NCT05627297招募中不适用
Artificial Intelligence to Optimize Early-stage Hepatocellular CarcinomaTreatment Based on Multi-modal Image
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School1 个研究点 分布在 1 个国家目标入组 200 人开始时间: 2022年12月1日最近更新:
适应症
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 200
- 试验地点
- 1
- 主要终点
- Good/Poor overall survival
研究概览
简要总结
This study intends to establish two prognostic models based on contrast-enhanced ultrasound (CEUS) and dynamic enhanced magnetic resonance (DE-MRI) multimodal images: prognostic model of liver cancer patients after hepatectomy and prognostic model of liver cancer patients after radiofrequency ablation. Combined with artificial intelligence imaging omics, traditional imaging omics and clinical information, to predict and compare the prognosis of two different treatment methods for early liver cancer, so as to realize the individual selection of treatment methods for early liver cancer patients
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Primary single hepatocellular carcinoma confirmed by histology or cytology, with a maximum diameter ≤5.0 cm;
- •Good liver function, Child-Pugh grade A;
- •No serious dysfunction of heart, lung, kidney and other important organs ④ Liver resection or radiofrequency ablation was performed in our hospital, and the study protocol and follow-up procedure were followed.
排除标准
- •Patients who cannot perform DCE-MRI examination due to metal implants in the body ② Patients who had received other treatment before DCE-MRI or CEUS;
- •Invisible lesions, diffuse lesions or poor DCE-MRI/CEUS image quality under CEUS; ④ Drug abuse, clinical or psychological or social factors that make informed consent or study implementation affected.
结局指标
主要结局
Good/Poor overall survival
时间窗: 2022/12/01-2025/12/01
次要结局
未报告次要终点
研究者
研究点 (1)
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