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临床试验/NCT04511481
NCT04511481Unknown不适用

Deep Learning Magnetic Resonance Imaging Radiomic Predict Platinum-sensitive in Patients With Epithelial Ovarian Cancer

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University1 个研究点 分布在 1 个国家目标入组 93 人开始时间: 2020年4月15日最近更新:
适应症

试验速览

阶段
不适用
入组人数
93
试验地点
1
主要终点
Platinum sensitivity

研究概览

简要总结

Platinum-sensitive is an important basis for the treatment of recurrent epithelial ovarian cancer (EOC) without effective methods to predict.We aimed to develop and validate the EOC deep learning system to predict the platinum-sensitive of EOC patients through analysis of enhanced magnetic resonance imaging (MRI) images before initial treatment.Ninety-three EOC patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery from Sun Yat-sen Memorial Hospitalin China from January 2011 to January 2020 were enrolled. This deep-learning EOC signature achieved a high predictive power for platinum-sensitive, and the signature based on MRI whole volume is better than that on primary tumor area only.

研究设计

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

入排标准

年龄范围
22 Years 至 99 Years(Adult, Older Adult)
性别
Female
接受健康志愿者

入选标准

  • (1)Patients with epithelial ovarian cancer (2 )Patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery

排除标准

  • Patients with epithelial ovarian cancer received less than 4 cycles platinum-based chemotherapy or no debulking surgery

结局指标

主要结局

Platinum sensitivity

时间窗: 9 years

Platinum sensitivity

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Herui Yao

Principal Investigator

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

研究点 (1)

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