Article(id=1322210923205472765, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322210840242139234, articleNumber=null, orderNo=null, doi=10.16016/j.2097-0927.202411115, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732550400000, receivedDateStr=2024-11-26, revisedDate=1734364800000, revisedDateStr=2024-12-17, acceptedDate=null, acceptedDateStr=null, onlineDate=1793169249583, onlineDateStr=2026-10-28, pubDate=1744646400000, pubDateStr=2025-04-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793169249583, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793169249583, creator=13701087609, updateTime=1793169249583, updator=13701087609, issue=Issue{id=1322210840242139234, tenantId=1146029695717560320, journalId=1319373162502258839, year='2025', volume='47', issue='7', pageStart='629', pageEnd='748', issueExtLink='null', onlineDate='null', pubDate='1744646400000', pubDateStr='2025-04-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793169229803, creator='13701087609', updateTime=1793325214855, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322865089049383299, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322210840242139234, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322865089049383300, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322210840242139234, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=708, endPage=719, ext={EN=ArticleExt(id=1322210923582960126, articleId=1322210923205472765, tenantId=1146029695717560320, journalId=1319373162502258839, language=EN, title=Clinical value and prognosis analysis of enhanced CT preoperative diagnosis for proliferative hepatocellular carcinoma, columnId=1320435174995772212, journalTitle=Journal of Army Medical University, columnName=Clinical Medicine, runingTitle=null, highlight=null, articleAbstract=
Objective

To construct a preoperative prediction model for proliferative hepatocellular carcinoma(HCC) based on enhanced CT image features, and to analyze the prognosis of the disease.

Methods‍

A retrospective case-control study was conducted on 603 patients with pathologically confirmed HCC. Among them, 519 cases from the First Affiliated Hospital of Army Medical University were randomly divided into a training group(n=363) and an internal verification group(n=156) in a ratio of 7:3. Another 84 patients from the Second Affiliated Hospital of Chongqing Medical University served as an external validation group. All patients underwent abdominal CT scan with contrast before surgery. The clinical data and CT imaging characteristics of proliferative and non-proliferative HCC patients were observed. Binary logistic regression analysis was used to identify the independent risk factors of proliferative HCC, and a nomogram prediction model was constructed. Receiver operating characteristic(ROC) curve was plotted to evaluate its diagnostic performance, and calibration curve and decision curve analysis(DCA) were applied to evaluate its calibration performance and clinical application value. The model was validated in both the internal and external validation groups. Kaplan-Meier survival curves were employed to compare the prognosis between proliferative and non-proliferative HCC.

Results‍

Multivariate analysis showed that negative result of HBV-DNA quantification, incomplete tumor capsule, intratumoral necrosis or ischemia(≥20%), and annular hyperenhancement in arterial phase were independent predictors in predicting proliferative HCC(P<0.05). Our nomogram model for predicting proliferative HCC based on the above clinical imaging features had an AUC value of 0.805(95%CI: 0.756~0.854), a sensitivity of 83.19% and a specificity of 64.80% in the training group. For the internal validation group, the AUC value was 0.793(95%CI: 0.721~0.854), the sensitivity was 67.86%, and the specificity was 75.00%. In the external validation group, the AUC value was 0.842(95%CI: 0.746~0.912), the sensitivity was 72.41%, and the specificity was 90.91%. Calibration curve and DCA showed that the model had good calibration performance and clinical applicability. The disease free survival(DFS) of the patients with proliferative HCC diagnosed by pathologically confirmed/predictive models was significantly shorter than that of non-proliferative HCC patients(training group: P=0.005, P<0.001; internal validation group: P=0.006, P=0.006; external validation group: P=0.002, P=0.015).

Conclusion‍

Our prediction model based on clinical and imaging features can accurately diagnose proliferative HCC before surgery, and the prognosis of proliferative HCC is generally poor.

, authors=Jie CHENG1, 2, Xiaofan WEI1, Wei CHEN2, Xiaolong YE3, Wei ZHANG1, authorsList=Jie CHENG, Xiaofan WEI, Wei CHEN, Xiaolong YE, Wei ZHANG, authorCompany=null, correspAuthors=Wei ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=© 2025 Journal of Army Medical University, copyrightOwner=Editorial Office of Journal of Army Medical University, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322210927789847051, articleId=1322210923205472765, tenantId=1146029695717560320, journalId=1319373162502258839, language=CN, title=基于增强CT术前诊断增殖型肝细胞癌的临床价值及预后分析, columnId=1322185541475488183, journalTitle=陆军军医大学学报, columnName=临床医学, runingTitle=null, highlight=null, articleAbstract=

‍

目的

基于增强CT影像特征构建增殖型肝细胞癌(hepatocellular carcinoma,HCC)的术前预测模型并进行预后分析。

方法

采用回顾性病例-对照研究方法。共纳入经病理证实为HCC的患者603例;其中陆军军医大学第一附属医院519例,以7:3的比例随机分为训练组(n=363)和内部验证组(n=156);将重庆医科大学附属第二医院84例患者作为外部验证组。患者术前均行腹部CT增强检查,观察增殖型与非增殖型HCC患者临床资料情况及CT影像学特征。采用二元Logistic回归分析筛选增殖型HCC的独立危险因素,构建列线图预测模型,通过受试者工作特征曲线(receiver operating characteristic curve,ROC)、ROC曲线下面积(area under curve,AUC)评价其诊断效能,绘制校准曲线、决策曲线(decision curve analysis,DCA)评估列线图模型的校准性能和临床应用价值,并在内部验证组和外部验证组对模型进行验证。使用Kaplan-Meier生存曲线对比增殖型和非增殖型HCC的预后。

结果

多因素分析结果示乙型肝炎病毒脱氧核糖核酸(hepatitis B virus deoxyribonucleic acid,HBV-DNA)定量阴性、肿瘤包膜不完整、瘤内坏死或缺血(≥20%)、动脉期环形高强化是预测增殖型HCC的独立预测因子(P<0.05)。基于以上临床影像特征绘制预测增殖型HCC的列线图,在训练组AUC为0.805(95%CI:0.756~0.854),敏感度83.19%,特异度64.80%;在内部验证组中,AUC为0.793(95%CI:0.721~0.854),敏感度67.86%,特异度75.00%;在外部验证组中,AUC为0.842(95%CI:0.746~0.912),敏感度72.41%,特异度90.91%;校准曲线、DCA曲线示列线图模型的校准性能和临床适用性均较好。经病理证实/预测模型诊断的增殖型HCC患者术后无病生存期(disease free survival,DFS)均显著低于非增殖型HCC(训练组:P=0.005,P<0.001;内部验证组:P=0.006,P=0.006;外部验证组:P=0.002,P=0.015)。

结论

基于临床与影像特征构建的预测模型能较准确术前诊断增殖型HCC,且增殖型HCC预后较差。

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张维,E-mail:
ZHANG Wei,E-mail:
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Gastroenterology,2016,151(5):986-998.e4., articleTitle=HBV DNA integration and clonal hepatocyte expansion in chronic hepatitis B patients considered immune tolerant, refAbstract=null), Reference(id=1322210953664508533, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, doi=10.1007/s00330-022-08643-4, pmid=null, pmcid=null, year=2022, volume=32, issue=8, pageStart=5119, pageEnd=5133, url=null, language=null, rfNumber=31, rfOrder=32, authorNames=YOON J K, CHOI J Y, RHEE H, journalName=Eur Radiol, refType=null, unstructuredReference=YOON J K,CHOI J Y,RHEE H,et al. MRI features of histologic subtypes of hepatocellular carcinoma:correlation with histologic,genetic,and molecular biologic classification[J]. Eur Radiol,2022,32(8):5119-5133., articleTitle=MRI features of histologic subtypes of hepatocellular carcinoma:correlation with histologic,genetic,and molecular biologic classification, refAbstract=null), Reference(id=1322210953811309174, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, doi=10.1148/radiol.230457, pmid=null, pmcid=null, year=2023, volume=308, issue=2, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=32, rfOrder=33, authorNames=BAO Y, LI J X, ZHOU P, journalName=Radiology, refType=null, unstructuredReference=BAO Y,LI J X,ZHOU P,et al. Identifying proliferative hepatocellular carcinoma at pretreatment CT:implications for therapeutic outcomes after transarterial chemoem-bolization[J]. Radiology,2023,308(2):e230457., articleTitle=Identifying proliferative hepatocellular carcinoma at pretreatment CT:implications for therapeutic outcomes after transarterial chemoem-bolization, refAbstract=null), Reference(id=1322210953916166775, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, doi=10.1186/s12967-024-05393-3, pmid=null, pmcid=null, year=2024, volume=22, issue=1, pageStart=683, pageEnd=null, url=null, language=null, rfNumber=33, rfOrder=34, authorNames=WANG G Z, DING F E, CHEN K G, journalName=J Transl Med, refType=null, unstructuredReference=WANG G Z,DING F E,CHEN K G,et al. CT-based radiomics nomogram to predict proliferative hepatocellular carcinoma and explore the tumor microenvironment[J]. 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J Hepatocell Carcinoma,2023,10:2059-2071., articleTitle=Prognostic factors for patients with proliferative hepatocellular carcinoma after liver resection, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322210928066671117, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, xref=1, ext=[AuthorCompanyExt(id=1322210928075059726, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, companyId=1322210928066671117, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Department of Radiology,the Second Affiliated Hospital of Chongqing Medical University,Chongqing), AuthorCompanyExt(id=1322210928083448335, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, companyId=1322210928066671117, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1重庆医科大学附属第二医院放射科,重庆;)]), AuthorCompany(id=1322210929740198416, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, xref=2, ext=[AuthorCompanyExt(id=1322210929748587025, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, companyId=1322210929740198416, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2Department of Radiology,Research Center for 7T Magnetic Resonance Translational Medicine,Chongqing,China), AuthorCompanyExt(id=1322210929756975634, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, companyId=1322210929740198416, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2陆军军医大学(第三军医大学)第一附属医院:7T磁共振转化医学研究中心/放射科)]), AuthorCompany(id=1322210929874416147, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, xref=3, ext=[AuthorCompanyExt(id=1322210929882804756, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, companyId=1322210929874416147, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3Department of Pathology,First Affiliated Hospital,Army Medical University(Third Military Medical University),Chongqing,China), AuthorCompanyExt(id=1322210929891193365, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, companyId=1322210929874416147, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3陆军军医大学(第三军医大学)第一附属医院:病理科,重庆)])], figs=[ArticleFig(id=1322210936140706360, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=Bkb8yajXyhLFQcWg+OQ0NA==, figureFileBig=HBW/TG6hU/iQuL7us/VakA==, tableContent=null), ArticleFig(id=1322210936459473465, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=图1, caption=603例HCC患者纳入流程图, figureFileSmall=Bkb8yajXyhLFQcWg+OQ0NA==, figureFileBig=HBW/TG6hU/iQuL7us/VakA==, tableContent=null), ArticleFig(id=1322210938577596988, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=7vpODfo5sLmtJWwiAHl+wA==, figureFileBig=wC6l/+Cy7AQgSvpNaGXn8Q==, tableContent=null), ArticleFig(id=1322210938648900157, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=图2, caption=增殖型HCC增强CT影像及病理表现

A:增强CT平扫;B:增强CT动脉期;C:增强CT门静脉期;D:增强CT平衡期;E~F:肿瘤细胞HE染色

, figureFileSmall=7vpODfo5sLmtJWwiAHl+wA==, figureFileBig=wC6l/+Cy7AQgSvpNaGXn8Q==, tableContent=null), ArticleFig(id=1322210938707620414, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=Rj67ORqhYvghMWlx5zxdOQ==, figureFileBig=jg5i1HRLWE1YAZPy+zxumA==, tableContent=null), ArticleFig(id=1322210938976055871, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=图3, caption=非增殖型HCC增强CT影像及病理表现

A:增强CT平扫;B:增强CT动脉期;C:增强CT门静脉期;D:增强CT平衡期;E~F:肿瘤细胞HE染色

, figureFileSmall=Rj67ORqhYvghMWlx5zxdOQ==, figureFileBig=jg5i1HRLWE1YAZPy+zxumA==, tableContent=null), ArticleFig(id=1322210939387097664, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=sR2vr8e1Tt2UYL5rmCL1XQ==, figureFileBig=Z2F1z4Z0R1gaFpzdO14N3g==, tableContent=null), ArticleFig(id=1322210939475178049, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=图4, caption=增殖型HCC患者的临床影像联合预测模型列线图, figureFileSmall=sR2vr8e1Tt2UYL5rmCL1XQ==, figureFileBig=Z2F1z4Z0R1gaFpzdO14N3g==, tableContent=null), ArticleFig(id=1322210939810722370, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=YRCIBYr4WdyqcEgMPCKB0A==, figureFileBig=R0nSTHPAl1y3ZRhAb5VmOQ==, tableContent=null), ArticleFig(id=1322210939877831235, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=图5, caption=训练组、内部验证组、外部验证组预测增殖型HCC的ROC曲线、校准曲线和决策曲线

A:训练组ROC曲线下面积;B:训练组校准曲线;C:训练组决策曲线;D:内部验证组ROC曲线下面积;E:内部验证组校准曲线;F:内部验证组决策曲线;G:外部验证组ROC曲线下面积;H:外部验证组校准曲线;I:外部验证组决策曲线

, figureFileSmall=YRCIBYr4WdyqcEgMPCKB0A==, figureFileBig=R0nSTHPAl1y3ZRhAb5VmOQ==, tableContent=null), ArticleFig(id=1322210939936551492, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=1UM+d4aZMTOxqqMq8KH/ng==, figureFileBig=LaQLQyfOW5kOD1Jhud0kQg==, tableContent=null), ArticleFig(id=1322210940267901509, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=图6, caption=训练组、内部验证组、外部验证组分别在病理模型和预测模型的生存曲线

A:训练组病理生存曲线;B:内部验证组病理生存曲线;C:外部验证组病理生存曲线;D:训练组预测模型生存曲线;E:内部验证组预测模型生存曲线;F:外部验证组预测模型生存曲线

, figureFileSmall=1UM+d4aZMTOxqqMq8KH/ng==, figureFileBig=LaQLQyfOW5kOD1Jhud0kQg==, tableContent=null), ArticleFig(id=1322210940368564806, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
临床指标训练组内部验证组外部验证组
非增殖型HCC(n=250)增殖型HCC
(n=113)
P值非增殖型HCC
(n=100)
增殖型HCC
(n=56)
P值非增殖型HCC
(n=55)
增殖型HCC
(n=29)
P值
性别0.0740.0860.429
女性45(18.00)12(10.62)14(14.00)14(25.00)11(20.00)8(27.59)
男性205(82.00)101(89.38)86(86.00)42(75.00)44(80.00)21(72.41)
年龄/岁55±1153±110.06455±1054±130.74459±1054±110.045
抗病毒治疗病史0.0950.0740.327
无156(62.40)60(53.10)68(68.00)30(53.57)36(65.45)22(75.86)
有94(37.60)53(46.90)32(32.00)26(46.43)19(34.55)7(24.14)
乙肝表面抗原0.2630.1250.691
阳性215(86.00)92(81.42)82(82.00)51(91.07)42(76.36)21(72.41)
阴性35(14.00)21(18.58)18(18.00)5(8.93)13(23.64)8(27.59)
白蛋白/(g/L)39.6±5.839.7±5.80.93639±639±70.70738.6±6.739.1±5.50.713
碱性磷酸酶/(IU/L)84(67,105)86(67,109)0.61785(68,110)90(79,103)0.39687(74,107)82(74,118)0.959
谷氨酰转肽酶/(IU/L)45(28,74)49(35,85)0.03345(30,71)42(24,72)0.51956(36,87)62(34,83)0.955
活化部分凝血活酶时间/s27.28±2.4827.68±2.710.18527.44±2.6427.51±2.360.86428.11±2.4527.61±2.980.440
国际标准化比值1.01±0.121.03±0.110.0631.02±0.101.01±0.120.6661.06±0.111.06±0.100.766
血浆凝血酶原时间/s11.60
(10.90,12.40)
11.90
(11.10,12.50)
0.19811.90
(11.00,13.00)
11.45
(10.80,12.80)
0.16112.10
(10.85,12.90)
11.60
(11.00,12.60)
0.641
纤维蛋白原/(g/L)2.43(2.01,3.35)2.44(2.00,3.13)0.8332.50(2.11,3.24)2.39(2.09,2.91)0.4942.77(2.37,3.64)2.86(2.37,3.18)0.738
凝血酶时间/s18.04±1.5818.03±1.380.94818.12±1.8017.95±1.220.47817.73±1.4217.63±1.410.760
HBV-DNA定量0.0200.4090.027
阳性93(37.20)28(24.78)31(31.00)21(37.50)9(16.36)11(37.93)
阴性157(62.80)85(75.22)69(69.00)35(62.50)46(83.64)18(62.07)
白细胞/(×109/L)5.94
(4.45,8.36)
5.97
(4.71,8.08)
0.2415.65
(4.43,8.67)
6.13
(4.96,8.54)
0.2216.02(4.40,8.85)5.63(4.51,6.48)0.460
中性粒细胞/(×109/L)3.69
(2.61,6.42)
3.87
(2.71,6.14)
0.9834.03
(2.85,6.23)
4.53
(2.95,6.71)
0.1704.16(3.03,6.23)3.97(2.73,6.13)0.538
淋巴细胞/(×109/L)1.20(0.83,1.54)1.10(0.80,1.61)0.2971.16(0.74,1.53)1.23(0.93,1.64)0.3771.24(0.98,1.62)1.22(0.97,1.76)0.585
血小板/(×109/L)151±63143±590.282144±63148±660.714145±60132±590.330
AFP/(ng/mL)0.0040.0170.357
<200182(72.80)65(57.52)74(74.00)31(55.36)48(87.27)23(79.31)
≥20068(27.20)48(42.48)26(26.00)25(44.64)7(12.73)6(20.69)
), ArticleFig(id=1322210940741857863, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=表1, caption=

603例HCC患者的一般资料[M(P25,P75),x¯±s,例(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
临床指标训练组内部验证组外部验证组
非增殖型HCC(n=250)增殖型HCC
(n=113)
P值非增殖型HCC
(n=100)
增殖型HCC
(n=56)
P值非增殖型HCC
(n=55)
增殖型HCC
(n=29)
P值
性别0.0740.0860.429
女性45(18.00)12(10.62)14(14.00)14(25.00)11(20.00)8(27.59)
男性205(82.00)101(89.38)86(86.00)42(75.00)44(80.00)21(72.41)
年龄/岁55±1153±110.06455±1054±130.74459±1054±110.045
抗病毒治疗病史0.0950.0740.327
无156(62.40)60(53.10)68(68.00)30(53.57)36(65.45)22(75.86)
有94(37.60)53(46.90)32(32.00)26(46.43)19(34.55)7(24.14)
乙肝表面抗原0.2630.1250.691
阳性215(86.00)92(81.42)82(82.00)51(91.07)42(76.36)21(72.41)
阴性35(14.00)21(18.58)18(18.00)5(8.93)13(23.64)8(27.59)
白蛋白/(g/L)39.6±5.839.7±5.80.93639±639±70.70738.6±6.739.1±5.50.713
碱性磷酸酶/(IU/L)84(67,105)86(67,109)0.61785(68,110)90(79,103)0.39687(74,107)82(74,118)0.959
谷氨酰转肽酶/(IU/L)45(28,74)49(35,85)0.03345(30,71)42(24,72)0.51956(36,87)62(34,83)0.955
活化部分凝血活酶时间/s27.28±2.4827.68±2.710.18527.44±2.6427.51±2.360.86428.11±2.4527.61±2.980.440
国际标准化比值1.01±0.121.03±0.110.0631.02±0.101.01±0.120.6661.06±0.111.06±0.100.766
血浆凝血酶原时间/s11.60
(10.90,12.40)
11.90
(11.10,12.50)
0.19811.90
(11.00,13.00)
11.45
(10.80,12.80)
0.16112.10
(10.85,12.90)
11.60
(11.00,12.60)
0.641
纤维蛋白原/(g/L)2.43(2.01,3.35)2.44(2.00,3.13)0.8332.50(2.11,3.24)2.39(2.09,2.91)0.4942.77(2.37,3.64)2.86(2.37,3.18)0.738
凝血酶时间/s18.04±1.5818.03±1.380.94818.12±1.8017.95±1.220.47817.73±1.4217.63±1.410.760
HBV-DNA定量0.0200.4090.027
阳性93(37.20)28(24.78)31(31.00)21(37.50)9(16.36)11(37.93)
阴性157(62.80)85(75.22)69(69.00)35(62.50)46(83.64)18(62.07)
白细胞/(×109/L)5.94
(4.45,8.36)
5.97
(4.71,8.08)
0.2415.65
(4.43,8.67)
6.13
(4.96,8.54)
0.2216.02(4.40,8.85)5.63(4.51,6.48)0.460
中性粒细胞/(×109/L)3.69
(2.61,6.42)
3.87
(2.71,6.14)
0.9834.03
(2.85,6.23)
4.53
(2.95,6.71)
0.1704.16(3.03,6.23)3.97(2.73,6.13)0.538
淋巴细胞/(×109/L)1.20(0.83,1.54)1.10(0.80,1.61)0.2971.16(0.74,1.53)1.23(0.93,1.64)0.3771.24(0.98,1.62)1.22(0.97,1.76)0.585
血小板/(×109/L)151±63143±590.282144±63148±660.714145±60132±590.330
AFP/(ng/mL)0.0040.0170.357
<200182(72.80)65(57.52)74(74.00)31(55.36)48(87.27)23(79.31)
≥20068(27.20)48(42.48)26(26.00)25(44.64)7(12.73)6(20.69)
), ArticleFig(id=1322210941123539528, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
影像学
特征
肿瘤
大小
肿瘤
形态
瘤内
脂肪
瘤内
出血
动脉期瘤周
强化
肿瘤
包膜
瘤内坏死或
缺血(≥20%)
卫星灶静脉内癌栓形成动脉期环形高强化瘤内马赛克结构瘤内
动脉
Kappa值0.9170.8030.8360.7300.6650.6730.7630.8760.6790.7420.6700.745
), ArticleFig(id=1322210941480055369, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=表2, caption=

603名患者CT增强影像学特征一致性分析

, figureFileSmall=null, figureFileBig=null, tableContent=
影像学
特征
肿瘤
大小
肿瘤
形态
瘤内
脂肪
瘤内
出血
动脉期瘤周
强化
肿瘤
包膜
瘤内坏死或
缺血(≥20%)
卫星灶静脉内癌栓形成动脉期环形高强化瘤内马赛克结构瘤内
动脉
Kappa值0.9170.8030.8360.7300.6650.6730.7630.8760.6790.7420.6700.745
), ArticleFig(id=1322210943182942794, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
影像特征训练组内部验证组外部验证组
非增殖型
HCC(n=250)
增殖型
HCC(n=113)
P值非增殖型HCC(n=100)增殖型
HCC(n=56)
P值非增殖型HCC(n=55)增殖型HCC(n=29)P值
肿瘤大小/cm3.99±1.874.25±2.140.2803.71±1.804.13±2.030.2043.42±1.614.19±1.540.035
肿瘤形态0.0140.0030.259
不规则194(77.60)100(88.50)76(76.00)53(94.64)33(60.00)21(72.41)
规则56(22.40)13(11.50)24(24.00)3(5.36)22(40.00)8(27.59)
瘤内脂肪0.2950.0990.373
无221(88.40)104(92.04)90(90.00)55(98.21)43(78.18)25(86.21)
有29(11.60)9(7.96)10(10.00)1(1.79)12(21.82)4(13.79)
瘤内出血0.2460.4680.009
无183(73.20)76(67.26)80(80.00)42(75.00)49(89.09)19(65.52)
有67(26.80)37(32.74)20(20.00)14(25.00)6(10.91)10(34.48)
动脉期瘤周异常强化<0.0010.0180.045
无233(93.20)91(80.53)93(93.00)45(80.36)53(96.36)24(82.76)
有17(6.80)22(19.47)7(7.00)11(19.64)2(3.64)5(17.24)
肿瘤包膜<0.001<0.0010.002
不完整119(47.60)96(84.96)51(51.00)52(92.86)24(43.64)23(79.31)
完整131(52.40)17(15.04)49(49.00)4(7.14)31(56.36)6(20.69)
瘤内坏死或缺血(≥20%)<0.001<0.001<0.001
无196(78.40)56(49.56)81(81.00)29(51.79)52(94.55)14(48.28)
有54(21.60)57(50.44)19(19.00)27(48.21)3(5.45)15(51.72)
卫星灶0.3360.7470.116
无227(90.80)106(93.81)94(94.00)52(92.86)54(98.18)26(89.66)
有23(9.20)7(6.19)6(6.00)4(7.14)1(1.82)3(10.34)
静脉内癌栓形成0.1140.2200.001
无202(80.80)83(73.45)72(72.00)35(62.50)49(89.09)17(58.62)
有48(19.10)30(26.55)28(28.00)21(37.50)6(10.91)12(41.38)
动脉期环形高强化<0.001<0.0010.003
无244(97.60)84(74.34)95(95.00)41(73.21)53(96.36)21(72.41)
有6(2.40)29(25.66)5(5.00)15(26.79)2(3.64)8(27.59)
瘤内马赛克结构0.0400.0580.067
无156(62.40)83(73.45)66(66.00)45(80.36)49(89.09)21(72.41)
有94(37.60)30(26.55)34(34.00)11(19.64)6(10.91)8(27.59)
瘤内动脉0.0810.2720.003
无157(62.80)60(53.10)66(66.00)32(57.14)44(80.00)14(48.28)
有93(37.20)53(46.90)34(34.00)24(42.86)11(20.00)15(51.72)
), ArticleFig(id=1322210943287800395, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=表3, caption=

603例HCC患者影像特征的单因素分析[x¯±s,例(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
影像特征训练组内部验证组外部验证组
非增殖型
HCC(n=250)
增殖型
HCC(n=113)
P值非增殖型HCC(n=100)增殖型
HCC(n=56)
P值非增殖型HCC(n=55)增殖型HCC(n=29)P值
肿瘤大小/cm3.99±1.874.25±2.140.2803.71±1.804.13±2.030.2043.42±1.614.19±1.540.035
肿瘤形态0.0140.0030.259
不规则194(77.60)100(88.50)76(76.00)53(94.64)33(60.00)21(72.41)
规则56(22.40)13(11.50)24(24.00)3(5.36)22(40.00)8(27.59)
瘤内脂肪0.2950.0990.373
无221(88.40)104(92.04)90(90.00)55(98.21)43(78.18)25(86.21)
有29(11.60)9(7.96)10(10.00)1(1.79)12(21.82)4(13.79)
瘤内出血0.2460.4680.009
无183(73.20)76(67.26)80(80.00)42(75.00)49(89.09)19(65.52)
有67(26.80)37(32.74)20(20.00)14(25.00)6(10.91)10(34.48)
动脉期瘤周异常强化<0.0010.0180.045
无233(93.20)91(80.53)93(93.00)45(80.36)53(96.36)24(82.76)
有17(6.80)22(19.47)7(7.00)11(19.64)2(3.64)5(17.24)
肿瘤包膜<0.001<0.0010.002
不完整119(47.60)96(84.96)51(51.00)52(92.86)24(43.64)23(79.31)
完整131(52.40)17(15.04)49(49.00)4(7.14)31(56.36)6(20.69)
瘤内坏死或缺血(≥20%)<0.001<0.001<0.001
无196(78.40)56(49.56)81(81.00)29(51.79)52(94.55)14(48.28)
有54(21.60)57(50.44)19(19.00)27(48.21)3(5.45)15(51.72)
卫星灶0.3360.7470.116
无227(90.80)106(93.81)94(94.00)52(92.86)54(98.18)26(89.66)
有23(9.20)7(6.19)6(6.00)4(7.14)1(1.82)3(10.34)
静脉内癌栓形成0.1140.2200.001
无202(80.80)83(73.45)72(72.00)35(62.50)49(89.09)17(58.62)
有48(19.10)30(26.55)28(28.00)21(37.50)6(10.91)12(41.38)
动脉期环形高强化<0.001<0.0010.003
无244(97.60)84(74.34)95(95.00)41(73.21)53(96.36)21(72.41)
有6(2.40)29(25.66)5(5.00)15(26.79)2(3.64)8(27.59)
瘤内马赛克结构0.0400.0580.067
无156(62.40)83(73.45)66(66.00)45(80.36)49(89.09)21(72.41)
有94(37.60)30(26.55)34(34.00)11(19.64)6(10.91)8(27.59)
瘤内动脉0.0810.2720.003
无157(62.80)60(53.10)66(66.00)32(57.14)44(80.00)14(48.28)
有93(37.20)53(46.90)34(34.00)24(42.86)11(20.00)15(51.72)
), ArticleFig(id=1322210943401046605, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
特征回归系数标准误Wald值风险比95%置信区间P值
HBV-DNA定量阴性0.7580.3145.8312.1351.154 ~ 3.9510.016
肿瘤包膜不完整1.6400.32425.6915.1552.734 ~ 9.720<0.001
瘤内坏死或缺血(≥20%)0.8910.3018.7712.4371.351 ~ 4.3930.003
动脉期环形高强化1.9640.51014.8167.1302.622 ~ 19.385<0.001
), ArticleFig(id=1322210943598178894, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322210923205472765, language=CN, label=表4, caption=

训练组诊断增殖型HCC相关的临床及影像学特征多因素分析

, figureFileSmall=null, figureFileBig=null, tableContent=
特征回归系数标准误Wald值风险比95%置信区间P值
HBV-DNA定量阴性0.7580.3145.8312.1351.154 ~ 3.9510.016
肿瘤包膜不完整1.6400.32425.6915.1552.734 ~ 9.720<0.001
瘤内坏死或缺血(≥20%)0.8910.3018.7712.4371.351 ~ 4.3930.003
动脉期环形高强化1.9640.51014.8167.1302.622 ~ 19.385<0.001
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基于增强CT术前诊断增殖型肝细胞癌的临床价值及预后分析
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成杰 1, 2 , 魏晓凡 1 , 陈伟 2 , 叶小龙 3 , 张维 1
陆军军医大学学报 | 临床医学 2025,47(7): 708-719
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陆军军医大学学报 |临床医学 2025 , 47 (7) : 708 -719
基于增强CT术前诊断增殖型肝细胞癌的临床价值及预后分析
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成杰1, 2, 魏晓凡1, 陈伟2, 叶小龙3, 张维1
作者信息
  • 1重庆医科大学附属第二医院放射科,重庆;
  • 2陆军军医大学(第三军医大学)第一附属医院:7T磁共振转化医学研究中心/放射科
  • 3陆军军医大学(第三军医大学)第一附属医院:病理科,重庆
通讯作者:
ZHANG Wei,E-mail:
Clinical value and prognosis analysis of enhanced CT preoperative diagnosis for proliferative hepatocellular carcinoma
Jie CHENG1, 2, Xiaofan WEI1, Wei CHEN2, Xiaolong YE3, Wei ZHANG1
Affiliations
  • 1Department of Radiology,the Second Affiliated Hospital of Chongqing Medical University,Chongqing
  • 2Department of Radiology,Research Center for 7T Magnetic Resonance Translational Medicine,Chongqing,China
  • 3Department of Pathology,First Affiliated Hospital,Army Medical University(Third Military Medical University),Chongqing,China
出版时间: 2025-04-15 doi: 10.16016/j.2097-0927.202411115
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‍

目的

基于增强CT影像特征构建增殖型肝细胞癌(hepatocellular carcinoma,HCC)的术前预测模型并进行预后分析。

方法

采用回顾性病例-对照研究方法。共纳入经病理证实为HCC的患者603例;其中陆军军医大学第一附属医院519例,以7:3的比例随机分为训练组(n=363)和内部验证组(n=156);将重庆医科大学附属第二医院84例患者作为外部验证组。患者术前均行腹部CT增强检查,观察增殖型与非增殖型HCC患者临床资料情况及CT影像学特征。采用二元Logistic回归分析筛选增殖型HCC的独立危险因素,构建列线图预测模型,通过受试者工作特征曲线(receiver operating characteristic curve,ROC)、ROC曲线下面积(area under curve,AUC)评价其诊断效能,绘制校准曲线、决策曲线(decision curve analysis,DCA)评估列线图模型的校准性能和临床应用价值,并在内部验证组和外部验证组对模型进行验证。使用Kaplan-Meier生存曲线对比增殖型和非增殖型HCC的预后。

结果

多因素分析结果示乙型肝炎病毒脱氧核糖核酸(hepatitis B virus deoxyribonucleic acid,HBV-DNA)定量阴性、肿瘤包膜不完整、瘤内坏死或缺血(≥20%)、动脉期环形高强化是预测增殖型HCC的独立预测因子(P<0.05)。基于以上临床影像特征绘制预测增殖型HCC的列线图,在训练组AUC为0.805(95%CI:0.756~0.854),敏感度83.19%,特异度64.80%;在内部验证组中,AUC为0.793(95%CI:0.721~0.854),敏感度67.86%,特异度75.00%;在外部验证组中,AUC为0.842(95%CI:0.746~0.912),敏感度72.41%,特异度90.91%;校准曲线、DCA曲线示列线图模型的校准性能和临床适用性均较好。经病理证实/预测模型诊断的增殖型HCC患者术后无病生存期(disease free survival,DFS)均显著低于非增殖型HCC(训练组:P=0.005,P<0.001;内部验证组:P=0.006,P=0.006;外部验证组:P=0.002,P=0.015)。

结论

基于临床与影像特征构建的预测模型能较准确术前诊断增殖型HCC,且增殖型HCC预后较差。

增殖型  /  肝细胞癌  /  X线计算机体层摄影术  /  预后研究
Objective

To construct a preoperative prediction model for proliferative hepatocellular carcinoma(HCC) based on enhanced CT image features, and to analyze the prognosis of the disease.

Methods‍

A retrospective case-control study was conducted on 603 patients with pathologically confirmed HCC. Among them, 519 cases from the First Affiliated Hospital of Army Medical University were randomly divided into a training group(n=363) and an internal verification group(n=156) in a ratio of 7:3. Another 84 patients from the Second Affiliated Hospital of Chongqing Medical University served as an external validation group. All patients underwent abdominal CT scan with contrast before surgery. The clinical data and CT imaging characteristics of proliferative and non-proliferative HCC patients were observed. Binary logistic regression analysis was used to identify the independent risk factors of proliferative HCC, and a nomogram prediction model was constructed. Receiver operating characteristic(ROC) curve was plotted to evaluate its diagnostic performance, and calibration curve and decision curve analysis(DCA) were applied to evaluate its calibration performance and clinical application value. The model was validated in both the internal and external validation groups. Kaplan-Meier survival curves were employed to compare the prognosis between proliferative and non-proliferative HCC.

Results‍

Multivariate analysis showed that negative result of HBV-DNA quantification, incomplete tumor capsule, intratumoral necrosis or ischemia(≥20%), and annular hyperenhancement in arterial phase were independent predictors in predicting proliferative HCC(P<0.05). Our nomogram model for predicting proliferative HCC based on the above clinical imaging features had an AUC value of 0.805(95%CI: 0.756~0.854), a sensitivity of 83.19% and a specificity of 64.80% in the training group. For the internal validation group, the AUC value was 0.793(95%CI: 0.721~0.854), the sensitivity was 67.86%, and the specificity was 75.00%. In the external validation group, the AUC value was 0.842(95%CI: 0.746~0.912), the sensitivity was 72.41%, and the specificity was 90.91%. Calibration curve and DCA showed that the model had good calibration performance and clinical applicability. The disease free survival(DFS) of the patients with proliferative HCC diagnosed by pathologically confirmed/predictive models was significantly shorter than that of non-proliferative HCC patients(training group: P=0.005, P<0.001; internal validation group: P=0.006, P=0.006; external validation group: P=0.002, P=0.015).

Conclusion‍

Our prediction model based on clinical and imaging features can accurately diagnose proliferative HCC before surgery, and the prognosis of proliferative HCC is generally poor.

proliferative type  /  hepatocellular carcinoma  /  X-ray computed tomography  /  prognostic study
成杰, 魏晓凡, 陈伟, 叶小龙, 张维. 基于增强CT术前诊断增殖型肝细胞癌的临床价值及预后分析. 陆军军医大学学报, 2025 , 47 (7) : 708 -719 . DOI: 10.16016/j.2097-0927.202411115
Jie CHENG, Xiaofan WEI, Wei CHEN, Xiaolong YE, Wei ZHANG. Clinical value and prognosis analysis of enhanced CT preoperative diagnosis for proliferative hepatocellular carcinoma[J]. Journal of Army Medical University, 2025 , 47 (7) : 708 -719 . DOI: 10.16016/j.2097-0927.202411115
肝细胞癌(hepatocellular carcinoma,HCC)是最常见的肝脏原发性恶性肿瘤[1]。手术切除与局部消融虽是早期HCC主要疗法,但术后复发率达50%~70%,5年总生存率仅约18%[2]。由于HCC的高度异质性,不同病理亚型的患者预后存在显著差异[3]。2019年CALDERARO等[4]提出增殖型HCC的病理概念,包括粗梁-团块型、肉瘤样、硬化型HCC和细胞角蛋白19(cytokeratin 19,CK19)阳性HCC,这种类型的HCC与细胞增殖相关的多种基因组途径的激活有关[5-6],表现为染色体不稳定和较强的血管侵袭能力。此外,增殖型HCC患者在术前通常具有较高的甲胎蛋白(alpha-fetoprotein,AFP)水平,预后较差[7-9]。然而,已有研究表明增殖型HCC对靶向及免疫治疗反应较敏感[3-4]。因此,如果能够在术前准确预测增殖型HCC,将有助于优化个体化治疗策略,提高患者的生存率。影像学检查是HCC术前诊断和评估的关键手段。其中,增强CT因其可重复性高、能够提供丰富的肿瘤血供及组织学信息,已成为HCC的常规筛查和术前评估方法。然而,目前的影像学方法在HCC分子亚型预测方面仍存在一定局限性,临床上尚未建立可靠的影像学特征来准确识别增殖型HCC,导致术前难以区分不同亚型患者。近年来,影像组学和人工智能在HCC诊断中的研究逐渐增多,但针对增殖型HCC的影像组学特征研究仍较为有限,尚缺乏广泛应用的预测模型。本研究拟探讨基于增强CT影像特征术前预测增殖型HCC的临床价值,旨在构建影像学预测模型,为临床精准治疗提供有力支持。
本研究为病例-对照研究,回顾性收集经病理证实为HCC的患者603例:其中陆军军医大学第一附属医院519例,以7:3的比例随机分为训练组(n=363)和内部验证组(n=156);将重庆医科大学附属第二医院84例患者作为外部验证组,见图1。本研究经陆军军医大学第一附属医院[(B)KY2023107]和重庆医科大学附属第二医院[第(2021)240号]伦理委员会批准,且免除患者知情同意书。纳入标准:①临床资料、实验室生化检查以及病理报告,包括具体病理学分型完整;②术前1个月内进行上腹部增强CT检查,且与实验室检查时间间隔<7 d;③肝内单个病灶。排除标准:①上腹部增强CT检查图像质量不佳,存在伪影;②患者既往有相关肝脏疾病治疗史,包括射频消融术、手术切除、肝移植、肝动脉化疗栓塞术(transarterial chemoembolization,TACE)治疗等;③术前出现肝外转移;④无明确HCC病理亚型。
所有腹部CT扫描采用Somatom Definition Flash(德国,西门子)和Revolution CT(GE Healthcare),CT扫描参数如下:80~140 kV,自动管电流,层厚5 mm,旋转速度0.5 s/r,螺距分别为:0.992、1:1,经前臂肘正中静脉注射碘海醇(欧乃派克)对比剂约1.5 mL/kg,浓度320~350 mg/mL,注射速度为3.0~4.0 mL/s,感兴趣区放置于胸主动脉,当该区域CT值>140 HU时触发扫描获得动脉期,延时20~25 s后获得门静脉期,48~60 s后获得平衡期。所有图像评估采用层厚均为1 mm。
CT图像的评估分别由2名具有11年和12年腹部诊断经验的放射科医生进行,采用盲法独立阅片,如果存在意见分歧,则由1名具有31年腹部诊断经验的放射科医生进行最终评估。
病理评估由2名病理科医生根据世界卫生组织(World Health Organization,WHO)发布的第五版《消化系统肿瘤分类》分别对2个中心的组织学切片进行分类[4,10],CK19阳性定义为免疫组织化学检测≥5%的肿瘤细胞胞膜和/或细胞质中呈阳性表达;增殖型HCC包括粗梁-团块型肝细胞癌(macrotrabecular-massive hepatocellular carcinoma,MTM-HCC)、肉瘤样HCC、硬化型HCC及CK19阳性HCC,非增殖型HCC包括CK19阴性表达、透明细胞型、脂肪型、富含淋巴细胞型。
包括性别、年龄、长期抗病毒治疗史、乙肝表面抗原、白蛋白、碱性磷酸酶、谷氨酰转肽酶、国际标准化比值、活化部分凝血活酶时间、血浆凝血酶原时间、纤维蛋白原、凝血酶时间、乙型肝炎病毒脱氧核糖核酸(hepatitis B virus deoxyribonucleic acid,HBV-DNA)定量、白细胞、中性粒细胞、淋巴细胞、血小板、AFP。
增殖型HCC和非增殖型HCC的CT检查影像学特征包括肿瘤大小、肿瘤形态、肿瘤包膜、瘤内脂肪、瘤内出血、瘤内坏死或缺血(≥20%)、动脉期瘤周异常强化、动脉期环形强化、瘤内动脉、瘤周卫星灶、静脉内癌栓、瘤内马赛克结构。
所有影像学征象均按照LI-RADS标准进行评估[11]:①肿瘤大小:定义为在横断面CT门静脉期病灶的最大径;②肿瘤形态:形态规则表现为圆形或椭圆形且表面光滑,形态不规则表现为分叶、棘状突起,表面不光整;③肿瘤包膜:定义为门静脉或过渡期肿瘤边缘出现环形高强化结构;④瘤内脂肪:CT平扫序列测得CT值为-20~-90 HU,否则为瘤内乏脂肪;⑤瘤内出血:平扫序列测得CT值低于钙化[12];⑥瘤内坏死或缺血:定义为瘤内各期增强扫描均存在无强化或弱强化区域且占肿瘤体积≥20%;⑦动脉期瘤周异常强化:定义为动脉期瘤周“条带状”或“火焰状”明显强化,门脉期强化程度未减弱;⑧动脉期环形高强化:动脉期病灶边缘不规则环形强化高于肝实质,中心呈低强化区;⑨瘤内动脉:肿瘤内部持续存在的强化动脉;⑩瘤周卫星灶:主瘤灶周围<2 cm范围内出现子灶;⑪静脉内癌栓:静脉腔内明确强化的软组织影。⑫瘤内马赛克结构:随机分布的内部结节或分隔区,具有不同的CT值。
术后每3个月随访1次,且至少行上腹部增强CT、MRI或超声任意一种影像学检查,同时监测患者的AFP以及异常凝血酶原水平。复发定义为肝内外病灶在影像学上表现为典型快进快出强化方式。术后无病生存期(disease free survival,DFS)定义为手术结束到复发的时间间隔,随访截止时间为2024年9月1日。
采用SPSS 26.0和MedCal 20.022统计软件进行数据分析。诊断一致性采用Kappa系数进行检验(Kappa值≥0.75表示一致性较好;0.4≤Kappa值<0.75,表示一致性一般;Kappa值<0.4表示一致性较差)。本研究根据不同数据类型及分布特征选择相应的统计学方法。首先,对连续变量进行正态性检验,使用Kolmogorov-Smirnov检验来评估数据是否符合正态分布。若数据符合正态分布且方差齐性,采用独立样本t检验进行组间比较,正态分布且方差齐性计量资料以x¯±s表示;若数据不符合正态分布或方差不齐,采用Mann-Whitney U检验,结果以中位数M(P25,P75)表示。分类变量采用χ2检验进行组间比较,以分析增殖型和非增殖型HCC在各分类变量上的差异。为了评估增殖型HCC的独立预测因素,采用二元Logistic回归分析,并通过逐步回归法筛选显著变量纳入模型。同时,为避免多重比较带来的错误,采用Bonferroni校正方法对多重检验进行调整,控制假阳性率。采用R 4.2.2软件构建列线图预测模型,通过校准曲线评估模型的校准度,通过DCA来评估列线图模型的临床应用价值,通过ROC评价指标其诊断价值,根据计算约登指数选择最佳截断值,划分高风险组和低风险组。使用Kaplan-Meier生存曲线分析增殖型和非增殖型HCC的生存预后,P<0.05表示差异有统计学意义。
单因素分析显示,不同组别间临床指标存在显著差异。训练组增殖型HCC患者中、AFP(≥200)及谷氨酰转肽酶水平比非增殖型HCC患者比例增多,HBV-DNA定量阳性降低(P<0.05);内部验证组增殖型HCC患者中AFP(≥200)水平比非增殖型HCC患者比例增多(P=0.017);而外部验证组中增殖型HCC患者与非增值组相比年龄较大(P=0.045)且HBV-DNA定量阳性更多(P=0.027),见表1。
2名医师对肿瘤大小、肿瘤形态、瘤内脂肪、瘤内坏死或缺血(≥20%)、卫星灶5种征象中一致性评价均为较好(Kappa值≥0.75);在瘤内出血、肿瘤包膜、动脉期瘤周强化、静脉内癌栓、动脉期环形高强化、瘤内马赛克结构、瘤内动脉7种征象中的一致性评价一般(0.4≤Kappa值<0.75),见表2。
训练组中,肿瘤形态、动脉期瘤周异常强化、肿瘤包膜、瘤内坏死或缺血(≥20%)、动脉期环形高强化、瘤内马赛克结构均具有统计学差异(P<0.05,表3);多因素分析结果显示,与非增殖型HCC相比,增殖型HCC更容易出现肿瘤包膜不完整、瘤内坏死或缺血、动脉期环形高强化3种影像征象,且存在显著统计学差异(P<0.05,表3、4) 。
增殖型肝细胞癌,患者男性,52岁。腹部增强CT检查情况:肝6段稍低密度肿块影,形态不规则,边界不清(图2A);增强扫描动脉期肿瘤边缘环形明显强化(图2B);增强扫描门脉期肿瘤边缘强化、程度减弱,强化方式呈快进快出,包膜不完整(图2C);平衡期示肿瘤边缘强化低于正常肝实质(图2D);增强三期图像肿瘤中心见大片低密度无强化区,提示坏死。HE染色肿瘤细胞病理学显示:粗梁结构(图2E),可见大量坏死(图2F)。
非增殖型肝细胞癌,患者男性,56岁。腹部增强CT检查情况:肝6段稍低密度肿块影,形态规则,边界较清(图3A);增强扫描动脉期肿瘤明显不均匀强化(图3B);增强扫描门脉期肿瘤不均匀强化、程度减弱,强化方式呈快进快出(图3C);增强扫描平横期肿瘤不均匀强化低于正常肝实质(图3D)。HE染色肿瘤细胞病理学显示:小梁结构(图3E),可见大量透明细胞(图3F)。
最终纳入HBV-DNA定量阴性及CT影像征象肿瘤包膜不完整、瘤内坏死或缺血(≥20%)、动脉期环形高强化构建临床-影像诊断模型(图4),在训练组中,模型的ROC曲线下面积(area under curve,AUC)为0.805(95%CI:0.756~0.854),敏感度83.19%,特异度64.80%;在内部验证组中,AUC为0.793(95%CI:0.721~0.854),敏感度67.86%,特异度75.00%;在外部验证组中,AUC为0.842(95%CI:0.746~0.912),敏感度72.41%,特异度90.91%。校准曲线示训练组和验证组中的预测概率曲线与实际概率曲线接近,表明该预测模型校准度较高。决策曲线表明,训练组阈值位于0.13~0.80、内部验证组阈值位于0.08~0.78、外部验证组阈值位于0.09~0.80,在临床应用中可获得净收益(图5)
本研究603例患者均按计划随访,训练组中363例患者生存时间为895.00(626.54,1163.47)d,内部验证组中156例患者生存时间为455.00(385.85,524.15)d,外部验证组84例患者生存时间为1 442.00(812.31,2 071.69)d。根据诊断模型AUC的最佳临界值,将合并的队列分为高风险组和低风险组;训练组中病理证实/预测模型诊断的增殖型HCC患者DFS显著低于非增殖型HCC患者(P=0.005,P<0.001);内部验证组中经病理证实/模型诊断的增殖型HCC患者DFS显著低于非增殖型HCC患者(P=0.006,P=0.006);外部验证组中经病理证实/模型诊断的增殖型HCC患者DFS显著低于非增殖型HCC患者(P=0.002,P=0.015)。无论是病理证实还是模型预测,在所有组中增殖型HCC患者在肝切除后预后生存率显著低于非增殖型HCC(P<0.05,图6)。
本研究通过对增殖型HCC的增强CT影像特征进行分析,发现肿瘤包膜不完整、瘤内坏死或缺血(≥20%)以及动脉期环形高强化在增殖型HCC和非增殖型HCC之间具有显著的统计学差异(P<0.05)。基于这些变量构建的模型在训练组(AUC=0.805)和验证组(内部AUC=0.793、外部AUC=0.842)中均表现出较高的预测效能,这表明本研究模型具有较好的区分能力和稳健性,可为术前早期诊断增殖型HCC提供可靠依据。辅助临床医生在术前对患者进行肿瘤亚型的早期识别,优化治疗决策,进行更积极的治疗方案如免疫治疗或联合治疗,从而改善患者的预后。
增强CT在肝细胞癌诊断中的价值已在多项研究中得以证实。本研究显示,动脉期环形高强化特征在增殖型HCC的诊断中具有重要意义,与既往文献的结果一致[13-14]。据报道动脉期环形高强化征象与肿瘤的高侵袭性相关,与较差的治疗效果和预后相关[15-16]。RHEE等[16]研究发现,环形高强化的HCC肿瘤组织中碳酸酐酶Ⅸ和上皮细胞黏附分子的表达水平较高,这两者分别是缺氧和HCC干细胞的标志物。此外,环形高强化特征的形成与肿瘤中央存在丰富的纤维基质有关,这种纤维基质阻碍了动脉期对比剂的分布。MTM-HCC和细胞角蛋白19阳性肝细胞癌(cytokeratin 19-positive hepatocellular carcinoma,CK19-HCC)这2种类型中常出现动脉期环形高强化征象[17-19]。本研究中大多数增殖型HCC由这2种亚型组成,这可能是本研究得到相似结论的部分原因。肿瘤包膜不完整也是诊断增殖型HCC的重要影像特征,与多项研究结论一致[20-21]。增殖型HCC的细胞分裂和增长速度通常比普通型HCC更快,导致肿瘤体积迅速扩大,超过周围结构的支持能力,从而使得肿瘤包膜在形成过程中出现不完整。肿瘤包膜的不完整性常提示肿瘤具有更高的侵袭性,与其突破肿瘤边界并向周围肝实质扩展的能力密切相关。此外,瘤内坏死或缺血(≥20%)作为另一重要影像特征,反映了肿瘤恶性程度和疾病进展程度,在多种癌症中都被认为是疾病进展和较差预后的指征[22-23]。已有研究表明,瘤内坏死或缺血的机制主要是由于肿瘤微环境中内皮细胞特异性分子1的表达[24],这会激活肿瘤周围血管的再生[25],导致肿瘤过度生长、肿瘤内灌注减少和缺氧[26-27],从而进一步促进瘤内坏死的发生。
与既往研究结果相比,本研究进一步验证了增强CT在增殖型HCC诊断中的有效性。然而,与MRI相比,增强CT在某些方面存在一定不足。MRI的DWI和DCE-MRI技术可以提供更丰富的肿瘤功能信息,尤其是在评估肿瘤微环境和纤维化程度方面。尽管如此,增强CT在快速成像和显示血管细节方面的优势,使其在肝细胞癌诊断中的应用不可替代。
本研究通过结合HBV-DNA定量阴性这一实验室指标,进一步完善了预测模型。从列线图的结果可以看出,HBV-DNA定量阴性与瘤内坏死或缺血(≥20%)在模型中的权重相似。确切的原因目前尚不明确,可能与慢性乙肝患者的抗病毒治疗有关,已有文献指出[28],核苷类似物治疗能够显著降低HBV-DNA水平,但低水平HBV-DNA可能与病毒整合入宿主基因组导致的基因组不稳定性有关[29]。有研究指出,HBV基因组整合可能导致基因的表达异常或结构改变,HBV基因组整合也可能导致肝细胞的染色体不稳定,增加突变率,进一步推动HCC的发生[30]。此外,本研究未发现AFP(≥200 ng/mL)水平对增殖型HCC的诊断具有显著价值(OR=0.528),这可能与本研究分层数值的不同或样本选择有关,也提示AFP水平并非增殖型HCC特有的诊断标志物。这一发现与其它研究结果不一致,且目前的文献尚未有统一结果[6,14,31-33]。HCC中AFP的表达可能与肝细胞分化失常有关,这种分化失常可能由多种机制引起,包括基因突变、基因表达改变以及炎症反应[34]。尽管AFP在HCC诊断中的价值被广泛研究,但目前并没有明确的一致性结论。
本研究采用列线图法来预测增殖型HCC患者的DFS,结果发现在列线图模型预测的高低风险组中预后生存率存在显著差异。生存分析研究结果证实,增殖型HCC的预测模型和病理模型预后均较差。因此,增殖型HCC预测模型可以为患者提供有效的风险分层和预后预测,且与病理模型预后评估表现出类似的价值。已有研究[7-8,35-36]发现,增殖型HCC是术后总体生存率低、肝内外转移的独立危险因素。本研究的临床意义主要体现在对增殖型HCC的术前早期识别上。通过精准的亚型诊断,临床医生可以更合理地选择个体化治疗方案,例如术前新辅助治疗或更积极的联合治疗策略,从而改善患者的预后。尤其是对于计划接受TACE治疗的患者,研究结果显示[6,32]增殖型HCC疗效较差,因为增殖型HCC通常具有很高的侵袭特征;影像学特征预测为增殖型HCC时,可建议患者进行穿刺活检明确病理诊断,从而优化治疗选择。
本研究也存在一定局限性。首先,研究为回顾性分析,可能存在选择偏倚;其次,影像特征的评估依赖于肉眼判断,可能影响结果的客观性;再次,本研究外部验证组的样本量较少(n=84),外部验证组AUC高于训练组和内部验证组可能是由于样本选择偏倚、数据分布差异、模型泛化能力以及统计波动等因素所致。未来将增加外部数据集的样本量、引入多中心数据等方式进一步验证和优化模型的稳定性及适用性。结合人工智能技术实现影像特征的自动化提取,以提高研究的可重复性和稳定性,并进行组学分析及深度学习研究。此外,多模态影像技术的联合应用(如CT与MRI)也值得进一步探索,以提高诊断的全面性和准确性。
综上所述,基于临床与影像特征构建的预测模型能较准确术前诊断增殖型HCC,且增殖型HCC预后较差。该诊断模型的早期预测有助于临床医生对增殖型HCC患者制订个性化的诊疗决策并改善患者预后。

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doi: 10.16016/j.2097-0927.202411115
  • 接收时间:2024-11-26
  • 首发时间:2026-10-28
  • 出版时间:2025-04-15
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  • 收稿日期:2024-11-26
  • 修回日期:2024-12-17
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    1重庆医科大学附属第二医院放射科,重庆;
    2陆军军医大学(第三军医大学)第一附属医院:7T磁共振转化医学研究中心/放射科
    3陆军军医大学(第三军医大学)第一附属医院:病理科,重庆

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