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Using the gradient boosting algorithm to construct an image-based radiomics model based on enhanced MRI to non-invasively predict high-grade gliomas and investigate the value of EGF in clinical prognosis

Using the gradient boosting algorithm to construct an image-based radiomics model based on enhanced MRI to non-invasively predict high-grade gliomas and investigate the value of EGF in clinical prognosis

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500112723
Enrollment
Unknown
Registered
2025-11-19
Start date
2025-11-20
Completion date
Unknown
Last updated
2025-11-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

glioma

Interventions

WHO grade III and IV gliomas group:None
Intracranial benign disease tissue group:non-interfering

Sponsors

Dalian Medical University First Affiliated Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Select gliomas of WHO grade III and IV; 2. With complete pathological and imaging data

Exclusion criteria

Exclusion criteria: 1. Eliminate those with missing survival data and survival time shorter than one month; 2. Eliminate missing clinical data; 3. Eliminate those with poor image quality

Design outcomes

Primary

MeasureTime frame
The correlation between EGFR expression level and the radiomics model;—

Secondary

MeasureTime frame
Overall survival time;progression-free survival time;—

Countries

China

Contacts

Public ContactWang Xiaojie

Dalian Medical University First Affiliated Hospital

wxj860408@163.com+86 180 9887 6712

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026