109906
论文已发表
注册即可获取德孚的最新动态
IF 收录期刊
- 3.4 Breast Cancer (Dove Med Press)
- 3.2 Clin Epidemiol
- 2.6 Cancer Manag Res
- 2.9 Infect Drug Resist
- 3.7 Clin Interv Aging
- 5.1 Drug Des Dev Ther
- 3.1 Int J Chronic Obstr
- 6.6 Int J Nanomed
- 2.6 Int J Women's Health
- 2.9 Neuropsych Dis Treat
- 2.8 OncoTargets Ther
- 2.0 Patient Prefer Adher
- 2.2 Ther Clin Risk Manag
- 2.5 J Pain Res
- 3.0 Diabet Metab Synd Ob
- 3.2 Psychol Res Behav Ma
- 3.4 Nat Sci Sleep
- 1.8 Pharmgenomics Pers Med
- 2.0 Risk Manag Healthc Policy
- 4.1 J Inflamm Res
- 2.0 Int J Gen Med
- 3.4 J Hepatocell Carcinoma
- 3.0 J Asthma Allergy
- 2.2 Clin Cosmet Investig Dermatol
- 2.4 J Multidiscip Healthc
已发表论文
基于 CT 影像组学的临床模型预测肝切除术后 VETC 阳性肝细胞癌患者的复发情况
Authors Lei Y , Bai Y , Su Y, Bai X , Wang Y, Zheng C
Received 26 June 2025
Accepted for publication 13 November 2025
Published 19 November 2025 Volume 2025:12 Pages 2585—2598
DOI https://doi.org/10.2147/JHC.S549825
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Prof. Dr. Imam Waked
Yu Lei,1– 3,* Yaowei Bai,1– 3,* Yang Su,1– 3,* Xiatong Bai,1– 3 Yingliang Wang,1– 3 Chuansheng Zheng1– 3
1Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People’s Republic of China; 2Hubei Provincial Clinical Research Center for Precision Radiology & Interventional Medicine, Wuhan, 430022, People’s Republic of China; 3Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Chuansheng Zheng, Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue #1277, Wuhan, 430022, People’s Republic of China, Email hqzcsxh@sina.com Yingliang Wang, Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue #1277, Wuhan, 430022, People’s Republic of China, Email 18345197920@163.com
Objective: To construct a radiomics-based model for predicting postoperative recurrence in hepatocellular carcinoma (HCC) patients with vessels encapsulating tumor clusters (VETC) positive based on CT scan.
Methods: This retrospective study enrolled patients who underwent surgical resection between January 2016 and January 2024 at Union Hospital, with pathologic confirmation of HCC and VETC status. An external test set was drawn from Chegu Hospital, covering January 2018 to January 2022. Tumor segmentation was performed on portal venous phase CT scan, and then radiomics features were extracted. These features were further analyzed using the LASSO algorithm and combined with clinical features to construct a radiomics-clinical combination model. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Patients were divided into high- and low-risk groups based on model scores, and Kaplan-Meier (KM) curves were compared.
Results: A total of 243 patients were included (median age 56.7 years, 211 males). Nine radiomics features and two clinical features were selected to construct the combined model. The area under the ROC curve (AUC) for predicting 1-year recurrence was 0.898 (95% CI: 0.797– 0.999) in the internal test set and 0.804 (95% CI: 0.641– 0.967) in the external test set. Calibration curves and DCA demonstrated high net clinical benefit of the combined model. The median recurrence-free survival (RFS) of patients in the high-risk group was significantly lower than that in the low-risk group (internal test set: 13.5 vs 30.0 months, respectively. P=0.004; external test set: 13.0 vs 31.0 months, respectively. P< 0.0001).
Conclusion: The radiomics-clinical combination model showed high accuracy for preoperatively predicting recurrence in patients with VETC-positive HCC receiving hepatectomy.
Keywords: radiomics, vessels encapsulating tumor clusters, VETC, hepatectomy, recurrence, computed tomography, hepatocellular carcinoma
1Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People’s Republic of China; 2Hubei Provincial Clinical Research Center for Precision Radiology & Interventional Medicine, Wuhan, 430022, People’s Republic of China; 3Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Chuansheng Zheng, Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue #1277, Wuhan, 430022, People’s Republic of China, Email hqzcsxh@sina.com Yingliang Wang, Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue #1277, Wuhan, 430022, People’s Republic of China, Email 18345197920@163.com
Objective: To construct a radiomics-based model for predicting postoperative recurrence in hepatocellular carcinoma (HCC) patients with vessels encapsulating tumor clusters (VETC) positive based on CT scan.
Methods: This retrospective study enrolled patients who underwent surgical resection between January 2016 and January 2024 at Union Hospital, with pathologic confirmation of HCC and VETC status. An external test set was drawn from Chegu Hospital, covering January 2018 to January 2022. Tumor segmentation was performed on portal venous phase CT scan, and then radiomics features were extracted. These features were further analyzed using the LASSO algorithm and combined with clinical features to construct a radiomics-clinical combination model. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Patients were divided into high- and low-risk groups based on model scores, and Kaplan-Meier (KM) curves were compared.
Results: A total of 243 patients were included (median age 56.7 years, 211 males). Nine radiomics features and two clinical features were selected to construct the combined model. The area under the ROC curve (AUC) for predicting 1-year recurrence was 0.898 (95% CI: 0.797– 0.999) in the internal test set and 0.804 (95% CI: 0.641– 0.967) in the external test set. Calibration curves and DCA demonstrated high net clinical benefit of the combined model. The median recurrence-free survival (RFS) of patients in the high-risk group was significantly lower than that in the low-risk group (internal test set: 13.5 vs 30.0 months, respectively. P=0.004; external test set: 13.0 vs 31.0 months, respectively. P< 0.0001).
Conclusion: The radiomics-clinical combination model showed high accuracy for preoperatively predicting recurrence in patients with VETC-positive HCC receiving hepatectomy.
Keywords: radiomics, vessels encapsulating tumor clusters, VETC, hepatectomy, recurrence, computed tomography, hepatocellular carcinoma