Multiparametric Saturation Transfer MR Fingerprinting Using Rosette-Accelerated Readout

利用玫瑰花结加速读出的多参数饱和转移磁共振指纹图谱

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Abstract

Quantitative MR-derived tissue parameters are typically measured one by one, which is time-consuming for clinical practice. MR fingerprinting (MRF) allows the efficient and simultaneous measurement of multiple tissue properties. The purpose of this study was to develop a novel, multiparametric MRF framework for the simultaneous measurement of quantitative bulk water, semisolid magnetization transfer (MT), myelin water fraction (MWF), and B(0) inhomogeneity (ΔB(0)) and susceptibility-weighted imaging (SWI) and chemical exchange saturation transfer (CEST) imaging contrast. A motion-robust, rosette-accelerated MRF sequence was developed by integrating RF saturation and T(2)-preparation modules. Optimized MRF acquisition parameters, including RF saturation strength, saturation duration, frequency offset, relaxation delay, T(2)-prep TE, and readout TE, were varied during image acquisition. Quantitative tissue parameters were estimated from unique MRF signal evolutions in human brain scans of healthy volunteers at 3T and evaluated against the reference parameters calculated using conventional standalone sequences. Quantitative bulk water, MTC, myelin water parameters, SWI, ΔB(0), and semiqualitative CEST estimated from a single scan using the multiparametric rosette-MRF technique were in very good agreement with reference parameters. Overall, the semisolid macromolecular pool size ratio (relative to bulk water) and MWF were higher in the white matter (WM) compared to the gray matter (GM). Susceptibility-dependent tissue contrast was visible in the SWI. An accurate ΔB(0) map was derived from the rosette images themselves. Furthermore, multimolecular (MTC, APT, rNOE, and CEST at 3 ppm) images were synthesized by solving forward Bloch equations with the tissue parameter estimated from the MRF reconstruction. In conclusion, a rosette-accelerated, multiparametric MRF technique, combined with synthetic MRI analysis, has the potential to offer valuable insights into disease pathology and serve as an efficient tool for the evaluation of various MRI biomarkers in clinical settings within a short time frame.

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