CEUS参数联合血清CEA、AFP在肝脏结节良恶性诊断中的应用价值-东南大学学报医学版

CEUS参数联合血清CEA、AFP在肝脏结节良恶性诊断中的应用价值

单位：1. 南京市浦口区中医院, 江苏南京 211800;
2. 高邮市人民医院, 江苏高邮 225600

分类号：R735.7;R445.1

出版年·卷·期（页码）：2026·45·第三期（483-491）

摘要：

目的: 探究超声造影(CEUS)参数联合血清癌胚抗原(CEA)、甲胎蛋白(AFP)诊断肝脏结节良恶性的价值。方法: 选取2022年1月至2024年12月南京市浦口区中医院116例肝脏结节性病变患者为训练集,按照1∶1比例,选取2025年1月至2025年9月南京市浦口区中医院116例肝脏结节性病变患者为验证集。训练集根据肝穿刺组织活检结果分为恶性组(恶性肝脏结节,n=92)和良性组(良性肝脏结节,n=24)。比较两组基线资料、CEUS参数[造影剂到达时间(AT)、达峰时间(TTP)、峰值强度(PI)、拟合曲线尖度、消退时间以及血清CEA、AFP水平,采用受试者工作特征(ROC)曲线、校准曲线、决策曲线分析CEUS参数、血清肿瘤标志物单独诊断肝脏结节良恶性的价值,将CEUS参数联合血清CEA、AFP构建联合模型,分析联合模型诊断肝脏结节良恶性的效能。结果: 恶性组AT、PI均较良性组高,TTP、拟合曲线尖度、消退时间均较良性组低,血清CEA、AFP水平均较良性组高(P＜0.05);AT、TTP、PI、拟合曲线尖度、消退时间以及血清CEA、AFP单独诊断肝脏结节良恶性的ROC曲线下面积(AUC)分别为0.830、0.738、0.802、0.782、0.775、0.776、0.786;基于CEUS参数联合血清CEA、AFP构建联合Logistic回归模型,以该模型生成的预测概率Logit(P)作为联合诊断指标,ROC曲线分析显示,联合模型诊断肝脏结节良恶性的AUC为0.916(95%CI:0.850~0.960),敏感度为84.78%,特异度为87.50%;联合模型诊断的AUC明显大于AT、TTP、PI、拟合曲线尖度、消退时间以及血清CEA、AFP单独诊断的AUC(P＜0.05)。Bootstrap法验证显示联合模型的诊断结果与实际结果贴合度Dxy值=0.901,Hosmer-Lemeshow检验显示P=0.770,校准度较高,决策曲线分析显示联合模型临床效用良好;外部验证显示,联合模型诊断肝脏结节良恶性的AUC为0.880(95%CI:0.803~0.956),敏感度为77.78%,特异度为75.28%,联合模型的诊断结果与实际结果贴合度Dxy值=0.862,Hosmer-Lemeshow检验显示P=0.739,联合模型临床效用良好。结论: 肝脏良、恶性结节患者CEUS参数及血清CEA、AFP均存在明显差异,AT、TTP、PI、拟合曲线尖度、消退时间与血清CEA、AFP联合应用有利于提高对肝脏结节性病变良恶性的诊断价值。

Objective: To explore the value of contrast-enhanced ultrasound(CEUS) parameters combined with serum carcinoembryonic antigen(CEA) and alpha-fetoprotein(AFP) in the diagnosis of benign and malignant liver nodules. Methods: A total of 116 patients with liver nodular lesions(training set) in Nanjing Pukou District Hospital of Traditional Chinese Medicine from January 2022 to December 2024 were selected, 116 patients with liver nodular lesions(validation set) from January 2025 to September 2025 were selected by 1∶1 ratio. The patients in training set were divided into malignant group(malignant liver nodules, n=92) and benign group(benign liver nodules, n=24) according to the results of liver biopsy. The baseline data, CEUS parameters [contrast agent arrival time(AT), time to peak(TTP), peak intensity(PI), fitting curve sharpness, regression time], serum CEA and AFP levels were compared between the two groups. The receiver operating characteristic(ROC) curve, calibration curve and decision curve were used to analyze the value of CEUS parameters and serum tumor markers in the diagnosis of benign and malignant liver nodules. The CEUS quantitative parameters combined with serum CEA and AFP were used to construct a combined model, and the efficacy of the combined model in the diagnosis of benign and malignant liver nodules was analyzed. Results: The AT and PI in the malignant group were higher than those in the benign group, the TTP, the sharpness of the fitting curve and the regression time were lower than those in the benign group, and the serum CEA and AFP levels were higher than those in the benign group(P<0.05). The area under the ROC curve(AUC) of AT, TTP, PI, fitting curve sharpness, regression time, serum CEA and AFP in the diagnosis of benign and malignant liver nodules were 0.830,0.738,0.802,0.782,0.775,0.776 and 0.786, respectively. Based on CEUS parameters combined with serum CEA and AFP, a combined Logistic regression model was constructed. The prediction probability Logit(P) generated by the model was used as the combined diagnostic index. ROC curve analysis showed that the AUC of the combined model in the diagnosis of benign and malignant liver nodules was 0.916(95%CI: 0.850-0.960 ), the sensitivity was 84.78%, and the specificity was 87.50%. The AUC of combined model was significantly greater than that of AT, TTP, PI, fitting curve sharpness, regression time, serum CEA and AFP alone(P<0.05). The Bootstrap method showed that the diagnostic results of the combined model were consistent with the actual results(Dxy value=0.901), and the Hosmer-Lemeshow test showed that P=0.770, the calibration degree was high, and the decision curve analysis showed that the combined model had good clinical efficacy. External validation showed that the AUC of the combined model for the diagnosis of benign and malignant liver nodules was 0.880(95%CI: 0.803-0.956), the sensitivity was 77.78%, and the specificity was 75.28%. The diagnostic results of the combined model were in good agreement with the actual results(Dxy value=0.862, Hosmer-Lemeshow test P=0.739), and the clinical efficacy of the combined model was good. Conclusion: There are significant differences in CEUS quantitative parameters, serum CEA and AFP between patients with benign and malignant liver nodules. The combined application of AT, TTP, PI, fitting curve sharpness, regression time and serum CEA and AFP is helpful to improve the diagnostic value of benign and malignant liver nodules.

参考文献：

[1] HARDIE A D,CHAMBERLIN J H,BOYUM J H,et al.Multi-center follow-up study to develop a classification system which differentiates mucinous cystic neoplasm of the liver and benign hepatic cyst using machine learning[J].Acad Radiol,2022,29(8):1149-1156.
[2] 林赛短,王云,陈家诚,等.肝癌患者疾病接受度现状及影响因素分析[J].现代医学,2023,51(4):468-473.
[3] TANG M,LI Y,LIN Z,et al.Hepatic nodules with arterial phase hyperenhancement and washout on enhanced computed tomography/magnetic resonance imaging:how to avoid pitfalls[J].Abdom Radiol,2020,45(11):3730-3742.
[4] PARK S,YOU M W,KANG H J,et al.Contrast-enhanced ultrasound for focal hepatic lesions:when to use and how to differentiate lesions[J].Ultrasound Q,2020,36(3):224-234.
[5] KANG H J,LEE J M,,et al.Sonazoid^TM versus SonoVue^® for diagnosing hepatocellular carcinoma using contrast-enhanced ultrasound in at-risk individuals:a prospective,single-center,intraindividual,noninferiority study[J].Korean J Radiol,2022,23(11):1067-1077.
[6] 石文龙,孟小玉.血清GPX3、FGFR4联合超声造影定量参数对甲状腺良恶性结节的鉴别诊断价值[J].陕西医学杂志,2025,54(12):1650-1654.
[7] 邢凯,孙晶晶,张鲁,等.超声造影联合血清miR-9-5p、miR-214-5p水平对乳腺结节良恶性的鉴别诊断价值[J].医学影像学杂志,2025,35(11):67-71.
[8] DIETRICH C F,SHI L,LÖWE A,et al.Conventional ultrasound for diagnosis of hepatic steatosis is better than believed[J].Z Gastroenterol,2022,60(8):1235-1248.
[9] 张炜彬,王文平,董怡,等.手术证实的肝脏局灶性结节增生超声造影特征与大小的关系[J].复旦学报(医学版),2021,48(4):463-468.
[10] BREHAR R,MITREA D A,VANCEA F,et al.Comparison of deep-learning and conventional machine-learning methods for the automatic recognition of the hepatocellular carcinoma areas from ultrasound images[J].Sensors,2020,20(11):3085-3086.
[11] 陈永超,周旺,李岩,等.超声造影指导肝穿刺对肝脏占位性病变的诊断价值研究[J].实用肝脏病杂志,2021,24(4):569-572.
[12] HUANG J Y,LI J W,LING W W,et al.Can contrast enhanced ultrasound differentiate intrahepatic cholangiocarcinoma from hepatocellular carcinoma[J].World J Gastroenterol,2020,26(27):3938-3951.
[13] AINORA M E,IEZZI R,PONZIANI F R,et al.Contrast-enhanced ultrasound in the short-term evaluation of hepatocellular carcinoma after locoregional treatment[J].Dig Dis,2020,38(6):522-533.
[14] WATANABE Y,OGAWA M,KUMAGAWA M,et al.Utility of contrast-enhanced ultrasound for early therapeutic evaluation of hepatocellular carcinoma after transcatheter arterial chemoembolization[J].J Ultrasound Med,2020,39(3):431-440.
[15] LIU F,LIU D,WANG K,et al.Deep learning radiomics based on contrast-enhanced ultrasound might optimize curative treatments for very-early or early-stage hepatocellular carcinoma patients[J].Liver Cancer,2020,9(4):397-413.
[16] 孙园园,阮骊韬.超声造影在肝脏占位性病变穿刺活检中的应用价值[J].中国超声医学杂志,2022,38(10):1115-1119.
[17] PARK J,LEE J M,KIM T H,et al.Imaging diagnosis of hepatocellular carcinoma:future directions with special emphasis on hepatobiliary magnetic resonance imaging and contrast-enhanced ultrasound[J].Clin Mol Hepatol,2022,28(3):362-379.
[18] 李加伍,凌文武,陈爽,等.肝脏病灶大小及肝细胞癌分化程度对超声造影肝脏影像报告与数据管理系统分类诊断的影响[J].中国医学影像技术,2022,38(9):1356-1360.
[19] STROBEL D.Using contrast-enhanced ultrasound in the diagnosis of hepatocellular carcinoma-what we have and have not achieved[J].Ultraschall Med,2021,42(2):120-124.
[20] 葛建丽,刘敏洁,徐更田,等.超声造影参数在甲状腺癌诊断中的应用价值及与病灶组织中癌细胞恶性生物学特征的相关性[J].实用癌症杂志,2021,36(2):265-270.
[21] 肖倩,周展,胡小丽.肝细胞癌患者肝内病灶超声造影参数变化[J].实用肝脏病杂志,2022,25(1):92-95.
[22] DONG Y,WANG W P,MAO F,et al.Imaging features of fibrolamellar hepatocellular carcinoma with contrast-enhanced ultrasound[J].Ultraschall Med,2021,42(3):306-313.
[23] 周长航,陈涛,李忍.超声造影中肝脏占位性病变中的图像特征及诊断价值[J].川北医学院学报,2022,37(7):935-938.
[24] EISENBREY J R,GABRIEL H,SAVSANI E,et al.Contrast-enhanced ultrasound(CEUS) in HCC diagnosis and assessment of tumor response to locoregional therapies[J].Abdom Radiol,2021,46(8):3579-3595.
[25] 毛丽娟,曹佳颖,杨敏捷,等.三维超声造影定量分析评价肝细胞肝癌血流灌注的可行性研究[J].中华超声影像学杂志,2021,30(11):932-937.
[26] 韩伟,候雪琴,宋涛,等.肝脏血管周上皮细胞肿瘤与肝细胞肝癌及肝血管瘤的超声特征分析[J].中国临床医学影像杂志,2021,32(5):342-346,355.
[27] RIAZ A,VOGELZANG R,YOUNG V,et al.Endovascular management of acquired hepatic arterial-portal venous malformations[J].CardioVascular Interv Radiol,2020,43(3):466-477.
[28] ALMAGUER J,KHAN A,SALEEM A.Pre-transarterial radioembolizationof tumoral arteriovenous fistula associated with recanalized umbilical vein shuntin a case of hepatocellular carcinoma with hepatic vein and inferior vena CavaInvasion[J].Cureus,2023,15(9):44784-44786.
[29] 刘允刚,徐敏,欧希龙,等.RIPK2是肝细胞癌潜在的新型生物标志物和治疗靶点[J].东南大学学报(医学版),2025,44(1):60-66.
[30] 张利红,李亚莉,吴九阳.血清CEA、AFP对原发性肝癌辅助诊断及分期评估的价值分析[J].实用癌症杂志,2025,40(7):1109-1112.

服务与反馈：

【文章下载】【发表评论】【查看评论】【加入收藏】

提示：您还未登录，请登录！点此登录