Integration of Multimodal Computed Tomography Radiomic Features of Primary Tumors and the Spleen to Predict Early Recurrence in Patients with Postoperative Adjuvant Transarterial Chemoembolization

Abstract

Cong Chen,1,* Jian Liu,2,* Zhuxin Gu,1 Yanjun Sun,1 Wenwu Lu,3 Xiaokan Liu,4 Kang Chen,1 Tianzhi Ma,5 Suming Zhao,1 Hui Zhao1 1Department of Interventional & Vascular Surgery, Affiliated Hospital of Nantong University, Nantong, 226001, People’s Republic of China; 2Dalian Medical University and Affiliated Hospital of Nantong University, Nantong, 226001, People’s Republic of China; 3Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, 226001, People’s Republic of China; 4Department of Interventional Radiology, Affiliated Hospital 2 of Nantong University, Nantong, 226001, People’s Republic of China; 5Nanjing University of Aeronautics and Astronautics, Nanjing, 210000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Suming Zhao; Hui Zhao, The Affiliated Hospital of Nantong University, No. 20, Xisi Road, Chongchuan District, Nantong City, Jiangsu Province, People’s Republic of China, Tel [phone], Email [email protected]; [email protected]: Hepatocellular carcinoma (HCC) is one of the most lethal malignancies in the world. Patients with HCC choose postoperative adjuvant transarterial chemoembolization (PA-TACE) after surgical resection to reduce the risk of recurrence. However, many of them have recurrence within a short period.Methods: In this retrospective analysis, a total of 173 patients who underwent PA-TACE between September 2016 and March 2020 were recruited. Radiomic features were derived from the arterial and venous phases of each patient. Early recurrence (ER)-related radiomics features of HCC and the spleen were selected to build two rad-scores using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Logistic regression was applied to establish the Radiation (Rad)_score by combining the two regions. We constructed a nomogram containing clinical information and dual-region rad-scores, which was evaluated in terms of discrimination, calibration, and clinical usefulness.Results: All three radiological scores showed good performance for ER prediction. The combined Rad_score performed the best, with an area under the curve (AUC) of 0.853 (95% confidence interval [CI], 0.783– 0.908) in the training set and 0.929 (95% CI, 0.789– 0.988) in the validation set. Multivariate analysis identified total bilirubin (TBIL) and the combined Rad_score as independent prognostic factors for ER. The nomogram was found to be clinically valuable, as determined by the decision curves (DCA) and clinical impact curves (CIC).Conclusion: A multimodal dual-region radiomics model combining HCC and the spleen is an independent prognostic tool for ER. The combination of dual-region radiomics features and clinicopathological factors has a good clinical application value.Keywords: hepatocellular carcinoma, radiomics, nomogram, transcatheter arterial chemoembolization, computed tomography

Keywords

• hepatocellular carcinoma
• radiomics
• nomogram
• transcatheter arterial chemoembolization
• computed tomography.