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

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.

Study Overview

• Status: Unknown
• Conditions: Glioma
• Intervention / Treatment: Diagnostic test: MR and Histopathology images based prediction of molecular pathology and patient survival

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.

• Study Type: Observational
• Enrollment (Anticipated): 500

Contacts and Locations

Study Locations

• China
  • Henan
    • Zhengzhou, Henan, China, 450052
      • Recruiting
      • Department of Neurosurgery, First Affiliated Hospital of Zhengzhou University
      • Contact: Zhenyu Zhang, Dr.; Phone Number: +86 17839973727; Email: fcczhangzy1@zzu.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 1 year to 95 years (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Patients with newly diagnosed glioma that receive tumor resection with preoperative MR images and postoperative histopathology images

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
• Must have sufficient frozen tissues and peripheral blood samples for sequencing
• Must have high-quality MR images and histopathology images
• 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

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AUC of Prediction performance	AUC of Prediction performance=sensitivity+specificity-1	up to 2 years

Collaborators and Investigators

• Sponsor: The First Affiliated Hospital of Zhengzhou University
• Collaborators: Sun Yat-sen University

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2018
• Primary Completion (Anticipated): January 1, 2022
• Study Completion (Anticipated): March 1, 2022

Study Registration Dates

• First Submitted: January 4, 2020
• First Submitted That Met QC Criteria: January 4, 2020
• First Posted (Actual): January 7, 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: Artificial intelligence; sequencing; mechanism; MR images; histopathology images
• Additional Relevant MeSH Terms: Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Neoplasms, Neuroepithelial; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms, Nerve Tissue; Glioma
• Other Study ID Numbers: GliomaAI-6

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