Artificial intelligence-based pathological application to predict regional lymph node metastasis in Papillary Thyroid Cancer

• Published in: Current problems in cancer 2024-12, Vol.53, p.101150, Article 101150
• Main Authors: Sun, Dawei, Li, Huichao, Wang, Yaozong, Li, Dayuan, Xu, Di, Zhang, Zhoujing
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial Intelligence; Artificial intelligence (AI); Female; Humans; Lymph Nodes - pathology; Lymphatic Metastasis - pathology; Male; Middle Aged; Neural network; Neural Networks, Computer; Papillary thyroid cancer; Prognosis; Secondary malignant tumors of lymph nodes; Thyroid Cancer, Papillary - pathology; Thyroid Neoplasms - pathology
• ISSN: 0147-0272; 1535-6345; 1535-6345
• DOI: 10.1016/j.currproblcancer.2024.101150

In this study, a model for predicting lymph node metastasis in papillary thyroid cancer was trained using pathology images from the TCGA(The Cancer Genome Atlas) public dataset of papillary thyroid cancer, and a front-end inference model was trained using our center's dataset based on the concept of probabilistic propagation of nodes in graph neural networks. Effectively predicting whether a tumor will spread to regional lymph nodes using a single pathological image is the capacity of the model described above. This study demonstrates that regional lymph nodes in papillary thyroid cancer are a common and predictable occurrence, providing valuable ideas for future research. Now we publish the above research process and code for further study by other researchers, and we also make the above inference algorithm public at the URL: http:// thyroid-diseases-research.com/, with the hope that other researchers will validate it and provide us with ideas or datasets for further study. [Display omitted]