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Published on: October 20, 2023
Impact of iron deposit on the accuracy of quantifying liver fat fraction using multi-material decomposition algorithm
Dandan Du1, Xingwang Wu1, Jinchuan Wang1
1Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
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.

