NCT07050576招募中不适用
Deep Learning and Radiomics for Prediction of Lymph Node Metastasis in Early-stage Esophageal Squamous Cell Carcinoma
The First Affiliated Hospital of Anhui Medical University1 个研究点 分布在 1 个国家目标入组 500 人开始时间: 2024年5月1日最近更新:
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 500
- 试验地点
- 1
- 主要终点
- AUC(the area under the curve) values of the model
研究概览
简要总结
This study aims to develop a predictive model using deep learning and radiomics to assess the likelihood of lymph node metastasis in patients with early-stage esophageal squamous cell carcinoma (ESCC). Lymph node metastasis is a critical factor in determining the treatment approach and prognosis for ESCC patients. By analyzing medical imaging data, we hope to create a non-invasive method that can assist doctors in making more accurate treatment decisions. This research could improve patient outcomes by enabling earlier and more tailored interventions.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Retrospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients with pathologically confirmed early-stage (T1) ESCC
- •Preoperative contrast-enhanced CT data within 2 weeks before surgery
- •Without any treatment before surgical resection
排除标准
- •Patients who underwent neoadjuvant therapy or endoscopic treatment
- •Insufficient CT imaging or poor CT quality
- •Incomplete pathology results
- •Presence of metastatic disease
结局指标
主要结局
AUC(the area under the curve) values of the model
时间窗: 4 years
The performance and clinical relevance of the models were assessed by analyzing the area under the curve (AUC).
次要结局
未报告次要终点
研究者
研究点 (1)
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