Chemical-shift based multi-spectral fat-water models accounting for single or dual R2* correction are used to assess hepatic iron concentration (HIC) and fat fraction (FF). In this study, we developed a Monte-Carlo based approach for simulating steatosis and iron overload models mimicking the in-vivo characteristics and synthesizing MRI signal to compare the accuracy of the R2* models to estimate FF in the presence of iron. Our results show that R2* estimated by single R2* model is highly governed by iron whereas dual R2* model predicts R2*-FF relationship close to the in-vivo calibration. Nevertheless, FF predicted by both the models were close to the true FF.
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