scholarly journals Predictive value of the Delphian lymph node in cervical lymph node metastasis of papillary thyroid carcinoma

2021 ◽  
Author(s):  
Yunfei Yan ◽  
Yu Wang ◽  
Na Liu ◽  
Yuansheng Duan ◽  
Xiaohan Chen ◽  
...  
Keyword(s):  
Lymph Node ◽  
Papillary Thyroid Carcinoma ◽  
Lymph Node Metastasis ◽  
Thyroid Carcinoma ◽  
Predictive Value ◽  
Cervical Lymph Node ◽  
Cervical Lymph Node Metastasis ◽  
Papillary Thyroid ◽  
Node Metastasis

scholarly journals A Comparative Analysis of Six Machine Learning Models Based on Ultrasound to Distinguish the Possibility of Central Cervical Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Ying Zou ◽  
Yan Shi ◽  
Jihua Liu ◽  
Guanghe Cui ◽  
Zhi Yang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lymph Node ◽  
Papillary Thyroid Carcinoma ◽  
Lymph Node Metastasis ◽  
Thyroid Carcinoma ◽  
Predictive Value ◽  
Cervical Lymph Node ◽  
Cervical Lymph Node Metastasis ◽  
Papillary Thyroid ◽  
Node Metastasis

Current approaches to predict central cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) have failed to identify patients who would benefit from preventive treatment. Machine learning has offered the opportunity to improve accuracy by comparing the different algorithms. We assessed which machine learning algorithm can best improve CLNM prediction. This retrospective study used routine ultrasound data of 1,364 PTC patients. Six machine learning algorithms were compared to predict the possibility of CLNM. Predictive accuracy was assessed by sensitivity, specificity, positive predictive value, negative predictive value, and the area under the curve (AUC). The patients were randomly split into the training (70%), validation (15%), and test (15%) data sets. Random forest (RF) led to the best diagnostic model in the test cohort (AUC 0.731 ± 0.036, 95% confidence interval: 0.664–0.791). The diagnostic performance of the RF algorithm was most dependent on the following five top-rank features: extrathyroidal extension (27.597), age (17.275), T stage (15.058), shape (13.474), and multifocality (12.929). In conclusion, this study demonstrated promise for integrating machine learning methods into clinical decision-making processes, though these would need to be tested prospectively.

scholarly journals Cooccurrence of Metastatic Papillary Thyroid Carcinoma andSalmonellaInduced Neck Abscess in a Cervical Lymph Node

2017 ◽  
Vol 2017 ◽  
pp. 1-4 ◽  
Author(s):  
Jae-Myung Kim ◽  
Ju-Yeon Kim ◽  
Eun Jung Jung ◽  
Eun Jin Song ◽  
Dong Chul Kim ◽  
...  
Keyword(s):  
Lymph Node ◽  
Papillary Thyroid Carcinoma ◽  
Lymph Node Metastasis ◽  
Thyroid Carcinoma ◽  
Cervical Lymph Node ◽  
Cervical Lymph Node Metastasis ◽  
Salmonella Typhi ◽  
Cystic Mass ◽  
Papillary Thyroid ◽  
Node Metastasis

Cervical lymph node metastasis is common in patients with papillary thyroid carcinoma (PTC).Salmonellaspecies are rarely reported as causative agents in focal infections of the head and neck. The cooccurrence of lymph node metastasis from PTC and a bacterial infection is rare. This report describes a 76-year-old woman with a cervical lymph node metastasis from PTC andSalmonellainfection of the same lymph node. The patient presented with painful swelling in her left lateral neck region for 15 days, and neck ultrasonography and computed tomography showed a cystic mass along left levels II–IV. The cystic mass was suspected of being a metastatic lymph node; modified radical neck dissection was performed. Histopathological examination confirmed the presence of PTC in the resected node and laboratory examination of the combined abscess cavity confirmed the presence ofSalmonella Typhi. Following antibiotic sensitivity testing of the culturedSalmonella Typhi, she was treated with proper antibiotics. Cystic lesions in lymph nodes with metastatic cancer may indicate the presence of cooccurring bacterial infection. Thus, culturing of specimen can be option to make accurate diagnosis and to provide proper postoperative management.

scholarly journals Prediction of Ipsilateral Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma: A Combined Dual-energy CT and Thyroid Functional Indicators Study

2020 ◽  
Author(s):  
Ying Zou ◽  
Huanlei Zhang ◽  
Wenfei Li ◽  
Yu Guo ◽  
Fang Sun ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lymph Node ◽  
Papillary Thyroid Carcinoma ◽  
Lymph Node Metastasis ◽  
Thyroid Carcinoma ◽  
Cervical Lymph Node ◽  
Cervical Lymph Node Metastasis ◽  
Dual Energy ◽  
Papillary Thyroid ◽  
Node Metastasis

Abstract BackgroundThe prediction of ipsilateral lateral cervical lymph node metastasis (ipsi-LLNM) was crucial to the operation plan in patients with papillary thyroid carcinoma (PTC). This study aimed to investigate the risk factors for ipsi-LLNM using dual-energy computed tomography (DECT) and thyroid functional indicators in patients with PTC. MethodsThe medical records of 406 patients with a pathological diagnosis of PTC were retrospectively reviewed from Jan 2016 to Dec 2019. Demographic, clinical, pathological findings, and parameters from DECT were evaluated. Risk factors for ipsi-LLNM were explored by univariate and multivariate analyses. Receiver operating characteristic (ROC) curves were used to evaluate the cut-off value of each risk factor.ResultsTotally 406 patients with PTC were analyzed, including 128 with ipsi-LLNM and 278 without. There were statistical differences of parameters between the two groups (P < .0001), including serum Tg, Anti-Tg, Anti-TPO, the volume of the primary lesion, calcification, extrathyroidal extension (ETE), and iodine concentration (IC) in arterial and venous phases. Independent risk factors for ipsi-LLNM included serum Tg, Anti-Tg, ETE, and IC in arterial and venous phases (P < .05). Ipsi-LLNM was more likely to occur when the following conditions were met: with ETE, Tg > 100.01 ng/ml, Anti-Tg > 89.43 IU/ml, IC in arterial phase > 3.4 mg/ml and IC in venous phase > 3.1 mg/ml.ConclusionsApplication of DECT parameters and thyroid functional indicators can improve the diagnostic performance in the evaluation of ipsi-LLNM in patients with PTC.

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