No abstract

R2*‐MRI has emerged as a noninvasive alternative to liver biopsy for assessment of hepatic iron content (HIC). Multispectral fat–water R2* modeling techniques such as the nonlinear least squares (NLSQ) fitting and autoregressive moving average (ARMA) models have been proposed for the accurate assessment of iron overload by also considering fat, which can otherwise confound R2*‐based HIC measurements in conditions of coexisting iron overload and steatosis. However, the R2* estimation by these multispectral models has not been systematically investigated for various acquisition methods in iron overload only conditions and across the full clinically relevant range of HICs (0–40 mg Fe/g dry liver weight). The purpose of this study is to evaluate the R2* accuracy and precision of multispectral models for various multiecho gradient echo (GRE) and ultrashort echo time (UTE) imaging acquisitions by constructing virtual iron overload models based on true histology and synthesizing MRI signals via Monte Carlo simulations at 1.5 T and 3 T, and comparing their results with monoexponential model and published in vivo R2*–HIC calibrations. The signals were synthesized with TE1 = 1.0 ms for GRE and TE1 = 0.1 ms for UTE acquisition for varying echo spacing, ΔTE (0.1, 0.5, 1, 2 ms), and maximum echo time, TEmax (2, 4, 6, 10 ms). An iron‐doped phantom study is also conducted to validate the simulation results in experimental GRE (TE1 = 1.2 ms, ΔTE = 0.72 ms, TEmax = 6.24 ms) and UTE (TE1 = 0.1 ms, ΔTE = 0.5 ms, TEmax = 6.1 ms) acquisitions. For GRE acquisitions, the multispectral ARMA and NLSQ models produced higher slopes (0.032–0.035) compared with the monoexponential model and published in vivo R2*–HIC calibrations (0.025–0.028). However, for UTE acquisition for shorter echo spacing (≤0.5 ms) and longer maximum echo time, TEmax (≥6 ms), the multispectral and monoexponential signal models produced similar R2*–HIC slopes (1.5 T, 0.028–0.032; 3 T, 0.014–0.016) and precision values (coefficient of variation < 25%) across the full clinical spectrum of HICs at both 1.5 T and 3 T. The phantom analysis also showed that all signal models demonstrated a significant improvement in R2* estimation for UTE acquisition compared with GRE, confirming our simulation findings. Future work should investigate the performance of multispectral fat–water models by simulating liver models in coexisting conditions of iron overload and steatosis for accurate R2* and fat quantification.

R2* correction is necessary for improving the accuracy of fat fraction quantification in assessing steatosis. However, the dephasing effects of concurrent iron overload may be dependent on the size of iron and fat particles. In this study, we controlled the size of fat droplets in fat-iron emulsion phantoms by traditional stir bar methods and homogenization. R2* and far fraction (FF) values were estimated with multi-spectral models that assume a common or independent R2* for water and fat. Our results show that R2* was slightly reduced in homogenized phantoms at higher fat fractions compared to stir bar phantoms.