Actively Recruiting
Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer
Led by Fudan University · Updated on 2025-01-20
6000
Participants Needed
1
Research Sites
82 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
This nationwide, multicenter observational study aims to develop and validate a multimodal artificial intelligence (AI) model for detecting occult lymph node metastasis in early-stage non-small cell lung cancer (NSCLC) patients. Despite advances in lymph node staging, 12.9%-39.3% of occult nodal metastasis cases remain undetected preoperatively, affecting treatment decisions. This study will use deep learning to extract imaging features of occult metastasis and combine them with clinical data to build an AI model for risk prediction. This study will provide insights into the feasibility of AI-driven detection of occult metastasis, supporting clinical decision-making and potentially revealing underlying biological mechanisms of lymph node metastasis in NSCLC.
CONDITIONS
Official Title
Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Pathologically confirmed non-small cell lung cancer
- Clinical stage I (AJCC, 8th edition, 2017)
- Age 18 years or older
- Karnofsky Performance Status (KPS) score of 70 or higher
- Patients who have undergone primary NSCLC radical surgery or stereotactic body radiotherapy (SBRT)
- Complete systemic lesion imaging assessment before primary NSCLC radical surgery or SBRT (PET/CT and/or invasive mediastinal staging required for tumors 2 3 cm or centrally located tumors)
- Patients willing to cooperate with follow-up after primary NSCLC treatment
- Informed consent provided by the patient
You will not qualify if you...
- Poor quality of computed tomography imaging
- Baseline imaging shows pure ground-glass nodules (GGO)
- Uncontrolled epilepsy, central nervous system disease, or history of mental disorders that may interfere with consent or compliance
- Loss to follow-up
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Fudan university Shanghai Cancer Center
Shanghai, China
Actively Recruiting
Research Team
Z
Zhengfei Zhu, PhD
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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