistic image reconstruction.