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Purpose <p>Glypican 3 (GPC-3) in hepatocellular carcinoma (HCC) is receiving attention as a potential biomarker for treatment options. However, GPC-3 expression can only be assessed through surgical pathology. Therefore, we aim to develop and validate a practical tool based on contrast-enhanced ultrasound (CEUS) and clinical features to preoperatively identify GPC-3 expression in HCC.</p> Methods <p>From August 2021 to July 2024, 197 patients with pathologically confirmed HCC were retrospectively enrolled. The least absolute shrinkage and selection operator (LASSO) and stepwise logistic regression analyses were performed in training cohort to identify predictors and establish a model for predicting GPC-3 expression. The performance of model was evaluated by C-index, area under the receiver operating characteristic curve (ROC), calibration curves, and decision curve analysis (DCA).</p> Results <p>Our study showed that heterogeneous arterial phase hyperenhancement (APHE), mosaic architecture, alpha-fetoprotein (AFP) ≥ 100 ng/mL, rim enhancement in arterial phase (AP), neutrophil count (Nc) level and age were independently associated with GPC-3 expression. The model demonstrated strong predictive performance and the areas under curve were 0.811 (95% confidence interval[CI]: 0.737–0.885) and 0.750 (95%CI: 0.622–0.878) in training and validation cohorts. Good calibration and prominent net benefit were exhibited in both cohorts. Moreover, The risk score calculated by the model presented promising stratification ability between high-risk and low-risk groups in terms of relapse-free survival (RFS) .</p> Conclusion <p>Based on CEUS and clinical features, the model can help identify GPC-3 expression accurately and may provide valuable preoperative insights for customizing personalized treatment planning in HCC patients.</p>

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Contrast-enhanced ultrasound and clinical features for preoperative prediction of GPC-3 expression in hepatocellular carcinoma

  • 期刊论文

  • 发表日期：

    2026年1月23日

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  • Qing Shu,
  • Chuan Pang,
  • Zhen Wang,
  • Xueqin Tian,
  • Shuo Wang,
  • Xizi Yan,
  • Ping Liang,
  • Jie Yu,
  • Xiaoling Yu

摘要

Purpose

Glypican 3 (GPC-3) in hepatocellular carcinoma (HCC) is receiving attention as a potential biomarker for treatment options. However, GPC-3 expression can only be assessed through surgical pathology. Therefore, we aim to develop and validate a practical tool based on contrast-enhanced ultrasound (CEUS) and clinical features to preoperatively identify GPC-3 expression in HCC.

Methods

From August 2021 to July 2024, 197 patients with pathologically confirmed HCC were retrospectively enrolled. The least absolute shrinkage and selection operator (LASSO) and stepwise logistic regression analyses were performed in training cohort to identify predictors and establish a model for predicting GPC-3 expression. The performance of model was evaluated by C-index, area under the receiver operating characteristic curve (ROC), calibration curves, and decision curve analysis (DCA).

Results

Our study showed that heterogeneous arterial phase hyperenhancement (APHE), mosaic architecture, alpha-fetoprotein (AFP) ≥ 100 ng/mL, rim enhancement in arterial phase (AP), neutrophil count (Nc) level and age were independently associated with GPC-3 expression. The model demonstrated strong predictive performance and the areas under curve were 0.811 (95% confidence interval[CI]: 0.737–0.885) and 0.750 (95%CI: 0.622–0.878) in training and validation cohorts. Good calibration and prominent net benefit were exhibited in both cohorts. Moreover, The risk score calculated by the model presented promising stratification ability between high-risk and low-risk groups in terms of relapse-free survival (RFS) .

Conclusion

Based on CEUS and clinical features, the model can help identify GPC-3 expression accurately and may provide valuable preoperative insights for customizing personalized treatment planning in HCC patients.