Prediction of Microvascular Invasion in HCC Using Spatiotemporal Radiomics of Contrast-enhanced Ultrasound: a Deep Learning Model With Transcriptomics Correlation
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 250
- 试验地点
- 2
- 主要终点
- area under operating characteristic curves (AUC)
研究概览
简要总结
An artificial intelligence (AI) model to predict MVI of HCC using contrast-enhanced ultrasound was constructed. This model also has biological explainability. The investigators named it as MAPUSE (MVI AI prediction via contrast-enhanced ultrasound with explainability).
The goal of MAPUSE study is to prospectively test the performance of MAPUSE model on MVI prediction and its biological correlation in different geographical areas of China.
详细描述
The presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a critical prognostic indicator, but its preoperative diagnosis remains challenging. Contrast-enhanced ultrasound (CEUS), with its dynamic microvascular imaging capability, holds promise in prediction of MVI.
The investigators constructed an artificial intelligence (AI) model to predict MVI using contrast-enhanced ultrasound. This model also has biological explainability. We named it as MAPUSE (MVI AI prediction via contrast-enhanced ultrasound with explainability).
The goal of MAPUSE study is to prospectively test the performance of MAPUSE model on MVI prediction and its biological correlation in different geographical areas of China.
The performance of MAPUSE is to be tested in two prospective testing cohorts from two centers in southern and northern China. Before surgery, patient CEUS videos will be collected and analysed by MAPUSE model to generate an MVI risk score. According to the postoperative pathological diagnosis of MVI (golden criterion), the result of MAPUSE will be evaluated. Parameters include area under curve (AUC), accuracy (ACC), sensitivity, specificity and F1-score.
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 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age >18 years old.
- •The HCC diagnosis and the presence of MVI were confirmed by surgical pathology.
- •Complete and clear CEUS videos obtained within two weeks preoperatively.
排除标准
- •Unqualified CEUS images.
- •Missing surgical pathological diagnosis.
- •Lesions underwent local treatments.
- •Non-HCC diagnosis
结局指标
主要结局
area under operating characteristic curves (AUC)
时间窗: From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively)
the area under operating characteristic curves (AUC) to evaluate the performance of MAPUSE model in predicting MVI in HCC patients
次要结局
- ACC (accuracy)(From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively))
- Specificity(From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively))
- Sensitivity(From preoperative enrollment to the postoperative confirmation of pathological diagnosis (7-15 days postopertively))
研究者
Ping Liang
Professor
Chinese PLA General Hospital