Histopathology Images Based Prediction of Molecular Pathology in Glioma Using Artificial Intelligence

Glioma Clinical Trial

Official title:

Histopathology Images Based Prediction of Molecular Pathology in Glioma Using Deep Learning or Machine Learning

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04217044
• Other study ID #: GliomaAI-3
• Status: Recruiting
• Start date: January 1, 2017
• Est. completion date: June 1, 2027

Study information

• Verified date: February 2021
• Source: The First Affiliated Hospital of Zhengzhou University
• Contact: Zhenyu Zhang, Dr.
• Phone: +86 17839973727
• Email: fcczhangzy1[@]zzu.edu.cn
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial 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.

Description:

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 3000
• Est. completion date: June 1, 2027
• Est. primary completion date: January 1, 2027
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 1 Year to 95 Years

Eligibility

Inclusion Criteria:

• 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

Exclusion Criteria:

• No gliomas
• No sufficient amount of tumor tissues for detection of molecular pathology
• Patients who are pregnant or breast feeding
• Patients who are suffered from severe systematic malfunctions

Related Conditions & MeSH terms

• Glioma

Intervention

Diagnostic Test:
• Histopathology images based prediction of molecular pathology
Histopathology images based prediction of 1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations or molecular subgroups by leveraging AI

Locations

Country	Name	City	State
China	Department of Neurosurgery, First Affiliated Hospital of Zhengzhou University	Zhengzhou	Henan

Sponsors (2)

Lead Sponsor	Collaborator
The First Affiliated Hospital of Zhengzhou University	Sun Yat-sen University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	AUC of prediction performance	AUC=sensitivity+specificity-1	up to 10 years