Predicting Pathological Response of Neoadjuvant Conversion Therapy for Hepatocellular Carcinoma Patients Using CT-Based Radiomics Model

Abstract

Haoxiang Wen,1,2,* Ruiming Liang,3,* Xiaofei Liu,4 Yang Yu,1 Shuirong Lin,1 Zimin Song,1 Yihao Huang,1 Xi Yu,1 Shuling Chen,5 Lili Chen,6 Baifeng Qian,1 Jingxian Shen,7 Han Xiao,8 Shunli Shen1 1Center of Hepato-Pancreatico-Biliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong Province, People’s Republic of China; 2Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong Province, People’s Republic of China; 3Department of Medical Statistics, Clinical Trials Unit, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong Province, People’s Republic of China; 4Department of Gastroenterology, The First Affiliated Hospital of Sun Yat-senUniversity, Guangzhou, Guangdong Province, People’s Republic of China; 5Precision Medicine Institute, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong Province, People’s Republic of China; 6Department of Pathology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong Province, People’s Republic of China; 7Department of Radiology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province, People’s Republic of China; 8Division of Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Shunli Shen, Center of Hepato-Pancreatico-Biliary Surgery, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhong-Shan Road2, Guangzhou, Guangdong Province, People’s Republic of China, Email [email protected] Han Xiao, Division of Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road2, Guangzhou, Guang- Dong Province, People’s Republic of China, Email [email protected]: Predicting the pathological response after neoadjuvant conversion therapy for initially unresectable hepatocellular carcinoma (HCC) is essential for surgical decision-making and survival outcomes but remains a challenge. We aimed to develop a radiomics model to predict pathological responses.Methods: We included 203 patients with HCC who underwent hepatectomy after neoadjuvant conversion therapy between 2015 and 2023 and separated them into a training set (100 patients from Center A) and a validation set (103 patients from Center B). Pathological complete response (pCR)-related radiomic features were extracted from the largest tumor layer in the arterial and portal vein phases of the CT. A synthetic minority oversampling technique (SMOTE) was used to balance the minority groups in the training set. The SMOTE radiomics model was constructed using a logistic regression model in the SMOTE training set and its performance was verified in the validation set.Results: The AUC of the preoperative modified response evaluation criteria in solid tumors (mRECIST) assessment for pCR was 0.656 and 0.589 in the training and validation sets, respectively. The SMOTE radiomics model was established based on ten radiomic features and showed good pCR-predictive performance in the SMOTE training set (AUC, 0.889; accuracy, 87.7%) and the validation set (AUC: 0.843, accuracy: 86.4%). The RFS of the radiomics-predicted-pCR group was significantly better than that of the predicted-non-pCR group in the training cohort (P = 0.001, 2-year RFS: 69.5% and 30.1% respectively) and the validation cohort (P = 0.012, 2-year RFS: 65.9% and 38.0% respectively).Conclusion: The SMOTE radiomics model has great potential for predicting pathological response and evaluating RFS in patients with unresectable HCC after neoadjuvant conversion therapy.Keywords: hepatocellular carcinoma, radiomics, pathological complete response, neoadjuvant conversion therapy

Keywords

• hepatocellular carcinoma
• radiomics
• pathological complete response
• neoadjuvant conversion therapy.