NCT06331130招募中不适用
CT Detected Tumour Infiltration Patterns of the Mesentery in High Grade Ovarian Carcinoma (HGSOC) Patients, Their Role in Treatment Planning and Outcome Prediction and How Machine Learning Can be Applied to Identify Them.
Fondazione Policlinico Universitario Agostino Gemelli IRCCS1 个研究点 分布在 1 个国家目标入组 510 人开始时间: 2024年3月1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
- 510
- 试验地点
- 1
- 主要终点
- Preoperative Artificial Intelligence assisted CT-based evaluation
研究概览
简要总结
To evaluate if CT features at diagnosis in patients with HGSOC can be used to build an Artificial Intelligence model capable of discerning the pathological involvement of the mesentery, assessing the potential impediments for an optimal debulking surgery and predicting the development of resistance to platinum based chemotherapeutic agents.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •Women with confirmed HGSOC wiht mesenteric involvment
- •Age > 18 years
- •FIGO STAGE IIIB-IV
- •Primary diagnosis
- •Signed informed consent
排除标准
- •Non-serous high grade epithelial ovarian cancer (serous low grade, mucinous, clear cell carcinoma, endometrioid or non-epithelial ovarian cancer)
- •Early stage disease (I and II stage)
- •CT scan not available
- •Non-primary diagnosis or patient subjected to neoadjuvant chemotherapy
结局指标
主要结局
Preoperative Artificial Intelligence assisted CT-based evaluation
时间窗: 1 year
Preoperative Artificial Intelligence assisted CT-based prediction of patients with suboptimal debulking at surgery due to diffuse mesenteric disease or mesenteric retraction.
次要结局
- Prediction of Platinum Resistance(1 year)
- Evaluation of the Radiologist Assessment of the CT(1 year)
- Prediction of Progression Free Survival (PFS) and Overall Survival (OS)(2 years)
研究者
研究点 (1)
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