Free-Breathing Water, Fat,R∗2 and B0 Field Mapping of the Liver Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (MERLOT)

Authors

Tan Z, Rosenzweig S, Wang X, Scholand N, Holme HCM, Blumenthal M, Voit D, Frahm J, Uecker M

Journal

ArXiv

Citation

arXiv:2101.02788.

Abstract

Purpose: To achieve free-breathing quantitative fat and R⋆2 mapping of the liver using a generalized model-based iterative reconstruction, dubbed as MERLOT. Methods: For acquisition, we use a multi-echo radial FLASH sequence that acquires multiple echoes with different complementary radial spoke encodings. We investigate real-time single-slice and volumetric multi-echo radial FLASH acquisition. For the latter, the sampling scheme is extended to a volumetric stack-of-stars acquisition. Model-based reconstruction based on generalized nonlinear inversion is used to jointly estimate water, fat, R⋆2, B0 field inhomogeneity, and coil sensitivity maps from the multi-coil multi-echo radial spokes. Spatial smoothness regularization is applied onto the B 0 field and coil sensitivity maps, whereas joint sparsity regularization is employed for the other parameter maps. The method integrates calibration-less parallel imaging and compressed sensing and was implemented in BART. For the volumetric acquisition, the respiratory motion is resolved with self-gating using SSA-FARY. The quantitative accuracy of the proposed method was validated via numerical simulation, the NIST phantom, a water/fat phantom, and in in-vivo liver studies. Results: For real-time acquisition, the proposed model-based reconstruction allowed acquisition of dynamic liver fat fraction and R⋆2 maps at a temporal resolution of 0.3 s per frame. For the volumetric acquisition, whole liver coverage could be achieved in under 2 minutes using the self-gated motion-resolved reconstruction. Conclusion: The proposed multi-echo radial sampling sequence achieves fast k -space coverage and is robust to motion. The proposed model-based reconstruction yields spatially and temporally resolved liver fat fraction, R⋆2 and B0 field maps at high undersampling factor and with volume coverage.

DOI

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