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Primary central nervous system (CNS) tumors, the vast majority (>90%) occurring in the brain and the remainder occurring in the meninges, spinal cord, and cranial nerves, showing an annual incidence of about 6-8 people per 100,000 population but its effects on health-care systems is out of proportion with incidence due to the substantial high rates of morbidity and mortality. Among which, glioma disease is the most common primary malignant CNS tumor, while the glioblastoma that showed 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 CNS tumor database (over 50,000 cases, including 10,000 glioma) integrating clinical information, preoperative magnetic resonance imaging examination and molecular pathological results, and a prospective glioma database (3,000 cases) integrating advanced magnetic resonance sequences and postoperative follow-up. It aims to form a standardized database integrating magnetic resonance imaging, pathological results, and clinical-prognostic information.
Based on the construction of the above standardized database, the specifications for the acquisition of cranial magnetic resonance images, the image segmentation, tumor classification and labeling process, and the expert consensus on database construction and use management of CNS tumors were established. We aim to 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 CNS tumor diseases, prognosis judgment criteria and treatment efficacy evaluation system are formulated, and providing comprehensive resources of retrospective data and prospective cohorts for large-scale reasearches, such as classification or treatment intervention predictions.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Retrospective database of CNS tumors included in the WHO classification (2021) | The subtypes of brain tumors were confirmed by the postoperative histopathology or molecular pathology |
| |
| Prospective cohort of suspected CNS tumors | Intracranial mass lesion comfirmed by preoperative neuroimaging |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| This study does not intervene in this process. | Diagnostic Test | This study does not intervene in this process. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Establish standardized clinical-MRI-molecular markers database for CNS tumors | Collecting at least 50,000 retrospective data of CNS tumors patients, including preoperative brain MRI, clinical infromations, histopathology resuluts, and molecular markers, to establish a multi-modal clinical-MRI-molecular database | 2022.06-2023.12 |
| Establish prospective brain tumor cohort with multiomics information | Prospectively include at leaset 10,000 patients with brain space occupying lesions comfirmed by neuroimaging, recording their pre- and postoperative brain MRI, imaging diagnosis, histopathology or molecular pathology results, clinical intervention, treatment effect, and survival time. | 2022.06.01-2030.12.31 |
| Measure | Description | Time Frame |
|---|---|---|
| Accurately predicting the molecular and survival of glioma patients based on a deep learning model | Build a MRI-based deep-learning model to predict molecular and survival on glioma. | 2022.01-2024.12 |
| Measure | Description | Time Frame |
|---|---|---|
| Establish a large-scale foundation model for brain tumors on MRI | Developing artificial intelligence (AI) tools for brain tumors diagnosis and prediction using the retrospective MRI database with paired imaging reports and histopathological labeling, and conducting internal tests on the prospective cohort to evaluate AI model performance. | 2024.12-2026.12 |
Inclusion Criteria:
Exclusion Criteria:
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To reflect the daily practices, this study includes all patients with diffuse glioma at the beginning of the study.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yaou Liu, Doctor | Contact | +86 1059975396 | yaouliu80@163.com | |
| Junjie Li, Master | Contact | 86-19834515120 | 19834515120@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Yaou Liu, Doctor | Beijing Tiantan Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Beijing Tiantan Hospital | Recruiting | Beijing | Beijing Municipality | 100053 | China |
Clinical and MR data can be shared.
Within 3 years after the end of the trial.
Neurosurgeon and radiologist who submitting an application to Prof. Liu.
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| ID | Term |
|---|---|
| D009461 | Neurologic Manifestations |
| D009369 | Neoplasms |
| D005910 | Glioma |
| D001932 | Brain Neoplasms |
| ID | Term |
|---|---|
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D018302 | Neoplasms, Neuroepithelial |
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| D017599 | Neuroectodermal Tumors |
| D009373 | Neoplasms, Germ Cell and Embryonal |
| D009370 | Neoplasms by Histologic Type |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009380 | Neoplasms, Nerve Tissue |
| D016543 | Central Nervous System Neoplasms |
| D009423 | Nervous System Neoplasms |
| D009371 | Neoplasms by Site |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |