YanZhuo Li, Lei Huo, LianLian Liu, NingYang Jia, Bin Song
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Independent influencing variables for different subtypes of invasive HCC were identified by multivariate analysis. The diagnostic performance of variables was measured using ROC analysis.</p><p><strong>Results: </strong>Cases with EpCAM and GPC3 expression were classified into four subtypes based on IHC staining. Among them, EpCAM+/GPC3+ HCC had the highest risk. Significant predictors of HCC expressing aggressive markers included tumor size (<i>p</i> = 0.01), AFP level (<i>p</i> = 0.008), MVI (<i>p</i> = 0.003), satellite nodule (<i>p</i> = 0.002), proliferative pattern (<i>p</i> = 0.04), and arterial peripheral enhancement (<i>p</i> = 0.03). By integrating all of these relevant variables, the resulting diagnostic accuracy was enhanced to 0.914 (95% CI 0.830-0.960) with a sensitivity of 0.964 (95% CI 0.922-1.000) and a specificity of 0.833 (95% CI 0.365-0.911).</p><p><strong>Conclusion: </strong>The research demonstrated that combining biochemical and radiological data allows for accurate prognosis and patient management, along with non-invasive detection of aggressive HCC with high accuracy.</p>","PeriodicalId":14131,"journal":{"name":"International Journal of General Medicine","volume":"18 ","pages":"1691-1708"},"PeriodicalIF":2.1000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955402/pdf/","citationCount":"0","resultStr":"{\"title\":\"MRI Parameters and Clinicopathologic Features in Predicting Hepatocellular Carcinomas With Aggressive-Related Marker Expression, Defined by Epithelial Cell Adhesion Molecule and Glypican-3 Status.\",\"authors\":\"YanZhuo Li, Lei Huo, LianLian Liu, NingYang Jia, Bin Song\",\"doi\":\"10.2147/IJGM.S502309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Epithelial cell adhesion molecule (EpCAM) and glypican-3 (GPC3) are associated with a poor survival rate in hepatocellular carcinoma (HCC). Predicting aggressive HCC non-invasively should be investigated using preoperative gadoxetic acid-enhanced MRI and clinical characteristics.</p><p><strong>Methods: </strong>This retrospective study examined 134 patients with confirmed cases of HCC who had undergone gadolinic acid-enhanced MRI before surgery. The data were collected between November 2017 and December 2021. Significant parameters were subjected to quantitative analysis and univariate testing. HCC characterized by poor differentiation and progenitor traits was identified by the positive expression of EpCAM and/or GPC3. Independent influencing variables for different subtypes of invasive HCC were identified by multivariate analysis. The diagnostic performance of variables was measured using ROC analysis.</p><p><strong>Results: </strong>Cases with EpCAM and GPC3 expression were classified into four subtypes based on IHC staining. Among them, EpCAM+/GPC3+ HCC had the highest risk. Significant predictors of HCC expressing aggressive markers included tumor size (<i>p</i> = 0.01), AFP level (<i>p</i> = 0.008), MVI (<i>p</i> = 0.003), satellite nodule (<i>p</i> = 0.002), proliferative pattern (<i>p</i> = 0.04), and arterial peripheral enhancement (<i>p</i> = 0.03). By integrating all of these relevant variables, the resulting diagnostic accuracy was enhanced to 0.914 (95% CI 0.830-0.960) with a sensitivity of 0.964 (95% CI 0.922-1.000) and a specificity of 0.833 (95% CI 0.365-0.911).</p><p><strong>Conclusion: </strong>The research demonstrated that combining biochemical and radiological data allows for accurate prognosis and patient management, along with non-invasive detection of aggressive HCC with high accuracy.</p>\",\"PeriodicalId\":14131,\"journal\":{\"name\":\"International Journal of General Medicine\",\"volume\":\"18 \",\"pages\":\"1691-1708\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955402/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of General Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/IJGM.S502309\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of General Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/IJGM.S502309","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
摘要
目的:上皮细胞粘附分子(EpCAM)和甘聚糖-3 (GPC3)与肝细胞癌(HCC)的低生存率相关。术前加多西酸增强MRI和临床特征可用于无创预测侵袭性HCC。方法:本回顾性研究对134例确诊HCC患者术前行钆酸增强MRI检查。数据收集于2017年11月至2021年12月。重要参数进行定量分析和单因素检验。EpCAM和/或GPC3的阳性表达确定了分化差和祖细胞特征的HCC。通过多因素分析确定不同亚型浸润性HCC的独立影响变量。采用ROC分析测量各变量的诊断效能。结果:通过免疫组化染色将EpCAM和GPC3表达的病例分为4个亚型。其中EpCAM+/GPC3+ HCC风险最高。肝癌表达侵袭性标志物的重要预测因子包括肿瘤大小(p = 0.01)、AFP水平(p = 0.008)、MVI (p = 0.003)、卫星结节(p = 0.002)、增殖模式(p = 0.04)和动脉外周强化(p = 0.03)。通过整合所有这些相关变量,最终的诊断准确性提高到0.914 (95% CI 0.830-0.960),灵敏度为0.964 (95% CI 0.922-1.000),特异性为0.833 (95% CI 0.365-0.911)。结论:研究表明,结合生化和放射学资料可以准确的预后和患者管理,以及无创检测侵袭性HCC的准确性高。
MRI Parameters and Clinicopathologic Features in Predicting Hepatocellular Carcinomas With Aggressive-Related Marker Expression, Defined by Epithelial Cell Adhesion Molecule and Glypican-3 Status.
Objective: Epithelial cell adhesion molecule (EpCAM) and glypican-3 (GPC3) are associated with a poor survival rate in hepatocellular carcinoma (HCC). Predicting aggressive HCC non-invasively should be investigated using preoperative gadoxetic acid-enhanced MRI and clinical characteristics.
Methods: This retrospective study examined 134 patients with confirmed cases of HCC who had undergone gadolinic acid-enhanced MRI before surgery. The data were collected between November 2017 and December 2021. Significant parameters were subjected to quantitative analysis and univariate testing. HCC characterized by poor differentiation and progenitor traits was identified by the positive expression of EpCAM and/or GPC3. Independent influencing variables for different subtypes of invasive HCC were identified by multivariate analysis. The diagnostic performance of variables was measured using ROC analysis.
Results: Cases with EpCAM and GPC3 expression were classified into four subtypes based on IHC staining. Among them, EpCAM+/GPC3+ HCC had the highest risk. Significant predictors of HCC expressing aggressive markers included tumor size (p = 0.01), AFP level (p = 0.008), MVI (p = 0.003), satellite nodule (p = 0.002), proliferative pattern (p = 0.04), and arterial peripheral enhancement (p = 0.03). By integrating all of these relevant variables, the resulting diagnostic accuracy was enhanced to 0.914 (95% CI 0.830-0.960) with a sensitivity of 0.964 (95% CI 0.922-1.000) and a specificity of 0.833 (95% CI 0.365-0.911).
Conclusion: The research demonstrated that combining biochemical and radiological data allows for accurate prognosis and patient management, along with non-invasive detection of aggressive HCC with high accuracy.
期刊介绍:
The International Journal of General Medicine is an international, peer-reviewed, open access journal that focuses on general and internal medicine, pathogenesis, epidemiology, diagnosis, monitoring and treatment protocols. The journal is characterized by the rapid reporting of reviews, original research and clinical studies across all disease areas.
A key focus of the journal is the elucidation of disease processes and management protocols resulting in improved outcomes for the patient. Patient perspectives such as satisfaction, quality of life, health literacy and communication and their role in developing new healthcare programs and optimizing clinical outcomes are major areas of interest for the journal.
As of 1st April 2019, the International Journal of General Medicine will no longer consider meta-analyses for publication.