Impact of iron deposit on the accuracy of quantifying liver fat fraction using multi‐material decomposition algorithm in dual‐energy spectral computed tomography. Issue 8 (20th July 2021) - Du, Dandan; Wu, Xingwang; Wang, Jinchuan; Chen, Hua; Song, Jian; Liu, Bin
Abstract: Objectives: To investigate the accuracy of using multi‐material decomposition (MMD) algorithm in dual‐energy spectral computed tomography (CT) for quantifying fat fraction (FF) in the presence of iron. Materials: Nine tubes with various proportions of fat and iron were prepared. FF were divided into three levels (10%, 20%, and 30%), recorded as references (FFref ). Iron concentrations (in mg/100 g) were divided into three ranges (25.25–25.97, 50.38–51.55 and 75.57–77.72). The nine‐tube phantom underwent dual‐energy CT and MR. CT attenuation was measured and FF were determined using MMD in CT (FFCT ) and Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL‐IQ) in MR (FFMR ) for each tube. Statistical analyses used were: Spearman rank correlation for correlations between FFref and CT attenuation, FFCT, and FFMR ; one‐way ANOVA, and one‐sample t ‐test for the differences between FFCT and FFref and between FFMR and FFref . A multivariate linear regression model was established to analyze the differences between the corresponding values with different iron concentrations under the same FFref . Results: Fat fraction on CT (FFCT) and FFMR were positively correlated with FFref (all p < 0.001), while the CT attenuation was negatively correlated with FFref in the three iron concentration ranges. For a given FFref, FFCT decreased and FFMR increased as the iron concentration increased. The mean difference between FFCT and FFref over the nine tube measurements was 0.25 ± 2.45%, 5.7% lower the 5.98 ± 3.33% value between FFMR and FFref ( F = 310.017, p < 0.01). Conclusion: The phantom results indicate that MMD in dual‐energy CT can directly quantify volumetric FF and is less affected by iron concentration than MR IDEAL‐IQ method.