A Comprehensive Study of Liver Cancer Diagnosis and Prognosis Prediction Based on Artificial Intelligence and Multimodal Data
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 600
- 试验地点
- 1
研究概览
简要总结
This study aims to develop a comprehensive artificial intelligence model system integrating preoperative multimodal data (CT/MRI imaging, clinical laboratory data, and radiology report text) to achieve two core objectives. First, to develop a multimodal fusion diagnostic model for non-invasive and accurate preoperative differentiation of liver cancer subtypes, including distinguishing benign from malignant lesions and differentiating hepatocellular carcinoma from intrahepatic cholangiocarcinoma. Second, to develop a prognostic prediction model for patients with confirmed liver cancer undergoing radical surgery to assess postoperative progression-free survival and overall survival. This is a multicenter retrospective cohort study with an anticipated sample size of ≥600 patients. Model performance will be evaluated using AUC, accuracy, sensitivity, specificity, C-index, and calibration curves. Subgroup analysis will be conducted based on whether patients received neoadjuvant therapy.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Diagnostic Model Cohort:
- •Age ≥18 years
- •Underwent preoperative contrast-enhanced CT or MRI for clinically suspected liver space-occupying lesion
- •Have complete preoperative clinical laboratory data
- •Have complete original CT/MRI imaging data and radiology reports
- •Have definite pathological diagnosis from surgery or biopsy as gold standard
- •Prognostic Prediction Model Cohort (selected from diagnostic cohort):
- •Meet all diagnostic cohort inclusion criteria
- •Pathologically confirmed liver cancer
- •Underwent radical hepatectomy
- •Have complete preoperative multimodal data (CT/MRI imaging, clinical laboratory data, radiology reports)
- •Have complete postoperative follow-up data to determine progression-free survival and overall survival endpoints and time (minimum follow-up of 24 months)
排除标准
- •· Key clinical, imaging, or pathological data severely missing or incomplete
- •Preoperative CT or MRI images of poor quality or missing sequences, unable to perform reliable image analysis
- •Prior local treatment for the target liver lesion, unless clearly recorded as neoadjuvant therapy before surgery
- •Concurrent other malignant tumors
- •Lost to follow-up or follow-up data cannot meet endpoint determination requirements
研究组 & 干预措施
Diagnostic
Diagnostic Model Cohort: Patients with suspected liver space-occupying lesions who underwent preoperative contrast-enhanced CT or MRI and have definite pathological diagnosis (surgical or biopsy) as gold standard.
Prognostic
Prognostic Prediction Model Cohort: Patients selected from the diagnostic cohort who were pathologically diagnosed with liver cancer, received radical hepatectomy, and have complete postoperative follow-up data (minimum 24 months) to determine progression-free survival and overall survival endpoints.
研究者
Fubo Wang
Doctor of Medicine
Guangxi Medical University