MR Based Survival Prediction of Glioma Patients Using Artificial Intelligence

February 5, 2021 updated by: Zhenyu Zhang, The First Affiliated Hospital of Zhengzhou University

MR Based Survival Prediction of Patients With Primary Glioma Ssing Deep Learning or Machine Learning

This registry aims to collect clinical, molecular and radiologic data including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, MGMT methylation, IDH and TERTp mutations, etc) and conventional/advanced/new MR sequences (T1, T1c, T2, FLAIR, ADC, DTI, PWI, etc) of patients with primary gliomas. By leveraging artificial intelligence, this registry will seek to construct and refine algorithms that able to predict patients' survivals in the frame of molecular pathology or subgroups of gliomas.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

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 preoperative conventional/advanced MR imaging (T1 weighted imaging, T2 weighted imaging, FLAIR, contrast-enhanced T1 weighted imaging, diffusion-weighted imaging, and perfusion imaging) 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, radiological 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.

Study Type

Observational

Enrollment (Anticipated)

2500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Henan
      • Zhengzhou, Henan, China, 450052
        • Recruiting
        • Department of Neurosurgery, First Affiliated Hospital of Zhengzhou University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

1 year to 90 years (Child, Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Paitents with newly diagnosed glioma who receive tumor resection with life expectancy of greater than 3 months

Description

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 have any type of bioimplant activated by mechanical, electronic, or magnetic devices
  • Patients who are pregnant or breast feeding
  • Patients who are suffered from severe systematic malfuctions

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
AUC of survival prediction performance
Time Frame: up to 10 years
AUC of survival prediction performance=sensitivity+specificity-1
up to 10 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

The First Affiliated Hospital of Zhengzhou University

Collaborators

Sun Yat-sen University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2017

Primary Completion (Anticipated)

January 1, 2027

Study Completion (Anticipated)

June 1, 2027

Study Registration Dates

First Submitted

December 30, 2019

First Submitted That Met QC Criteria

December 30, 2019

First Posted (Actual)

January 2, 2020

Study Record Updates

Last Update Posted (Actual)

February 8, 2021

Last Update Submitted That Met QC Criteria

February 5, 2021

Last Verified

February 1, 2021

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • GliomaAI-2

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

Undecided

IPD Plan Description

Undecided

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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