scholarly journals Correlation Analysis of Nodular Sonographic Parameters with Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma

2021 ◽  
Author(s):  
Liuhua Zhou ◽  
Qiaodan Zhu ◽  
Jincao Yao ◽  
Chen Yang ◽  
Dong Xu
Keyword(s):  
Aspect Ratio ◽  
Thyroid Carcinoma ◽  
Cervical Lymph Node ◽  
Tumor Diameter ◽  
Papillary Thyroid ◽  
Cross Sectional ◽  
Logistic Analysis ◽  
Maximum Tumor Diameter ◽  
Node Metastases ◽  
Multivariate Logistic Analysis

Abstract Background Papillary thyroid carcinoma (PTC) is the most common thyroid carcinoma, and is prone to cervical lymph node metastases (CLNM). We aim to analyze the correlation between clinical information, ultrasonic parameters of PTC and CLNM. Methods 1335 patients who had pathologically confirmed unifocal PTC were enrolled. Univariate and multivariate logistic analysis were performed to predict CLNM in PTC patients. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance. Results Univariate analysis showed that gender, age, maximum tumor diameter and volume, cross-sectional and longitudinal aspect ratio were related to CLNM (P<0.05). Multivariate logistic analysis showed that gender, age, maximum tumor diameter and volume were independent correlative factors, cross-sectional aspect ratio had significant difference for PTC2 to predict CLNM. The area under the curve (AUC) of the maximum tumor diameter and volume was 0.738 and 0.733, respectively. Maximum tumor diameter and volume, and cross-sectional and longitudinal aspect ratio were statistically significant following analysis of variance (P < 0.05). Conclusions Younger age, male, and larger tumor were high risk factors for CLNM in patients with unifocal PTC. Cross-sectional aspect ratio had a more effective predictive value for CLNM in patients with larger thyroid tumors.

scholarly journals Correlation Analysis of Nodular Sonographic Parameters with Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma

2021 ◽  
Author(s):  
Liuhua Zhou ◽  
Qiaodan Zhu ◽  
Jincao Yao ◽  
Chen Yang ◽  
Dong Xu
Keyword(s):  
Aspect Ratio ◽  
Thyroid Carcinoma ◽  
Cervical Lymph Node Metastasis ◽  
Tumor Diameter ◽  
Papillary Thyroid ◽  
Cross Sectional ◽  
Node Metastasis ◽  
Logistic Analysis ◽  
Maximum Tumor Diameter ◽  
Multivariate Logistic Analysis

Abstract Objective Papillary thyroid carcinoma (PTC) is the most common thyroid carcinoma, and is prone to cervical lymph node metastasis (CLNM). We aim to analyze the correlation between clinical information, ultrasonic parameters of PTC and CLNM. Methods 1335 patients who had pathologically confirmed unifocal PTC were enrolled. Univariate and multivariate logistic analysis were performed to predict CLNM in PTC patients. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance. Results Univariate analysis showed that gender, age, maximum tumor diameter and volume, cross-sectional and longitudinal aspect ratio were related to CLNM (P < 0.05). Multivariate logistic analysis showed that gender, age, maximum tumor diameter and volume were independent correlative factors, cross-sectional aspect ratio had significant difference for PTC patients excluding PTMC to predict CLNM. The area under the curve (AUC) of the maximum tumor diameter and volume was 0.738 and 0.733, respectively. Maximum tumor diameter and volume, and cross-sectional and longitudinal aspect ratio were statistically significant following analysis of variance (P < 0.05). Conclusions Younger age, male, and larger tumor were high risk factors for CLNM in patients with unifocal PTC. Cross-sectional aspect ratio had a more effective predictive value for CLNM in patients with larger thyroid tumors.

scholarly journals Correlation Analysis of Papillary Thyroid Carcinoma on Sonographic Features and Cervical Lymph Node Metastasis

2020 ◽  
Author(s):  
Liuhua Zhou ◽  
Qiaodan Zhu ◽  
Jincao Yao ◽  
Di Ou ◽  
Chen Yang ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Thyroid Carcinoma ◽  
Univariate Analysis ◽  
Cervical Lymph Node Metastasis ◽  
Maximum Diameter ◽  
Papillary Thyroid ◽  
Cross Sectional ◽  
Node Metastasis ◽  
Logistic Analysis ◽  
Echogenic Foci

Abstract Background Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid carcinoma. We aim to evaluate the correlation between sonographic features of PTC and cervical lymph node metastasis (CLNM). Methods A total of 1335 patients who underwent thyroidectomy and had pathologically confirmed unifocal PTC were enrolled in the retrospective research. Univariate analysis and logistic analysis were performed to predict CLNM by several independent variables. Receiver operating characteristic (ROC) curve was executed to evaluate the diagnostic performance. Results Univariate analysis showed that location, aspect ratio, margin, echogenic foci, TI-RADS score and grade were related to CLNM (P<0.05). Logistic analysis on sonographic features showed that margin and echogenic foci were independent correlative factors. Meanwhile, logistic analysis included clinical information, ultrasonic measurements and sonographic features showed that gender, age, tumour maximum diameter and volume, cross-sectional aspect ratio, location, margin and echogenic foci were independent correlative factors. The ROC curves were established based on the relevant factors, the AUC of tumour maximum diameter, tumour volume and margin were 0.738, 0.733, and 0.711, respectively. The regression model was constructed with AUC of 0.813, specificity of 70.3%, and sensitivity of 78.5%. ANOVA variance analysis on positive and negative group, tumour maximum diameter, margin, echogenic foci, TI-RADS score and grade had statistical significance (P < 0.05). Conclusion Lower location, larger lesion, margin and echogenic foci were high risk factors for CLNM in PTC, cross-sectional aspect ratio≥1 had more effective predictive value than longitudinal-sectional aspect ratio. Tumor volume was more effective to evaluate the lateral metastasis than maximum tumour diameter, it could guide preoperative FNA for CLNM.

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