A Hierarchical Multi-modal AI Framework for Pathological and Genetic Subtyping of Lung Cancer Based on PET/CT Imaging
Recruiting · NCT07463300 · Observational (researchers observe without assigning treatment) · Lead sponsor: Second Affiliated Hospital, Zhejiang University, School of Medicine
View the official record on ClinicalTrials.gov →Interventions studied
PET imaging analysis, data mining, and AI model developing
What this trial is about
PET/CT imaging and clinical information (age, gender, smoking history, family history of cancer, history of present illness, and several tumor biomarkers, etc.) were used to establish a hierarchical multi-modal AI framework for pathological and genetic subtyping of lung cancer
Who can take part
Age range
18 Years and older
Sex
All (male and female)
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not specified
Study type
Observational (researchers observe without assigning treatment)
Inclusion criteria
- Newly diagnosed NSCLC confirmed pathologically
- Age ≥18 y
- Underwent pre-treatment 18F-FDG PET/CT scan
- No prior anti-tumor treatments
- No history of other malignancies
Exclusion criteria
- ▪ Pure ground-glass nodules with no FDG uptake
Where it is running
9 locations listed.
- Guangdong Second Provincial General Hospital - Guangzhou, Guangdong, China
- Wuhan Tongji Hospital - Wuhan, Hubei, China
- Zhongnan Hospital - Wuhan, Hubei, China
- Northern Jiangsu People's Hospital - Yangzhou, Jiangsu, China
- First Hospital of China Medical University - Shenyang, Liaoning, China
- West China Hospital - Chengdu, Sichuan, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University - Hangzhou, Zhejiang, China
- Department of Nuclear Medicine and PET/CT Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University - Hangzhou, Zhejiang, China
- Zhejiang Cancer Hospital - Hangzhou, Zhejiang, China