A Hierarchical Multi-modal AI Framework for Pathological and Genetic Subtyping of Lung Cancer Based on PET/CT Imaging

Recruiting now

Conditions studied: Lung Cancer

In brief

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

Key facts

Study ID

NCT07463300

Run by

Second Affiliated Hospital, Zhejiang University, School of Medicine

People needed

5500

Starts

2024-08-01

Expected to finish

2027-08-01

Last updated by the study team

2026-03-11

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• 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

You may not qualify if…

• ▪ Pure ground-glass nodules with no FDG uptake

Where it is running

• Guangdong Second Provincial General Hospital — Guangzhou, Guangdong, China (enrolling)
• Wuhan Tongji Hospital — Wuhan, Hubei, China (enrolling)
• Zhongnan Hospital — Wuhan, Hubei, China (enrolling)
• Northern Jiangsu People's Hospital — Yangzhou, Jiangsu, China (enrolling)
• First Hospital of China Medical University — Shenyang, Liaoning, China (enrolling)
• West China Hospital — Chengdu, Sichuan, China (enrolling)
• The First Affiliated Hospital of Zhejiang Chinese Medical University — Hangzhou, Zhejiang, China (enrolling)
• Department of Nuclear Medicine and PET/CT Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University — Hangzhou, Zhejiang, China (enrolling)
• Zhejiang Cancer Hospital — Hangzhou, Zhejiang, China (enrolling)

Full record on ClinicalTrials.gov

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