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

Abstract

Purpose To develop a free‐breathing hepatic fat and quantification method by extending a previously described stack‐of‐stars model‐based fat‐water separation technique with additional modeling of the transverse relaxation rate . 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 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 parameter maps were compared to a breath‐holding Cartesian reference approach. Results Linear regression analyses demonstrated strong ( r > 0.96) and significant ( P ≪ .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 values (slope: 0.35; intercept: 30.2 1/s) compared to the Cartesian reference. However, performing a respiratory‐resolved reconstruction led to better value consistency (slope: 0.77; intercept: 7.5 1/s). Conclusions The proposed techniques are promising alternatives to conventional Cartesian imaging for fat and quantification in patients with limited breath‐holding capabilities. For accurate estimation, respiratory‐resolved reconstruction should be used.

Magnetization‐prepared GRASP MRI for rapid 3D T1 mapping and fat/water‐separated T1 mapping

“…The framework can also be further extended for T2 mapping by employing T2 preparation, or for joint T1 and T2 mapping using multiple preparations, as shown in prior studies. [70][71][72][73] It can also be further extended to include estimation of R2 * and proton density fat fraction (PDFF) 25,37,43 and to further remove the influence of iron in T1 estimation. This would lead to a comprehensive free-breathing quantitative imaging framework.…”

“…The performance of stack-of-stars sampling has been previously demonstrated in gradient-echo (GRE) imaging, 7,15 fast spin-echo (FSE) imaging, 16,17 multi-echo Dixon imaging, 9,18,19 and balanced steady-state free precession (bSSFP) imaging. [20][21][22] The stack-of-stars versions of these sequences have been applied for free-breathing dynamic contrastenhanced MRI (DCE-MRI), 3,6,23,24 cardiovascular MRI, 9,[20][21][22] fat/water MRI, 18,19,25 arterial spin labeling (ASL) MRI 26 and others. 27 However, to date, the use of stack-of-stars imaging is primarily limited to steady-state acquisitions and its combination with magnetization-prepared data acquisition has been limited to only a few prior studies.…”

Physics-based reconstruction methods for magnetic resonance imaging

“…The first physics-based reconstruction methods for parametric mapping appeared in the literature more than a decade ago [1][2][3] and constitute now a major research area in the field of magnetic resonance imaging (MRI) [4][5][6][7][8][9][10][11][12][13]. Model-based reconstruction is based on modelling the physics of the MRI signal and has been used, for example, to estimate T 1 [6,9,[13][14][15][16], T 2 relaxation [3,5,10,17], for T 2 estimation and water-fat separation [18][19][20][21][22], as well as for quantification of flow [11] and diffusion [23,24]. Quantitative maps of the underlying physical parameters can then be extracted directly from the measurement data without intermediate image reconstruction.…”

Quantification of Liver Fat Content with CT and MRI: State of the Art

“…On the basis of recent developments, advanced methods including compressed sensing and MR fingerprinting may also enable liver fat quantification (103)(104)(105). Compressed sensing reconstruction allows reconstruction of the MRI scans using fewer phase encodes and thus shortens acquisition time (103,104), whereas fingerprinting allows for direct measurements of tissue properties and relaxation parameters (105). In fingerprinting, MRI settings and parameters deliberately vary during the data acquisition to generate a unique signal pattern or "fingerprint."…”