Development of a model combining CEUS LI-RADS and clinical features for predicting glypican-3 expression in hepatocellular carcinoma.
Objective: To establish a predictive model incorporating clinical features and contrast-enhanced ultrasound (CEUS) liver Imaging Reporting and Data System (LI-RADS) for predicting glypican-3 (GPC3) expression in hepatocellular carcinoma (HCC). Methods: A total of 142 HCC patients between January 202...
| Publicado en: | Abdominal Radiology Vol. 50; no. 11; pp. 5187 - 5197 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188951985&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188951985 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Nov2025 vid: 50 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 188951985 184376218 10.1007/s00261-025-04861-8 188951985 ppf: 5187 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Development of a model combining CEUS LI-RADS and clinical features for predicting glypican-3 expression in hepatocellular carcinoma. aug: au: Huang, Fen Pang, Jinshu Wu, Yuquan Sun, Yueting Wen, Rong Bai, Xiumei Nong, Wanxian Gao, Ruizhi He, Yun Li, Cuiling Huang, Guangliang Yang, Hong affil: https://ror.org/030sc3x20 Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China sug: ab: Objective: To establish a predictive model incorporating clinical features and contrast-enhanced ultrasound (CEUS) liver Imaging Reporting and Data System (LI-RADS) for predicting glypican-3 (GPC3) expression in hepatocellular carcinoma (HCC). Methods: A total of 142 HCC patients between January 2020 to June 2021 in our institution were retrospectively analyzed. All patients underwent CEUS before surgery, and the reference standard was immunohistochemical analysis of surgical specimen. The clinical features, conventional ultrasound features, and CEUS LI-RADS features of patients in the GPC3-positive and GPC3-negative groups were evaluated and compared. The variables screened by multivariable logistic regression were used to develop a model for predicting GPC3 expression and the predictive precision and clinical utility of the model was evaluated using receiver operating characteristic analysis and decision curve analysis. Results: Among the 142 HCC patients, 96 (67.6%) were classified as LR-4/5 lesions, 46 (32.4%) were classified as LR-M lesions, 101 (71.1%) were GPC3-positive and 41 (28.9%) were negative. Multivariable logistic regression analysis showed that younger age (OR = 0.947; 95% CI: 0.910–0.985; p = 0.007), alpha-fetoprotein > 400 ng/ml (OR = 5.202; 95% CI: 1.808–14.966; p = 0.002) and LI-RADS M (OR = 2.822; 95% CI: 1.101–7.236; p = 0.031) was independent risk factors for GPC3-positive HCC. The model combining clinical features and LI-RADS categories showed better performance than single variable, with AUC of 0.759 (p < 0.05). The nomogram and decision curves revealed substantial clinical benefit of the prediction model in predicting GPC3 expression. Conclusion: The combined model incorporating clinical features and CEUS LI-RADS achieved a satisfactory performance for predicting GPC3 expression in HCC patients. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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