Clinical, patHOlogical and Imaging Project of nEuro-oncology (HOPE)

Yaou Liu70,000 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

70,000

Conditions

Brain (Nervous System) Cancers

Eligibility

Sex: ALLMin age: 18 YearsMax age: 90 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * (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 Exclusion Criteria: * (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.

Outcomes

Primary Outcomes

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

Time frame: 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.

Time frame: 2022.06.01-2030.12.31

Secondary Outcomes

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.

Time frame: 2022.01-2024.12