Using AI to predict molecular pathology in glioma from histopathology images
Official title: Histopathology Images Based Prediction of Molecular Pathology in Glioma Using Deep Learning or Machine Learning
Run by The First Affiliated Hospital of Zhengzhou University · NCT04217044 · Data updated 2026-11-12
This study is trying to see if artificial intelligence can help predict the specific types of gliomas using images of the tumors to improve treatment options for patients.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 1 Year to 95 Years |
| Sex | All |
| Enrollment | 3000 (estimated) |
| Sponsor | The First Affiliated Hospital of Zhengzhou University Academic / other |
| Locations | 1 site (Zhengzhou, Henan) |
| Status | Recruiting |
| Started | January 1, 2017 |
| Main results expected | January 1, 2027 |
| Study ends | June 1, 2027 |
| Registry record updated | February 8, 2021 |
| Trial ID | NCT04217044 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are patients with a confirmed diagnosis of primary glioma who are scheduled for tumor resection and have a life expectancy of more than three months.
✕Probably not a fit
Patients without gliomas, insufficient tumor tissue for molecular detection, or those with severe systemic malfunctions may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational registry collects clinical, molecular, and radiologic data from patients with primary gliomas, including detailed clinical parameters and histopathology images. By utilizing artificial intelligence, the study aims to develop algorithms that can accurately predict molecular pathology and subgroups of gliomas based on these images. The registry will include over 1000 samples to enhance the precision and non-invasive nature of molecular predictions, ultimately aiding in personalized treatment approaches for glioma patients.
Why it matters
Potential benefit: If successful, this approach could lead to more accurate and personalized treatment options for glioma patients based on their molecular pathology.
How similar studies have gone: Other studies utilizing artificial intelligence for histopathology image analysis have shown promising results, indicating potential success for this approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
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
Where it's running
-
Department of Neurosurgery, First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China Recruiting
Study contacts
- Study coordinator: Zhenyu Zhang, Dr.
- Email: fcczhangzy1@zzu.edu.cn
- Phone: +86 17839973727
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
-
YN003 injection in glioma patients
This phase 1 study tests whether YN003 injected IV is safe and tolerable for adults with recurrent or progressive glioma, and to explore how the drug behaves in the body and any early signs of activity.
-
Brain connectome project in adults with brain glioma undergoing surgery
This registry collects MRI data and clinical information from adults with glioma to see how brain networks relate to surgery and recovery.
-
Proton vs. Photon Radiation for Certain Grade 2–3 Gliomas
This study tests whether proton therapy can better preserve thinking and memory than photon therapy for adults with IDH-mutated grade 2–3 gliomas who need radiation.
-
Connectome-guided network planning for brain tumor surgery in eloquent areas
This study tests whether using patient-specific brain network maps from diffusion MRI can help surgeons plan and guide brain tumor removal in eloquent areas.
-
AI-powered analysis of brain MRI to help glioma care
Doctors will use AI to study existing MRI scans and patient data from adults with glioma to see if it can help with non-invasive diagnosis and treatment planning.
-
Safusidenib in IDH1-mutant glioma after vorasidenib progression
This trial tests safusidenib in people with IDH1-mutant glioma who progressed on vorasidenib and did not need immediate chemo or radiation.
How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.