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.
Non-invasive and precise prediction for molecular biomarkers such as 1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations is challenging. With the development of artificial intelligence, much more potential lies in the histopathology images of HE slices in primary gliomas could be excavated to aid prediction of molecular pathology of gliomas. The creation of a registry for primary glioma with detailed molecular pathology, histopathology image data and with sufficient sample size for deep learning (\>1000) provide considerable opportunities for personalized prediction of molecular pathology with non-invasiveness and precision.
Study Type
OBSERVATIONAL
Enrollment
3,000
Histopathology images based prediction of 1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations or molecular subgroups by leveraging AI
Department of Neurosurgery, First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China
RECRUITINGAUC of prediction performance
AUC=sensitivity+specificity-1
Time frame: up to 10 years
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