Condition: NSCLC (Non-small Cell Lung Cancer) · Artificial Intelligence (AI) · Lymphnode Metastasis · Sponsor: Fudan University
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.
This description comes directly from the study's public registry record.
Zhengfei Zhu, PhD · +86-18017312901 · fuscczzf@163.com
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| Fudan university Shanghai Cancer Center | Shanghai, China | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06684418