Clinical, patHOlogical and Imaging Project of nEuro-oncology (HOPE)
- Conditions
- Glioma
- Interventions
- Diagnostic Test: This study does not intervene in this process.
- Registration Number
- NCT05859659
- Lead Sponsor
- Beijing Tiantan Hospital
- Brief Summary
Glioma disease is the most common primary malignant tumor of the central nervous system, with an annual incidence of about 3-8 people per 100,000 population, of which glioblastoma with the highest degree of malignancy and the worst prognosis accounts for 70-75%. The construction goal of this project is to construct a multivariate retrospective glioma database (3000 cases) integrating clinical information, magnetic resonance imaging examination and molecular pathological results, and a prospective glioma database (500 cases) integrating advanced magnetic resonance sequences. It aims to form a standardized database integrating clinical-prognostic information, magnetic resonance imaging and pathological results. Based on the construction of the above standardized database, the specifications for the acquisition of cranial magnetic resonance images, the image segmentation and labeling process, and the expert consensus on database construction and use management of glioma diseases were established. Form a multimodal, large-capacity, high-quality, and rich medical imaging database that conforms to the characteristics of Chinese groups and clinical diagnosis and treatment norms; On this basis, the data are dynamically updated, in-depth mining, and the classification and grading standards of glioma diseases, prognosis judgment criteria and treatment efficacy evaluation system are formulated.
- Detailed Description
Glioma disease is the most common primary malignant tumor of the central nervous system, with an annual incidence of about 3-8 people per 100,000 population, of which glioblastoma with the highest degree of malignancy and the worst prognosis accounts for 70-75%. The construction goal of this project is to construct a multivariate retrospective glioma database (3000 cases) integrating clinical information, magnetic resonance imaging examination and molecular pathological results, and a prospective glioma database (500 cases) integrating advanced magnetic resonance sequences. It aims to form a standardized database integrating clinical-prognostic information, magnetic resonance imaging and pathological results. Based on the construction of the above standardized database, the specifications for the acquisition of cranial magnetic resonance images, the image segmentation and labeling process, and the expert consensus on database construction and use management of glioma diseases were established. Form a multimodal, large-capacity, high-quality, and rich medical imaging database that conforms to the characteristics of Chinese groups and clinical diagnosis and treatment norms; On this basis, the data are dynamically updated, in-depth mining, and the classification and grading standards of glioma diseases, prognosis judgment criteria and treatment efficacy evaluation system are formulated.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 3500
- (1) a clear diagnosis of glioma based on pathological results;
- (2) The MRI sequence is complete and there are no obvious artifacts in the image;
- (3) The patient signs an informed consent form
- (1) Suffering from other neurological diseases;
- (2) Prior to enrollment, surgery or biopsy, or a history of radiation therapy or chemotherapy;
- (3) Unable to complete clinical scoring and related laboratory tests, unable to complete follow-up;
- (4) Unable to tolerate MRI examination; Poor image quality, such as motion artifacts.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Molecular pathology of glioma negative This study does not intervene in this process. - Molecular pathology of glioma positive This study does not intervene in this process. -
- Primary Outcome Measures
Name Time Method Establish standardized clinical-MRI -molecular markers database for glioma 2022.01-2024.12 1) Collect clinical, MRI and molecular markers data of glioma patients; 2) Establish a standardized tumor labeling database; 3) Establish an automatic segmentation and recognition model of glioma
Establish an accurate MRI-based deep-learning model for the prediction of glioma 2022.01-2024.12 1) Build an accurate MRI-based deep-learning model with retrospective data. 2) The multicenter data was used to verify the repeatability and widespread use of the model again
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Beijing Tiantan Hospital
🇨🇳Beijing, Beijing, China