Microscopic regional lymph node status in papillary thyroid carcinoma with and without lymphadenopathy and its relation to outcomes

2007 ◽  
Vol 392 (4) ◽  
pp. 417-422 ◽  
Author(s):  
Nobuyuki Wada ◽  
Nobuyasu Suganuma ◽  
Hirotaka Nakayama ◽  
Katsuhiko Masudo ◽  
Yasushi Rino ◽  
...  
2017 ◽  
Vol 17 (3) ◽  
pp. 122
Author(s):  
Yoon Hyeong Byeon ◽  
Jung Eun Choi ◽  
Jeong Yeong Park ◽  
Jeong Hyun Song ◽  
Kyeong Jun Yeo ◽  
...  

2015 ◽  
Vol 136 (3) ◽  
pp. 319-324 ◽  
Author(s):  
Young Min Park ◽  
Soo-Geun Wang ◽  
Dong Hoon Shin ◽  
In-Ju Kim ◽  
Seok-Man Son ◽  
...  

2019 ◽  
Vol 18 ◽  
pp. 153303381983171 ◽  
Author(s):  
Tongtong Liu ◽  
Shichong Zhou ◽  
Jinhua Yu ◽  
Yi Guo ◽  
Yuanyuan Wang ◽  
...  

Background: Papillary thyroid carcinoma is a type of indolent tumor with a dramatically increasing incidence rate and stably high survival rate. Reducing the overdiagnosis and overtreatment of papillary thyroid carcinoma is clinically emergent and important. A radiomics model is proposed in this article to predict lymph node metastasis, the most important risk factor of papillary thyroid carcinoma, based on noninvasive routine preoperative ultrasound images. Methods: Four hundred fifty ultrasound manually segmented images of patients with papillary thyroid carcinoma with lymph node status obtained from pathology report were enrolled in our retrospective study. A radiomics evaluation of 614 high-throughput features were calculated, including size, shape, margin, boundary, orientation, position, echo pattern, posterior acoustic pattern, and calcification features. Then, combined feature selection strategy was used to select features with the greatest ability to discriminate lymph node status. A support vector machine classifier was employed to build and validate the prediction model. Another independent testing cohort was used to further evaluate the performance of the radiomics model. Results: Among 614 radiomics features, 50 selected features most reflecting echo pattern, posterior acoustic pattern, and calcification showed the superior lymph node status distinguishable performance with area under the receiver operating characteristic curve of 0.753, 0.740, and 0.743 separately when using each type of features predicting the lymph node status. The results of model based on all 50 final features predicting the lymph node status shown an area under the receiver operating characteristic curve of 0.782, and accuracy of 0.712. In the independent testing cohort, the proposed approach showed similar results, with area under the receiver operating characteristic curve of 0.727 and accuracy of 0.710. Conclusion: Papillary thyroid carcinoma with lymph node metastasis usually shows a complex echo pattern, posterior region homogeneity, and macrocalcification or multiple calcification. The radiomics model proposed in this article is a promising method for assessing the risk of papillary thyroid carcinoma metastasis noninvasively.


Head & Neck ◽  
2015 ◽  
Vol 38 (S1) ◽  
pp. E1172-E1176 ◽  
Author(s):  
Young Min Park ◽  
Soo-Geun Wang ◽  
Jin-Choon Lee ◽  
Dong Hoon Shin ◽  
In-Ju Kim ◽  
...  

2020 ◽  
Author(s):  
Vanessa Guerreiro ◽  
Cláudia Costa ◽  
Joana Oliveira ◽  
Ana Paula Santos ◽  
Mónica Farinha ◽  
...  

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