Histopathology Images Based Survival Prediction of Glioma Patients Using Artificial Intelligence
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Histopathology images based survival prediction for glioma patients.
- Who it may be relevant to
- Registry conditions: Glioma. Basic parameters: 1 year — 90 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Histopathology Images Based Survival Prediction of Patients With Primary Glioma Using Deep Learning or Machine Learning
Overview
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.
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 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.
Interventions
- 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
Primary outcome measures
- AUC of survival prediction performance [Time frame: up to 10 years]
Eligibility 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 malfuctions
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Department of Neurosurgery, First Affiliated Hospital of Zhengzhou University — Zhengzhou
Identifiers
NCT: NCT04215224 · GliomaAI-4