Researchers analyzed data from patients with hepatocellular carcinoma to see if computer models could predict treatment outcomes. The study focused on people with Barcelona Clinic Liver Cancer stage A or B tumors larger than 3 centimeters. These patients were scheduled for transarterial chemoembolization, a common local therapy for liver cancer.
The team compared standard clinical information against AI models that used gadoxetic acid-enhanced MRI scans. The AI models applied radiomics and deep learning techniques to the images. They found that the deep learning model performed best, correctly predicting outcomes in 96% of the training group and 92% of the test group. Standard clinical scores were less accurate, reaching only 79% and 70% accuracy respectively.
The study also found that the AI model's output was linked to overall survival. Patients with a higher risk score from the model had a significantly lower chance of long-term survival. While the AI tools showed promise for planning individualized treatment, this research was based on a specific group of patients and the models were not yet proven for general use.