Impact of iron deposit on the accuracy of quantifying liver fat fraction using multi-material decomposition algorithm in dual-energy spectral computed tomography

铁沉积对双能光谱计算机断层扫描中采用多物质分解算法量化肝脏脂肪分数准确性的影响

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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 (FF(ref) ). 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 (FF(CT) ) and Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL-IQ) in MR (FF(MR) ) for each tube. Statistical analyses used were: Spearman rank correlation for correlations between FF(ref) and CT attenuation, FF(CT) , and FF(MR) ; one-way ANOVA, and one-sample t-test for the differences between FF(CT) and FF(ref) and between FF(MR) and FF(ref) . A multivariate linear regression model was established to analyze the differences between the corresponding values with different iron concentrations under the same FF(ref) . RESULTS: Fat fraction on CT (FFCT) and FF(MR) were positively correlated with FF(ref) (all p < 0.001), while the CT attenuation was negatively correlated with FF(ref) in the three iron concentration ranges. For a given FF(ref) , FF(CT) decreased and FF(MR) increased as the iron concentration increased. The mean difference between FF(CT) and FF(ref) over the nine tube measurements was 0.25 ± 2.45%, 5.7% lower the 5.98 ± 3.33% value between FF(MR) and FF(ref) (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.

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