Deep Learning-Based Intraoperative Dual-tracer Video Analysis of Sentinel Lymph Node Mapping for Metastasis Prediction in cN0 Papillary Thyroid Carcinoma

Plain-language summary

The goal of this observational study is to learn if a computer program (deep learning) can accurately predict lymph node spread in adults with papillary thyroid cancer who have no signs of lymph node involvement before surgery (called cN0). The main questions it aims to answer are: * Can video analysis of lymph node mapping during surgery predict if cancer has spread to lymph nodes beyond the first-draining (sentinel) lymph node? * Can this prediction help surgeons decide how much tissue to remove during surgery? During surgery, participants will receive an injection of two special dyes (carbon nanoparticles and indocyanine green) near the thyroid tumor. These dyes travel through the lymphatic system and help surgeons see the lymph nodes. A special camera records a video of how the dyes move and light up the lymph nodes. Researchers will use computer programs to analyze these videos along with other medical information (such as ultrasound results and tumor characteristics) to predict whether cancer has spread to additional lymph nodes. The predictions will be compared against the actual results from tissue samples examined after surgery. Participants will receive standard thyroid cancer surgery. The study does not change the surgical treatment. The video recording adds no extra risk to participants.

Who can participate

What they're measuring

Trial details