Sun Dawei, Li Huichao, Wang Yaozong, Li Dayuan, Xu Di, Zhang Zhoujing
The Affiliated Hospital of Qingdao University, PR China.
Ningbo Huamei Hospital University of Chinese Academy of Sciences(Ningbo No.2 Hospital), PR China.
Curr Probl Cancer. 2024 Dec;53:101150. doi: 10.1016/j.currproblcancer.2024.101150. Epub 2024 Sep 28.
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.
在本研究中，使用来自TCGA（癌症基因组图谱）甲状腺乳头状癌公共数据集的病理图像训练了一个预测甲状腺乳头状癌淋巴结转移的模型，并基于图神经网络中节点概率传播的概念，使用我们中心的数据集训练了一个前端推理模型。使用单个病理图像有效预测肿瘤是否会扩散到区域淋巴结是上述模型的能力。本研究表明，甲状腺乳头状癌的区域淋巴结转移是一种常见且可预测的现象，为未来的研究提供了有价值的思路。现在我们公布上述研究过程和代码以供其他研究人员进一步研究，并且我们还在网址http://thyroid-diseases-research.com/公开了上述推理算法，希望其他研究人员能对其进行验证，并为我们提供进一步研究的思路或数据集。
