Research on AI-assisted Diagnosis of Common Malignant Brain Tumors Based on Magnetic Resonance Imaging
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 3,000
- 试验地点
- 2
- 主要终点
- Construct an AI-assisted diagnostic system for multiple subtypes of brain tumors based on deep learning.
研究概览
简要总结
This study aims to establish a large-scale, multi-center MRI database for malignant brain tumors. It will develop an artificial intelligence system for the segmentation and classification of multiple subtypes of brain tumors (including glioma, metastatic tumor and lymphoma et al.) using deep learning technology. This will address the issues of small sample sizes and limited classification performance in existing methods, thereby improving the accuracy of non-invasive preoperative diagnosis, reducing the need for biopsies, and having significant clinical translational value.
详细描述
This study is mainly based on two centers, the Second Affiliated Hospital of Zhejiang University School of Medicine and the Zhejiang Cancer Hospital. It retrospectively collects cases of malignant brain tumors (including gliomas, brain metastases, and brain lymphomas) that have been confirmed by histopathology and have preoperative multimodal MRI images (mainly including CE-T1WI and T2-FLAIR). It is expected to include 3,000 cases. Axial CE-T1WI and T2-FLAIR images of all patients were obtained on 3.0T or 1.5T magnetic resonance imaging systems. A large-scale, multi-center MRI image database for common malignant brain tumors (gliomas, brain metastases, and brain lymphomas) was planned to be constructed. To address the automatic segmentation of complex lesion tissues in brain tumors and the auxiliary diagnosis of common malignant brain tumors, a deep learning technical approach was adopted. A deep learning-based multi-subtype brain tumor segmentation and classification diagnostic method was proposed, aiming to build an image artificial intelligence-assisted diagnostic system for common malignant brain tumors and improve the accuracy of auxiliary diagnosis of common brain malignancies.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 100 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients diagnosed with glioma, brain metastases, and brain lymphoma by pathology, with the patient being at least 18 years old; preoperative MRI was complete.
排除标准
- •Poor image quality; history of previous brain surgery or radiotherapy; accompanied by other intracranial lesions.
结局指标
主要结局
Construct an AI-assisted diagnostic system for multiple subtypes of brain tumors based on deep learning.
时间窗: 30 days
Construct an AI-assisted diagnostic system for multiple subtypes of brain tumors based on deep learning, mainly including glioma, metastatic tumor and lymphoma.
次要结局
未报告次要终点