Objective: To explore the value of radiomics features of liver dynamic contrast enhanced magnetic resonance imaging in evaluating liver reserve function in patients with liver cirrhosis. Methods: A total of 474 patients with cirrhosis who met the inclusion criteria were collected from our hospital from January 2018 to September 2022. According to the Child-Pugh classification standard, they were divided into Child-Pugh A (222 patients) and Child-Pugh B+C (252 patients). Meanwhile, according to the ratio of 7∶3, they were randomly divided into training group and validation group. The 3D Slicer software was used to delineate the region of interest and extract the radiomics features of the portal phase images. The consistency test of the delineation results of the two physicians was performed using the intra-group correlation coefficient. The minimum absolute shrinkage and selection algorithm was used to reduce the dimension of the data and screen the features. The receiver operating characteristic (ROC) curve was used to quantitatively evaluate its diagnostic efficacy. Results: The 1 223 texture feature parameters extracted by 3D Slicer software were used for dimensionality reduction and screening, and finally 18 radiomics feature parameters were obtained. Based on the above characteristics, a radiomics model was constructed, and the area under the ROC curve of the radiomics model in predicting the diagnostic efficacy of liver reserve function in the training group and the validation group was 0.80 and 0.61, respectively. Conclusion: The radiomics features of dynamic contrast enhanced magnetic resonance imaging can accurately evaluate the liver reserve function of patients with cirrhosis. The model can be used as a more accurate and reliable auxiliary detection tool for liver reserve function, which provides a more accurate and three-dimensional new method for clinicians to evaluate the liver reserve function of patients with cirrhosis.
JIANG Shengzhe
,
CHEN Qiang
,
LUO Lin
. Value of liver DCE-MRI radiomics in evaluating liver reserve function for patients with cirrhosis[J]. Journal of Baotou Medical College, 2025
, 41(2)
: 52
-57
.
DOI: 10.16833/j.cnki.jbmc.2025.02.010
[1] Li M, Wang ZQ, Zhang L, et al. Burden of cirrhosis and other chronic liver diseases caused by specific etiologies in china, 1990-2016:findings from the global burden of disease study 2016[J]. Biomed Environ Sci, 2020, 33(1): 1-10.
[2] Li C, Liu H, Wang J, et al. Multiparametric MRI combined with liver volume for quantitative evaluation of liver function in patients with cirrhosis[J]. Diagn Interv Radiol, 2022, 28(6): 547-554.
[3] Ginès P, Krag A, Abraldes JG, et al. Liver cirrhosis[J]. Lancet, 2021, 398(10308): 1359-1376.
[4] Zhou W, Hu HJ, Shen B, et al. Application values of gadolinium-ethoxybenzyl diethylenetriaminepentaacetic acid enhanced magnetic resonance imaging-based radiomics in the quantitative assessment of liver reserve function of patients withliver cirrhosis[J].Zhongguo Yi Xue Ke Xue Yuan Xue Bao, 2020, 42(4): 459-467.
[5] 张喆, 李民, 赵丽琴, 等.基于CT影像组学特征评估肝硬化患者肝脏储备功能[J]. CT理论与应用研究, 2022, 31(1): 55-62.
[6] Abraldes JG, Caraceni P, Ghabril M, et al. Update in the Treatment of the Complications of Cirrhosis[J]. Clin Gastroenterol Hepatol, 2023, 21(8): 2100-2109.
[7] 中华医学会肝病学分会. 肝硬化诊治指南[J]. 现代医药卫生, 2020, 36(2): 320, 1-18.
[8] Gwak GY. Renewed 2015 clinical practice guidelines for management of hepatitis c by Korean association for the study of the liver;what has been changed?Treatment of patients with decompensated cirrhosis[J].Korean J Gastroenterol, 2016, 67(3): 137-141.
[9] Tang G, Liu J, Liu P, et al. Evaluation of liver function in patients with liver cirrhosis and chronic liver dis-ease using functional liver imaging scores at different acquisition time points[J]. Front Genet, 2022, 13: 1071025
[10] Huang Z, Zhang G, Liu J, et al. LRFNet: a deep learning model for the assessment of liver reserve function based on Child-Pugh score and CT image[J]. Comput Methods Programs Biomed, 2022, 223: 106993.
[11] 刘宏, 刘光耀, 周俊林. 肝硬化食管静脉曲张及出血风险影像学研究进展[J]. 磁共振成像, 2021,12(9): 109-112.
[12] Wei Y, Gong J, He X, et al. An MRI-Based Radiomic model for individualized prediction of hepatocellular carcinoma in patients with hepatitis b virus-related cirrhosis[J]. Front Oncol, 2022, 12: 800787.
[13] 周玮, 胡红杰, 沈博, 等. 基于钆塞酸二钠增强磁共振成像影像组学定量评估肝硬化患者肝脏储备功能的应用价值[J]. 中国医学科学院学报, 2020, 42(4): 459-467.
[14] Park HJ, Park B, Lee SS. Radiomics and Deep Learning: Hepatic Applications[J]. Korean J Radiol, 2020, 21(4): 387-401.
[15] Cao JM, Yang JQ, Ming ZQ, et al. A radiomics model of liver CT to predict risk of hepatic encephalopathy secondary to hepatitis B related cirrhosis[J]. Eur J Radiol, 2020, 130: 109201.
[16] Wu J, Xie F, Ji H, et al. A clinical-radiomic model for predicting indocyanine green retention rate at 15 min in patients with hepatocellular carcinoma[J]. Front Surg, 2022, 9: 857838.
[17] 陈敏山. 中国肿瘤整合诊治指南-肝癌(2022精简版)[J]. 中国肿瘤临床, 2022, 49(17): 865-873.
[18] 李宏为, 陈皓. 当代门静脉高压症治疗方法合理选择[J]. 中国实用外科杂志, 2014, 34(1): 24-27.
[19] Nitsch J, Sack J, Halle MW, et al. MRI-based radiomic feature analysis of end-stage liver disease for severity stratification[J]. Int J Comput Assist Radiol Surg, 2021,16(3): 457-466.
[20] 张智星, 黄忠江, 何生, 等. 基于增强CT影像组学评估肝硬化患者肝储备功能的应用[J]. 放射学实践, 2022, 37(6): 676-682.
