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Open Access 26-07-2023 | Hepatocellular Carcinoma | Hepatobiliary

DCE-MRI-based radiomics in predicting angiopoietin-2 expression in hepatocellular carcinoma

Authors: Jing Zheng, Pei-Zhuo Du, Cui Yang, Yun-Yun Tao, Li Li, Zu-Mao Li, Lin Yang

Published in: Abdominal Radiology | Issue 11/2023

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Abstract

Background

Hepatocellular carcinoma (HCC) is the sixth most common cancer, and the third leading cause of cancer death worldwide. Studies have shown that increased angiopoietin-2 (Ang-2) expression relative to Ang-1 expression in tumors is associated with a poor prognosis.The purpose of this study was to investigate the efficacy of predicting Ang-2 expression in HCC by preoperative dynamic contrast‐enhanced magnetic resonance imaging (DCE-MRI)-based radiomics.

Methods

The data of 52 patients with HCC who underwent surgical resection in our hospital were retrospectively analyzed. Ang-2 expression in HCC was analyzed by immunohistochemistry. All patients underwent preoperative upper abdominal DCE-MRI and intravoxel incoherent motion diffusion-weighted imaging scans. Radiomics features were extracted from the early and late arterial and portal phases of axial DCE-MRI. Univariate analysis and least absolute shrinkage and selection operator (LASSO) was performed to select the optimal radiomics features for analysis. A logistic regression analysis was performed to establish a DCE-MRI radiomics model, clinic-radiologic (CR) model and combined model integrating the radiomics score with CR factors. The stability of each model was verified by 10-fold cross-validation. Receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA) were employed to evaluate these models.

Results

Among the 52 HCC patients, high Ang-2 expression was found in 30, and low Ang-2 expression was found in 22. The areas under the ROC curve (AUCs) for the radiomics model, CR model and combined model for predicting Ang-2 expression were 0.800, 0.874, and 0.933, respectively. The DeLong test showed that there was no significant difference in the AUC between the radiomics model and the CR model (p > 0.05) but that the AUC for the combined model was significantly greater than those for the other 2 models (< 0.05). The DCA results showed that the combined model outperformed the other 2 models and had the highest net benefit.

Conclusion

The DCE-MRI-based radiomics model has the potential to predict Ang-2 expression in HCC patients; the combined model integrating the radiomics score with CR factors can further improve the prediction performance.

Graphical abstract

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Metadata
Title
DCE-MRI-based radiomics in predicting angiopoietin-2 expression in hepatocellular carcinoma
Authors
Jing Zheng
Pei-Zhuo Du
Cui Yang
Yun-Yun Tao
Li Li
Zu-Mao Li
Lin Yang
Publication date
26-07-2023
Publisher
Springer US
Published in
Abdominal Radiology / Issue 11/2023
Print ISSN: 2366-004X
Electronic ISSN: 2366-0058
DOI
https://doi.org/10.1007/s00261-023-04007-8

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