Peng Yun, Ye Jing, Liu Chang, Jia Hongru, Sun Jun, Ling Jun, Prince Martin, Li Chang, Luo Xianfu
Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical College, Yangzhou University, Yangzhou, China.
Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
Quant Imaging Med Surg. 2021 May;11(5):2001-2012. doi: 10.21037/qims-20-902.
Liver iron and fat are often co-deposited, synergistically aggravating the progression of chronic liver disease. Accurate determination of liver iron and fat content is helpful for patient management. To assess the accuracy of hepatic iron/fat decomposition using dual-energy computed tomography (DECT) for simultaneously quantifying hepatic iron and fat when both are present.
Sixty-eight New Zealand rabbits on a high-fat/cholesterol diet plus iron injections were used to establish a model of coexisting hepatic iron/fat. Abdominal imaging was performed using dual-source DECT. The iron and fat fractions (Iron- and Fat-, respectively) were calculated using a 3-material decomposition algorithm. The spectroscopic liver iron concentration (LIC) grading (normal, mild, moderate, severe, and massive iron overload) and the histopathological fat fraction (Fat-ref) grading (normal, mild, moderate, severe steatosis) were used as references. Correlations between the DECT parameters and the references were analyzed. Hepatic iron/fat quantification equations were established and validated. Analysis of covariance was used to assess the influence of fat on iron measurements and vice versa.
Iron- highly correlated with LIC (r=0.94, P<0.001), and Fat- highly correlated with Fat- (r=0.88, P<0.001). Both the Iron-- and Fat--derived LIC and fat fraction showed good agreement with spectroscopy/histology. The linear relationship between Iron- and spectroscopic LIC was not affected by the grade of hepatic fat (F=1.93, P=0.16). The linear relationship between Fat- and Fat- was unaffected by hepatic iron grades from normal to severe (F=0.18, P=0.91). However, with massive iron overload [>15.0 mg Fe/g (270 µmol/g)] the regression began to deviate, causing fat underestimation (F=5.50, P=0.04).
Our DECT-based iron/fat decomposition algorithm accurately measured hepatic iron and fat when both were present in a rabbit model. Hepatic fat may be underestimated when there is massive iron overload.
肝脏铁和脂肪常共同沉积,协同加剧慢性肝病的进展。准确测定肝脏铁和脂肪含量有助于患者管理。评估使用双能计算机断层扫描(DECT)进行肝脏铁/脂肪分解以同时定量存在铁和脂肪时肝脏铁和脂肪含量的准确性。
68只食用高脂/高胆固醇饮食并注射铁剂的新西兰兔用于建立肝脏铁/脂肪共存模型。使用双源DECT进行腹部成像。使用三物质分解算法计算铁和脂肪分数(分别为Iron-和Fat-)。将光谱肝脏铁浓度(LIC)分级(正常、轻度、中度、重度和大量铁过载)和组织病理学脂肪分数(Fat-ref)分级(正常、轻度、中度、重度脂肪变性)用作参考。分析DECT参数与参考值之间的相关性。建立并验证肝脏铁/脂肪定量方程。使用协方差分析评估脂肪对铁测量的影响,反之亦然。
Iron-与LIC高度相关(r = 0.94,P < 0.001),Fat-与Fat-高度相关(r = 0.88,P < 0.001)。Iron-和Fat-衍生的LIC和脂肪分数与光谱学/组织学均显示出良好的一致性。Iron-与光谱LIC之间的线性关系不受肝脏脂肪分级的影响(F = 1.93,P = 0.16)。Fat-与Fat-之间的线性关系不受从正常到重度的肝脏铁分级的影响(F = 0.18,P = 0.91)。然而,当存在大量铁过载[>15.0 mg Fe/g(270 µmol/g)]时,回归开始偏离,导致脂肪低估(F = 5.50,P = 0.04)。
我们基于DECT的铁/脂肪分解算法在兔模型中同时存在铁和脂肪时能准确测量肝脏铁和脂肪。当存在大量铁过载时,肝脏脂肪可能被低估。