Clinical Efficacy of Interventional Chemotherapy Embolization Combined with Monopolar Radiofrequency Ablation on Patients with Liver Cancer

Due to the greater prevalence of chronic hepatitis B infection, liver tumor is especially popular in China. In China, it is the 4th most prevalent tumor and the 3rd main reason for cancer fatalities. Hepatocellular carcinomas (HCCs) account for more than 91% of every liver tumor case, and chemotherapy and immunotherapy are the better therapy choices. It is a serious threat to the lives and health of Chinese citizens. Patients diagnosed with liver tumors have a bad prognosis. Surgical resection, liver transplantation, chemotherapeutic embolization, and radiofrequency ablation (RFA) are all choices for patients who are detected early. More effective therapies can result in a better prognosis. This paper analyzes the clinical efficiency of interventional transarterial chemoembolization (TACE) integrated with monopolar radiofrequency ablation (RFA) on patients with a liver tumor. Initially, the dataset is collected and the patients are treated with combined TACE and RFA. The computed tomography (CT) images are obtained using three-phase CT imaging. The images are segmented using adaptive U-Net-based segmentation. The clinical efficiency of the patients is evaluated using Robust Residual Convolutional Neural Network (RR-CNN) which is optimized using Firefly Particle Swarm Optimization (FPSO) algorithm. The performance of the system is analyzed using the MATLAB simulation tool. In performance analysis, the proposed method of RR-CNN is high when compared to the existing method of CNN, logistic regression using genetic algorithm and KNN in overall parameters are accuracy, sensitivity, F1-score, and specificity. These integrated treatments have a suggested greater response frequency, indicating a synergistic impact by combination treatment in the initial stages.