切换至 "中华医学电子期刊资源库"

中华肝脏外科手术学电子杂志 ›› 2025, Vol. 14 ›› Issue (04) : 561 -568. doi: 10.3877/cma.j.issn.2095-3232.2025.04.010

临床研究

基于CiteSpace可视化分析MVI预测肝癌预后研究领域的热点及趋势
彭艳红1, 李乐1,2,(), 刘中华2, 刘蕊1, 李鑫1   
  1. 1010000 呼和浩特,内蒙古医科大学
    2024000 内蒙古自治区赤峰市医院肝胆外科
  • 收稿日期:2025-02-16 出版日期:2025-08-10
  • 通信作者: 李乐
  • 基金资助:
    内蒙古医学科学院公立医院科研联合基金(2023GLLH0305); 赤峰市自然科学科研课题(SZR2023076)

CiteSpace-based visualization analysis of hot spots and trends of MVI in prognostic prediction for hepatocellular carcinoma

Yanhong Peng1, Le Li1,2,(), Zhonghua Liu2, Rui Liu1, Xin Li1   

  1. 1Inner Mongolia Medical University, Hohhot 010000, China
    2Department of Hepatobiliary Surgery, Chifeng Municipal Hospital, Chifeng 024000, China
  • Received:2025-02-16 Published:2025-08-10
  • Corresponding author: Le Li
引用本文:

彭艳红, 李乐, 刘中华, 刘蕊, 李鑫. 基于CiteSpace可视化分析MVI预测肝癌预后研究领域的热点及趋势[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(04): 561-568.

Yanhong Peng, Le Li, Zhonghua Liu, Rui Liu, Xin Li. CiteSpace-based visualization analysis of hot spots and trends of MVI in prognostic prediction for hepatocellular carcinoma[J/OL]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2025, 14(04): 561-568.

目的

通过文献计量学可视化分析探讨全球范围内微血管侵犯(MVI)预测肝细胞癌(HCC)预后的热点与趋势。

方法

文献检索2014年1月至2024年3月Web of Science数据库中MVI预测肝癌预后的相关文章,文献类型包括article和review,语种:English。采用CiteSpace软件从发表文献的年份、作者、机构、国家、期刊及关键词等方面进行统计和可视化分析。

结果

2014年至2024年HCC-MVI研究领域的发文量共计1 778篇,总体呈逐年上升趋势,被引频次6 843。共49个国家参与发文,发文量最高的5个国家分别是中国1 156篇、美国176篇、韩国157篇、日本119篇、意大利85篇。该领域的发文量主要集中在欧洲、亚洲、南美洲。中国发文量最多,最活跃的国家和机构分别是中国和中国海军军医大学。最活跃和被引用最多的作者分别是Lau WY和Bruix J。中国机构的国际合作较少,而美国中心度最高且与其他国家的合作更加紧密。共同引用网络中关键节点的聚类和时间线视图显示,从2014年开始研究热点持续时间最长是血管形成,而近两年最新出现的频次最高的相关关键词是预测模型。关键词的突显图显示,2021年以前主要围绕生物标志物、肝移植和手术切除的选择展开。2014年开始肝切除术后的复发和预后是研究的重点。2015年开始出现关于HCC的生物标志物及长期生存率,还有预测因子相关研究一直持续爆发。最近,该领域的兴趣开始转向关于HCC的影像组学学习及其相关列线图计算。影像组学及列线图计算是近3年突显的关键词,是目前HCC-MVI领域的重要研究方向。

结论

基于CiteSpace可视化分析显示,近10年来MVI预测肝癌切除术后的预后相关研究不断发展,血管问题一直受到关注,随着影像组学的发展,影像方面的模型构建备受关注。

Objective

To investigate the hot spots and trends of microvascular invasion (MVI) in predicting clinical prognosis of hepatocellular carcinoma (HCC) worldwide through bibliometric and visual analysis.

Methods

Studies related to MVI in predicting clinical prognosis of HCC were obtained from Web of Science core literature database from January 2014 to March 2024. Study types included article and review in English. Statistical and visual analyses of the published articles were performed from the aspects of year, author, institution, country, journal and keywords by using CiteSpace software.

Results

From 2014 to 2024, 1 778 articles were published in the field of HCC-MVI research, showing an overall increasing trend year by year, with a citation frequency of 6 843. These articles were published from 49 countries. The five countries with the highest number of articles were China (1 156), the United States (176), South Korea (157), Japan (119) and Italy (85), mainly from Europe, Asia and North America. The most active country was China and the most active institution was Naval Medical University from China. The most active and cited authors were Lau WY and Bruix J. Chinese institutions conducted less international cooperation, while other countries carried out closer cooperation. The United States had the highest degree of centralization and closer cooperation with other countries. The clustering and timeline map of key nodes in the co-cited network showed that angiogenesis has been the hotspot with the longest duration of research since 2014. Prediction model was the latest keyword with the highest frequency in recent two years. The highlight map of keywords revealed that before 2021, studies mainly focused on biomarkers, liver transplantation and the selection of surgical resection. The recurrence and prognosis after hepatectomy were the hot spots after 2014. In 2015, HCC-related biomarkers and long-term survival rate became the hot spots. The number of predictor-related studies has been significantly increased. Recently, the interests in this field began to shift to radiomics study of HCC and related nomogram calculation. Radiomics and nomogram calculation were the prominent keywords in recent three years, which are currently the important research directions in HCC-MVI field.

Conclusions

CiteSpace-based visualization analysis shows that the research on MVI in predicting clinical prognosis of HCC after surgical resection has been ever advanced in recent decade. Vascular disease has drawn widespread attention. With the advancement of radiomics, the construction of radiomic models captivates extensive attention.

图1 2014年至2024年HCC-MVI研究领域的年发文量注:MVI为微血管侵犯,HCC为肝细胞癌
图2 HCC-MVI研究文献的合作网络分析图谱注:a为发文国家合作网络分析,b为发文机构合作网络分析,c为发文作者合作网络分析,d为被引作者合作网络分析;合作网络分析图中,圆形大小代表发文量,越外层越浅色的圆弧代表着年份越近,线条粗细代表着合作密度,最外层紫色代表着高中心度;MVI为微血管侵犯,HCC为肝细胞癌
图3 HCC-MVI研究领域发文量和中心度前5名的国家和机构注:MVI为微血管侵犯,HCC为肝细胞癌
表1 HCC-MVI研究领域高发文量前十名作者和被引作者
表2 HCC-MVI研究领域引文量前五名的文献
图4 HCC-MVI研究领域高频关键词时间线视图注:在时间线视图中,左侧的节点表示较旧的引用,右侧的节点表示较新的引用,同一水平位置的直线表示属于该簇的所有参照的集合,聚类标签位于线的最右端;MVI为微血管侵犯,HCC为肝细胞癌
图5 HCC-MVI研究领域引用爆发最强的前25个关键词注:MVI为微血管侵犯,HCC为肝细胞癌
[1]
Shen J, Wen J, Li C, et al. The prognostic value of microvascular invasion in early-intermediate stage hepatocelluar carcinoma: a propensity score matching analysis[J]. BMC Cancer, 2018, 18(1): 278. DOI: 10.1186/s12885-018-4196-x.
[2]
Huang C, Zhu XD, Ji Y, et al. Microvascular invasion has limited clinical values in hepatocellular carcinoma patients at Barcelona Clinic Liver Cancer (BCLC) stages 0 or B[J]. BMC Cancer, 2017, 17(1): 58. DOI: 10.1186/s12885-017-3050-x.
[3]
Zhang K, Zhang L, Li WC, et al. Radiomics nomogram for the prediction of microvascular invasion of HCC and patients’ benefit from postoperative adjuvant TACE: a multi-center study[J]. Eur Radiol, 2023, 33(12): 8936-8947. DOI: 10.1007/s00330-023-09824-5.
[4]
Yang L, Gu D, Wei J, et al. A radiomics nomogram for preoperative prediction of microvascular invasion in hepatocellular carcinoma[J]. Liver Cancer, 2019, 8(5): 373-386. DOI: 10.1159/000494099.
[5]
中华人民共和国国家卫生健康委员会医政司.原发性肝癌诊疗指南(2024年版)[J/OL].中华肝脏外科手术学电子杂志, 2024, 13(4): 407-449. DOI: 10.3877/cma.j.issn.2095-3232.2024.04.001.
[6]
刘建生, 吕永波, 任远, 等. 中国技术预测(预见)研究脉络与热点追踪——基于CiteSpace的文献计量分析[J]. 中国科技论坛, 2023(6): 29-40. DOI: 10.13580/j.cnki.fstc.2023.06.011.
[7]
袁媛,陈平.国内外热环境的研究热点及进展趋势——基于CiteSpace的可视化分析[J].中外建筑,2024,(11):108-115.DOI: 10.19940/j.cnki.1008-0422.2024.11.017.
[8]
Hirsch JE. An index to quantify an individual’s scientific research output[J]. Proc Natl Acad Sci USA, 2005, 102(46): 16569-16572. DOI: 10.1073/pnas.0507655102.
[9]
Lei Z, Li J, Wu D, et al. Nomogram for preoperative estimation of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma within the Milan criteria[J]. JAMA Surg, 2016, 151(4): 356-363. DOI: 10.1001/jamasurg.2015.4257.
[10]
Xu X, Zhang HL, Liu QP, et al. Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma[J]. J Hepatol, 2019, 70(6): 1133-1144. DOI: 10.1016/j.jhep.2019.02.023.
[11]
Zhang C, Zhong H, Zhao F, et al. Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: machine learning model based on contrast-enhanced computed tomography[J]. World J Gastrointest Oncol, 2024, 16(3): 857-874. DOI: 10.4251/wjgo.v16.i3.857.
[12]
Jolissaint JS, Wang T, Soares KC, et al. Machine learning radiomics can predict early liver recurrence after resection of intrahepatic cholangiocarcinoma[J]. HPB, 2022, 24(8): 1341-1350. DOI: 10.1016/j.hpb.2022.02.004.
[13]
Ouyang X, Yan Y, Zhang S, et al. Microvascular invasion is associated with poor survival in patients with dual-phenotype hepatocellular carcinoma[J]. Am J Clin Pathol, 2024, 161(3): 245-255. DOI: 10.1093/ajcp/aqad143.
[14]
Xie Q, Zhao Z, Yang Y, et al. Radiomics-guided prognostic assessment of early-stage hepatocellular carcinoma recurrence post-radical resection[J]. J Cancer Res Clin Oncol, 2023, 149(16): 14983-14996. DOI: 10.1007/s00432-023-05291-z.
[15]
王培宇,黄祺,王少东,等.《全球癌症统计数据2022》要点解读[J].中国胸心血管外科临床杂志,2024,31(7):933-954. DOI: 10.7507/1007-4848.202405013.
[16]
Zhao X, Wang Y, Xia H, et al. Roles and molecular mechanisms of biomarkers in hepatocellular carcinoma with microvascular invasion: a review[J]. J Clin Transl Hepatol, 2023, 11(5): 1170-1183. DOI: 10.14218/JCTH.2022.00013S.
[17]
Liu MT, Zhang JY, Xu L, et al. A multivariate model based on gadoxetic acid-enhanced MRI using Li-RADS v2018 and other imaging features for preoperative prediction of dual-phenotype hepatocellular carcinoma[J]. Radiol Med, 2023, 128(11): 1333-1346. DOI: 10.1007/s11547-023-01715-5.
[18]
Ji GW, Zhu FP, Xu Q, et al. Radiomic features at contrast-enhanced CT predict recurrence in early stage hepatocellular carcinoma: a multi-institutional study[J]. Radiology, 2020, 294(3): 568-579. DOI: 10.1148/radiol.2020191470.
[19]
Kaibori M, Ishizaki M, Matsui K, et al. Predictors of microvascular invasion before hepatectomy for hepatocellular carcinoma[J]. J Surg Oncol, 2010, 102(5): 462-468. DOI: 10.1002/jso.21631.
[20]
Lv K, Cao X, Du P, et al. Radiomics for the detection of microvascular invasion in hepatocellular carcinoma[J]. World J Gastroenterol, 2022, 28(20): 2176-2183. DOI: 10.3748/wjg.v28.i20.2176.
[21]
Wu C, Yu S, Zhang Y, et al. CT-based radiomics nomogram improves risk stratification and prediction of early recurrence in hepatocellular carcinoma after partial hepatectomy[J]. Front Oncol, 2022, 12: 896002. DOI: 10.3389/fonc.2022.896002.
[22]
Balachandran VP, Gonen M, Joshua Smith J, et al. Nomograms in oncology: more than meets the eye[J]. Lancet Oncol, 2015, 16(4): e173-e180. DOI: 10.1016/S1470-2045(14)71116-7.
[23]
Lv B, Wang H, Zhang Z, et al. Nomogram for predicting postoperative deep vein thrombosis in patients with spinal fractures caused by high-energy injuries[J]. Arch Orthop Trauma Surg, 2024, 144(1): 171-177. DOI: 10.1007/s00402-023-05085-5.
[24]
Panaiyadiyan S, Kumar R. Prostate cancer nomograms and their application in Asian men: a review[J]. Prostate Int, 2024, 12(1): 1-9. DOI: 10.1016/j.prnil.2023.07.004.
[25]
Mahajan A, Shukla S, Vaish R, et al. Editorial: editor’s challenge: Abhishek Mahajan - how can precision oncology be advanced with validated imaging-based nomograms?[J]. Front Oncol, 2024, 14: 1362187. DOI: 10.3389/fonc.2024.1362187.
[1] 顾怡君, 李奕冉, 钱艺, 蒋栋. 基于超声造影定量指标预测肝细胞癌微血管侵犯及评估其复发的研究[J/OL]. 中华医学超声杂志(电子版), 2025, 22(05): 451-461.
[2] 邱益霖, 何坤. 肝细胞癌合并门静脉癌栓的治疗进展[J/OL]. 中华普通外科学文献(电子版), 2025, 19(03): 197-202.
[3] 卢超, 陈波, 邢志祥, 周鹏, 王帅. 不同入路下腹腔镜解剖性肝脏切除术治疗肝细胞癌的临床对比[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(03): 254-257.
[4] 韦洋, 赵远权, 王小波, 黄海, 陈洁. BCLC 0/A期肝细胞癌患者术后辅助治疗后早期复发风险分析及预测模型建立[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(02): 157-161.
[5] 陈明付, 王庆惠, 纪辉涛, 陈银珍, 余小娟, 陈怀章, 赵虎, 王瑜. 基于CiteSpace 对结直肠癌铁死亡研究现状的可视化分析[J/OL]. 中华细胞与干细胞杂志(电子版), 2025, 15(03): 179-189.
[6] 杨钰泽, 徐家豪, 杨一石, 王明达, 杨田. 肝细胞癌新辅助治疗进展[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(04): 515-521.
[7] 罗臻, 韦鹏程, 孙馨, 李照. 肝细胞癌骨转移研究进展[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(04): 522-527.
[8] 王楚斯, 刘家伟, 卢逸, 汤照峰. ICG荧光显影在腹腔镜肝癌切除术中临床应用[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(04): 549-553.
[9] 匡嘉文, 陈铁军, 龚远锋, 唐辉, 唐云强. TACE-HAIC联合仑伐替尼和PD-1抑制剂四联治疗Ⅲa期肝癌的疗效[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(04): 554-560.
[10] 龙吟, 何晓东, 廖建国, 黄珏, 张磊. 高复发风险肝癌患者术后靶向免疫治疗的安全性及疗效[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(03): 379-386.
[11] 张宏斌, 杨振宇, 谭凯, 刘冠, 尚磊, 杜锡林. 不可切除肝癌转化治疗后手术的影响因素及预测模型构建[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(03): 387-394.
[12] 甘翌翔, 欧阳俐颖, 潘扬勋, 张耀军, 陈敏山, 徐立. ICGR15和ALBI评分对肝动脉灌注化疗后肝癌肝切除术后肝衰竭和预后的预测价值[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(03): 395-401.
[13] 张铭燊, 胡永威, 陈德盛, 俞浩远, 梁智星, 陈玉涛, 叶林森, 李华, 杨扬. CEBPZOS通过调控肿瘤增殖与迁移促进肝癌进展的机制研究[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(03): 463-470.
[14] 吴春霖, 侯一夫, 陈凯, 赵冀, 唐世杰, 杨洪吉. 肝动脉灌注化疗联合PD-1/TKI 治疗不可切除性肝癌的安全性和疗效[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(02): 217-224.
[15] 管昊琳, 周嘉奕, 田天宁, 唐慧珍, 叶亮. 基于1995—2024年Web of Science数据库的支气管胸膜瘘的文献计量学分析[J/OL]. 中华胸部外科电子杂志, 2025, 12(02): 83-95.
阅读次数
全文


摘要