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C-11 Acetate PET/CT based Glioma analysis using Deep Learning algorithms

C-11 Acetate PET/CT based Glioma analysis using Deep Learning algorithms

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0006277
Enrollment
100
Registered
2021-06-21
Start date
2021-05-11
Completion date
Unknown
Last updated
2021-07-12

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

Conditions

None listed

Interventions

None listed

Sponsors

Yonsei University Health System, Severance Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Adult males and females 20 years of age or older 2. Patients with primary brain tumor diagnosed for the first time

Exclusion criteria

Exclusion criteria: 1. Patients who received chemotherapy or radiation therapy as a pre-treatment 2. In the case of those who cannot read the consent form (eg, illiterate, foreigner, etc.)

Design outcomes

Primary

MeasureTime frame
The predictive power of a deep learning network that distinguishes between glioma grade and IDH mutation—

Secondary

MeasureTime frame
Association of Acetate PET/CT with Overall Survival and Progression Free Survival—

Countries

Korea, Republic of

Contacts

Public ContactDongwoo Kim

Yonsei University Health System, Severance Hospital

kdwoo@yuhs.ac+82-2-2228-4855

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 12, 2026