A Multimodal Deep Learning-Driven Study for Perioperative Risk Stratification and Precision Intervention in Hepatocellular Carcinoma Recurrence
This study is for patients with early-stage liver cancer who are planning to have surgery. The goal of this research is to see if a personalized treatment plan, guided by a computer model (an artificial intelligence tool), can help prevent the cancer from coming back after surgery. First, the computer model will analyze each patient's medical images and health data to predict their personal risk of the cancer returning. Patients whom the model predicts have a high risk of the cancer coming back will be offered a special treatment plan. This plan involves receiving medication (neoadjuvant therapy) before surgery and additional medication (adjuvant therapy) after surgery. The effectiveness of this plan will be compared to the standard approach of surgery alone. The main goal is to see if this new, personalized plan can better prevent the cancer from returning within 2 years after surgery. The study will also closely monitor the safety of the medications used. All patients in the study will be followed closely for 2 years with regular scans and check-ups to monitor their health.
• Age and Consent: Patients aged 18-75 years who are able to understand and voluntarily sign an Informed Consent Form.
⁃ Diagnosis: Clinical diagnosis of BCLC stage 0-A hepatocellular carcinoma, confirmed by histopathology or non-invasive imaging criteria per guidelines.
⁃ Surgical Candidacy: Scheduled to undergo curative-intent liver resection. Risk Stratification: Predicted as high-risk for aggressive recurrence by the pre-operative multimodal deep learning model (PRE score ≥ 0.5).
⁃ Liver Function: Child-Pugh liver function class A (score ≤ 7). Performance Status: ECOG Performance Status of 0 or 1. Imaging Requirement: Availability of a standard pre-operative MRI scan (including non-contrast, arterial, portal venous, and delayed phases) performed within 1 month prior to enrollment, with acceptable image quality.
⁃ Follow-up Commitment: Willing and able to comply with the study procedures and scheduled follow-up for at least 2 years.