医学
甲状腺癌
超声波
放射科
养生
淋巴结
淋巴结转移
临床实习
转移
甲状腺
病理
内科学
癌症
家庭医学
作者
Yingying Li,Wen-Xuan Sun,Xian-Dong Liao,Mingbo Zhang,Fang Xie,Donghao Chen,Yan Zhang,Yukun Luo
出处
期刊:PubMed
[National Institutes of Health]
日期:2021-12-30
卷期号:43 (6): 911-916
被引量:2
标识
DOI:10.3881/j.issn.1000-503x.13823
摘要
Objective To establish an artificial intelligence model based on B-mode thyroid ultrasound images to predict central compartment lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC). Methods We retrieved the clinical manifestations and ultrasound images of the tumors in 309 patients with surgical histologically confirmed PTC and treated in the First Medical Center of PLA General Hospital from January to December in 2018.The datasets were split into the training set and the test set.We established a deep learning-based computer-aided model for the diagnosis of CLNM in patients with PTC and then evaluated the diagnosis performance of this model with the test set. Result The accuracy,sensitivity,specificity,and area under receiver operating characteristic curve of our model for predicting CLNM were 80%,76%,83%,and 0.794,respectively. Conclusion Deep learning-based radiomics can be applied in predicting CLNM in patients with PTC and provide a basis for therapeutic regimen selection in clinical practice.
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