ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1628054
This article is part of the Research TopicInnovative Diagnostic and Therapeutic Strategies for Neuroendocrine Tumors: A Multidisciplinary ApproachView all 3 articles
Visualized Clinical-Radiomics Model for Predicting Efficacy of Surufatinib in Hepatic Metastases of Neuroendocrine Neoplasms
Provisionally accepted
- Fourth Hospital of Hebei Medical University, Shijiazhuang, China
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Background: Hepatic metastatic neuroendocrine neoplasms (HM-NENs) have few treatment biomarkers and low survival rates. We created a clinical-radiomics fusion model to predict surufatinib efficacy in HM-NENs and presented it as a nomogram, meeting unmet requirements in precision hepatology. Methods: This study included 76 HM-NEN patients (131 hepatic metastases) treated with surufatinib. SlicerRadiomics was used to extract radiomics features from Arterial Phase Computed Tomography (APCT). The Least Absolute Shrinkage and Selection Operator (LASSO) was used to select radiomics features and calculate a Radiomics score (Radscore). Multivariable logistic regression analysis was utilized to create the clinical-radiomics fusion model, which included clinical characteristics and Radscore and was displayed as a nomogram. The area under the receiver operating characteristic curve (ROC) was used to assess model performance, and internal validation was done using the bootstrap resampling approach. Results: After multivariate logistic regression analysis, the Radscore, Ki67 antigen(Ki67), number of hepatic metastases, and extrahepatic metastasis were included as predictors in the final model. The area under the curve (AUC) of the clinical-radiomics fusion model to predict the response of surufatinib of HM-NENs was 0.928(95%CI:0.885-0.971). The AUC verified by bootstrap is 0.928(95%CI:0.881-0.965), indicating a good performance of the fusion model. Conclusion: The clinical-radiomics fusion model can effectively identify patients with HM-NENs sensitive to surufatinib therapy. The nomogram provided clinicians with a convenient and dependable tool for decision-making.
Keywords: Hepatic metastatic neuroendocrine neoplasms, surufatinib, Clinical-radiomics model, Arterial phase computed tomography, efficacy
Received: 13 May 2025; Accepted: 11 Aug 2025.
Copyright: © 2025 Feng, Zhao, Duan, Hou, Wang and Yin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Fei Yin, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
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