scholarly journals Real-Time Elastography: A Web-Based Nomogram Improves the Preoperative Prediction of Central Lymph Node Metastasis in cN0 PTC

2022 ◽  
Vol 11 ◽  
Author(s):  
Chunwang Huang ◽  
Wenxiao Yan ◽  
Shumei Zhang ◽  
Yanping Wu ◽  
Hantao Guo ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lymph Node ◽  
Prediction Model ◽  
Central Lymph Node Metastasis ◽  
Central Lymph Node ◽  
Web Based ◽  
Training Cohort ◽  
Node Metastasis ◽  
Central Lymph ◽  
Risk Predictors

BackgroundGiven the difficulty of accurately determining the central lymph node metastasis (CLNM) status of patients with clinically node-negative (cN0) papillary thyroid carcinoma (PTC) before surgery, this study aims to combine real-time elastography (RTE) and conventional ultrasound (US) features with clinical features. The information is combined to construct and verify the nomogram to foresee the risk of CLNM in patients with cN0 PTC and to develop a network-based nomogram.MethodsFrom January 2018 to February 2020, 1,157 consecutive cases of cN0 PTC after thyroidectomy and central compartment neck dissection were retrospectively analyzed. The patients were indiscriminately allocated (2:1) to a training cohort (771 patients) and validation cohort (386 patients). Multivariate logistic regression analysis of US characteristics and clinical information in the training cohort was performed to screen for CLNM risk predictors. RTE data were included to construct prediction model 1 but were excluded when constructing model 2. DeLong’s test was used to select a forecast model with better receiver operator characteristic curve performance to establish a web-based nomogram. The clinical applicability, discrimination, and calibration of the preferable prediction model were assessed.ResultsMultivariate regression analysis showed that age, sex, tumor size, bilateral tumors, the number of tumor contacting surfaces, chronic lymphocytic thyroiditis, and RTE were risk predictors of CLNM in cN0 PTC patients, which constituted prediction model 1. Model 2 included the first six risk predictors. Comparison of the areas under the curves of the two models showed that model 1 had better prediction performance (training set 0.798 vs. 0.733, validation set 0.792 vs. 0.715, p < 0.001) and good discrimination and calibration. RTE contributed significantly to the performance of the prediction model. Decision curve analysis showed that patients could obtain good net benefits with the application of model 1.ConclusionA noninvasive web-based nomogram combining US characteristics and clinical risk factors was developed in the research. RTE could improve the prediction accuracy of the model. The dynamic nomogram has good performance in predicting the probability of CLNM in cN0 PTC patients.

scholarly journals Web-Based Ultrasonic Nomogram Predicts Preoperative Central Lymph Node Metastasis of cN0 Papillary Thyroid Microcarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Chunwang Huang ◽  
Shuzhen Cong ◽  
Shiyao Shang ◽  
Manli Wang ◽  
Huan Zheng ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Prediction Model ◽  
Central Lymph Node Metastasis ◽  
Central Lymph Node ◽  
Web Based ◽  
Node Metastasis ◽  
Multivariable Regression ◽  
Central Lymph

BackgroundMany clinicians are facing the dilemma about whether they should apply the active surveillance (AS) strategy for managing Clinically Node-negative (cN0) PTMC patients in daily clinical practice. This research plans to construct a dynamic nomogram based on network, connected with ultrasound characteristics and clinical data, to predict the risk of central lymph node metastasis (CLNM) in cN0 PTMC patients before surgery.MethodsA retrospective analysis of 659 patients with cN0 PTMC who had underwent thyroid surgery and central compartment neck dissection. Patients were randomly (2:1) divided into the development cohort (439 patients) and validation cohort (220 patients). The group least absolute shrinkage and selection operator (Group Lasso) regression method was used to select the ultrasonic features for CLNM prediction in the development cohort. These features and clinical data were screened by the multivariable regression analysis, and the CLNM prediction model and web-based calculator were established. Receiver operating characteristic, calibration curve, Clinical impact curve and decision curve analysis (DCA) were used to weigh the performance of the prediction model in the validation set.ResultsMultivariable regression analysis showed that age, tumor size, multifocality, the number of contact surface, and real-time elastography were risk factors that could predict CLNM. The area under the curve of the prediction model in the development and validation sets were 0.78 and 0.77, respectively, with good discrimination and calibration. A web-based dynamic calculator was built. DCA proved that the prediction model had excellent net benefits and clinical practicability.ConclusionsThe web-based dynamic nomogram incorporating US and clinical features was able to forecast the risk of preoperative CLNM in cN0 PTMC patients, and has good predictive performance. As a new observational indicator, NCS can provide additional predictive information.

scholarly journals Role of intraoperative neuromonitoring of recurrent laryngeal nerve in thyroid and parathyroid surgery

2020 ◽  
Vol 48 (9) ◽  
pp. 030006052095264
Author(s):  
Yuwei Ling ◽  
Jing Zhao ◽  
Ye Zhao ◽  
Kaifu Li ◽  
Yajun Wang ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Dissection ◽  
Cervical Lymph Node ◽  
Intraoperative Neuromonitoring ◽  
Central Lymph Node Metastasis ◽  
Node Dissection ◽  
Central Lymph Node ◽  
Node Metastasis ◽  
Cervical Lymph Node Dissection ◽  
Central Lymph

Objective To investigate whether intraoperative neuromonitoring (IONM) has a significant advantage in reducing the incidence of recurrent laryngeal nerve (RLN) injury. Methods Patients who underwent thyroid and parathyroid surgery from October 2012 to December 2017 at the Center for Thyroid and Breast Surgery of Xuanwu Hospital were retrospectively analyzed. They were divided into the IONM group and visualization alone group (VA group) according to whether IONM was used. Results In total, 1696 nerves at risk of injury (IONM group, n = 1104; VA group, n = 592) were included in the analysis. Among the high-risk nerves, permanent damage occurred in no cases in the IONM group but in one case in the VA group. Because the higher proportion of central lymph node metastasis caused difficulties in central cervical lymph node dissection and identification of the RLN, the patients undergoing lateral cervical lymph node dissection in the VA group had a significantly higher risk of postoperative RLN injury (11.76% vs. 0.00%). Conclusion IONM technology has advantages in protection of the RLN, especially in high-risk nerves and patients with a high proportion of central lymph node metastasis who require central and lateral cervical lymph node dissection.

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