Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China; Department of Biomedical Engineering, the Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, PR China.
The Third Hospital of Hebei Medical University, the Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, PR China.
Diagn Interv Radiol. 2022 Nov;28(6):547-554. doi: 10.5152/dir.2022.211325.
PURPOSE We aimed to establish a liver function evaluation model by combining multiparametric magnetic resonance imaging (MRI) with liver volume (LV) and further verify the effectiveness of the model to evaluate liver function. METHODS This retrospective study included 101 consecutive cirrhosis patients (69 cases for modeling group and 32 cases for validation group) who underwent gadoxetic acid-enhanced MRI. Five signal intensity parameters were obtained by measuring the signal intensities of the liver, spleen, and erector spinae before and 20 minutes after gadoxetic acid disodium enhancement. The dif fusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were obtained from intravoxel incoherent motion diffusion-weighted imaging. The LV parameters (Vliver, Vspleen, and Vliver/Vspleen) were obtained using 3-dimensional image generation software. The most effec tive parameter was selected from each of the 3 methods, and a multivariate regression model for liver function evaluation was established and validated. RESULTS In the modeling group, relative enhancement (RE), D*, and Vliver/Vspleen showed significant dif ferences among the different liver function groups (P < .001). Receiver operating characteristic analysis showed that these parameters had the highest area under the curve (AUC) values for dis tinguishing Child-Pugh A from Child-Pugh B and C groups (0.917, 0.929, and 0.885, respectively). The following liver function model was obtained by multivariate regression analysis: F(x)=3.96 - 1.243 (RE) - 0.034 (D*) - 0.080 (Vliver/Vspleen) (R2=0.811, P < .001). In the patients with cirrhosis, the F(x) of Child-Pugh A, B, and C were 1.16 ± 0.44, 1.95 ± 0.29, and 2.79 ± 0.38, respectively. In the validation group, the AUC for F(x) to distinguish Child-Pugh A from Child-Pugh B and C was 0.973. CONCLUSION Combining multiparametric MRI with LV effectively distinguished patients with different Child Pugh grades. This model could hence be useful as a novel radiological marker to estimate the liver function.
目的 通过结合多参数磁共振成像（MRI）与肝体积（LV）建立肝功能评估模型，并进一步验证该模型评估肝功能的有效性。
方法 本回顾性研究纳入了 101 例连续的肝硬化患者（建模组 69 例，验证组 32 例），均行钆塞酸二钠增强 MRI 检查。在钆塞酸二钠增强前后，通过测量肝脏、脾脏和竖脊肌的信号强度，获得 5 个信号强度参数。通过体素内不相干运动扩散加权成像获得扩散系数（D）、假性扩散系数（D*）和灌注分数（f）。使用三维图像生成软件获得 LV 参数（Vliver、Vspleen 和 Vliver/Vspleen）。从这 3 种方法中，每种方法选择一个最有效的参数，建立并验证肝功能评估的多元回归模型。
结果 在建模组中，相对增强（RE）、D和 Vliver/Vspleen 在不同肝功能组之间存在显著差异（P<0.001）。受试者工作特征分析显示，这些参数在区分 Child-Pugh A 与 Child-Pugh B 和 C 组时具有最高的曲线下面积（AUC）值（分别为 0.917、0.929 和 0.885）。通过多元回归分析得出以下肝功能模型：F（x）=3.96-1.243（RE）-0.034（D）-0.080（Vliver/Vspleen）（R2=0.811，P<0.001）。在肝硬化患者中，Child-Pugh A、B 和 C 的 F（x）分别为 1.16±0.44、1.95±0.29 和 2.79±0.38。在验证组中，F（x）区分 Child-Pugh A 与 Child-Pugh B 和 C 的 AUC 为 0.973。
结论 多参数 MRI 与 LV 相结合可有效区分不同 Child-Pugh 分级的患者。因此，该模型可作为一种新的影像学标志物，用于评估肝功能。
