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

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.

Sex

All

Minimum age

18 Years

Inclusion Criteria:

1. Age 18 years or older at the time of enrollment
2. Histologically confirmed papillary thyroid carcinoma (PTC) by preoperative fine-needle aspiration biopsy
3. Clinically node-negative (cN0) status confirmed by preoperative imaging (ultrasound and/or cross-sectional imaging showing no evidence of lymph node metastasis)
4. Scheduled to undergo thyroid surgery with simultaneous central lymph node dissection
5. Willing and able to provide written informed consent
6. Complete preoperative clinical data available, including:

   * Demographic information (age, sex, body mass index)
   * Thyroid ultrasound report with detailed tumor characteristics
   * Fine-needle aspiration biopsy pathology report
   * Genetic testing results (when available)
7. Able to undergo intraoperative dual-tracer sentinel lymph node mapping with near-infrared fluorescence video recording

Exclusion Criteria:

1. History of previous neck surgery (including thyroid surgery, parathyroid surgery, or other cervical operations)
2. History of external beam radiotherapy to the head and neck region
3. Diagnosis of thyroid malignancy other than papillary thyroid carcinoma (e.g., follicular thyroid carcinoma, medullary thyroid carcinoma, anaplastic thyroid carcinoma, or thyroid lymphoma)
4. Known allergy or hypersensitivity to indocyanine green (ICG), iodine, or carbon nanoparticles
5. Severe hepatic insufficiency (ICG is metabolized by the liver)
6. Pregnancy or breastfeeding
7. Incomplete medical records or missing essential preoperative data
8. Refusal to undergo dual-tracer imaging procedure
9. Inability to obtain satisfactory intraoperative near-infrared fluorescence video recording due to technical issues or poor image quality
10. Participation in another interventional clinical trial that may interfere with the current study
11. Any condition that, in the investigator's opinion, would compromise the participant's safety or the quality of the study data

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