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3D Deep Learning model predicts molecular typing and prognosis of diffuse glioma

3D Deep Learning model predicts molecular typing and prognosis of diffuse glioma

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000031208
Enrollment
Unknown
Registered
2020-03-24
Start date
2020-05-01
Completion date
Unknown
Last updated
2020-03-30

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

Conditions

Glioma

Interventions

Gold Standard:Pathologic diagnosis
qPCR
clinical outcomes.
Index test:3D-MRI&#32
deep&#32
learning&#32
model

Sponsors

Shenzhen Second People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
16 Years to 70 Years

Inclusion criteria

Inclusion criteria: Surgical resection confirmed diffuse glioma; preoperative MRI (T1WI, T2WI) imaging data; IDH molecular status.

Exclusion criteria

Exclusion criteria: Patients were younger than 16 years; those who underwent chemoradiotherapy before surgery; images with motion or metal artifacts that affected the observer of the lesion; those with incomplete clinical pathological data and IDH molecular status.

Design outcomes

Primary

MeasureTime frame
IDH;prognosis;SEN, SPE, ACC, AUC of ROC;—

Countries

China

Contacts

Public ContactFeng Yuning

Shenzhen Second People's Hospital

fynhyj@qq.com+86 13510645332

Outcome results

None listed

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