Free-breathing fat and R2* quantification in the liver using a stack-of-stars multi-echo acquisition with respiratory-resolved model-based reconstruction

Purpose: To develop a free-breathing hepatic fat and R-2* quantification method by extending a previously described stack-of-stars model-based fat-water separation technique with additional modeling of the transverse relaxation rate R-2*. Methods: The proposed technique combines motion-robust radial sampling using a stack-of-stars bipolar multi-echo 3D GRE acquisition with iterative model-based fat-water separation. Parallel-Imaging and Compressed-Sensing principles are incorporated through modeling of the coil-sensitivity profiles and enforcement of total-variation (TV) sparsity on estimated water, fat, and R-2* parameter maps. Water and fat signals are used to estimate the confounder-corrected proton-density fat fraction (PDFF). Two strategies for handling respiratory motion are described: motion-averaged and motion-resolved reconstruction. Both techniques were evaluated in patients (n = 14) undergoing a hepatobiliary research protocol at 3T. PDFF and R-2*parameter maps were compared to a breath-holding Cartesian reference approach. Results: Linear regression analyses demonstrated strong (r > 0.96) and significant (P MUCH LESS-THAN .01) correlations between radial and Cartesian PDFF measurements for both the motion-averaged reconstruction (slope: 0.90; intercept: 0.07%) and the motion-resolved reconstruction (slope: 0.90; intercept: 0.11%). The motion-averaged technique overestimated hepatic R-2* values (slope: 0.35; intercept: 30.2 1/s) compared to the Cartesian reference. However, performing a respiratory-resolved reconstruction led to better R-2* value consistency (slope: 0.77; intercept: 7.5 1/s). Conclusions: The proposed techniques are promising alternatives to conventional Cartesian imaging for fat and R-2* quantification in patients with limited breath-holding capabilities. For accurate R-2* estimation, respiratory-resolved reconstruction should be used.