Accelerated 3D metabolite T1 mapping of the brain using variable‐flip‐angle SPICE

• Published in: Magnetic resonance in medicine Vol. 92; no. 4; pp. 1310 - 1322
• Main Authors: Zhao, Yibo, Li, Yudu, Guo, Rong, Jin, Wen, Sutton, Brad, Ma, Chao, El Fakhri, Georges, Li, Yao, Luo, Jie, Liang, Zhi‐Pei
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01.10.2024
• Subjects: Brain; Brain mapping; Data acquisition; Data processing; FID MRSI; Imaging; In vivo methods and tests; Information processing; Lipids; low‐rank tensor modeling; Mapping; metabolite T1 mapping; Metabolites; Neuroimaging; Signal processing; Signal quality; Subspaces; Substantia alba; Substantia grisea; Tensors; variable flip angle
• ISSN: 0740-3194; 1522-2594; 1522-2594
• DOI: 10.1002/mrm.30200

Purpose To develop a practical method to enable 3D T1 mapping of brain metabolites. Theory and Methods Due to the high dimensionality of the imaging problem underlying metabolite T1 mapping, measurement of metabolite T1 values has been currently limited to a single voxel or slice. This work achieved 3D metabolite T1 mapping by leveraging a recent ultrafast MRSI technique called SPICE (spectroscopic imaging by exploiting spatiospectral correlation). The Ernst‐angle FID MRSI data acquisition used in SPICE was extended to variable flip angles, with variable‐density sparse sampling for efficient encoding of metabolite T1 information. In data processing, a novel generalized series model was used to remove water and subcutaneous lipid signals; a low‐rank tensor model with prelearned subspaces was used to reconstruct the variable‐flip‐angle metabolite signals jointly from the noisy data. Results The proposed method was evaluated using both phantom and healthy subject data. Phantom experimental results demonstrated that high‐quality 3D metabolite T1 maps could be obtained and used for correction of T1 saturation effects. In vivo experimental results showed metabolite T1 maps with a large spatial coverage of 240 × 240 × 72 mm3 and good reproducibility coefficients (< 11%) in a 14.5‐min scan. The metabolite T1 times obtained ranged from 0.99 to 1.44 s in gray matter and from 1.00 to 1.35 s in white matter. Conclusion We successfully demonstrated the feasibility of 3D metabolite T1 mapping within a clinically acceptable scan time. The proposed method may prove useful for both T1 mapping of brain metabolites and correcting the T1‐weighting effects in quantitative metabolic imaging.