跳至主要内容
临床试验/NCT07111364
NCT07111364招募中不适用

Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound

Peking University First Hospital1 个研究点 分布在 1 个国家目标入组 400 人开始时间: 2025年5月27日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
400
试验地点
1
主要终点
Overall Diagnostic Accuracy

研究概览

简要总结

This study aims to develop an ultrasound image-based deep learning system to enable automatic segmentation, T-staging, and pathological grading prediction of bladder tumors. It seeks to enhance the objectivity, accuracy, and efficiency of bladder cancer diagnosis, reduce reliance on physician experience, and provide support for precision medicine and resource optimization.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Other

入排标准

年龄范围
18 Years 至 85 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • ① Suspected bladder mass detected by abdominal ultrasound (age ≥18 years);② Patients scheduled for surgical treatment of bladder tumors.

排除标准

  • Age >85 years;
  • Patients unable to undergo abdominal/transrectal ultrasound (e.g., uncooperative individuals, technically inadequate images);
  • History of bladder tumor surgery, radiotherapy, chemotherapy, or systemic therapy within 3 months; ④ Patients with indwelling medical devices (e.g., double-J ureteral stents, urinary catheters);
  • Failure to undergo bladder tumor surgery within 2 weeks post-ultrasound; ⑥ Non-urothelial carcinoma or pathologically unconfirmed diagnoses.

结局指标

主要结局

Overall Diagnostic Accuracy

时间窗: From may 2025 to may 2027

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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