Chemical-shift encoding-based water-fat separation with multifrequency fat spectrum modeling in spin-lock MRI

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Biomedical Engineering
• Spectroscopy

Background:

• Chemical exchange saturation transfer (CEST) and spin-lock techniques are vital for MRI contrast and probing molecular motion.
• Fat signals in spin-lock MRI can introduce errors, as conventional suppression methods fail with multiple fat peaks.
• Multifrequency fat spectrum modeling is crucial for accurate water-fat separation in complex biological systems.

Purpose of the Study:

• To develop and evaluate chemical-shift encoding-based water-fat separation approaches using multifrequency fat spectrum modeling for spin-lock MRI.
• To overcome limitations of conventional fat suppression techniques in spin-lock imaging.
• To compare the performance of conventional spin-lock and adiabatic continuous-wave constant-amplitude spin lock (ACCSL) acquisitions.

Main Methods:

• Investigated conventional spin-lock and ACCSL with multi-echo acquisitions for water-fat separation.
• Compared reconstructions using single-peak, precalibrated 6-peak, and self-calibrated 3-peak fat spectrum models.
• Validated methods through Bloch simulations, phantom studies, and in vivo experiments at 3 Tesla.

Main Results:

• Conventional spin-lock acquisitions are unreliable for water-fat separation with multipeak fat spectra.
• ACCSL acquisitions demonstrate superior water-fat separation performance compared to conventional spin-lock.
• Optimal results were obtained using ACCSL with self-calibrated relaxation-dependent multipeak fat spectrum modeling.

Conclusions:

• ACCSL acquisition enables robust chemical-shift encoding-based water-fat separation with multipeak fat spectrum modeling.
• This approach holds significant potential for enhancing quantitative analysis in spin-lock MRI.
• The method can improve the assessment of biochemical properties in various tissues.