Application of CT Radiomics in the Short-Term Prognosis of Combined Therapy for Hepatocellular Carcinoma

Qianting DUAN; Guanshun WANG; Rong DING; Na WANG; Hongli CUN; Ling YANG

doi:10.12259/j.issn.2095-610X.S20220818

Volume 44 Issue 1

Jan. 2023

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Article Navigation > Journal of Kunming Medical University > 2023 > 44(1): 128-134

Qianting DUAN, Guanshun WANG, Rong DING, Na WANG, Hongli CUN, Ling YANG. Application of CT Radiomics in the Short-Term Prognosis of Combined Therapy for Hepatocellular Carcinoma[J]. Journal of Kunming Medical University, 2023, 44(1): 128-134. doi: 10.12259/j.issn.2095-610X.S20220818

Citation:

Qianting DUAN, Guanshun WANG, Rong DING, Na WANG, Hongli CUN, Ling YANG. Application of CT Radiomics in the Short-Term Prognosis of Combined Therapy for Hepatocellular Carcinoma[J]. Journal of Kunming Medical University, 2023, 44(1): 128-134. doi: 10.12259/j.issn.2095-610X.S20220818

Citation:

Qianting DUAN, Guanshun WANG, Rong DING, Na WANG, Hongli CUN, Ling YANG. Application of CT Radiomics in the Short-Term Prognosis of Combined Therapy for Hepatocellular Carcinoma[J]. Journal of Kunming Medical University, 2023, 44(1): 128-134. doi: 10.12259/j.issn.2095-610X.S20220818

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Application of CT Radiomics in the Short-Term Prognosis of Combined Therapy for Hepatocellular Carcinoma

doi: 10.12259/j.issn.2095-610X.S20220818

Dept . of Radiology，The 3rd Affiliated Hospital of Kunming Medical University/ Yunnan Tumor Hospital，Kunming Yunnan 650118，China

Received Date: 2022-09-22
Available Online: 2022-07-14
Publish Date: 2023-01-18

Abstract

Abstract

Objective To investigate the value of enhanced CT radiomics model in predicting the short-term efficacy （within 6 months） of TACE combined with sorafenib in hepatocellular carcinoma. Method The clinical, pathological and preoperative CT images of 159 HCC patients treated with TACE combined with solafenib were retrospectively analyzed. Local tumor control rate was assessed according to the modified Response Evalaution Criteria in Solid Tumors （mRECIST） 6 months later. The imaging features of arterial and portal phases were extracted to establish radiomics model. The general preoperative clinical risk factors and basic imaging features were analyzed to establish a preoperative clinical model. Radiomics model were added to the preoperative clinical model to form a combined model. The receiver operating characteristic curves （ROC） of the three models were drawn and calculate the area under the curve （AUC） respectively. Results A total of 11 feature values were selected from 1 708 radiomic features to establish the raduomics model. The AUC of training group and the validation group was 0.945 and 0.918 respectively. Except the maximum diameter line and number of tumors, the differences were statistically significant （P < 0.05）, while the other differences were not statistically significant （P > 0.05）. The AUC of the clinical model training group and the validation group was 0.811 and 0.857 respectively. The AUC of the combined model training group is 0.958, and that of validation group is about 0.95. Conclusion The radiomics model constructed in this study is a powerful independent predictor for predicting the short-term efficacy of TACE combined with sorafenib, which can significantly improve the predictive ability of preoperative clinical model, screen patients with higher risk of progression before TACE combined with sorafenib treatment, and help clinicians to develop personalized treatment and follow-up plan to improve the prognosis of patients.
- Hepatocellular carcinoma,
- Radiomics,
- Sorafenib,
- Transcatheter arterial chemoembolization

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References(18)

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