Radiomics-Based Visualization and Quantitative Validation of Isocitrate Dehydrogenase 1 Heterogeneity in Gliomas
Trial Snapshot
- Phase
- Not Applicable
- Status
- Active, not recruiting
- Sponsor
- Mingge LLC
- Enrollment
- 18
- Locations
- 1
- Primary Endpoint
- accuracy
Study Overview
Brief Summary
The goal of this clinical trail is to non-invasively visualise and quantitatively validate an radiomics model of genetic heterogeneity in adult patients with diffuse glioma to help clinicians better guide surgical resection and treatment options. It aims to answer are:
- To overcome the limitations of the existing genetic diagnostic process in terms of equipment and technology requirements, high costs and long timelines, and to enable quantitative studies of isocitrate dehydrogenase 1 (IDH1) mutations, thus allowing refined patient stratification and further exploration of the role of molecular markers in improving patient prognosis.
- To achieve non-invasive diagnosis of gene mutations within tumours by taking advantage of artificial intelligence and medical images, and to test the clinical feasibility of the model through typical target puncture, gene sequencing and quantitative gene expression analysis.
Participants will read an informed consent agreement before surgery and voluntarily decide whether or not to join the experimental group. They will undergo preoperative magnetic resonance imaging, intraoperative brain puncture of typical tumour sites, and postoperative genotype identification. Their imaging data, genotype data, clinical history data, and pathology data will be used for the experimental study.
Detailed Description
BACKGROUND
The WHO 2016 officially introduced molecular markers into the pathological diagnosis of gliomas, marking a step into the era of molecular diagnosis of gliomas. Among them, isocitrate dehydrogenase 1 (IDH1) mutation is considered to be the 'backbone' in the development of gliomas, and affects the treatment plan and prognosis of patients. However, the clinical use of this molecular biomarker is still controversial, which is rooted in the lack of quantitative studies on IDH1 mutations. The spatial heterogeneity of gliomas has been demonstrated in existing studies, i.e., tumor tissues in different parts of the same glioma belong to different genetic subtypes. This implies that IDH1-mutant tumors do not indicate the presence of mutations in all tumor cells, thus further exacerbating the problems in clinical genetic diagnosis.
OBJECTIVE
To quantify gene mutations in tumours, we plan to use radiomics model with artificial intelligence and clinical big data, and verify its accuracy by tissue puncture. In this way, we can overcome the challenges of multisite sampling and second-generation sequencing, such as high equipment and technology requirements, high cost and long time, and thus theoretically realise the visualisation and quantification of genetic heterogeneity within gliomas.
PROCESS
Study Design
- Study Type
- Interventional
- Allocation
- Na
- Intervention Model
- Single Group
- Primary Purpose
- Other
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to 80 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Patients aged 18-70 years, male or female;
- •Patients with complete preoperative magnetic resonance imaging and were initially diagnosed with glioma based on the magnetic resonance imaging results;
- •Patients who were proposed for craniectomy without contraindications to surgery and who had signed an informed consent form by themselves or their proxy;
- •Patients with confirmed diagnosis of glioma by postoperative pathological diagnosis.
Exclusion Criteria
- •Patients to be admitted for a simple puncture biopsy;
- •Patients with a combination of serious medical conditions and those who cannot tolerate surgery;
- •Patients with a bleeding tendency or abnormal coagulation function, or those who have not discontinued long-term use of anticoagulants such as aspirin and clopidogrel;
- •Pregnant and breastfeeding women;
- •Patients participate in other clinical trials during the same period.
Arms & Interventions
Validation of IDH1 mutations from the radiomics model
In this experiment, we validate the accuracy of radiomics model for IDH1 prediction by puncturing typical targets of gliomas, gene sequencing and quantitative gene analysis.
Intervention: Validation of IDH1 mutations from the radiomics model (Diagnostic Test)
Outcomes
Primary Outcomes
accuracy
Time Frame: End of study (24 weeks)
The ratio of correct model predictions to all predictions is calculated by comparing the results with the puncture results.
Secondary Outcomes
No secondary outcomes reported