A Vision-Language Foundation Model for Brain Disease Diagnosis From Multimodal Data
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 100,000
- 试验地点
- 1
- 主要终点
- Brain Disease Diagnostic performance
研究概览
简要总结
The goal of this observational study is to develop an innovative, comprehensive, and explainable AI vision-language foundation model (VLM) to advance the diagnosis and interpretation of brain diseases using multi-modal data. We will include patient demographics, medical imaging data (such as MRI, CT, and PET scans), histopathological data, genomic data when available, and other necessary laboratory examinations and tests to establish a screening and diagnostic model for brain diseases.
详细描述
Secondary Objective: To establish a comprehensive diagnostic model with uncertainty quantification and automated report generation that covers all brain diseases based on clinical indicators.
Exploratory Objective: To include MRI scans from large-scale populations for model validation.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Retrospective
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Patients with brain diseases:
- •Patients with brain tumors were pathologically diagnosed.
- •Patients with other brain diseases were correctly diagnosed.
- •The clinical case data of all patients were complete.
- •Non-brain disease population:
- •All patients have complete clinical case data, complete brain MRI, no history brain diseases, no brain surgery or other brain diseases that affect the diagnosis and observation of MR imaging.
排除标准
- •Cases in which MRI were incomplete or with significant noise and artifacts.
结局指标
主要结局
Brain Disease Diagnostic performance
时间窗: Perioperative
This study will evaluate how accurately the AI model can identify and differentiate between: 1. Brain tumors including gliomas, glioneuronal tumors, and neuronal tumor, meningioma, germ cell tumors, embryonal tumors, tumors of the sellar region, pineal region tumors, mesenchymal, non-meningothelial tumors, choroid plexus tumors, hematolymphoid tumors, cranial and paraspinal nerve tumors, melanocytic tumors and brain metastases based on WHO CNS 5 classification; 2. Brain diseases apart from brain tumors such as brain arterial disease, neurodegenerative disorders, etc.; 3. Normal brain findings; The model's performance will be assessed using sensitivity, specificity, F1-score AUC-ROC. Diagnostic ability of AI model will be compared against with pathological diagnosis(if possible), final clinical diagnoses by neurologists or radiologists.
次要结局
未报告次要终点
研究者
Xuan Gong
Associate Consultant
Xiangya Hospital of Central South University