Ignite Creation Date:
2025-12-24 @ 2:58 PM
Ignite Modification Date:
2026-01-29 @ 1:13 PM
Study NCT ID:
NCT05859659
Status:
UNKNOWN
Last Update Posted:
2023-05-17
First Post:
2023-05-05
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Clinical, patHOlogical and Imaging Project of nEuro-oncology (HOPE)
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D005910', 'term': 'Glioma'}], 'ancestors': [{'id': 'D018302', 'term': 'Neoplasms, Neuroepithelial'}, {'id': 'D017599', 'term': 'Neuroectodermal Tumors'}, {'id': 'D009373', 'term': 'Neoplasms, Germ Cell and Embryonal'}, {'id': 'D009370', 'term': 'Neoplasms by Histologic Type'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D009375', 'term': 'Neoplasms, Glandular and Epithelial'}, {'id': 'D009380', 'term': 'Neoplasms, Nerve Tissue'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 3500}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2022-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-05', 'completionDateStruct': {'date': '2024-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-05-16', 'studyFirstSubmitDate': '2023-05-05', 'studyFirstSubmitQcDate': '2023-05-05', 'lastUpdatePostDateStruct': {'date': '2023-05-17', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-05-16', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Establish standardized clinical-MRI -molecular markers database for glioma', 'timeFrame': '2022.01-2024.12', 'description': '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'}, {'measure': 'Establish an accurate MRI-based deep-learning model for the prediction of glioma', 'timeFrame': '2022.01-2024.12', 'description': '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'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Glioma']}, 'descriptionModule': {'briefSummary': '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.', 'detailedDescription': '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.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '90 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'To reflect the daily practices, this study includes all patients with diffuse glioma at the beginning of the study.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* (1) a clear diagnosis of glioma based on pathological results;\n* (2) The MRI sequence is complete and there are no obvious artifacts in the image;\n* (3) The patient signs an informed consent form\n\nExclusion Criteria:\n\n* (1) Suffering from other neurological diseases;\n* (2) Prior to enrollment, surgery or biopsy, or a history of radiation therapy or chemotherapy;\n* (3) Unable to complete clinical scoring and related laboratory tests, unable to complete follow-up;\n* (4) Unable to tolerate MRI examination; Poor image quality, such as motion artifacts.'}, 'identificationModule': {'nctId': 'NCT05859659', 'briefTitle': 'Clinical, patHOlogical and Imaging Project of nEuro-oncology (HOPE)', 'organization': {'class': 'OTHER', 'fullName': 'Beijing Tiantan Hospital'}, 'officialTitle': 'Clinical, patHOlogical and Imaging Project of nEuro-oncology (HOPE)', 'orgStudyIdInfo': {'id': 'KY2022-078-04'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Molecular pathology of glioma positive', 'interventionNames': ['Diagnostic Test: This study does not intervene in this process.']}, {'label': 'Molecular pathology of glioma negative', 'interventionNames': ['Diagnostic Test: This study does not intervene in this process.']}], 'interventions': [{'name': 'This study does not intervene in this process.', 'type': 'DIAGNOSTIC_TEST', 'description': 'This study does not intervene in this process.', 'armGroupLabels': ['Molecular pathology of glioma negative', 'Molecular pathology of glioma positive']}]}, 'contactsLocationsModule': {'locations': [{'zip': '100053', 'city': 'Beijing', 'state': 'Beijing Municipality', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Yaou Liu, PhD', 'role': 'CONTACT', 'email': 'yaouliu80@163.com'}], 'facility': 'Beijing Tiantan Hospital', 'geoPoint': {'lat': 39.9075, 'lon': 116.39723}}], 'centralContacts': [{'name': 'Yaou Liu, Doctor', 'role': 'CONTACT', 'email': 'yaouliu80@163.com', 'phone': '+86 1059975396'}, {'name': 'Junjie Li, Master', 'role': 'CONTACT', 'email': '19834515120@163.com', 'phone': '86-19834515120'}], 'overallOfficials': [{'name': 'Yaou Liu, Doctor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Beijing Tiantan Hospital'}]}, 'ipdSharingStatementModule': {'infoTypes': ['STUDY_PROTOCOL', 'SAP', 'ICF', 'CSR', 'ANALYTIC_CODE'], 'timeFrame': 'Within 3 years after the end of the trial.', 'ipdSharing': 'YES', 'description': 'Clinical and MR data can be shared.', 'accessCriteria': 'Neurosurgeon and radiologist who submitting an application to Prof. Liu.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Beijing Tiantan Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Yaou Liu', 'investigatorAffiliation': 'Beijing Tiantan Hospital'}}}}