实用肝脏病杂志 ›› 2024, Vol. 27 ›› Issue (4): 611-614.doi: 10.3969/j.issn.1672-5069.2024.04.030

• 肝癌 • 上一篇    下一篇

CT定量参数鉴别诊断肝局灶性结节增生与肝细胞癌的价值研究*

隋虎, 毛佳, 陈露, 王超逸, 兰邦涛   

  1. 430023 武汉市 华中科技大学同济医学院附属武汉金银潭医院放射科(隋虎,毛佳,陈露,王超逸);十堰市太和医院放射科(兰邦涛)
  • 收稿日期:2023-07-07 出版日期:2024-07-10 发布日期:2024-07-10
  • 通讯作者: 兰邦涛,E-mail:hb19sh87@163.com
  • 作者简介:隋虎,男,37岁,大学本科,主治医师。研究方向:临床放射学诊断。E-mail:hb19sh87@163.com
  • 基金资助:
    *武汉市科技局医学科研项目(编号:WX21C20)

Application of CT quantitative parameters in the differentiation of hepatocellular carcinoma from focal nodular hyperplasia

Sui Hu, Mao Jia, Chen Lu, et al   

  1. Department of Radiology, Jinyintan Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430023, Hubei Province, China
  • Received:2023-07-07 Online:2024-07-10 Published:2024-07-10

摘要: 目的 探讨CT定量参数鉴别诊断肝局灶性结节性增生(FNH)与肝细胞癌(HCC)的价值。方法 2017年8月~2022年8月我院诊治的HCC患者51例和同期就诊的FNH患者41例,均接受病理学检查及CT平扫和灌注增强扫描,记录两组CT定量参数肝血容量(HBV)、肝血流量(HBF)、肝动脉灌注量(HAP)、门静脉灌注量(PVP)、总肝灌注量(TLP)、肝动脉灌注指数(HPI)和平均通过时间(mTT)。应用ROC曲线评估CT参数诊断HCC的价值,一致性分析采用Kappa检验。结果 HCC组HBV、HBF和PVP水平分别为(31.9±10.1)mL/100mL、(204.7±66.3)mL/(100mL·min)和(22.8±6.4)mL/(100mL·min),均显著高于FNH组【分别为(21.4±6.8)mL/100mL、(115.7±33.9)mL/(100mL·min)和(9.2±3.0)mL/(100mL·min),P<0.05】,而HAP、HPI和mTT水平分别为(42.8±12.7)mL/(100mL·min)、(64.1±10.7)%和(5.3±1.5)s,均显著低于FNH组【分别为(61.8±20.4)mL/(100mL·min)、(87.5±6.1)%和(8.2±2.4)s,P<0.05】;经ROC分析发现,应用CT参数HBV、HBF、HAP、PVP、HPI和mTT能够诊断HCC,其曲线下面积(AUC)分别为0.787、0.951、0.811、0.915、0.949和0.841(均P<0.05);经一致性分析,HBV、HBF、HAP、PVP、HPI和mTT联合诊断HCC的灵敏度为0.941,特异度为0.976,准确率为0.957,Kappa=0.912。结论 应用CT扫描参数可帮助鉴别诊断FNH与HCC,在临床上有很大的实用价值。

关键词: 肝细胞癌, 肝脏局灶性结节性增生, CT定量参数, 肝血流量, 诊断

Abstract: Objective The aim of this study was to investigate the performance of CT quantitative parameters in the differential diagnosis of focal nodular hyperplasia (FNH) and hepatocellular carcinoma (HCC). Methods Fifty-one patients with HCC and forty-one patients with FNH were encountered in our hospital between August 2017 and August 2022, and the diagnosis was proved by histo-pathological examination. All patients underwent CT plain scan and perfusion scan, and the CT quantitative parameters, including hepatic blood volume (HBV), hepatic blood flow (HBF), hepatic artery perfusion (HAP), portal vein perfusion (PVP), total liver perfusion (TLP), hepatic artery perfusion index (HPI) and mean transit time (mTT), were recorded. The diagnostic efficacy was analyzed by ROC curve, and the diagnostic accuracy was analyzed by Kappa consistency. Results The HBV, HBF and PVP in cancerous foci were (31.9±10.1)mL/100mL,(204.7±66.3)mL/(100mL·min) and (22.8±6.4)mL/(100mL·min), all significantly higher than [(21.4±6.8)mL/100mL, (115.7±33.9)mL/(100mL·min) and (9.2±3.0)mL/(100mL·min), P<0.05], while the HAP, HPI and mTT were (42.8±12.7)mL/(100mL·min), (64.1±10.7)% and (5.3±1.5)s, all significantly lower than [(61.8±20.4)mL/(100mL·min), (87.5±6.1)% and (8.2±2.4)s, respectively, P<0.05] in foci of FNH; the ROC analysis showed that the AUCs were 0.787, 0.951, 0.811, 0.915, 0.949 and 0.841(all P<0.05), when the HBV, HBF, HAP, PVP, HPI and mTT were applied to predict HCC; the Kappa consistency demonstrated that the sensitivity, specificity and accuracy were 0.941, 0.976 and 0.957 (Kappa=0.912) when the combination of HBV, HBF, HAP, PVP, HPI and mTT was applied for the diagnosis of HCC. Conclusion The differentiating diagnosis of HCC from FNH by CT quantitative parameters is efficacious, which might greatly help appropriate management in clinical practice.

Key words: Hepatoma, Focal nodular hyperplasia of liver, CT quantitative parameters, Hepatic blood flow, Diagnosis