Lymphatic Metastasis

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.

Thyroid cancer is one of the most common malignant tumors in women, ranking seventh in the United States and fourth in China. Papillary thyroid carcinoma is the most common pathological type (about 85% to 90% of thyroid cancers), and lateral cervical lymph node metastasis can reach 0.6-37.5% at diagnosis. For papillary thyroid cancer with lateral cervical lymph node metastasis, the 2015 ATA Guidelines in the United States recommend surgical resection and neck lymph node dissection as the primary treatment. Traditional cervical lymph node dissection often leaves obvious scars in the neck, which seriously affects the postoperative quality of life of patients. The previous studies have shown that endoscopy-assisted surgery with external cervical approach can achieve oncologic effects similar to traditional open surgery in the treatment of N1b papillary thyroid cancer, and can obtain better aesthetic results. However, endoscopic surgery still has some shortcomings, such as poor exposure of some surgical areas and difficult operation. Since November 2016, the investigators tried to apply modified transaxillary robotic-assisted surgery technology to the treatment of thyroid papillary carcinoma in China. The preliminary study included 30 patients, and the results showed that robot-assisted surgery via combined transaxillary-retroaural approach in the treatment of N1b papillary thyroid carcinoma achieved a good oncologic effect (5-year overall survival rate was 100.0%). As the surgical techniques improved, now the investigators can complete robotic-assisted lateral neck lymph node dissection via single-incision transaxillary approach. However, there is still a lack of high-quality evidence on the long-term oncologic outcome and quality of life of this procedure. In this study, a prospective, multi-center, randomized controlled study was conducted to compare the safety, long-term oncologic outcomes and postoperative quality of life of the robot-assisted surgery via single-incision transaxillary approach and open surgery in the treatment of N1b papillary thyroid cancer, which may provide an alternative for the patients with N1b papillary thyroid cancer.

The goal of this diagnostic test is to develop an artificial intelligence (AI)-based pan-cancer universal diagnostic model for detecting pathological lymph node metastasis (LNM), and prospectively evaluate its apllication value in the real-world clinical practice.
Investigators will compare the diagnostic performance (sensitivity, specificity, etc.) of the AI model and routine pathological report issued by pathologists, to see if the AI model can improve the clinical workflow of pathological evaluation of cancer LNM in in the real world.