Prediction of initial objective response to drug-eluting beads transcatheter arterial chemoembolization for hepatocellular carcinoma using CT radiomics-based machine learning model

Zhang, Xueying1; He, Zijun1; Zhang, Yucong2; Kong, Jian3

2024-01-25

10.3389/fphar.2024.1315732

FRONTIERS IN PHARMACOLOGY   影响因子和分区

1663-9812

Objective: A prognostic model utilizing CT radiomics, radiological, and clinical features was developed and validated in this study to predict an objective response to initial transcatheter arterial chemoembolization with drug-eluting beads (DEB-TACE) for hepatocellular carcinoma (HCC).Methods: Between January 2017 and December 2022, the baseline clinical characteristics and preoperative and postoperative follow-up imaging data of 108 HCC patients who underwent the first time treatment of DEB-TACE were analyzed retrospectively. The training group (n = 86) and the validation group (n = 22) were randomly assigned in an 8:2 ratio. By logistic regression in machine learning, radiomics, and clinical-radiological models were constructed separately. Finally, the integrated model construction involved the integration of both radiomics and clinical-radiological signatures. The study compared the integrated model with radiomics and clinical-radiological models using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).Results: The objective response rate observed in a group of 108 HCC patients who received initial DEB-TACE treatment was found to be 51.9%. Among the three models, the integrated model exhibited superior predictive accuracy in both the training and validation groups. The training group resulted in an area under the curve (AUC) of 0.860, along with sensitivity and specificity values of 0.650 and 0.913, respectively. Based on the findings from the validation group, the AUC was estimated to be 0.927. Additionally, it was found that values of sensitivity and specificity were 0.875 and 0.833, respectively. In the validation group, the AUC of the integrated model showed a significant improvement when contrasted to the clinical-radiological model (p = 0.042). Nevertheless, no significant distinction was observed in the AUC when comparing the integrated model with the radiomics model (p = 0.734). The DCA suggested that the integrated model demonstrates advantageous clinical utility.Conclusion: The integrated model, which combines the CT radiomics signature and the clinical-radiological signature, exhibited higher predictive efficacy than either the radiomics or clinical-radiological models alone. This suggests that during the prediction of the objective responsiveness of HCC patients to the first DEB-TACE treatment, the integrated model yields superior outcomes.

hepatocellular carcinoma drug-eluting beads transcatheter arterial chemoembolization initial response objective response computed tomography radiomics nomogram prediction

SCI

英语

通讯

Key-Area Research and Development Program of Guangdong Province[2020B010165004] ; Beijing Medical Award Foundation[YXJL-2020-0972-1220]

Pharmacology & Pharmacy

Pharmacology & Pharmacy

WOS:001157082500001

FRONTIERS MEDIA SA

Web of Science

1.Jinan Univ, Clin Med Coll 2, Shenzhen, Guangdong, Peoples R China
2.Southern Univ Sci & Technol, Jinan Univ, Shenzhen Peoples Hosp,Clin Med Coll 2, Dept Radiat Oncol,Affiliated Hosp 1, Shenzhen, Guangdong, Peoples R China
3.Southern Univ Sci & Technol, Jinan Univ, Shenzhen Peoples Hosp,Affiliated Hosp 1, Dept Intervent Radiol,Clin Med Coll 2, Shenzhen, Guangdong, Peoples R China

Zhang, Xueying,He, Zijun,Zhang, Yucong,et al. Prediction of initial objective response to drug-eluting beads transcatheter arterial chemoembolization for hepatocellular carcinoma using CT radiomics-based machine learning model[J]. FRONTIERS IN PHARMACOLOGY,2024,15.

Zhang, Xueying,He, Zijun,Zhang, Yucong,&Kong, Jian.(2024).Prediction of initial objective response to drug-eluting beads transcatheter arterial chemoembolization for hepatocellular carcinoma using CT radiomics-based machine learning model.FRONTIERS IN PHARMACOLOGY,15.

Zhang, Xueying,et al."Prediction of initial objective response to drug-eluting beads transcatheter arterial chemoembolization for hepatocellular carcinoma using CT radiomics-based machine learning model".FRONTIERS IN PHARMACOLOGY 15(2024).