Spots Global Cancer Trial Database for Histopathology Images Based Survival Prediction of Glioma Patients Using Artificial Intelligence

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Trial Identification

Brief Title: Histopathology Images Based Survival Prediction of Glioma Patients Using Artificial Intelligence

Official Title: Histopathology Images Based Survival Prediction of Patients With Primary Glioma Using Deep Learning or Machine Learning

Study ID: NCT04215224

Conditions

Glioma

Interventions

Histopathology images based survival prediction for glioma patients

Study Description

Brief Summary: This registry aims to collect clinical, molecular and histopathology imaging including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, 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 hstopathology imaging based algorithms that able to predict patients' survivals in the frame of molecular pathology or subgroups of gliomas.

Detailed Description: Non-invasive and precise prediction for survivals of glioma patients 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 patients' prognosis in the frame of molecular pathology of gliomas. The creation of a registry for primary glioma with detailed survival data, molecular pathology, histopathology image data and with sufficient sample size for deep learning (\>1000) provides opportunities for personalized prediction of survival of glioma patients with non-invasiveness and precision.