Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid Microcarcinoma
Objective: To determine the value of CT in predicting CLNM in PTMC. Methods: 157 patients with PTMC confirmed by pathology in our hospital were enrolled, and the CT and clinicopathological data of the patients were retrospectively analyzed. ROC curve was used to determine the optimal cutoff value of...
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| Format: | Article |
| Language: | English |
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Editorial Office of Computerized Tomography Theory and Application
2023-01-01
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| Series: | CT Lilun yu yingyong yanjiu |
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| Online Access: | https://www.cttacn.org.cn/cn/article/doi/10.15953/j.1004-4140-2023.32.01.10 |
| _version_ | 1827897592885805056 |
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| author | Jiangyu TIAN Zhiwei TAN |
| author_facet | Jiangyu TIAN Zhiwei TAN |
| author_sort | Jiangyu TIAN |
| collection | DOAJ |
| description | Objective: To determine the value of CT in predicting CLNM in PTMC. Methods: 157 patients with PTMC confirmed by pathology in our hospital were enrolled, and the CT and clinicopathological data of the patients were retrospectively analyzed. ROC curve was used to determine the optimal cutoff value of PTMC greatest diameter for CLNM. The binary logistic regression model of PTMC CLNM was established based on CT and clinical pathological data, and the diagnostic value of the model was evaluated by ROC curve. Results: According to the ROC curve, the optimal cutoff value for predicting PTMC CLNM was 6 mm. Univariate analysis: Cookie bite sign , microcalcification, multifocality, PTMC greastest diameter ≥6 mm, male, Age<45 were risk factors for PTMC CLNM. Binary Logistic regression analysis: Cookie bite sign with protruding (OR=5.159, 95% CI=1.137 ~ 23.400), multifocality (OR=2.734, 95% CI=1.215 ~ 6.154), PTMC greastest diameter ≥6 mm (OR=3.259, 95% CI=1.326 ~ 8.008), male (OR=3.776, 95% CI=1.339 ~ 10.653), age <45 (OR=3.222, 95% CI=1.419 ~ 7.777), were independent risk factors for PTMC CLNM. According to the ROC curve, when the Youden index=0.502, the sensitivity and specificity in predicting CLNM were 82.5% and 68.0%, respectively. Conclusion: The binary logistic regression model is helpful in predicting PTMC CLNM. Cookie bite sign with protruding, PTMC greastest diameter≥6 mm, male, and age<45 were independent risk factors for PTMC CLNM. For this type of patients, we suggest that surgeons should consider central lymph node dissection. |
| first_indexed | 2024-03-12T22:52:20Z |
| format | Article |
| id | doaj.art-b6f7ee70b7944d6b8e92b0ad7f027358 |
| institution | Directory Open Access Journal |
| issn | 1004-4140 |
| language | English |
| last_indexed | 2024-03-12T22:52:20Z |
| publishDate | 2023-01-01 |
| publisher | Editorial Office of Computerized Tomography Theory and Application |
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| series | CT Lilun yu yingyong yanjiu |
| spelling | doaj.art-b6f7ee70b7944d6b8e92b0ad7f0273582023-07-20T08:51:18ZengEditorial Office of Computerized Tomography Theory and ApplicationCT Lilun yu yingyong yanjiu1004-41402023-01-01321909610.15953/j.1004-4140-2023.32.01.1020210904-175Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid MicrocarcinomaJiangyu TIAN0Zhiwei TAN1Department of Radiology, the Third People's Hospital of Chengdu, Chengdu 610000, ChinaDepartment of Pathology, China National Nuclear Corporation 416 Hospital, Chengdu 610000, ChinaObjective: To determine the value of CT in predicting CLNM in PTMC. Methods: 157 patients with PTMC confirmed by pathology in our hospital were enrolled, and the CT and clinicopathological data of the patients were retrospectively analyzed. ROC curve was used to determine the optimal cutoff value of PTMC greatest diameter for CLNM. The binary logistic regression model of PTMC CLNM was established based on CT and clinical pathological data, and the diagnostic value of the model was evaluated by ROC curve. Results: According to the ROC curve, the optimal cutoff value for predicting PTMC CLNM was 6 mm. Univariate analysis: Cookie bite sign , microcalcification, multifocality, PTMC greastest diameter ≥6 mm, male, Age<45 were risk factors for PTMC CLNM. Binary Logistic regression analysis: Cookie bite sign with protruding (OR=5.159, 95% CI=1.137 ~ 23.400), multifocality (OR=2.734, 95% CI=1.215 ~ 6.154), PTMC greastest diameter ≥6 mm (OR=3.259, 95% CI=1.326 ~ 8.008), male (OR=3.776, 95% CI=1.339 ~ 10.653), age <45 (OR=3.222, 95% CI=1.419 ~ 7.777), were independent risk factors for PTMC CLNM. According to the ROC curve, when the Youden index=0.502, the sensitivity and specificity in predicting CLNM were 82.5% and 68.0%, respectively. Conclusion: The binary logistic regression model is helpful in predicting PTMC CLNM. Cookie bite sign with protruding, PTMC greastest diameter≥6 mm, male, and age<45 were independent risk factors for PTMC CLNM. For this type of patients, we suggest that surgeons should consider central lymph node dissection.https://www.cttacn.org.cn/cn/article/doi/10.15953/j.1004-4140-2023.32.01.10computed tomographpapillary thyroid microcarcinomalogistic regression analysis |
| spellingShingle | Jiangyu TIAN Zhiwei TAN Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid Microcarcinoma CT Lilun yu yingyong yanjiu computed tomograph papillary thyroid microcarcinoma logistic regression analysis |
| title | Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid Microcarcinoma |
| title_full | Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid Microcarcinoma |
| title_fullStr | Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid Microcarcinoma |
| title_full_unstemmed | Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid Microcarcinoma |
| title_short | Evaluation of CT in Predicting Central Lymph Node Metastasis of Papillary Thyroid Microcarcinoma |
| title_sort | evaluation of ct in predicting central lymph node metastasis of papillary thyroid microcarcinoma |
| topic | computed tomograph papillary thyroid microcarcinoma logistic regression analysis |
| url | https://www.cttacn.org.cn/cn/article/doi/10.15953/j.1004-4140-2023.32.01.10 |
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