Clinical trial NCT05859659: Clinical, patHOlogical and Imaging Project of nEuro-oncology (HOPE)
Official title: Clinical, patHOlogical and Imaging Project of nEuro-oncology (HOPE)
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Glioma
Lead sponsor: Beijing Tiantan Hospital
Sponsor class: OTHER
First posted: 2023-05-16
Enrollment: 3500
Sex: ALL
Minimum age (years): 18
Maximum age (years): 90
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: To reflect the daily practices, this study includes all patients with diffuse glioma at the beginning of the study.

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.

Eligibility criteria: 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.

Primary outcomes:
measure: Establish standardized clinical-MRI -molecular markers database for glioma
timeFrame: 2022.01-2024.12
measure: Establish an accurate MRI-based deep-learning model for the prediction of glioma
timeFrame: 2022.01-2024.12
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Beijing Tiantan Hospital
state: Beijing
Study officials:
affiliation: Beijing Tiantan Hospital
name: Yaou Liu, Doctor
role: PRINCIPAL_INVESTIGATOR
References: