Histopathology Images Based Survival Prediction of Glioma Patients Using Artificial Intelligence

Glioma Clinical Trial

Official title:

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

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04215224
• Other study ID #: GliomaAI-4
• 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 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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 3500
• Est. completion date: June 1, 2027
• Est. primary completion date: January 1, 2027
• Accepts healthy volunteers: No
• Gender: All
• Age group: 1 Year to 90 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 malfuctions

Related Conditions & MeSH terms

• Glioma

Intervention

Diagnostic Test:
• Histopathology images based survival prediction for glioma patients
Histopathology images based survival prediction of glioma patients in the frame of molecular pathology 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 survival prediction performance	AUC of survival prediction performance=sensitivity+specificity-1	up to 10 years