NCT04220424

Glioma Patients Registry Based on Radiological, Histopathological and Genetic Analysis

Glioma Patients Registry Based on MR Images, Histopathology Images and Genetic Sequencing Analyzed by Artificial Intelligence

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 500 (estimated)
• Sponsor: The First Affiliated Hospital of Zhengzhou University · Academic / Other
• Sex: All
• Age: 1 Year – 95 Years
• Healthy volunteers: Accepted

Summary

This prospective study aims to collect clinical, radiological, pathological, molecular and genetic data including detailed clinical parameters, MR and histopathology images, molecular pathology and genetic sequencing data. By leveraging artificial intelligence, this registry seeks to construct and refine algorithms that able to predict molecular pathology or clinical outcomes of glioma patients based on MR images and histopathology images, as well as revealing related mechanisms from genetic perspective.

Detailed description

Non-invasive and precise prediction for molecular biomarkers such as 1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations, and patients survival is challenging for gliomas. With the development of artificial intelligence, much more potential lies in the preoperative conventional/advanced MR imaging (T1 weighted imaging, T2 weighted imaging, FLAIR, contrast-enhanced T1 weighted imaging, diffusion-weighted imaging, and perfusion imaging), and in the histopathology images of HE slices of gliomas could be excavated to aid prediction of molecular pathology and patients' survival of gliomas. This study aims to collect clinical, radiological, pathological, molecular and genetic data including detailed clinical parameters, MR and histopathology images, molecular pathology (1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations, etc) and genetic data (Whole exome sequencing, RNA sequencing, proteomics, etc), and seeks to construct and refine algorithms that able to predict molecular pathology or clinical outcomes of glioma patients based on MR images and histopathology images, as well as revealing related mechanisms from genetic perspective.

Conditions

• Glioma

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	MR and Histopathology images based prediction of molecular pathology and patient survival	MR and Histopathology images based prediction of molecular pathology and patient survival in gliomas by leverage artificial intelligence algorithms

Timeline

• Start date: 2018-11-01
• Primary completion: 2022-01-01
• Completion: 2022-03-01
• First posted: 2020-01-07
• Last updated: 2021-02-08

Locations

1 site across 1 country: China