Last reviewed · How we verify

NCT06684418

Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer

Recruiting now Last updated 20 January 2025
What this trial tests

trial testing chest enhanced CT in NSCLC (Non-small Cell Lung Cancer) in 6,000 participants. Currently enrolling.

Timeline
1 December 2024
Primary endpoint
1 December 2025
30 June 2026

Quick facts

Lead sponsorFudan University
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment6,000
Start date1 December 2024
Primary completion1 December 2025
Estimated completion30 June 2026
Sites1 location across China

Drugs / interventions tested

Conditions studied

Sponsor

Fudan University

Who can join

18 and older, any sex, with NSCLC (Non-small Cell Lung Cancer) or Artificial Intelligence (AI). Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

Verify or expand the search:

Other recruiting trials for NSCLC (Non-small Cell Lung Cancer)

Currently open trials in the same condition.

Other Fudan University trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06684418.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing