Development and Application of AI-Based Therapeutic Strategies for Esophageal Cancer Integrating Multimodal Imaging and Digital Pathology
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 7,000
- 主要终点
- Pathological Complete Response (pCR) Rate
研究概览
简要总结
The purpose of this clinical study is to conduct a multi-center, big data study to create a neural network decision model for predicting treatment efficacy and prognosis based on multi-modal, multi-temporal imaging features combined with tumor microenvironment scores. It will also use various model interpretation techniques to clarify the role and mechanism of key biomarkers or strongly associated biomarker groups in treatment efficacy and prognosis. Ultimately, it aims to achieve the research and application of AI treatment strategies combining multi-modal imaging and digital pathology to guide clinicians in the personalized treatment strategies for patients with esophageal squamous cell carcinoma.
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
- •Aged 18-70 years;
- •Histologically confirmed esophageal carcinoma by biopsy;
- •No prior antitumor therapy received.
排除标准
- •Contraindications to MRI examination;
- •Poor compliance with antitumor therapy;
- •Unwillingness to participate in the study;
- •Image quality inadequate for diagnostic requirements.
结局指标
主要结局
Pathological Complete Response (pCR) Rate
时间窗: January 2025 - December 2027
The proportion of patients achieving pathological complete response (ypT0 ypN0) after neoadjuvant therapy.
Overall Survival (OS)
时间窗: January 2025 - December 2027
The time from treatment initiation to death from any cause.
Event-Free Survival (EFS)
时间窗: January 2025 - December 2027
The time from treatment initiation to disease progression, recurrence, new primary cancer, or death.
Disease-Free Survival (DFS)
时间窗: January 2025 - December 2027
The time from curative-intent surgery to disease recurrence or death.
次要结局
未报告次要终点
研究者
Qujinrong
Clinical Professor
Henan Cancer Hospital
