Using Artificial Intelligence to Predict Recurrence of Colorectal Cancer Liver Metastases After Liver Surgery

What this Trial Is About

Colorectal cancer is a common and serious cancer worldwide, with survival mainly depending on disease stage and metastases presence. This research aims to evaluate whether a machine learning model that includes clinical and radiomic data can identify patients with colorectal cancer liver metastases who have a high risk of disease progression after chemotherapy and recurrence after liver resection. The study focuses on improving treatment allocation by predicting outcomes better than current methods. The study involves patients with colorectal cancer liver metastases who have undergone liver resection with or without liver ablation, combined with perioperative chemotherapy before, after, or both. This is an observational, retrospective study using data collected from medical records and imaging. The research will apply artificial intelligence techniques to analyze clinical and radiological information, especially from CT and MRI scans, to predict recurrence and chemotherapy response. Participants data will be analyzed to develop machine learning algorithms that predict early disease recurrence within six months after liver resection and response to neoadjuvant chemotherapy over an average period of 18 months. The study uses digital healthcare data and imaging features to enhance prediction accuracy. The involvement includes reviewing medical history, imaging scans, and clinical follow-up to monitor outcomes and inform future treatment decisions.

The Use of Artificial Intelligence for the Prediction of Recurrence After Resection of Colorectal Liver Metastases