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Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer: A Multicenter, Prospective, Observational Study
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.
Age
18 - No limit years
Sex
ALL
Healthy Volunteers
No
Fudan university Shanghai Cancer Center
Shanghai, China
Start Date
December 1, 2024
Primary Completion Date
December 1, 2025
Completion Date
June 30, 2026
Last Updated
January 20, 2025
6,000
ESTIMATED participants
chest enhanced CT
DIAGNOSTIC_TEST
Lead Sponsor
Fudan University
NCT04585750
NCT07079592
Data Source & Attribution
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