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Su B, Li L, Liu Y, Liu H, Zhan J, Chai Q, Fang L, Wang L, Chen L. Quantitative parameters of contrast-enhanced ultrasound effectively promote the prediction of cervical lymph node metastasis in papillary thyroid carcinoma. Drug Discov Ther 2024; 18:44-53. [PMID: 38355122 DOI: 10.5582/ddt.2023.01095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
Abstract
Papillary thyroid carcinoma (PTC), the most common endocrine tumor, often spreads to cervical lymph nodes metastasis (CLNM). Preoperative diagnosis of CLNM is important when selecting surgical strategies. Therefore, we aimed to explore the effectiveness of quantitative parameters of contrast-enhanced ultrasound (CEUS) in predicting CLNM in PTC. We retrospectively analyzed 193 patients with PTC undergoing conventional ultrasound (CUS) and CEUS. The CUS features and quantitative parameters of CEUS were evaluated according to PTC size ≤ 10 or > 10 mm, using pathology as the gold standard. For the PTC ≤ 10 mm, microcalcification and multifocality were significantly different between the CLNM (+) and CLNM (-) groups (both P < 0.05). For the PTC > 10 mm, statistical significance was noted between the two groups with respect to the margin, capsule contact, and multifocality (all P < 0.05). For PTC ≤ 10 mm, there was no significant difference between the CLNM (+) and CLNM (-) groups in all quantitative parameters of CEUS (all P > 0.05). However, for PTC > 10 mm, the peak intensity (PI), mean transit time, and slope were significantly associated with CLNM (all P < 0.05). Multivariate analysis showed that PI > 5.8 dB was an independent risk factor for predicting CLNM in patients with PTC > 10 mm (P < 0.05). The area under the curve of PI combined with CUS (0.831) was significantly higher than that of CUS (0.707) or PI (0.703) alone in the receiver operator characteristic curve analysis (P < 0.05). In conclusion, PI has significance in predicting CLNM for PTC > 10 mm; however, it is not helpful for PTC ≤ 10 mm.
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Affiliation(s)
- Biao Su
- Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China
- Department of Ultrasound, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Lisha Li
- Department of Reproductive Immunology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Clinical Geriatric Medicine, Shanghai, China
| | - Yingchun Liu
- Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China
| | - Hui Liu
- Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China
- Department of Ultrasound, Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Jia Zhan
- Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China
| | - Qiliang Chai
- Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China
| | - Liang Fang
- Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China
| | - Ling Wang
- Department of Reproductive Immunology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Clinical Geriatric Medicine, Shanghai, China
| | - Lin Chen
- Department of Ultrasound, Huadong Hospital, Fudan University, Shanghai, China
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Ma N, Tian HY, Yu ZY, Zhu X, Zhao DW. Integrating US-guided FNAB, BRAF V600E mutation, and clinicopathologic characteristics to predict cervical central lymph-node metastasis in preoperative patients with cN0 papillary thyroid carcinoma. Eur Arch Otorhinolaryngol 2023; 280:5565-5574. [PMID: 37540271 PMCID: PMC10620286 DOI: 10.1007/s00405-023-08156-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 07/25/2023] [Indexed: 08/05/2023]
Abstract
BACKGROUND The prevalence of cervical central lymph-node metastasis (CLNM) is high in patients with papillary thyroid carcinoma (PTC). There is considerable controversy surrounding the benefits of prophylactic central lymph-node dissection (pCLND) in patients with clinically negative central compartment lymph nodes (cN0). Therefore, it is crucial to accurately predict the likelihood of cervical CLNM before surgery to make informed surgical decisions. METHODS Date from 214 PTC patients (cN0) who underwent partial or total thyroidectomy and pCLND at the Guizhou Provincial People's Hospital were collected and retrospectively analyzed. They were divided into two groups in accordance with cervical CLNM or not. Their information, including clinical characteristics, ultrasound (US) features, pathological results of fine-needle aspirations biopsy (FNAB), and other characteristics of the groups, was analyzed and compared using univariate and multivariate logistic regression analyses. RESULTS A total of 214 patients were eligible in this study. Among them, 43.5% (93/214) of PTC patients had cervical CLNM, and 56.5% (121/214) did not. The two groups were compared using a univariate analyses, and there were no significant differences between the two groups in aspect ratio, boundary, morphology, component, and BRAFV600E (P > 0.05), and there were significant differences between gender, age, maximum tumor size, tumor location, capsule contact, microcalcifications, color Doppler flow imaging (CDFI), and Hashimoto's thyroiditis (HT) (P < 0.05). A multivariate logistic regression analysis was performed to further clarify the correlation of these indices. However, only age (OR = 2.455, P = 0.009), maximum tumor size (OR = 2.586, P = 0.010), capsule contact (OR = 3.208, P = 0.001), and CDFI (OR = 2.225, P = 0.022) were independent predictors of cervical CLNM. Combining these four factors, the area under the receiver-operating characteristic (ROC) curve for the joint diagnosis is 0.8160 (95% 0.7596-0.8725). Univariate analysis indicated that capsule contact (P = 0.001) was a possible predictive factor of BRAFV600E mutation. CONCLUSIONS In conclusion, four independent predictors of cervical CLNM, including age < 45 years, tumor size > 1.0 cm, capsule contact, and rich blood flow, were screened out. Therefore, a comprehensive assessment of these risk factors should be conducted when designing individualized treatment regimens for PTC patients.
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Affiliation(s)
- Ning Ma
- Clinical Medical College, Guizhou Medical University, Guiyang, China
- Department of Vascular and Thyroid Surgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Hai-Ying Tian
- Clinical Medical College, Guizhou Medical University, Guiyang, China
- Department of Ultrasound, Guizhou Provincial People's Hospital, Guiyang, China
| | - Zhao-Yan Yu
- Department of Vascular and Thyroid Surgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Xin Zhu
- Department of Vascular and Thyroid Surgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Dai-Wei Zhao
- Clinical Medical College, Guizhou Medical University, Guiyang, China.
- Department of Thyroid and Breast Surgery, Second People's Hospital of Guizhou Province, No. 206, South Section of Xintian. Avenue, Guiyang, 550004, China.
- Department of Breast and Thyroid Surgery, Guiqian International General Hospital, No. 1 Dongfeng Avenue, Wudang District, Guiyang, 550024, China.
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Lu S, Ren Y, Lu C, Qian X, Liu Y, Zhang J, Shan X, Sun E. Radiomics features from whole thyroid gland tissue for prediction of cervical lymph node metastasis in the patients with papillary thyroid carcinoma. J Cancer Res Clin Oncol 2023; 149:13005-13016. [PMID: 37466794 DOI: 10.1007/s00432-023-05184-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 07/13/2023] [Indexed: 07/20/2023]
Abstract
OBJECTIVE We aimed to develop a clinical-radiomics nomogram that could predict the cervical lymph node metastasis (CLNM) of patients with papillary thyroid carcinoma (PTC) using clinical characteristics as well as radiomics features of dual energy computed tomography (DECT). METHOD Patients from our hospital with suspected PTC who underwent DECT for preoperative assessment between January 2021 and February 2022 were retrospectively recruited. Clinical characteristics were obtained from the medical record system. Clinical characteristics and rad-scores were examined by univariate and multivariate logistic regression. All features were incorporated into the LASSO regression model, with penalty parameter tuning performed using tenfold cross-validation, to screen risk factors for CLNM. An easily accessible radiomics nomogram was constructed. Receiver Operating Characteristic (ROC) curve together with Area Under the Curve (AUC) analysis was conducted to evaluate the discrimination performance of the model. Calibration curves were employed to assess the calibration performance of the clinical-radiomics nomogram, followed by goodness-of-fit testing. Decision curve analysis (DCA) was performed to determine the clinical utility of the established models by estimating net benefits at varying threshold probabilities for training and testing groups. RESULTS A total of 461 patients were retrospectively recruited. The rates of CLNM were 49.3% (70 /142) in the training cohort and 53.3% (32/60) in the testing cohort. Out of the 960 extracted radiomics features, 192 were significantly different in positive and negative groups (p < 0.05). On the basis of the training cohort, 12 stable features with nonzero coefficients were selected using LASSO regression. LASSO regression identified 7 risk factors for CLNM, including male gender, maximum tumor size > 10 mm, multifocality, CT-reported central CLN status, US-reported central CLN status, rad-score, and TGAb. A nomogram was developed using these factors to predict the risk of CLNM. The AUC values in each cohort were 0.850 and 0.797, respectively. The calibration curve together with the Hosmer-Lemeshow test for the nomogram indicated good agreement between predicted and pathological CLN statuses in the training and testing cohorts. Results of DCA proved that the nomogram offers a superior net benefit for predicting CLNM compared to the "treat all or none" strategy across the majority of risk thresholds. CONCLUSION A nomogram comprising the clinical characteristics as well as radiomics features of DECT and US was constructed for the prediction of CLNM for patients with PTC, which in determining whether lateral compartment neck dissection is warranted.
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Affiliation(s)
- Siyuan Lu
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, Jiangsu Province, China
| | - Yongzhen Ren
- Department of Ultrasonography, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, Jiangsu Province, China
| | - Chao Lu
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, Jiangsu Province, China
| | - Xiaoqin Qian
- Department of Ultrasonography, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, Jiangsu Province, China
| | - Yingzhao Liu
- Department of Endocrinology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, Jiangsu Province, China
| | - Jiulou Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiuhong Shan
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, Jiangsu Province, China.
| | - Eryi Sun
- Department of Neurosurgery, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, Jiangsu Province, China.
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Yan X, Mou X, Yang Y, Ren J, Zhou X, Huang Y, Yuan H. Predicting central lymph node metastasis in patients with papillary thyroid carcinoma based on ultrasound radiomic and morphological features analysis. BMC Med Imaging 2023; 23:111. [PMID: 37620767 PMCID: PMC10463837 DOI: 10.1186/s12880-023-01085-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 08/21/2023] [Indexed: 08/26/2023] Open
Abstract
OBJECTIVES To build a combined model based on the ultrasound radiomic and morphological features, and evaluate its diagnostic performance for preoperative prediction of central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC). METHOD A total of 295 eligible patients, who underwent preoperative ultrasound scan and were pathologically diagnosed with unifocal PTC were included at our hospital from October 2019 to July 2022. According to ultrasound scanners, patients were divided into the training set (115 with CLNM; 97 without CLNM) and validation set (45 with CLNM; 38 without CLNM). Ultrasound radiomic, morphological, and combined models were constructed using multivariate logistic regression. The diagnostic performance was assessed by the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, sensitivity, and specificity. RESULTS A combined model was built based on the morphology, boundary, length diameter, and radiomic score. The AUC was 0.960 (95% CI, 0.924-0.982) and 0.966 (95% CI, 0.901-0.993) in the training and validation set, respectively. Calibration curves showed good consistency between prediction and observation, and DCA demonstrated the clinical benefit of the combined model. CONCLUSION Based on ultrasound radiomic and morphological features, the combined model showed a good performance in predicting CLNM of patients with PTC preoperatively.
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Affiliation(s)
- Xiang Yan
- Sichuan Key Laboratory of Medical Imaging, Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Xurong Mou
- Sichuan Key Laboratory of Medical Imaging, Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Yanan Yang
- Sichuan Key Laboratory of Medical Imaging, Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Jing Ren
- Sichuan Key Laboratory of Medical Imaging, Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Xingxu Zhou
- Sichuan Key Laboratory of Medical Imaging, Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Yifei Huang
- Sichuan Key Laboratory of Medical Imaging, Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Hongmei Yuan
- Sichuan Key Laboratory of Medical Imaging, Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China.
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Chen Q, Liu Y, Liu J, Su Y, Qian L, Hu X. Development and validation of a dynamic nomogram based on conventional ultrasound and contrast-enhanced ultrasound for stratifying the risk of central lymph node metastasis in papillary thyroid carcinoma preoperatively. Front Endocrinol (Lausanne) 2023; 14:1186381. [PMID: 37409231 PMCID: PMC10319155 DOI: 10.3389/fendo.2023.1186381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 06/05/2023] [Indexed: 07/07/2023] Open
Abstract
Purpose The aim of this study was to develop and validate a dynamic nomogram by combining conventional ultrasound (US) and contrast-enhanced US (CEUS) to preoperatively evaluate the probability of central lymph node metastases (CLNMs) for patients with papillary thyroid carcinoma (PTC). Methods A total of 216 patients with PTC confirmed pathologically were included in this retrospective and prospective study, and they were divided into the training and validation cohorts, respectively. Each cohort was divided into the CLNM (+) and CLNM (-) groups. The least absolute shrinkage and selection operator (LASSO) regression method was applied to select the most useful predictive features for CLNM in the training cohort, and these features were incorporated into a multivariate logistic regression analysis to develop the nomogram. The nomogram's discrimination, calibration, and clinical usefulness were assessed in the training and validation cohorts. Results In the training and validation cohorts, the dynamic nomogram (https://clnmpredictionmodel.shinyapps.io/PTCCLNM/) had an area under the receiver operator characteristic curve (AUC) of 0.844 (95% CI, 0.755-0.905) and 0.827 (95% CI, 0.747-0.906), respectively. The Hosmer-Lemeshow test and calibration curve showed that the nomogram had good calibration (p = 0.385, p = 0.285). Decision curve analysis (DCA) showed that the nomogram has more predictive value of CLNM than US or CEUS features alone in a wide range of high-risk threshold. A Nomo-score of 0.428 as the cutoff value had a good performance to stratify high-risk and low-risk groups. Conclusion A dynamic nomogram combining US and CEUS features can be applied to risk stratification of CLNM in patients with PTC in clinical practice.
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Shen H, Lv G, Li T, Wang Y, Chen K, Wang K, Li L, Zheng X, Yang S. Construction and Validation of a Predictive Nomogram Based on Ultrasound for Lymph Node Metastasis of Papillary Thyroid Carcinoma in the Cervical Central Region. Ultrasound Q 2023; 39:47-52. [PMID: 34743152 DOI: 10.1097/ruq.0000000000000583] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
ABSTRACT To establish and validate a nomogram for predicting lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) in the cervical central region. This retrospective study included 287 PTC patients with 309 nodules treated from December 2018 to May 2020 at our hospital. The cohort was divided randomly into a training set and a testing set according to a 7:3 ratio. The training set contained 216 nodules, and the testing set contained 93 nodules. The nomogram was developed using the training set, and the data of the testing set were used to validate the performance of nomogram. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index) and calibration curve. The study showed multifocality, thyroid lesion size, and American College of Radiology Thyroid Imaging, Reporting and Data System (TI-RADS) score were significantly independently associated with LNM in the cervical central region. In the testing set, the calibration curve showed that the nomogram had good discrimination with a C-index of 0.775 (95% confidence interval, 0.680-0.869) and adequate calibration ( P = 0.808). By decision curve analysis and clinical impact curve analysis, the nomogram was shown to have a satisfactory net benefit between thresholds of 0.40 and 0.75. The nomogram can be used for predicting LNM of PTC in the cervical central region and may provide valuable guidance for planning the surgical treatment of PTC patients.
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Affiliation(s)
- Haolin Shen
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
| | - Guorong Lv
- Department of Clinical Medicine, Quanzhou Medical College, Quanzhou, Fujian, China
| | - Tingting Li
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
| | - Yuegui Wang
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
| | - Keyue Chen
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
| | - Kangjian Wang
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
| | - Ling Li
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
| | - Xiaoyun Zheng
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
| | - Shuping Yang
- Department of Ultrasound, Zhangzhou Hospital affiliated to Fujian Medical University, Zhangzhou
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Wang Z, Qu L, Chen Q, Zhou Y, Duan H, Li B, Weng Y, Su J, Yi W. Deep learning-based multifeature integration robustly predicts central lymph node metastasis in papillary thyroid cancer. BMC Cancer 2023; 23:128. [PMID: 36750791 PMCID: PMC9906958 DOI: 10.1186/s12885-023-10598-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 02/01/2023] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND Few highly accurate tests can diagnose central lymph node metastasis (CLNM) of papillary thyroid cancer (PTC). Genetic sequencing of tumor tissue has allowed the targeting of certain genetic variants for personalized cancer therapy development. METHODS This study included 488 patients diagnosed with PTC by ultrasound-guided fine-needle aspiration biopsy, collected clinicopathological data, analyzed the correlation between CLNM and clinicopathological features using univariate analysis and binary logistic regression, and constructed prediction models. RESULTS Binary logistic regression analysis showed that age, maximum diameter of thyroid nodules, capsular invasion, and BRAF V600E gene mutation were independent risk factors for CLNM, and statistically significant indicators were included to construct a nomogram prediction model, which had an area under the curve (AUC) of 0.778. A convolutional neural network (CNN) prediction model built with an artificial intelligence (AI) deep learning algorithm achieved AUCs of 0.89 in the training set and 0.78 in the test set, which indicated a high prediction efficacy for CLNM. In addition, the prediction models were validated in the subclinical metastasis and clinical metastasis groups with high sensitivity and specificity, suggesting the broad applicability of the models. Furthermore, CNN prediction models were constructed for patients with nodule diameters less than 1 cm. The AUCs in the training set and test set were 0.87 and 0.76, respectively, indicating high prediction efficacy. CONCLUSIONS The deep learning-based multifeature integration prediction model provides a reference for the clinical diagnosis and treatment of PTC.
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Affiliation(s)
- Zhongzhi Wang
- grid.216417.70000 0001 0379 7164Department of General Surgery, the Affiliated Zhuzhou Hospital Xiangya Medical College, Central South University, Zhuzhou, Hunan China
| | - Limeng Qu
- grid.452708.c0000 0004 1803 0208Department of General Surgery, The Second Xiangya Hospital of Central South University, No. 139, Renmin Central Road, Changsha, 410011 P.R. China
| | - Qitong Chen
- grid.452708.c0000 0004 1803 0208Department of General Surgery, The Second Xiangya Hospital of Central South University, No. 139, Renmin Central Road, Changsha, 410011 P.R. China
| | - Yong Zhou
- grid.216417.70000 0001 0379 7164Department of General Surgery, the Affiliated Zhuzhou Hospital Xiangya Medical College, Central South University, Zhuzhou, Hunan China
| | - Hongtao Duan
- grid.216417.70000 0001 0379 7164Department of Ultrasound Diagnosis, the Affiliated Zhuzhou Hospital Xiangya Medical College, Central South University, Zhuzhou, Hunan China
| | - Baifeng Li
- grid.216417.70000 0001 0379 7164Department of General Surgery, the Affiliated Zhuzhou Hospital Xiangya Medical College, Central South University, Zhuzhou, Hunan China
| | - Yao Weng
- grid.216417.70000 0001 0379 7164Department of Metabolic Endocrinology, the Affiliated Zhuzhou Hospital Xiangya Medical College, Central South University, Zhuzhou, Hunan China
| | - Juan Su
- Department of Medical Administration, the Affiliated Zhuzhou Hospital Xiangya Medical College, Central South University, No.116, Changjiang South Road, Zhuzhou, 412007, P.R. China.
| | - Wenjun Yi
- Department of General Surgery, The Second Xiangya Hospital of Central South University, No. 139, Renmin Central Road, Changsha, 410011, P.R. China.
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Zhao F, Wang P, Yu C, Song X, Wang H, Fang J, Zhu C, Li Y. A LASSO-based model to predict central lymph node metastasis in preoperative patients with cN0 papillary thyroid cancer. Front Oncol 2023; 13:1034047. [PMID: 36761950 PMCID: PMC9905414 DOI: 10.3389/fonc.2023.1034047] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/09/2023] [Indexed: 01/26/2023] Open
Abstract
Introduction Central lymph node metastasis (CLNM) is common in papillary thyroid carcinoma (PTC). Prophylactic central lymph node dissection (PCLND) in clinically negative central compartment lymph node (cN0) PTC patients is still controversial. How to predict CLNM before the operation is very important for surgical decision making. Methods In this article, we retrospectively enrolled 243 cN0 PTC patients and gathered data including clinical characteristics, ultrasound (US) characteristics, pathological results of fine-needle aspiration (FNA), thyroid function, eight gene mutations, and immunoenzymatic results. Least absolute shrinkage and selection operator (LASSO) analysis was used for data dimensionality reduction and feature analysis. Results According to the results, the important predictors of CLNM were identified. Multivariable logistic regression analysis was used to establish a new nomogram prediction model. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve were used to evaluate the performance of the new prediction model. Discussion The new nomogram prediction model was a reasonable and reliable model for predicting CLNM in cN0 PTC patients, but further validation is warranted.
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Affiliation(s)
- Feng Zhao
- Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ping Wang
- Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chaoran Yu
- Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuefei Song
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hui Wang
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Fang
- Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chenfang Zhu
- Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China,*Correspondence: Yousheng Li, ; Chenfang Zhu,
| | - Yousheng Li
- Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China,*Correspondence: Yousheng Li, ; Chenfang Zhu,
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Zhu H, Yu B, Li Y, Zhang Y, Jin J, Ai Y, Jin X, Yang Y. Models of ultrasonic radiomics and clinical characters for lymph node metastasis assessment in thyroid cancer: a retrospective study. PeerJ 2023; 11:e14546. [PMID: 36650830 PMCID: PMC9840861 DOI: 10.7717/peerj.14546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/18/2022] [Indexed: 01/14/2023] Open
Abstract
Background Preoperative prediction of cervical lymph node metastasis in papillary thyroid carcinoma provided a basis for tumor staging and treatment decision. This study aimed to investigate the utility of machine learning and develop different models to preoperatively predict cervical lymph node metastasis based on ultrasonic radiomic features and clinical characteristics in papillary thyroid carcinoma nodules. Methods Data from 400 papillary thyroid carcinoma nodules were included and divided into training and validation group. With the help of machine learning, clinical characteristics and ultrasonic radiomic features were extracted and selected using randomforest and least absolute shrinkage and selection operator regression before classified by five classifiers. Finally, 10 models were built and their area under the receiver operating characteristic curve, accuracy, sensitivity, specificity, positive predictive value and negative predictive value were measured. Results Among the 10 models, RF-RF model revealed the highest area under curve (0.812) and accuracy (0.7542) in validation group. The top 10 variables of it included age, seven textural features, one shape feature and one first-order feature, in which eight were high-dimensional features. Conclusions RF-RF model showed the best predictive performance for cervical lymph node metastasis. And the importance features selected by it highlighted the unique role of higher-dimensional statistical methods for radiomics analysis.
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Affiliation(s)
- Hui Zhu
- Department of Ultrasound, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Bing Yu
- Department of Radiotherapy Center, The 1st Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yanyan Li
- Department of Ultrasound, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yuhua Zhang
- Department of Ultrasound, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Juebin Jin
- Department of Medical Engineering, The 1st Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yao Ai
- Department of Radiotherapy Center, The 1st Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Xiance Jin
- Department of Radiotherapy Center, The 1st Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yan Yang
- Department of Ultrasound, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
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Zhong L, Xie J, Shi L, Gu L, Bai W. Nomogram based on preoperative conventional ultrasound and shear wave velocity for predicting central lymph node metastasis in papillary thyroid carcinoma. Clin Hemorheol Microcirc 2023; 83:129-136. [PMID: 36213990 DOI: 10.3233/ch-221576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022]
Abstract
OBJECTIVE To establish a nomogram for predicting cervical lymph node metastasis (CLNM) based on the preoperative conventional ultrasound (US) and shear wave velocity (SWV) features of papillary thyroid carcinoma (PTC). METHODS A total of 101 patients with pathologically confirmed thyroid nodules were enrolled. These patients were divided into the CLNM-positive (n = 40) and CLNM-negative groups (n = 61). All patients underwent the preoperative conventional US and shear wave elastography (SWE) evaluation, and the US parameters and SWV data were collected. The association between SWV ratio and CLNM was compared to assess the diagnostic efficacy of SWV ratio alone as opposed to SWV ratio in combination with the conventional US for predicting CLNM. RESULTS There were significant differences in shape, microcalcification, capsule contact, SWV mean, and SWV ratio between the CLNM-positive and CLNM-negative groups (P < 0.05). Logistic regression analysis showed that taller-than-wide shape, microcalcification, capsule contact, and SWV ratio > 1.3 were risk factors for CLNM; Logistic(P)=-6.93 + 1.647 * (microcalcification)+1.138 * (taller-than-wide-shape)+1.612 * (capsule contact)+2.933 * (SWV ratio > 1.3). The area under the curve (AUC) of the receiver operating characteristic (ROC) of the model for CLNM prediction was 0.87, with 81.19% accuracy, 77.5% sensitivity, and 85.25% specificity. CONCLUSION The nomogram based on conventional US imaging in combination with SWV ratio has the potential for preoperative CLNM risk assessment. This nomogram serves as a useful clinical tool for active surveillance and treatment decisions.
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Affiliation(s)
- Lichang Zhong
- Department of Ultrasound in Medicine, Sixth People's Hospital Affiliated to Medical College of Shanghai Jiaotong University, Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Juan Xie
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lin Shi
- Department of Ultrasound in Medicine, Sixth People's Hospital Affiliated to Medical College of Shanghai Jiaotong University, Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Liping Gu
- Department of Ultrasound in Medicine, Sixth People's Hospital Affiliated to Medical College of Shanghai Jiaotong University, Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Wenkun Bai
- Department of Ultrasound in Medicine, Sixth People's Hospital Affiliated to Medical College of Shanghai Jiaotong University, Shanghai Institute of Ultrasound in Medicine, Shanghai, China
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Lai Y, Gu Y, Yu M, Deng J. Younger Than 55 Years Old and BRAF V600E Mutation are Risk Factors for Lymph Node Metastasis in Papillary Thyroid Carcinomas ≤1.0 cm but Not in >1.0 cm. Int J Gen Med 2023; 16:1403-1414. [PMID: 37155469 PMCID: PMC10122992 DOI: 10.2147/ijgm.s408588] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/13/2023] [Indexed: 05/10/2023] Open
Abstract
Background Studies on the relationship between BRAF V600E mutation and the clinicopathologic features of papillary thyroid carcinoma (PTC), risk of lymph node metastasis in papillary thyroid microcarcinoma (PTMC) have shown inconsistent results. Methods In this retrospective analysis, clinicopathological data of the patients were collected, and molecular testing was done for BRAF V600E mutation. PTC patients are divided into PTC≤1.0cm (PTMC) and PTC>1.0cm, and the relationship between BRAF V600E mutation and clinicopathologic features was analyzed respectively. Results Of the 520 PTC patients, 432 (83.1%) were female and 416 (80.0%) were <55 years old. BRAF V600E mutation was detected in 422 (81.2%) tumour samples of PTC. There was no significant difference in the frequency of BRAF V600E mutation between different age groups. There were 250 (48.1%) patients with PTMC and 270 (51.9%) patients with PTC>1.0cm. BRAF V600E mutation was significantly associated with bilateral cancer (23.0% vs 4.9%, P=0.005) and lymph node metastasis (61.7% vs 39.0%, P=0.009) in PTMC patients, while BRAF V600E mutation was significantly associated with bilateral cancer (24.9% vs 12.3%, P=0.048) in PTC>1.0cm patients. Logistic regression analysis showed that, after adjusting for gender, Hashimoto's thyroiditis and calcification, we found that younger age (<55 years old) (OR: 2.384, 95% CI: 1.241-4.579, P=0.009) and BRAF V600E mutation (OR: 2.213, 95% CI: 1.085-4.512, P=0.029) were significantly associated with lymph node metastasis in PTMC, similar results were not obtained in PTC>1.0cm. Conclusion Younger age (<55 years old) and BRAF V600E mutation was independent risk factor for lymph node metastasis in PTMC.
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Affiliation(s)
- Yeqian Lai
- Department of Thyroid Surgery, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
- Correspondence: Yeqian Lai, Department of Thyroid Surgery, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, 63 Huangtang Road, Meijiang District, Meizhou, People’s Republic of China, Email
| | - Yihua Gu
- Department of Thyroid Surgery, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
| | - Ming Yu
- Department of Thyroid Surgery, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
| | - Jiaqin Deng
- Department of Thyroid Surgery, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou People’s Hospital, Meizhou Academy of Medical Sciences, Meizhou, People’s Republic of China
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12
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Agyekum EA, Ren YZ, Wang X, Cranston SS, Wang YG, Wang J, Akortia D, Xu FJ, Gomashie L, Zhang Q, Zhang D, Qian X. Evaluation of Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma Using Clinical-Ultrasound Radiomic Machine Learning-Based Model. Cancers (Basel) 2022; 14:5266. [PMID: 36358685 PMCID: PMC9655605 DOI: 10.3390/cancers14215266] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/10/2022] [Accepted: 10/21/2022] [Indexed: 08/30/2023] Open
Abstract
We aim to develop a clinical-ultrasound radiomic (USR) model based on USR features and clinical factors for the evaluation of cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC). This retrospective study used routine clinical and US data from 205 PTC patients. According to the pathology results, the enrolled patients were divided into a non-CLNM group and a CLNM group. All patients were randomly divided into a training cohort (n = 143) and a validation cohort (n = 62). A total of 1046 USR features of lesion areas were extracted. The features were reduced using Pearson's Correlation Coefficient (PCC) and Recursive Feature Elimination (RFE) with stratified 15-fold cross-validation. Several machine learning classifiers were employed to build a Clinical model based on clinical variables, a USR model based solely on extracted USR features, and a Clinical-USR model based on the combination of clinical variables and USR features. The Clinical-USR model could discriminate between PTC patients with CLNM and PTC patients without CLNM in the training (AUC, 0.78) and validation cohorts (AUC, 0.71). When compared to the Clinical model, the USR model had higher AUCs in the validation (0.74 vs. 0.63) cohorts. The Clinical-USR model demonstrated higher AUC values in the validation cohort (0.71 vs. 0.63) compared to the Clinical model. The newly developed Clinical-USR model is feasible for predicting CLNM in patients with PTC.
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Affiliation(s)
- Enock Adjei Agyekum
- Department of Ultrasound, Jiangsu University Affiliated People’s Hospital, Zhenjiang 212002, China
- School of Medicine, Jiangsu University, Zhenjiang 212002, China
| | - Yong-Zhen Ren
- Department of Ultrasound, Jiangsu University Affiliated People’s Hospital, Zhenjiang 212002, China
- School of Medicine, Jiangsu University, Zhenjiang 212002, China
| | - Xian Wang
- Department of Ultrasound, Jiangsu University Affiliated People’s Hospital, Zhenjiang 212002, China
| | | | - Yu-Guo Wang
- Department of Ultrasound, Nanjing Lishui District Hospital of Traditional Chinese Medicine, Nanjing 211200, China
| | - Jun Wang
- Department of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
| | - Debora Akortia
- Department of Clinical Microbiology, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi 00233, Ghana
| | - Fei-Ju Xu
- Department of Ultrasound, Jiangsu University Affiliated People’s Hospital, Zhenjiang 212002, China
| | - Leticia Gomashie
- Department of Imaging, Klintaps University College, Accra 00233, Ghana
| | - Qing Zhang
- Department of Ultrasound, Jiangsu University Affiliated People’s Hospital, Zhenjiang 212002, China
| | - Dongmei Zhang
- Department of Ultrasound, Jiangsu University Affiliated People’s Hospital, Zhenjiang 212002, China
| | - Xiaoqin Qian
- Department of Ultrasound, Jiangsu University Affiliated People’s Hospital, Zhenjiang 212002, China
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13
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Tong Y, Zhang J, Wei Y, Yu J, Zhan W, Xia H, Zhou S, Wang Y, Chang C. Ultrasound-based radiomics analysis for preoperative prediction of central and lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multi-institutional study. BMC Med Imaging 2022; 22:82. [PMID: 35501717 PMCID: PMC9059387 DOI: 10.1186/s12880-022-00809-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/20/2022] [Indexed: 12/12/2022] Open
Abstract
Background An accurate preoperative assessment of cervical lymph node metastasis (LNM) is important for choosing an optimal therapeutic strategy for papillary thyroid carcinoma (PTC) patients. This study aimed to develop and validate two ultrasound (US) nomograms for the individual prediction of central and lateral compartment LNM in patients with PTC. Methods A total of 720 PTC patients from 3 institutions were enrolled in this study. They were categorized into a primary cohort, an internal validation, and two external validation cohorts. Radiomics features were extracted from conventional US images. LASSO regression was used to select optimized features to construct the radiomics signature. Two nomograms integrating independent clinical variables and radiomics signature were established with multivariate logistic regression. The performance of the nomograms was assessed with regard to discrimination, calibration, and clinical usefulness. Results The radiomics scores were significantly higher in patients with central/lateral LNM. A radiomics nomogram indicated good discrimination for central compartment LNM, with an area under the curve (AUC) of 0.875 in the training set, the corresponding value in the validation sets were 0.856, 0.870 and 0.870, respectively. Another nomogram for predicting lateral LNM also demonstrated good performance with an AUC of 0.938 and 0.905 in the training and internal validation cohorts, respectively. The AUC for the two external validation cohorts were 0.881 and 0.903, respectively. The clinical utility of the nomograms was confirmed by the decision curve analysis. Conclusion The nomograms proposed here have favorable performance for preoperatively predicting cervical LNM, hold promise for optimizing the personalized treatment, and might greatly facilitate the decision-making in clinical practice. Supplementary Information The online version contains supplementary material available at 10.1186/s12880-022-00809-2.
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Affiliation(s)
- Yuyang Tong
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dong'an Road, Shanghai, 200032, China
| | - Jingwen Zhang
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Yi Wei
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dong'an Road, Shanghai, 200032, China
| | - Jinhua Yu
- Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, 200433, China
| | - Weiwei Zhan
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Hansheng Xia
- Department of Ultrasound, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
| | - Shichong Zhou
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dong'an Road, Shanghai, 200032, China.
| | - Yuanyuan Wang
- Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, 200433, China
| | - Cai Chang
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dong'an Road, Shanghai, 200032, China
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14
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Zhang K, Qian L, Chen J, Zhu Q, Chang C. Preoperative Prediction of Central Cervical Lymph Node Metastasis in Fine-Needle Aspiration Reporting Suspicious Papillary Thyroid Cancer or Papillary Thyroid Cancer Without Lateral Neck Metastasis. Front Oncol 2022; 12:712723. [PMID: 35402238 PMCID: PMC8983925 DOI: 10.3389/fonc.2022.712723] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 02/28/2022] [Indexed: 12/30/2022] Open
Abstract
Purpose No non-invasive method can accurately determine the presence of central cervical lymph node (CCLN) metastasis in papillary thyroid cancer (PTC) until now. This study aimed to investigate factors significantly associated with CCLN metastasis and then develop a model to preoperatively predict CCLN metastasis in fine-needle aspiration (FNA) reporting suspicious papillary thyroid cancer (PTC) or PTC without lateral neck metastasis. Patients and Methods Consecutive inpatients who were diagnosed as suspicious PTC or PTC in FNA and underwent partial or total thyroidectomy and CCLN dissection between May 1st, 2016 and June 30th, 2018 were included. The total eligible patients were randomly divided into a training set and an internal validation set with the ratio of 7:3. Univariate analysis and multivariate analysis were conducted in the training set to investigate factors associated with CCLN metastasis. The predicting model was built with factors significantly correlated with CCLN metastasis and validated in the validation set. Results A total of 770 patients were eligible in this study. Among them, 268 patients had histologically confirmed CCLN metastasis, while the remaining patients did not. Factors including age, BRAF mutation, multifocality, size, and capsule involvement were found to be significantly correlated with the CCLN metastasis in univariate and multivariate analysis. A model used to predict the presence CCLN metastasis based on these factors and US CCLN status yielded AUC, sensitivity, specificity and accuracy of 0.933 (95%CI: 0.905-0.960, p < 0.001), 0.816, 0.966 and 0.914 in the training set and 0.967 (95%CI: 0.943-0.991, p < 0.001), 0.897, 0.959 and 0.936 in the internal validation set. Conclusion Age, BRAF mutation, multifocality, size, and capsule involvement were independent predictors of CCLN metastasis in FNA reporting suspicious PTC or PTC without lateral neck metastasis. A simple model was successfully built and showed excellent discrimination to distinguish patients with or without CCLN metastasis.
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Affiliation(s)
- Kai Zhang
- Department of Medical Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
- *Correspondence: Kai Zhang,
| | - Lang Qian
- Department of Medical Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Jieying Chen
- Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Qian Zhu
- Department of Medical Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Cai Chang
- Department of Medical Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
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15
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Tang J, Jiang S, Ma J, Xi X, Li H, Wang L, Zhang B. Nomogram based on radiomics analysis of ultrasound images can improve preoperative BRAF mutation diagnosis for papillary thyroid microcarcinoma. Front Endocrinol (Lausanne) 2022; 13:915135. [PMID: 36060960 PMCID: PMC9437521 DOI: 10.3389/fendo.2022.915135] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The preoperative identification of BRAF mutation could assist to make appropriate treatment strategies for patients with papillary thyroid microcarcinoma (PTMC). This study aimed to establish an ultrasound (US) radiomics nomogram for the assessment of BRAF status. METHODS A total of 328 PTMC patients at the China-Japan Friendship Hospital between February 2019 and November 2021 were enrolled in this study. They were randomly divided into training (n = 232) and validation (n = 96) cohorts. Radiomics features were extracted from the US images. The least absolute shrinkage and selection operator (LASSO) regression was applied to select the BRAF status-related features and calculate the radiomics score (Rad-score). Univariate and multivariate logistic regression analyses were subsequently performed to identify the independent factors among Rad-score and conventional US features. The US radiomics nomogram was established and its predictive performance was evaluated via discrimination, calibration, and clinical usefulness in the training and validation sets. RESULTS Multivariate analysis indicated that the Rad-score, composition, and aspect ratio were independent predictive factors of BRAF status. The US radiomics nomogram which incorporated the three variables showed good calibration. The discrimination of the US radiomics nomogram showed better discriminative ability than the conventional US model both in the training set (AUC 0.685 vs. 0.592) and validation set (AUC 0.651 vs. 0.622). Decision curve analysis indicated the superior clinical applicability of the nomogram compared to the conventional US model. CONCLUSIONS The US radiomics nomogram displayed better performance than the conventional US model in predicting BRAF mutation in patients with PTMC.
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Affiliation(s)
- Jiajia Tang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Ultrasound, China-Japan Friendship Hospital, Beijing, China
| | - Shitao Jiang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiaojiao Ma
- Department of Ultrasound, China-Japan Friendship Hospital, Beijing, China
| | - Xuehua Xi
- Department of Ultrasound, China-Japan Friendship Hospital, Beijing, China
| | - Huilin Li
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Ultrasound, China-Japan Friendship Hospital, Beijing, China
| | - Liangkai Wang
- Department of Ultrasound, China-Japan Friendship Hospital, Beijing, China
- Institute of Clinical Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Bo Zhang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Ultrasound, China-Japan Friendship Hospital, National Center for Respiratory Medicine, National Clinical Research Centerfor Respiratory Diseases, Institute of Respiratory Medicine of Chinese Academy of Medical Sciences, Beijing, China
- *Correspondence: Bo Zhang,
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16
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Li Y, Gao W, Cai X, Jin A, Shen J, Zhang Y, Chen Y, Hu B, Zeng T, Yu X, Zheng Y, Wang Y. Exploring Somatic Alteration Associating With Aggressive Behaviors of Papillary Thyroid Carcinomas by Targeted Sequencing. Front Oncol 2021; 11:722814. [PMID: 34692499 PMCID: PMC8529196 DOI: 10.3389/fonc.2021.722814] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 09/16/2021] [Indexed: 12/21/2022] Open
Abstract
Wisely differentiating high-risk papillary thyroid carcinoma (PTC) patients from low-risk PTC patients preoperatively is necessary when comes to making a personalized treatment plan. It is not easy to stratify the risk of patients according to sonography or lab results before surgery. This study aims to seek out potential mutation gene markers that may be helpful in stratifying the risk of PTC. A custom panel of 439 PTC relevant and classic tumor metabolic pathway relevant genes was designed. Targeted capture sequencing was performed on 35 pairs of samples from 35 PTC tumors and 35 para-tumor thyroid tissues obtained during surgery. Variant calling and detection of cancer gene mutations were identified by bio-information analysis. Ingenuity Pathway Analysis (IPA) was performed to do functional enrichment analysis of high-frequency mutant genes. Immunohistochemistry (IHC) was performed on 6 PTC patients to explore the expression of protein associated with interested genes. Event-free survival (EFS) was calculated to determine which genes might affect the prognosis of patients. We have identified 32 high-frequency mutant genes in PTC including BRAF. RBL2 was found to be significantly correlated to event-free survival, FOXO1, MUC6, PCDHB9, NOTCH1, FIZ1, and RTN1 were significantly associated with EFS, while BRAF mutant was not correlated to any of the prognosis indicators. Our findings in this study might open more choices when designing thyroid gene panels used in FNA samples to diagnose PTC and predict the potentially aggressive behavior of PTC.
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Affiliation(s)
- Yi Li
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Wei Gao
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Xiaojun Cai
- Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Anqi Jin
- Department of Ultrasound Medicine, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Jian Shen
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Yichun Zhang
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Yutong Chen
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China
| | - Bing Hu
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China.,Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Tao Zeng
- CAS Key Laboratory of Computational Biology, Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China
| | - Xiangtian Yu
- Clinical Research Center, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yuanyi Zheng
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China.,Shanghai Institute of Ultrasound in Medicine, Shanghai, China
| | - Yan Wang
- Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Shanghai Sixth People's Hospital, Shanghai, China.,Shanghai Institute of Ultrasound in Medicine, Shanghai, China
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17
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Qin H, Que Q, Lin P, Li X, Wang XR, He Y, Chen JQ, Yang H. Magnetic resonance imaging (MRI) radiomics of papillary thyroid cancer (PTC): a comparison of predictive performance of multiple classifiers modeling to identify cervical lymph node metastases before surgery. Radiol Med 2021; 126:1312-1327. [PMID: 34236572 DOI: 10.1007/s11547-021-01393-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 06/25/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To compare predictive efficiency of multiple classifiers modeling and establish a combined magnetic resonance imaging (MRI) radiomics model for identifying lymph node (LN) metastases of papillary thyroid cancer (PTC) preoperatively. MATERIALS AND METHODS A retrospective analysis based on the preoperative MRI scans of 109 PTC patients including 77 patients with LN metastases and 32 patients without metastases was conducted, and we divided enroll cases into trained group and validation group. Radiomics signatures were selected from fat-suppressed T2-weighted MRI images, and the optimal characteristics were confirmed by spearman correlation test, hypothesis testing and random forest methods, and then, eight predictive models were constructed by eight classifiers. The receiver operating characteristic (ROC) curves analysis were performed to demonstrate the effectiveness of the models. RESULTS The area under the curve (AUC) of ROC based on MRI texture diagnosed LN status by naked eye was 0.739 (sensitivity = 0.571, specificity = 0.906). Based on the 5 optimal signatures, the best AUC of MRI radiomics model by logistics regression classifier had a considerable prediction performance with AUCs 0.805 in trained group and 0.760 in validation group, respectively, and a combination of best radiomics model with visual diagnosis of MRI texture had a high AUC as 0.969 (sensitivity = 0.938, specificity = 1.000), suggesting combined model had a preferable diagnostic efficiency in evaluating LN metastases of PTC. CONCLUSION Our combined radiomics model with visual diagnosis could be a potentially effective strategy to preoperatively predict LN metastases in PTC patients before clinical intervention.
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Affiliation(s)
- Hui Qin
- Department of Medical Ultrasonics, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China
| | - Qiao Que
- Department of Medical Ultrasonics, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China
| | - Peng Lin
- Department of Medical Ultrasonics, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China
| | - Xin Li
- Department of GE Healthcare Global Research, GE Healthcare, Shanghai, 201203, People's Republic of China
| | - Xin-Rong Wang
- Department of GE Healthcare Global Research, GE Healthcare, Shanghai, 201203, People's Republic of China
| | - Yun He
- Department of Medical Ultrasonics, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China
| | - Jun-Qiang Chen
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China.
| | - Hong Yang
- Department of Medical Ultrasonics, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China.
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18
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Tong Y, Sun P, Yong J, Zhang H, Huang Y, Guo Y, Yu J, Zhou S, Wang Y, Wang Y, Ji Q, Wang Y, Chang C. Radiogenomic Analysis of Papillary Thyroid Carcinoma for Prediction of Cervical Lymph Node Metastasis: A Preliminary Study. Front Oncol 2021; 11:682998. [PMID: 34268116 PMCID: PMC8276635 DOI: 10.3389/fonc.2021.682998] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/09/2021] [Indexed: 12/19/2022] Open
Abstract
Background Papillary thyroid carcinoma (PTC) is characterized by frequent metastases to cervical lymph nodes (CLNs), and the presence of lymph node metastasis at diagnosis has a significant impact on the surgical approach. Therefore, we established a radiomic signature to predict the CLN status of PTC patients using preoperative thyroid ultrasound, and investigated the association between the radiomic features and underlying molecular characteristics of PTC tumors. Methods In total, 270 patients were enrolled in this prospective study, and radiomic features were extracted according to multiple guidelines. A radiomic signature was built with selected features in the training cohort and validated in the validation cohort. The total protein extracted from tumor samples was analyzed with LC/MS and iTRAQ technology. Gene modules acquired by clustering were chosen for their diagnostic significance. A radiogenomic map linking radiomic features to gene modules was constructed with the Spearman correlation matrix. Genes in modules related to metastasis were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a protein-protein interaction (PPI) network was built to identify the hub genes in the modules. Finally, the screened hub genes were validated by immunohistochemistry analysis. Results The radiomic signature showed good performance for predicting CLN status in training and validation cohorts, with area under curve of 0.873 and 0.831 respectively. A radiogenomic map was created with nine significant correlations between radiomic features and gene modules, and two of them had higher correlation coefficient. Among these, MEmeganta representing the upregulation of telomere maintenance via telomerase and cell-cell adhesion was correlated with ‘Rectlike’ and ‘deviation ratio of tumor tissue and normal thyroid gland’ which reflect the margin and the internal echogenicity of the tumor, respectively. MEblue capturing cell-cell adhesion and glycolysis was associated with feature ‘minimum calcification area’ which measures the punctate calcification. The hub genes of the two modules were identified by protein-protein interaction network. Immunohistochemistry validated that LAMC1 and THBS1 were differently expressed in metastatic and non-metastatic tissues (p=0.003; p=0.002). And LAMC1 was associated with feature ‘Rectlike’ and ‘deviation ratio of tumor and normal thyroid gland’ (p<0.001; p<0.001); THBS1 was correlated with ‘minimum calcification area’ (p<0.001). Conclusions The radiomic signature proposed here has the potential to noninvasively predict the CLN status in PTC patients. Merging imaging phenotypes with genomic data could allow noninvasive identification of the molecular properties of PTC tumors, which might support clinical decision making and personalized management.
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Affiliation(s)
- Yuyang Tong
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Surgical Oncology, The Ohio State University, Columbus, OH, United States
| | - Peixuan Sun
- Diagnostic Imaging Center, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Juanjuan Yong
- Department of Pathology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hongbo Zhang
- Pharmaceutical Sciences Laboratory, Åbo Akademi University, Turku, Finland.,Turku Biosciences Center, University of Turku and Åbo Akademi University, Turku, Finland
| | - Yunxia Huang
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi Guo
- Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, China
| | - Jinhua Yu
- Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, China
| | - Shichong Zhou
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yulong Wang
- Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yu Wang
- Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Qinghai Ji
- Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yuanyuan Wang
- Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, China
| | - Cai Chang
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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王 雍, 文 艺, 林 师, 文 丹, 谢 建. [Research progress on the relationship between the Raf murine sarcoma viral oncogene homolog B gene mutation and lymph node metastasis of papillary thyroid carcinoma]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2021; 38:191-195. [PMID: 33899445 PMCID: PMC10307564 DOI: 10.7507/1001-5515.202006040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 12/04/2020] [Indexed: 11/03/2022]
Abstract
In recent years, with the improvement of the sensitivity of examination equipment and the change of people's living environment and diet, the rate of thyroid cancer has risen rapidly, which has increased nearly five folds in 10 years. The pathogenesis, clinical manifestation, biological behavior, treatment and prognosis of thyroid carcinoma of different pathological types are obviously different. Papillary thyroid carcinoma (PTC) can develop at any age, which accounts for about 90% of thyroid cancer. It progresses slowly and has favourable prognosis, but lymph node metastasis appears easily. Whether PTC is accompanied by lymph node metastasis has an important impact on its prognosis and outcome. The Raf murine sarcoma viral oncogene homolog B(BRAF)gene mutation plays a crucial role in PTC lymph node metastasis. Having an in-depth understanding of the specific role and mechanism of BRAF gene mutation in PTC is expected to provide new ideas for diagnosis and treatment of PTC.
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Affiliation(s)
- 雍 王
- />川北医学院附属医院 核医学科(南充 637000)Department of Nuclear Medicine, the Affiliated Hospital of North Sichuan Medical College, Nanchong, P.R.China
| | - 艺 文
- />川北医学院附属医院 核医学科(南充 637000)Department of Nuclear Medicine, the Affiliated Hospital of North Sichuan Medical College, Nanchong, P.R.China
| | - 师宇 林
- />川北医学院附属医院 核医学科(南充 637000)Department of Nuclear Medicine, the Affiliated Hospital of North Sichuan Medical College, Nanchong, P.R.China
| | - 丹 文
- />川北医学院附属医院 核医学科(南充 637000)Department of Nuclear Medicine, the Affiliated Hospital of North Sichuan Medical College, Nanchong, P.R.China
| | - 建平 谢
- />川北医学院附属医院 核医学科(南充 637000)Department of Nuclear Medicine, the Affiliated Hospital of North Sichuan Medical College, Nanchong, P.R.China
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Gao X, Luo W, He L, Cheng J, Yang L. Predictors and a Prediction Model for Central Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma (cN0). Front Endocrinol (Lausanne) 2021; 12:789310. [PMID: 35154002 PMCID: PMC8828537 DOI: 10.3389/fendo.2021.789310] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 12/27/2021] [Indexed: 12/07/2022] Open
Abstract
OBJECTIVES To screen out the predictors of central cervical lymph node metastasis (CLNM) for papillary thyroid carcinoma (PTC) and establish a prediction model to guide the operation of PTC patients (cN0). METHODS Data from 296 PTC patients (cN0) who underwent thyroid operation at the Second Affiliated Hospital of Chongqing Medical University were collected and retrospectively analyzed. They were divided into two groups in accordance with central CLNM or not. Their information, including ultrasound (US) features, BRAFV600E status, and other characteristics of the two groups, was analyzed and compared using univariate and multivariate logistic regression analyses, and the independent predictors were selected to construct a nomogram. The calibration plot, C-index, and decision curve analysis were used to assess the prediction model's calibration, discrimination, and clinical usefulness. RESULTS A total of 37.8% (112/296) of PTC patients had central CLNM, and 62.2% (184/296) did not. The two groups were compared using a univariate logistic regression analysis, and there were no significant differences between the two groups in sex, aspect ratio, boundary, morphology, hypoechoic nodule, thyroid peroxidase antibody, or tumor location (P>0.05), and there were significant differences between age, tumor size, capsule contact, microcalcifications, blood flow signal, thyroglobulin antibodies (TgAb), and BRAF gene status (P<0.05). A multivariate logistic regression analysis was performed to further clarify the correlation of these indices. However, only tumor size (OR=2.814, 95% Cl=1.634~4.848, P<0.001), microcalcifications (OR=2.839, 95% Cl=1,684~4.787, P<0.001) and TgAb (OR=1.964, 95% Cl=1.039~3,711, P=0.038) were independent predictors of central CLNM and were incorporated and used to construct the prediction nomogram. The model had good discrimination with a C-index of 0.715. An ROC curve analysis was performed to evaluate the accuracy of this model. The decision curve analysis showed that the model was clinically useful when intervention was decided in the threshold range of 16% to 80%. CONCLUSION In conclusion, three independent predictors of central CLNM, including tumor size (> 1.0 cm), US features (microcalcifications), and TgAb (positive), were screened out. A visualized nomogram model was established based on the three predictors in this study, which could be used as a basis of central cervical lymph node dissection (CLND) for PTC patients (cN0).
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Affiliation(s)
- Xin Gao
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wenpei Luo
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lingyun He
- Department of Ultrasound, Second Affiliated Hospital of Chongqing Medical University and Chongqing Key Laboratory of Ultrasound Molecular Imaging, Chongqing, China
- Scientific Research and Education Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Juan Cheng
- Department of Ultrasound, Second Affiliated Hospital of Chongqing Medical University and Chongqing Key Laboratory of Ultrasound Molecular Imaging, Chongqing, China
| | - Lu Yang
- Department of Breast and Thyroid Surgery, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Lu Yang,
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Huang K, Gao N, Bian D, Zhai Q, Yang P, Zhang Y. Associations of BRAF V600E, clinical pathology and imaging factors with the recurrence rate of papillary thyroid microcarcinoma. Exp Ther Med 2020; 20:243. [PMID: 33178341 DOI: 10.3892/etm.2020.9373] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 05/13/2020] [Indexed: 01/17/2023] Open
Abstract
In the present study, the recurrence rate of papillary thyroid microcarcinoma (PTMC) was assessed by analyzing postoperative follow-up data of affected patients and its associations with BRAF V600E, clinical pathology and imaging factors were explored. A total of 506 patients with PTMC were selected who underwent surgery from January 2014 to March 2016. The maximal diameter of thyroid nodules was ≤1 cm and all patients who underwent BRAF V600E testing and evaluation for lymph node metastasis. Postoperatively, each patient was regularly followed up to detect recurrence. Categorical variables were comparatively analyzed using univariate Cox linear regression analysis to screen for protective and adverse factors influencing recurrence of PTMC. A stepwise Cox proportional hazards regression model analysis was performed to explore risk factors affecting recurrence. Among the 506 patients, 477 were followed up, 29 were lost to follow-up and 26 patients experienced recurrence. The 5-year recurrent rate of PTMC was 5.45%. The univariate Cox regression analysis indicated that PTMC recurrence was influenced by BRAF V600E, sex, multifocality, capsular invasion and lateral cervical lymph node metastasis (P<0.05), but not by age, tumor location on the thyroid, size, single central lymph node metastasis, distant metastasis and operative approach (P>0.05). The significant factors associated with recurrent PTMC were subjected to stepwise multivariate Cox proportional hazards regression model analysis and the results indicated that BRAF V600E, sex, multifocality and lateral cervical lymph node metastasis were independent factors influencing recurrence in patients with PTMC, with a statistically significant difference (P<0.05). In conclusion, BRAF V600E, sex, multifocality and lateral cervical lymph node metastasis are independent risk factors for recurrent PTMC.
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Affiliation(s)
- Kun Huang
- Department of Ultrasonic Diagnosis, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China
| | - Ningning Gao
- Department of Ultrasonic Diagnosis, Liaoning Province Cancer Hospital and Institute, Shenyang, Liaoning 110042, P.R. China
| | - Donglin Bian
- Department of Ultrasonic Diagnosis, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China
| | - Qixi Zhai
- Department of Ultrasonic Diagnosis, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China
| | - Puxu Yang
- Department of Ultrasonic Diagnosis, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China
| | - Yunfei Zhang
- Department of Ultrasonic Diagnosis, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China
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22
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Cao S, Yu S, Yin Y, Su L, Hong S, Gong Y, Lv W, Li Y, Xiao H. Genetic alterations in cfDNA of benign and malignant thyroid nodules based on amplicon-based next-generation sequencing. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:1225. [PMID: 33178757 PMCID: PMC7607131 DOI: 10.21037/atm-20-4544] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background Circulating cell-free DNA (cfDNA) serves as a biomarker in multiple malignant diseases. However, controversy still surrounds the role of cfDNA detection in the diagnosis and monitoring of papillary thyroid carcinoma (PTC). This study set out to identify the role of cfDNA detection in distinguishing between benign and malignant thyroid nodules. Methods Tissue, blood cell, and plasma samples were collected from 10 patients with benign nodules and 10 patients with malignant nodules. The DNA isolated from these samples was subject to PCR-based amplification using primers designed for 50 proto-oncogenes and tumor suppressor genes. PCR products were sequenced using Illumina technology, and the mutations were detected with varScan among sequencing data for each sample and comparative analysis was carried out. Results Through amplicon sequencing, we found one non-synonymous somatic mutation in the benign nodules and three in the malignant nodules. Among these four mutations, BRAFV600E mutation was detected in the tissue samples of 8 out of the 10 PTC patients, but it was not detected in the benign nodules. However, no BRAFV600E mutation was detected in cfDNA. Further differential analysis of cfDNA indicated that some genes had more mutations in benign patients than in malignant patients, such as MET and IDH, and some genes had more mutations in malignant patients, such as PIK3CA and EZH2. Conclusions We found that BRAFV600E mutation was a credible disease-related mutation in PTC; however, it could not be detected in cfDNA. Moreover, there was a large difference in mutation gene distribution between benign and malignant thyroid nodules.
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Affiliation(s)
- Siting Cao
- Department of Endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shuang Yu
- Department of Endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yali Yin
- Department of Endocrinology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Lei Su
- Department of Gerontology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shubin Hong
- Department of Endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yingying Gong
- Department of Gerontology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Weiming Lv
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yanbing Li
- Department of Endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Haipeng Xiao
- Department of Endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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Antibacterial, anti-efflux, anti-biofilm, anti-slime (exopolysaccharide) production and urease inhibitory efficacies of novel synthesized gold nanoparticles coated Anthemis atropatana extract against multidrug- resistant Klebsiella pneumoniae strains. Arch Microbiol 2020; 202:2105-2115. [PMID: 32500253 DOI: 10.1007/s00203-020-01930-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 05/24/2020] [Accepted: 05/27/2020] [Indexed: 12/26/2022]
Abstract
In this study, the antibacterial, anti-efflux, anti-biofilm, anti-slime (exopolysaccharide) production and urease inhibitory efficacies of green synthesized gold nanoparticles (AuNPs) coated Anthemis atropatana extract against multidrug- resistant (MDR) Klebsiella pneumoniae strains were evaluated. The green synthesized AuNPs were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffractometer (XRD), particle size distribution, zeta potential and Fourier-transform infrared spectroscopy (FTIR). Then, antibacterial, anti-slime (exopolysaccharide) production, anti-biofilm and anti-efflux activities of AuNPs were investigated using micro-dilation, Congored agar, microtiter plate and MIC of ethidium bromide methods, respectively. Subsequently, the expression of mrkA, wzm and acrB genes was evaluated using quantitative Real-Time PCR (qRT-PCR). The synthesized AuNPs exhibited antibacterial activity against MDR strains of K. pneumoniae (minimum inhibitory concentration (MIC) of 6.25-50 µg/ml), as well as showed significant anti-slime (exopolysaccharide) production, anti-biofilm and anti-efflux activities against MDR strains. AuNPs showed significant inhibition against jack-bean urease and down-regulated the expression of mrkA, wzm and acrB genes. Moreover, the in vitro cytotoxic activity confirmed by MTT assay on the HEK-293 normal cell line showed negligible cytotoxicity. Thus, the present study suggests the potential use of AuNPs in the development of novel therapeutics for the prevention of biofilm-associated K. pneumoniae infections.
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Li M, Jia H, Qian Q, Wen P, Chen C, Hua Y, Wang K, Zhang W, Shi F. Genomic characterization of high-recurrence risk papillary thyroid carcinoma in a southern Chinese population. Diagn Pathol 2020; 15:49. [PMID: 32393293 PMCID: PMC7212670 DOI: 10.1186/s13000-020-00962-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 04/28/2020] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND The objective of this study was to investigate genetic variations and the relationships between these genetic variations and clinicopathological features of high-recurrence risk papillary thyroid carcinoma in a southern Chinese population. METHODS One hundred sixty-eight patients of high-recurrence risk papillary thyroid carcinoma were recruited for this study from 2017 to 2018. Formalin-fixed paraffin-embedded tissue and the data of clinicopathological characteristics were all collected and analyzed from these patients. We used next-generation sequencing technology to investigate the targeted gene mutations and gene fusions of the pathology specimens. RESULTS The frequency of candidate tumor driver gene mutation was 85.1% in 143 patients, including BRAF V600E mutation in 119 patients(70.8%), RET fusion in 13 patients(7.7%), TERT promoter mutations in 11 patients(6.5%), RAS (HRAS, NRAS, KRAS) gene mutations in 10 patients(6.0%), and other mutations involving TP53, PIK3CA, AKT1, PTEN and NTRK1. Concomitant presence of more than two genetic aberrations was seen in 27 patients (16.1%). Our study showed that BRAF V600E mutation is highly correlated with conventional PTC (p < 0.001), BRAF V600E and TERT promoter mutation duet was associated with older patient age (> 45, p = 0.003) and higher disease stage of III or IV (p = 0.002). RAS gene and BRAF V600E co-mutations were only seen in multifocal PTC (p = 0.015). CONCLUSION In our high-recurrence risk PTC cohort, most patients had more than one driver gene aberration. Coexistence of BRAF V600E with TERT promoter mutations or with RAS mutations were significantly correlated with worse clinicopathological characteristics.
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Affiliation(s)
- Min Li
- Department of Nuclear Medicine, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, and Hunan Cancer Hospital, Changsha, 410013, China
| | - Haitao Jia
- Shenzhen Cheerland Biotechnology Co., Ltd, Shenzhen, 518055, China
| | - Qiuqin Qian
- Department of Nuclear Medicine, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, and Hunan Cancer Hospital, Changsha, 410013, China
| | - Peng Wen
- Department of Nuclear Medicine, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, and Hunan Cancer Hospital, Changsha, 410013, China
| | - Chuan Chen
- Shenzhen Cheerland Biotechnology Co., Ltd, Shenzhen, 518055, China
| | - Yaqiong Hua
- Shenzhen Cheerland Biotechnology Co., Ltd, Shenzhen, 518055, China
| | - Kai Wang
- Shenzhen Cheerland Biotechnology Co., Ltd, Shenzhen, 518055, China
| | - Wenyong Zhang
- School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Feng Shi
- Department of Nuclear Medicine, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, and Hunan Cancer Hospital, Changsha, 410013, China.
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Guo JN, Song LH, Yu PY, Yu SY, Deng SH, Mao XH, Xiu C, Sun J. Ultrasound Elastic Parameters Predict Central Lymph Node Metastasis of Papillary Thyroid Carcinoma. J Surg Res 2020; 253:69-78. [PMID: 32335393 DOI: 10.1016/j.jss.2020.03.042] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 02/10/2020] [Accepted: 03/08/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND This study aimed to explore the new factors that can predict central lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) independently from ultrasound characteristics, elastic parameters, and endocrine indicators. METHODS A total of 391 patients with PTC undergoing thyroidectomy and prophylactic central lymph node dissection from January 2017 to June 2019 were collected to determine the independent predictors of CLNM by single-factor and multivariate logistic regression analysis. RESULTS Multivariate logistic regression analysis showed 9 independent predictors of CLNM, age, male, tumors in the middle or lower poles (without tumors in the isthmus), tumors in the isthmus, multiple tumors, and maximum tumor diameter measured by ultrasound, microcalcification, visible surrounding blood flow signal, and the maximum value of elastic modulus (Emax).We used the aforementioned factors to establish a scoring prediction model: predictive score Y(P) = 1/[1 + exp (1.444 + 0.084 ∗ age - 0.834 ∗ men - 0.73 ∗ multifocality - 2.718 ∗ tumors in the isthmus - 0.954 ∗ tumors in the middle or lower poles - 0.086 ∗ tumor maximum diameter - 1.070 ∗ microcalcification - 0.892 ∗ visible surrounding blood flow signal - 0.021 ∗ Emax)]. The area under the curve of the receiver operating characteristic was 0.827. It was found that 0.524 was the highest index of Youden, and the best cutoff value for predicting CLNM. When Y(P)≥0.524, the risk of CLNM in patients with PTC is predicted to be high. Predictive accuracy was 78.5% and 72.4% in the internal validation group and 78.6% in the external validation group. CONCLUSIONS These data indicate that the scoring prediction model could provide a scientific and quantitative way to predict CLNM in patients with PTC.
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Affiliation(s)
- Jun-Nan Guo
- The First Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Lian-Hao Song
- Department of Microbiology, Harbin Medical University, Harbin, China
| | - Ping-Yang Yu
- The First Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Si-Yang Yu
- Department of Microbiology, Harbin Medical University, Harbin, China
| | - Shen-Hui Deng
- Anesthesiology Department, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xiong-Hui Mao
- The First Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Cheng Xiu
- The First Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ji Sun
- The First Department of Head and Neck Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
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Kun HMD, Ji-Bin LMD. Application of Ultrasonography in the Diagnosis and Management of Papillary Thyroid Microcarcinoma. ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY 2020. [DOI: 10.37015/audt.2020.200001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
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Associations of the BRAF V600E Mutation and PAQR3 Protein Expression with Papillary Thyroid Carcinoma Clinicopathological Features. Pathol Oncol Res 2019; 26:1833-1841. [PMID: 31758408 DOI: 10.1007/s12253-019-00779-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 11/12/2019] [Indexed: 10/25/2022]
Abstract
The BRAFV600E mutation is the most prevalent genetic event in patients with papillary thyroid cancer (PTC). However, no study has investigated the expression of PAQR3 in papillary thyroid tissues in relation to the BRAFV600E mutation and the clinicopathological features of PTC patients. Furthermore, the potential associations of the BRAFV600E mutation, PAQR3 expression and clinicopathological parameters in the cancerous tissues of PTC patients have not been investigated. This study was conducted on 60 patients with PTC who were treated surgically at our institution from 2017 to 2018. PCR was used to amplify DNA by the amplification refractory mutation system (ARMS) method to detect BRAFV600E gene mutations. In addition, immunohistochemical techniques were utilized to assess PAQR3 expression in tumor tissue sections. The BRAFV600E mutation was associated with lymph node metastasis (LNM, p < 0.05) but not with other clinicopathological features. Low PAQR3 expression was associated with extrathyroidal extension and LNM (χ2 = 7.143, p = 0.009; χ2 = 6.459, p = 0.014, respectively). Furthermore, a statistically significant association was observed between chronic lymphocytic thyroiditis and LNM (χ2 = 5.275, p = 0.0250). A linear relationship between the BRAFV600E mutation and PAQR3 protein expression has not been identified. These factors may be independent risk factors of extrathyroidal extension and LNM in PTC and be used to indicate the invasiveness of PTC tumors. Higher quality, multivariate analyses based on larger samples from around the world are urgently needed to further validate and revise our findings in the future.
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Li XJ, Mao XD, Chen GF, Wang QF, Chu XQ, Hu X, Ding WB, Zeng Z, Wang JH, Xu SH, Liu C. High BRAFV600E mutation frequency in Chinese patients with papillary thyroid carcinoma increases diagnostic efficacy in cytologically indeterminate thyroid nodules. Medicine (Baltimore) 2019; 98:e16343. [PMID: 31305422 PMCID: PMC6641833 DOI: 10.1097/md.0000000000016343] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
To estimate the BRAFV600E mutation frequency in Chinese patients with papillary thyroid carcinoma (PTC), and the diagnostic value of BRAFV600E mutation status in thyroid nodules with indeterminate TBSRTC categories.A total of 4875 consecutive samples for thyroid ultrasound-guided fine-needle aspiration cytology (FNAC) and BRAF mutation analysis were collected from patients at Jiangsu Province Hospital on Integration of Chinese and Western Medicine. Among all the cases, 314 underwent thyroidectomy. According to TBSRTC categories, FNAC was performed for a preoperative diagnosis. ROC of the subject was constructed to evaluate the diagnostic value of these 2 methods and their combination.BRAF mutation in FNAC of thyroid nodules occurred in 2796 samples (57.35%). Of 353 nodule samples from 314 patients with thyroid operation, 333 were pathologically diagnosed as PTC. Of these PTC patients, 292 (87.69%) were found to have BRAF mutation in their preoperative FNAC. In 175 cytologically indeterminate thyroid nodules, BRAF mutation identified 88% of PTC. According to ROC data, BRAF mutation testing had an obviously higher sensitivity (87.69%) and specificity (100.00%) than TBSRTC. Combining BRAF mutation testing and TBSRTC achieved the largest AUC (0.954). For 41 PTC with a negative BRAF mutation in preoperative evaluation, the repeated BRAF mutation testing found out 12 samples with BRAF mutation. The true BRAF mutation rate of Chinese PTC patients was 91.29%.Chinese patients with PTC have a higher frequency of BRAF mutation. The BRAF mutation testing affords a high diagnostic value in thyroid nodules with indeterminate cytology.
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Affiliation(s)
- Xing-Jia Li
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
| | - Xiao-dong Mao
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
| | - Guo-fang Chen
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
| | - Qi-feng Wang
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
| | - Xiao-qiu Chu
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
| | - Xin Hu
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
| | | | | | - Jian-hua Wang
- Department of General Surgery, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine (Jiangsu Province Academy of Traditional Chinese Medicine), Nanjing, Jiangsu, China
| | - Shu-hang Xu
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
| | - Chao Liu
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine
- Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine
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