Histopathology Images Based Prediction of Molecular Pathology in Glioma Using Deep Learning or Machine Learning
Status: Recruiting
Location: See location...
Intervention Type: Diagnostic test
Study Type: Observational
SUMMARY
This registry aims to collect clinical, molecular and radiologic data including detailed clinical parameters, molecular pathology (1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations, etc) and images of HE slices in primary gliomas. By leveraging artificial intelligence, this registry will seek to construct and refine histopathology image based algorithms that are able to predict molecular pathology or subgroups of gliomas.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 1
Maximum Age: 95
Healthy Volunteers: t
View:
• Patients must have radiologically and histologically confirmed diagnosis of primary glioma
• Life expectancy of greater than 3 months
• Must receive tumor resection
• Signed informed consent
Locations
Other Locations
China
Department of Neurosurgery, First Affiliated Hospital of Zhengzhou University
RECRUITING
Zhengzhou
Contact Information
Primary
Zhenyu Zhang, Dr.
fcczhangzy1@zzu.edu.cn
+86 17839973727
Time Frame
Start Date: 2017-01-01
Estimated Completion Date: 2027-06-01
Participants
Target number of participants: 3000
Related Therapeutic Areas
Sponsors
Collaborators: Sun Yat-sen University
Leads: The First Affiliated Hospital of Zhengzhou University