Conventional Ultrasound, Immunohistochemical Factors and BRAFV600E Mutation in Predicting Central Cervical Lymph Node Metastasis of Papillary Thyroid Carcinoma

The diagnosis and management of small and indeterminate lymph nodes in papillary thyroid cancer: preoperatively and intraoperatively

Although thyroid cancer is an indolent tumor with a favorable prognosis, lymph node metastasis (LNM) serves as a major concern for many patients. Because LNM is strongly correlated with recurrence, distant metastasis, and shortened survival, a precise and timely diagnosis and following appropriate management for LNM are necessary. However, significant challenges still exist in the diagnosis of small LNs (<1 cm in diameter), and their low volume makes it difficult to determine whether they are metastatic or benign. Therefore, the diagnostic technique for these small and indeterminate LNs (siLNs) has been one of the leading research subjects in recent years. The implementation of innovative technologies, such as contrast-enhanced ultrasonography, frozen section, and molecular detection, has brought great progress to the diagnosis of siLNs. Meanwhile, the strategies for managing siLNs in clinical practice have evolved considerably over the past several years, with several appropriate options recommended by guidelines. In this review, we aim to provide a systematic overview of the latest studies and potential evidence about effective approaches for detecting and evaluating siLNs. Furthermore, the following management modalities of siLNs in different situations are well discussed.

Identification of Potential Biomarkers in Papillary Thyroid Carcinoma Based on Proteomics

Background

To identify biomarkers of papillary thyroid carcinoma (PTC) and explore the possible pathogenic mechanism.

Methods

This study included five patients with PTC. Protein expression of cancer tissues and adjacent normal thyroid tissues from each patient were analyzed by TMT proteomics technology. Differentially expressed proteins were identified, and functional annotation of differentially expressed proteins was performed by bioinformatics and pathway enrichment analysis.

Results

A total of 639 differentially expressed proteins were identified, including 278 upregulated and 361 downregulated proteins. Six upregulated proteins were identified as potential specific markers of PTC.

Conclusion

Differentially expressed proteins may represent new molecular markers of PTC. These differentially expressed proteins and the related pathways may provide new insights into the pathogenic mechanisms of PTC.

Risk factors of cervical central lymph node metastasis in stage T1a unifocal papillary thyroid carcinoma

To investigate the correlation of cervical central lymph node metastasis (CLNM) in stage T1a unifocal papillary thyroid carcinoma (PTC) with the clinicopathological characteristics, ultrasonography features and the number of lymph node dissection, and to analyze the risk factors of CLNM. Data from 493 unifocal PTC patients (T1a) 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, and other characteristics of the groups, was analyzed and compared using univariate and multivariate logistic regression analyses. A total of 493 patients were eligible in this study. Among them, 33.7% (166/493) of PTC patients had cervical CLNM, and 66.3% (327/493) did not. The two groups were compared using a univariate analyses, and there were no significant differences between the two groups in age, maximum tumor size, tumor location, aspect ratio, boundary, morphology, echogenicity, BRAFV600E and HT (P > 0.05), and there were significant differences between gender, capsule contact, microcalcifications, rich vascularity, and number of lymph node dissection (P < 0.05). A multivariate logistic regression analyses was performed to further clarify the correlation of these indices. However, only male (OR = 1.770, P = 0.009), microcalcifications (OR = 1.791, P = 0.004), capsule contact (OR = 1.857, P = 0.01), and number of lymph node dissection (OR = 2.274, P < 0.001) were independent predictors of cervical CLNM. In conclusion, four independent predictors of cervical CLNM, including male, microcalcifications, capsule contact, and number of lymph node dissection, were screened out. Therefore, a comprehensive assessment of these risk factors should be conducted when designing individualized treatment regimens for PTC patients.

Sonographic characteristics of thyroid nodules with a Halo

OBJECTIVE

To investigate the sonographic characteristics of thyroid nodules with a halo, explore the value of contrast-enhanced ultrasound (CEUS) combined with fine needle aspiration (FNA) in identifying nodules with a halo, and predict the risk of metastasis by analyzing the pathological features of the halo.

METHODS

A retrospective analysis was conducted on 185 postoperative cases of thyroid nodules accompanied by halos between January 2019 and December 2022. After describing the ultrasound characteristics of the thyroid nodules and their halos, all patients were divided into three groups, the first group (group I = CEUS only) of patients underwent CEUS, the second group (group II = CEUS + FNA) underwent FNA based on the first group, and the third group (group III = FNA only) underwent FNA directly. The CEUS and FNA results were graded using the Chinese Thyroid Imaging Report and Data System (C-TIRADS) and Bethesda Reporting System for Thyroid Cytopathology, respectively. Those graded below C-TIRADS 4b or Bethesda IV were defined as benign, and the results of FNA were referenced when the two methods were combined. The surgical pathology results were used as the gold standard. We plotted working curves to compare the diagnostic efficacy of CEUS and FNA alone and in combination in the diagnosis of thyroid nodules with halos. The pathological features of the halo were analyzed and the number of patients with cervical lymph node metastases was recorded.

RESULTS

One hundred and sixty patients met the requirements. Benign nodules were mainly characterized by a thin (0.75 ± 0.31 mm) and uniform halo with good integrity, while malignant nodules had a thicker (1.48 ± 0.51 mm) halo with uneven and irregular margins (P < 0.05). The sensitivity and specificity were highest when the cutoff value was 1.09 mm, with 76.08% and 84.29%, respectively. The halos of benign nodules were mostly hyper- or iso-enhanced, whereas the halos of malignant nodules were predominantly hypo-enhanced (P < 0.05). The areas under the curve (AUCs) for CEUS, FNA, and CEUS + FNA were 0.751(95% CI = 0.642-0.841), 0.863(95% CI = 0.767-0.929), and 0.918(95% CI = 0.834-0.967), respectively. Cervical lymph node metastasis occurred in only 13 (11.5%) malignant nodes with halos. The primary pathological components of the halo around malignant nodules were almost reactive hyperplastic fibrous tissue.

CONCLUSION

The halo surrounding malignant thyroid nodules is thicker, with uneven and irregular margins, and shows hypo-enhancement on CEUS. Combining CEUS with FNA improves the diagnostic efficacy of thyroid nodules with halos. The reactive hyperplastic fibrous halo may be one of the reasons why malignant nodules are less likely to metastasize.

A nomogram for enhanced risk stratification for predicting cervical lymph node metastasis in papillary thyroid carcinoma patients

BACKGROUND

Cervical lymph node metastasis (CLNM) significantly impacts the prognosis of papillary thyroid carcinoma (PTC) patients. Accurate CLNM prediction is crucial for surgical planning and patient outcomes. This study aimed to develop and validate a nomogram-based risk stratification system to predict CLNM in PTC patients.

METHODS

This retrospective study included 1069 patients from Zhongshan Hospital and 253 from the Qingpu Branch of Zhongshan Hospital. Preoperative ultrasound (US) data and various nodule characteristics were documented. Patients underwent lobectomy with central lymph node dissection and lateral dissection if suspicious. Multivariate logistic regression, least absolute shrinkage and selection operator (LASSO) regression, and the random forest algorithm were used to identify CLNM risk factors. A nomogram was constructed and validated internally and externally. Model performance was assessed via receiver operating characteristic (ROC) curves, calibration plots, DeLong's test, decision curve analysis (DCA), and the clinical impact curve (CIC).

RESULTS

Six independent CLNM risk factors were identified: age, sex, tumor size, calcification, internal vascularity, and US-reported CLNM status. The model's area under the curve (AUC) was 0.77 for both the training and the external validation sets. Calibration plots and Hosmer‒Lemeshow (HL) tests showed good calibration. The optimal cutoff value was 0.57, with a sensitivity of 58.02% and a specificity of 83.43%. Risk stratification on the basis of the nomogram categorized patients into low-, intermediate-, and high-risk groups, effectively differentiating the likelihood of CLNM, and an online calculator was created for clinical use.

CONCLUSION

The nomogram accurately predicts CLNM risk in PTC patients, aiding personalized surgical decisions and improving patient management.

A comprehensive prediction model for central lymph node metastasis in papillary thyroid carcinoma with Hashimoto's thyroiditis: BRAF may not be a valuable predictor

Purpose

Papillary thyroid carcinoma (PTC) frequently coexists with Hashimoto's thyroiditis (HT), which poses challenges in detecting central lymph node metastasis (CLNM) and determining optimal surgical management. Our study aimed to identify the independent predictors for CLNM in PTC patients with HT and develop a comprehensive prediction model for individualized clinical decision-making.

Patients and methods

In this retrospective study, a total of 242 consecutive PTC patients who underwent thyroid surgery and central lymph node dissection between February 2019 and December 2021 were included. 129 patients with HT were enrolled as the case group and 113 patients without HT as control. The results of patients' general information, laboratory examination, ultrasound features, pathological evaluation, and BRAF mutation were collected. Multivariate logistic regression analysis was used to identify independent predictors, and the prediction model and nomogram were developed for PTC patients with HT. The performance of the model was assessed using the receiver operating characteristic curve, calibration curve, decision curve analysis, and clinical impact curve. In addition, the impact of the factor BRAF mutation was further evaluated.

Results

Multivariate analysis revealed that gender (OR = 8.341, P = 0.013, 95% CI: 1.572, 44.266), maximum diameter (OR = 0.316, P = 0.029, 95% CI: 0.113, 0.888), multifocality (OR = 3.238, P = 0.010, 95% CI: 1.319, 7.948), margin (OR = 2.750, P = 0.046, 95% CI: 1.020, 7.416), and thyrotropin receptor antibody (TR-Ab) (OR = 0.054, P = 0.003, 95% CI: 0.008, 0.374) were identified as independent predictors for CLNM in PTC patients with HT. The area under the curve of the model was 0.82, with accuracy, sensitivity, and specificity of 77.5%, 80.3% and 75.0%, respectively. Meanwhile, the model showed satisfactory performance in the internal validation. Moreover, the results revealed that BRAF mutation cannot further improve the efficacy of the prediction model.

Conclusion

Male, maximum diameter > 10mm, multifocal tumors, irregular margin, and lower TR-Ab level have significant predictive value for CLNM in PTC patients with HT. Meanwhile, BRAF mutation may not have a valuable predictive role for CLNM in these cases. The nomogram constructed offers a convenient and valuable tool for clinicians to determine surgical decision and prognostication for patients.

Modified TI-RADS Coupled with BRAFV600E Enhances Diagnostic Efficiency in Papillary Thyroid Carcinoma: Prospective Study

Background

Thyroid disorders, relatively common diseases of the endocrine system, have risen gradually in recent years. Early detection and accurate diagnosis of thyroid cancer hold exceptional importance. This study aimed to determine the efficacy of a modified TI-RADS and BRAFV600E mutation testing for thyroid cancer (PTC) diagnosis.

Methods

Ninety five thyroid nodules (48 benign and 47 malignant) from 81 patients were examined using Kwak Thyroid Imaging Reporting and Data System (TI-RADS) were subjected to shear wave elasticity (SWE), BRAFV600E genotyping and fine needle aspiration (FNA) cytology.

Results

The modified TI-RADS exhibited superior diagnostic accuracy compared to TI-RADS in differentiating benign nodules from malignant thyroid nodules. Moreover, the AUC of modified TI-RADS in conjunction with BRAFV600E was the highest at 95% CI (0.898-0.992, p=0.003), surpassing other diagnostic methods in enhanced sensitivity and maintaining high specificity.

Conclusion

The diagnostic efficiency of this combination surpassed that of individual diagnostic methods.

Deep learning predicts cervical lymph node metastasis in clinically node-negative papillary thyroid carcinoma

OBJECTIVES

Precise determination of cervical lymph node metastasis (CLNM) involvement in patients with early-stage thyroid cancer is fairly significant for identifying appropriate cervical treatment options. However, it is almost impossible to directly judge lymph node metastasis based on the imaging information of early-stage thyroid cancer patients with clinically negative lymph nodes.

METHODS

Preoperative US images (BMUS and CDFI) of 1031 clinically node negative PTC patients definitively diagnosed on pathology from two independent hospitals were divided into training set, validation set, internal test set, and external test set. An ensemble deep learning model based on ResNet-50 was built integrating clinical variables, BMUS, and CDFI images using a bagging classifier to predict metastasis of CLN. The final ensemble model performance was compared with expert interpretation.

RESULTS

The ensemble deep convolutional neural network (DCNN) achieved high performance in predicting CLNM in the test sets examined, with area under the curve values of 0.86 (95% CI 0.78-0.94) for the internal test set and 0.77 (95% CI 0.68-0.87) for the external test set. Compared to all radiologists averaged, the ensemble DCNN model also exhibited improved performance in making predictions. For the external validation set, accuracy was 0.72 versus 0.59 (p = 0.074), sensitivity was 0.75 versus 0.58 (p = 0.039), and specificity was 0.69 versus 0.60 (p = 0.078).

CONCLUSIONS

Deep learning can non-invasive predict CLNM for clinically node-negative PTC using conventional US imaging of thyroid cancer nodules and clinical variables in a multi-institutional dataset with superior accuracy, sensitivity, and specificity comparable to experts.

CRITICAL RELEVANCE STATEMENT

Deep learning efficiently predicts CLNM for clinically node-negative PTC based on US images and clinical variables in an advantageous manner.

KEY POINTS

• A deep learning-based ensemble algorithm for predicting CLNM in PTC was developed. • Ultrasound AI analysis combined with clinical data has advantages in predicting CLNM. • Compared to all experts averaged, the DCNN model achieved higher test performance.

Application of Ultrasound Shear Wave Elastography Combined With BRAFV600E Mutation for the Diagnosis of Papillary Thyroid Carcinoma

ABSTRACT

This prospective study aimed to investigate the combination of shear wave elastography (SWE) and BRAFV600E mutation testing for the diagnosis of papillary thyroid carcinoma (PTC). One hundred thyroid nodules with an American College of Radiology thyroid imaging reporting and data system classification of 4 or 5 were subjected to SWE measurement, BRAFV600E genotyping, fine-needle aspiration, and surgery. Nonparametric statistical tests were used to compare the differences in the elastic parameters and BRAF genotypes between benign and malignant thyroid nodules of PTC, and receiver operating characteristic curve analysis was conducted to compare the diagnostic efficacy. In addition, the correlations between elastic parameters and BRAFV600E mutation in PTC were analyzed using binary logistic regression. The SWE, BRAFV600E, and their combination exhibited sensitivities of 72.9%, 81.3%, and 85.4%, respectively, and specificities of 66.7%, 90.3%, and 86.5%, respectively, in the diagnosis of PTC ( P < 0.05). The SWE, BRAFV600E, and their combination exhibited sensitivities of 50.0%, 24.1% and 56.3%, respectively, and specificities of 89.7%, 87.5% and 82.8%, respectively, in the diagnosis of central cervical lymph node metastasis ( P < 0.05). The combined use of SWE and BRAFV600E detection had the largest area under the curve, indicating that this combination is more effective in diagnosing PTC and lymph node metastasis in the central region than either method alone. Furthermore, Emax was positively associated with the BRAFV600E genotype. In conclusion, the combination of SWE and BRAFV600E genotype detection can improve the diagnostic efficacy for PTC. Emax can predict the BRAFV600E mutation status.

Integrating US-guided FNAB, BRAFV600E mutation, and clinicopathologic characteristics to predict cervical central lymph-node metastasis in preoperative patients with cN0 papillary thyroid carcinoma

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.

Diagnostic value of contrast-enhanced ultrasonography in the preoperative evaluation of lymph node metastasis in papillary thyroid carcinoma: a single-center retrospective study

BACKGROUND

Contrast-enhanced ultrasound (CEUS) has been recently used for the assessment of cervical lymph node metastasis (LNM) to guide surgical operation in patients with papillary thyroid carcinoma (PTC). However, the specificity and sensitivity of CEUS reported from previous studies are not consistent. The objective of this study was to evaluate the diagnostic value of CEUS for the metastasis of cervical lymph nodes in PTC patients based on data from one regional central hospital.

METHODS

The diagnostic value of CEUS in preoperative LNM of PTC patients was concluded by comparing the results of CEUS on lymph node status with postoperative pathology examination. In addition, this study conducted hierarchical analysis of PTC patients to explore whether tumor size, different lymph node regions, and Hashimoto's thyroiditis influence the assessment of CEUS.

RESULTS

This research study ultimately enrolled 965 PTC patients, including 266 males and 699 females with a mean age of 42.27 ± 11.34 years. A total of 527 patients were considered clinical-node negative, and 438 were clinical-node positive before surgery. The specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of CEUS in the assessment of LNM in PTC patients were 56.00%, 71.00%, 57.06%, 69.76% and 62.59%, respectively. For central and lateral lymph nodes, the accuracy of CEUS in PTC patients was 49.43% and 54.30%, respectively. In addition, it was shown that the accuracy of CEUS in PTC patients with Hashimoto's thyroiditis (HT) slightly decreased to 58.44%, and the accuracy of CEUS in PTC patients with non-HT in turn increased to 64.17%. The accuracy of CEUS in non-papillary thyroid microcarcinoma (PTMC) and PTMC patients was 65.68% and 61.24%, respectively. The accuracy of CEUS in predicting central LNM was significantly different between PTC patients with or without HT (P < 0.001) in this study but not for lateral lymph nodes (P = 0.114).

CONCLUSION

The accuracy of CEUS in the assessment of LNM in PTC is not consistently satisfactory, especially for central lymph nodes, small tumor diameters, or patients with HT. More diagnostic technologies for abnormal lymph nodes should be considered in PTC patients.

Ultrasonic Feature Prediction of Large-Number Central Lymph Node Metastasis in Clinically Node-Negative Solitary Papillary Thyroid Carcinoma

BACKGROUND

The purpose of this study was to investigate the preoperative prediction of large-number central lymph node metastasis (CLNM) in single thyroid papillary carcinoma (PTC) with negative clinical lymph nodes.

METHODS

A total of 634 patients with clinically lymph node-negative single PTC who underwent thyroidectomy and central lymph node dissection at the First Affiliated Hospital of Anhui Medical University and the Nanchong Central Hospital between September 2018 and September 2021 were analyzed retrospectively. According to the CLNM status, the patients were divided into two groups: small-number (≤5 metastatic lymph nodes) and large-number (>5 metastatic lymph nodes). Univariate and multivariate analyses were used to determine the independent predictors of large-number CLNM. Simultaneously, a nomogram based on risk factors was established to predict large-number CLNM.

RESULTS

The incidence of large-number CLNM was 7.7%. Univariate and multivariate analyses showed that age, tumor size, and calcification were independent risk factors for predicting large-number CLNM. The combination of the three independent predictors achieved an AUC of 0.806. Based on the identified risk factors that can predict large-number CLNM, a nomogram was developed. The analysis of the calibration map showed that the nomogram had good performance and clinical application.

CONCLUSION

In patients with single PTC with negative clinical lymph nodes large-number CLNM is related to age, size, and calcification in patients with a single PTC with negative clinical lymph nodes. Surgeons and radiologists should pay more attention to patients with these risk factors. A nomogram can help guide the surgical decision for PTC.

Ultrasound-based Nomogram for Predicting the Pathological Nodal Negativity of Unilateral Clinical N1a Papillary Thyroid Carcinoma in Adolescents and Young Adults

RATIONALE AND OBJECTIVES

To develop and validate a nomogram incorporating clinical and ultrasound (US) characteristics for predicting the pathological nodal negativity of unilateral clinically N1a (cN1a) papillary thyroid carcinoma (PTC) among adolescents and young adults.

MATERIALS AND METHODS

From December 2016 to August 2021, 278 patients aged ≤ 30 years from two medical centers were enrolled and randomly assigned to the training and validation cohorts at a ratio of 2:1. After performing univariate and multivariate analyses, a nomogram combining all independent predictive factors was constructed and applied to the validation cohort. The performance of the nomogram was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis .

RESULTS

Multivariate logistic regression analysis showed that unilateral cN1a PTC in young patients with Hashimoto's thyroiditis, T1 stage, no intra-tumoral microcalcification, and tumors located in the upper third of the thyroid gland was more likely to be free of central lymph node metastases. The nomogram revealed good calibration and discrimination in both cohorts, with areas under the receiver operating characteristic curve of 0.764 (95% confidence interval [CI]: 0.684-0.843) and 0.728 (95% CI: 0.602-0.853) in the training and validation cohorts, respectively. The clinical application of the nomogram was further confirmed using decision curve analysis.

CONCLUSION

This US-based nomogram may assist the assessment of central cervical lymph nodes in young patients with unilateral cN1a PTC, enabling improved risk stratification and optimal treatment management in clinical practice.

Multimodal predictive factors of metastasis in lymph nodes posterior to the right recurrent laryngeal nerve in papillary thyroid carcinoma

Objective

The lymph node posterior to the right recurrent laryngeal nerve (LN-prRLN) is a crucial component of the central lymph nodes (LNs). We aimed to evaluate multimodal predictive factors of LN-prRLN metastasis in patients with papillary thyroid carcinomas (PTCs), including the clinical data, pathologic data, and preoperative sonographic characteristics of PTCs.

Methods

A total of 403 diagnosed PTC patients who underwent unilateral, sub-total, or total thyroidectomy with central neck dissection were enrolled in this retrospective study. The clinical data, pathologic data, conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) characteristics of PTCs were collected and evaluated for predicting LN-prRLN metastasis.

Results

In this study, 96 PTC patients with LN-prRLN metastasis and 307 PTC patients without LN-prRLN metastasis were included. Univariate analysis demonstrated that PTC patients with LN-prRLN metastasis more often had younger age, larger size, multifocal cancers, A/T < 1, well-margins, microcalcification, petal-like calcification, internal vascularity, centripetal perfusion pattern and surrounding ring enhancement. Multivariate logistic regression analysis revealed that the CEUS centripetal perfusion pattern, central LN detected by ultrasound and LN-arRLN metastasis were independent characteristics for predicting LN-prRLN metastasis in PTC patients.

Conclusion

According to our research, it is essential for clinicians to thoroughly dissect central LNs, particularly LN-prRLNs.

Value of clinical features combined with multimodal ultrasound in predicting lymph node metastasis in cervical central area of papillary thyroid carcinoma

OBJECTIVE

To explore the clinical features, multimodal ultrasound features and multimodal ultrasound imaging features in predicting lymph node metastasis in the central cervical region of papillary thyroid carcinoma.

METHODS

A total of 129 patients with papillary thyroid carcinoma (PTC) confirmed by pathology were selected from our hospital from September 2020 to December 2022. According to the pathological results of cervical central lymph nodes, these patients were divided into metastatic group and non-metastatic group. Patients were randomly sampled and divided into training group (n = 90) and verification group (n = 39) according to the ratio of 7:3. The independent risk factors for central lymph node metastasis (CLNM) were determined by least absolute shrinkage and selection operator and multivariate logistic regression. Based on independent risk factors to build a prediction model, select the best diagnostic effectiveness of the prediction model sketch line chart, and finally, the line chart calibration and clinical benefits were evaluated.

RESULTS

A total of 8, 11 and 17 features were selected from conventional ultrasound images, shear wave elastography (SWE) images and contrast-enhanced ultrasound (CEUS) images to construct the Radscore of conventional ultrasound, SWE and CEUS, respectively. After univariate and multivariate logistic regression analysis, male, multifocal, encapsulation, iso-high enhancement and multimodal ultrasound imaging score were independent risk factors for cervical CLNM in PTC patients (p < 0.05). Based on independent risk factors, a clinical combined with multimodal ultrasound feature model was constructed, and multimodal ultrasound Radscore were added to the clinical combined with multimodal ultrasound feature model to form a joint prediction model. In the training group, the diagnostic efficacy of combined model (AUC = 0.934) was better than that of clinical combined with multimodal ultrasound feature model (AUC = 0.841) and multimodal ultrasound radiomics model (AUC = 0.829). In training group and validation group, calibration curves show that the joint model has good predictive ability for cervical CLNM of PTC patients; The decision curve shows that most of the net benefits of the nematic chart are higher than those of clinical + multimodal ultrasound feature model and multimodal ultrasound radiomics model within a reasonable risk threshold range.

CONCLUSION

Male, multifocal, capsular invasion and iso-high enhancement are independent risk factors of CLNM in PTC patients, and the clinical plus multimodal ultrasound model based on these four factors has good diagnostic efficiency. The joint prediction model after adding multimodal ultrasound Radscore to clinical and multimodal ultrasound features has the best diagnostic efficiency, high sensitivity and specificity, which is expected to provide objective basis for accurately formulating individualized treatment plans and evaluating prognosis.

Combined Conventional Ultrasound and Contrast-Enhanced Computed Tomography for Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma

OBJECTIVES

This study aimed to evaluate conventional ultrasound (US) combined with contrast-enhanced computed tomography (CT) of the neck to predict central lymph node metastasis (CLNM) in clinical lymph-negative patients with papillary thyroid carcinoma (PTC), establish a simple preoperative risk-scoring model, and validate its effectiveness in a two-center dataset.

METHODS

A total of 423 patients with PTC preoperatively evaluated by US and contrast-enhanced CT were included in the modeling group, and 102 patients from two hospitals were enrolled in the validation group. Independent predictive factors were determined using multivariate logistic regression analysis. Diagnostic performance was evaluated using receiver operating characteristic curve analysis.

RESULTS

The independent predictive factors for CLNM were age ≤45 years (odds ratio [OR] = 3.950), nodule presence in the non-upper pole (OR = 2.385), nodule size >12.5 mm (OR = 2.130), Thyroid Imaging Reporting and Data System score ≥9 (OR = 2.857), normalized enhancement CT value ≥0.75 (OR = 3.132), central enhancement (OR = 0.222), and capsular invasion (OR = 3.478). The area under the curve (AUC) of the model was 0.790 (95% confidence interval [CI]: 0.747-0.834), and the sensitivity and specificity were 70.4% and 73.9%, respectively. The AUC in the validation group was 0.827 (95% CI: 0.747-0.907), and the sensitivity and specificity were 88.9% and 63.2%, respectively.

CONCLUSIONS

We found conventional US combined with contrast-enhanced CT of the neck to be useful in predicting CLNM preoperatively and established a simple risk-scoring model that might help surgeons with appropriate surgical plans and prognostic evaluation.

A nomogram based on the risk factors of cervical lymph node metastasis in papillary thyroid carcinoma coexistent with Hashimoto's thyroiditis

OBJECTIVE

The purpose of this study was to explore the risk factors of cervical lymph node metastasis(LNM) in papillary thyroid carcinoma(PTC) coexistent with Hashimoto's thyroiditis(HT).

METHODS

The clinical data of patients who underwent thyroid operation between November 2016 and January 2020 in our hospital were analyzed retrospectively. The association between sonographic features and the risk factors of cervical LNM in PTC coexistent with HT was analyzed and a nomogram based on the risk factors was built.

RESULTS

Age, US features as calcification, blood flow type, distance between thyroid nodule and fibrous capsule were risk factors of cervical LNM(P < 0.05).Size, SWVmax and SWVmean of thyroid nodule, SWVratio between thyroid nodule and thyroid gland were higher in PTCs with LNM than those without LNM(P < 0.05). The ROC curve showed that the cutoff value of SWVratio for predicting LNM was 1.29 (Sensitivity = 0.806, Specificity = 0.775, AUC = 0.823, P < 0.001). Based on the risk factors above, a relevant nomogram prediction model was established. The model verification showed that the C-index of the modeling set was 0.814, indicating that the nomogram model had good predicted accuracy.

CONCLUSION

Based on the risk factors above, a relevant nomogram prediction model was established. The model verification showed that the C-index of the modeling set was 0.814, indicating that the nomogram model had good predicted accuracy. The nomogram based on the risk factors above had good prediction ability, which could optimize thyroidectomy and cervical lymph node dissection and improving prognosis.

A UPLC Q-Exactive Orbitrap Mass Spectrometry-Based Metabolomic Study of Serum and Tumor Tissue in Patients with Papillary Thyroid Cancer

OBJECTIVE

To find the metabolomic characteristics of tumor or para-tumor tissues, and the differences in serums from papillary thyroid cancer (PTC) patients with or without lymph node metastasis.

METHODS

We collected serums of PTC patients with/without lymph node metastasis (SN1/SN0), tumor and adjacent tumor tissues of PTC patients with lymph node metastasis (TN1 and PN1), and without lymph node metastasis (TN0 and PN0). Metabolite detection was performed by ultra-high performance liquid chromatography combined with Q-Exactive orbitrap mass spectrometry (UPLC Q-Exactive).

RESULTS

There were 31, 15, differential metabolites in the comparisons of TN1 and PN1, TN0 and PN0, respectively. Seven uniquely increased metabolites and fourteen uniquely decreased metabolites appeared in the lymph node metastasis (TN1 and PN1) group. Meanwhile, the results indicated that four pathways were co-owned pathways in two comparisons (TN1 and PN1, TN0 and PN0), and four unique pathways presented in the lymph node metastasis (TN1 and PN1) group.

CONCLUSIONS

Common or differential metabolites and metabolic pathways were detected in the lymph node metastasis and non-metastatic group, which might provide novel ways for the diagnosis and treatment of PTC.

A machine learning-based approach to predicting the malignant and metastasis of thyroid cancer

Background

Thyroid Cancer (TC) is the most common malignant disease of endocrine system, and its incidence rate is increasing year by year. Early diagnosis, management of malignant nodules and scientific treatment are crucial for TC prognosis. The first aim is the construction of a classification model for TC based on risk factors. The second aim is the construction of a prediction model for metastasis based on risk factors.

Methods

We retrospectively collected approximately 70 preoperative demographic and laboratory test indices from 1735 TC patients. Machine learning pipelines including linear regression model ridge, Logistic Regression (LR) and eXtreme Gradient Boosting (XGBoost) were used to select the best model for predicting deterioration and metastasis of TC. A comprehensive comparative analysis with the prediction model using only thyroid imaging reporting and data system (TI-RADS).

Results

The XGBoost model achieved the best performance in the final thyroid nodule diagnosis (AUC: 0.84) and metastasis (AUC: 0.72-0.77) predictions. Its AUCs for predicting Grade 4 TC deterioration and metastasis reached 0.84 and 0.97, respectively, while none of the AUCs for Only TI-RADS reached 0.70. Based on multivariate analysis and feature selection, age, obesity, prothrombin time, fibrinogen, and HBeAb were common significant risk factors for tumor progression and metastasis. Monocyte, D-dimer, T3, FT3, and albumin were common protective factors. Tumor size (11.14 ± 7.14 mm) is the most important indicator of metastasis formation. In addition, GGT, glucose, platelet volume distribution width, and neutrophil percentage also contributed to the development of metastases. The abnormal levels of blood lipid and uric acid were closely related to the deterioration of tumor. The dual role of mean erythrocytic hemoglobin concentration in TC needs to be verified in a larger patient cohort. We have established a free online tool (http://www.cancer-thyroid.com/) that is available to all clinicians for the prognosis of patients at high risk of TC.

Conclusion

It is feasible to use XGBoost algorithm, combined with preoperative laboratory test indexes and demographic characteristics to predict tumor progression and metastasis in patients with TC, and its performance is better than that of Only using TI-RADS. The web tools we developed can help physicians with less clinical experience to choose the appropriate clinical decision or secondary confirmation of diagnosis results.

Contrast-enhanced ultrasound characteristics of preoperative central cervical lymph node metastasis in papillary thyroid carcinoma

This study evaluated the preoperative diagnostic value of lymph node ultrasonography in distinguishing between benign and malignant central cervical lymph nodes (CCLNs) in patients with papillary thyroid carcinoma (PTC). A total of 176 patients who had PTC with 216 CCLNs (49 benign and 155 malignant) were enrolled in this study and preoperatively imaged by ultrasonography, including conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS). We evaluated the ultrasonography parameters for each lymph node. Binary logistic regression analysis indicated that multifocality of PTC and the absence of Hashimoto's thyroiditis are independent clinical features related to patients with PTC who also have malignant CCLNs. For preoperative ultrasonography features, heterogeneous enhancement and centripetal perfusion are independent ultrasonographic features to identify malignant and benign CCLNs. This study demonstrated that preoperative CEUS characteristics help to distinguish malignant CCLNs from benign CCLNs.

Value of Contrast-Enhanced Ultrasound for Evaluation of Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma

The aim of the study was to evaluate the diagnostic value of contrast-enhanced ultrasound (CEUS) in distinguishing between benign and malignant cervical lymph nodes (LNs) in patients with papillary thyroid carcinoma (PTC). Two hundred and one cervical LNs (157 metastatic from PTC and 44 benign) were evaluated using conventional ultrasonography (US) and CEUS before biopsy or surgery. Histopathology was used as the gold standard. We evaluated the size, long axis/short axis ratio (L/S), fatty hilum, hyper-echogenicity, calcification, cystic change, peripheral vascularity and CEUS parameters for each lymph nodule. The CEUS parameters included enhancement type, homogeneity, perfusion type, ring enhancement, peak intensity (PI) index and area under the curve (AUC) index. Univariate analysis demonstrated that compared with benign LNs, malignant LNs more frequently had L/S < 2, absence of a fatty hilum, presence of hyper-echogenicity, presence of calcification, peripheral vascularity, hyper-enhancement, heterogeneous enhancement, centripetal perfusion, ring enhancement, PI index > 1 and AUC index > 1 on preoperative US and CEUS. Binary logistic regression analysis demonstrated that hyper-enhancement, centripetal perfusion, and ring enhancement are independent CEUS characteristics related to malignant LNs for their differentiation from benign LNs (all p < 0.05). Our study indicated that preoperative CEUS characteristics may serve as a useful tool to identify malignant cervical LNs from benign cervical LNs.

A Preoperative Nomogram for the Prediction of High-Volume Central Lymph Node Metastasis in Papillary Thyroid Carcinoma

Background

High-volume lymph node metastasis (HVLNM, equal to or more than 5 lymph nodes) is one of the adverse features indicating high recurrence risk in papillary thyroid carcinoma (PTC) and is recommended as one of the indications of completion thyroidectomy for patients undergoing thyroid lobectomy at first. In this study, we aim to develop a preoperative nomogram for the prediction of HVLNMs in the central compartment in PTC (cT1-2N0M0), where preoperative imaging techniques perform poor.

Methods

From October 2016 to April 2021, 423 patients were included, who were diagnosed as PTC (cT1-2N0M0) and underwent total thyroidectomy and prophylactic central compartment neck dissection in our center. Demographic and clinicopathological features were recorded and analyzed using univariate and multivariate logistic regression analysis. A nomogram was developed based on multivariate logistic regression analysis.

Results

Among the included patients, 13.4% (57 cases) were found to have HVLNMs in the central compartment. Univariate and multivariate logistic regression analysis showed that age (35 years), BRAF with V600E mutated, nodule diameter, and calcification independently predicted HVLNMs in the central compartment. The nomogram showed good discrimination with an AUC of 0.821 (95% CI, 0.768-0.875).

Conclusion

The preoperative nomogram can be used to quantify the probability of HVLNMs in the central compartment and may reduce the reoperation rate after thyroid lobectomy.

Ultrasound-Based Radiomic Nomogram for Predicting Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma

RATIONALE AND OBJECTIVES

Accurate preoperative identification of lateral cervical lymph node metastasis (LNM) is important for decision-making and clinical management of patients with papillary thyroid carcinoma (PTC). The aim of this study was to develop an ultrasound (US)-based radiomic nomogram to preoperatively predict the lateral LNM in PTC patients.

METHODS

In this retrospective study, a total of 886 patients were enrolled and randomly divided into 2 groups. Radiomic features were extracted from the preoperative US images. A radiomic signature was constructed using the least absolute shrinkage and selection operator algorithm in the training set. Multivariate logistic regression was performed to develop the radiomic nomogram, which incorporating the radiomic signature and the selected clinical characteristics. The performance of the nomogram was assessed by its discrimination, calibration, and clinical usefulness in both the training and validation sets.

RESULTS

The radiomic signature was significantly associated with the lateral LNM in both cohorts (p< 0.001). The nomogram that consisted of radiomic signature, US-reported cervical lymph node (CLN) status, and CT-reported CLN status demonstrated good discrimination and calibration in the training and validation sets with an AUC of 0.946 and 0.914, respectively. The decision curve analysis indicated that the radiomic nomogram was worthy of clinical application.

CONCLUSION

The radiomic nomogram proposed here has good performance for noninvasively predicting the lateral LNM and might be used to facilitate clinical decision-making and potentially improve the survival outcome in selected patients.

Predictive Factor of Large-Volume Central Lymph Node Metastasis in Clinical N0 Papillary Thyroid Carcinoma Patients Underwent Total Thyroidectomy

Large-volume central lymph node metastasis (large-volume CLNM) is associated with high recurrence rate in papillary thyroid carcinoma (PTC) patients. However, sensitivity in investigating large-volume CLNM on preoperative ultrasonography (US) is not high. The aim of this study is to investigate the clinical factors associated with large-volume CLNM in clinical N0 PTC patients. We reviewed 976 PTC patients undergoing total thyroidectomy with central lymph node dissection during 2017 to 2019. The rate of large-volume LNM was 4.1% (40 of 967 patients). Multivariate analysis showed that male gender and young age (age<45 years old) were independent risk factors for large-volume CLNM with odds ratios [(OR), 95% confidence interval (CI)] of 2.034 (1.015-4.073) and 2.997 (1.306-6.876), respectively. In papillary thyroid microcarcinoma (PTMC), capsule invasion was associated with large-volume CLNM with OR (95% CI) of 2.845 (1.110-7.288). In conventional papillary thyroid cancer (CPTC), tumor diameter (>2cm) was associated with large-volume CLNM, with OR (95% CI) 3.757 (1.061-13.310), by multivariate analysis. In ROC curve analysis on the diameter of the CPTC tumor, the Area Under Curve (AUC) =0.682(p=0.013), the best cut-off point was selected as 2.0cm. In conclusion, male gender and young age were predictors for large-volume CLNM of cN0 PTC. cN0 PTMC patient with capsule invasion and cN0 CPTC patient with tumor diameter >2cm were correlated with large-volume CLNM. Total thyroidectomy with central lymph node dissection may be a favorable primary treatment option for those patients.

Predictors and a Prediction Model for Central Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma (cN0)

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, BRAF^V600E 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).

A Novel Scoring System for Predicting the Metastases of Posterior Right Recurrent Laryngeal Nerve Lymph Node Involvement in Patients With Papillary Thyroid Carcinoma by Preoperative Ultrasound

OBJECTIVE

Our goal was to investigate the correlation between papillary thyroid carcinoma (PTC) characteristics on ultrasonography and metastases of lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN). There is still no good method for clinicians to judge whether a patient needs LN-prRLN resection before surgery, and we also wanted to establish a new scoring system to determine whether patients with papillary thyroid carcinoma require LN-prRLN resection before surgery.

PATIENTS AND METHODS

There were 482 patients with right or bilateral PTC who underwent thyroid gland resection from December 2015 to December 2017 recruited as study subjects. The relationship between the PTC characteristics on ultrasonography and the metastases of LN-prRLN was analyzed by univariate and logistic regression analyses. Based on the risk factors identified in univariate and logistic regression analysis, a nomogram-based LN-prRLN prediction model was established.

RESULT

LN-prRLN were removed from all patients, of which 79 had LN-prRLN metastasis, with a metastasis rate of 16.39%. Multivariate logistic regression analysis revealed that LN-prRLN metastasis was closely related to sex, age, blood supply, larger tumors (> 1 cm) and capsular invasion. A risk prediction model has been established and fully verified. The calibration curve used to evaluate the nomogram shows that the consistency index was 0.75 ± 0.065.

CONCLUSION

Preoperative clinical data, such as sex, age, abundant blood supply, larger tumor (> 1 cm) and capsular invasion, are positively correlated with LN-prRLN metastasis. Our scoring system can help surgeons non-invasively determine which patients should undergo LN-prRLN resection before surgery. We recommend that LN-prRLN resection should be performed when the score is above 103.1.

Ultrasound and Contrast-Enhanced Ultrasound Characteristics Associated With cN1 and Microscopic pN1 in Papillary Thyroid Carcinoma

OBJECTIVES

Lymph node metastases (LNMs) could be stratified into clinical N1 (cN1) and microscopic pN1 (pathological N1), which bear different biological behavior and prognosis. Our study aimed to investigate the associations between LNMs and primary tumor's US (ultrasound) and CEUS (contrast-enhanced ultrasound) characteristics based on the stratification of LNMs into cN1 and microscopic pN1 in papillary thyroid carcinoma (PTC).

METHODS

From August 2019 to May 2020, 444 consecutive PTC patients who underwent preoperative neck US and CEUS evaluation were included. According to regional lymph node status, the patients were classified into cN1 group versus cN0 (clinical N0) group and microscopic pN1 group versus pN0 (pathological N0) group. For multiple PTCs, the largest one was selected for the evaluation of US, CEUS and clinical features. Univariate and multivariate analyses were performed to determine independent predictors of cN1 and microscopic pN1.

RESULTS

85 cN1 versus 359 cN0 patients and 117 microscopic pN1 versus 242 pN0 patients were analyzed. Multivariate logistic regression analysis showed that <55-years-old (OR: 2.56 (1.08-6.04), male [OR: 2.18 (1.22-3.91)], large size [OR: 2.59 (1.71-3.92)], calcification [OR: 3.88 (1.58-9.51)], and hyper-enhancement [OR: 2.78 (1.22-6.30)] were independent risk factors of cN1, while <55-years-old [OR: 1.91 (1.04-3.51)], large size [OR: 1.56 (1.003-2.42)], multifocality [OR: 1.67 (1.04-2.66)] were independent risk factors of microscopic pN1.

CONCLUSIONS

For patients with PTC, young age, male, large size, calcification, and hyper-enhancement were independent predictors of cN1, while young age, large size and multifocality were independent predictors of microscopic pN1.

Sonographic Characteristics of Papillary Thyroid Carcinoma With Coexistent Hashimoto's Thyroiditis in the Preoperative Prediction of Central Lymph Node Metastasis

The purpose of this study was to evaluate the usefulness of the sonographic characteristics of papillary thyroid carcinoma (PTC) with Hashimoto's thyroiditis (HT) for predicting central lymph node metastasis (CLNM). One hundred thirty-three patients who underwent thyroidectomy and central cervical lymph node dissection for PTC with coexistent HT were retrospectively analyzed. All PTCs with HT were preoperatively evaluated by ultrasound (US) regarding their nodular number, size, component, shape, margin, echogenicity, calcification, capsule contact with protrusion, vascularity and contrast enhanced ultrasound (CEUS) parameters. Univariate analysis demonstrated that patients with PTCs with HT and CLNM more frequently had age ≤ 45 years, size > 10 mm, a wider than tall shape, microcalcification, hypo-enhancement and peak intensity index < 1 than those without CLNM (all p<0.05). Binary logistic regression analysis demonstrated that size > 10 mm and CEUS hypo-enhancement were independent characteristics for the presence of CLNM. Our study indicated that preoperative US characteristics could offer help in predicting CLNM in PTCs with coexistent HT.

An Ultrasound Radiomics Nomogram for Preoperative Prediction of Central Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma

Purpose: This study aimed to establish and validate an ultrasound radiomics nomogram for the preoperative prediction of central lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC).

Patients and Methods: The prediction model was developed in 609 patients with clinicopathologically confirmed unifocal PTC who received ultrasonography between Jan 2018 and June 2018. Radiomic features were extracted after the ultrasonography of PTC. Lasso regression model was used for data dimensionality reduction, feature selection, and radiomics signature building. The predicting model was established based on the multivariable logistic regression analysis in which the radiomics signature, ultrasonography-reported LN status, and independent clinicopathologic risk factors were incorporated, and finally a radiomics nomogram was established. The performance of the nomogram was assessed with respect to the discrimination and consistence. An independent validation was performed in 326 consecutive patients from July 2018 to Sep 2018.

Results: The radiomics signature consisted of 23 selected features and was significantly associated with LN status in both primary and validation cohorts. The independent predictors in the radiomics nomogram included the radiomics signature, age, TG level, TPOAB level, and ultrasonography-reported LN status. The model showed good discrimination and consistence in both cohorts: C-index of 0.816 (95% CI, 0.808–0.824) in the primary cohort and 0.858 (95% CI, 0.849–0.867) in the validation cohort. The area under receiver operating curve was 0.858. In the validation cohort, the accuracy, sensitivity, specificity and AUC of this model were 0.812, 0.816, 0.810, and 0.858 (95% CI, 0.785–0.930), respectively. Decision curve analysis indicated the radiomics nomogram was clinically useful.

Conclusion: This study presents a convenient, clinically useful ultrasound radiomics nomogram that can be used for the pre-operative individualized prediction of central LN metastasis in patients with PTC.

Prediction of cervical lymph node metastasis with contrast-enhanced ultrasound and association between presence of BRAFV600E and extrathyroidal extension in papillary thyroid carcinoma

Objective:

This study aimed to evaluate the correlation between cervical lymph node metastasis (CLNM) and each of the ultrasound features, immunohistochemical factors, and B-type Raf (BRAF^V600E) mutation.

Methods:

A retrospective analysis was performed on 405 patients with single papillary thyroid carcinoma (PTC) nodules, all of whom underwent preoperative sonographic examinations, including gray-scale ultrasound, color Doppler ultrasound, and contrast-enhanced ultrasound (CEUS). All PTC patients were evaluated using 14 clinical and sonographic features, eight immunohistochemical factors, and BRAF^V600E. Multivariate analyses were performed to identify the risk factors for CLNM, and an equation for CLNM was established. The diagnostic value of each modality was compared with a receiver operating characteristic (ROC) curve.

Results:

Among the 405 PTC nodules removed surgically, CLNM was confirmed in 138 patients, whereas extrathyroidal extension was confirmed in 185 patients. Multivariate analyses indicated significant differences between CLNM and non-CLNM groups in three conventional ultrasound features (p < 0.05), whereas other sonographic features, eight immunohistochemical factors, and BRAF^V600E did not indicate significant differences. A ROC curve of 0.757 in the equation exhibited a significant difference compared with the solo factors (p < 0.05 for all). Hyper or isoechoic enhancement at peak time on CEUS was associated with CLNM, whereas the presence of the BRAF^V600E mutation was associated with extrathyroidal extensions although BRAF appeared to be uncorrelated with CLNM in the present study.

Conclusion:

Intensity at peak time, homogeneity, and size are the three most significant features in predicting CLNM in PTC patients, and the presence of the BRAF^V600E mutation was associated with extrathyroidal extensions when PTCs showed a hyper or isoechoic enhancement at peak time in CEUS.

Development and validation of an ultrasound-based nomogram for preoperative prediction of cervical central lymph node metastasis in papillary thyroid carcinoma

Background

Preoperative prediction of central lymph node metastasis (CLNM) holds significant value in determining a patient's suitability for surgical resection and the need for adjuvant treatment, thereby contributing to better therapeutic strategies. This study aimed to build and confirm a nomogram that integrates ultrasound (US) characteristics with clinical features to predict CLNM in patients with papillary thyroid carcinoma (PTC) preoperatively.

Methods

The prediction model was set up with a training dataset that included 512 patients with histopathologically confirmed PTC. The least absolute shrinkage and selection operator (LASSO) regression method was applied to select US features in the development cohort. The patients' US characteristics and clinical features were incorporated into a multivariate logistic regression analysis to develop the nomogram. The clinical feasibility, calibration, and discriminatory ability of the nomogram were evaluated in an independent validation cohort of 306 patients.

Results

Age, sex, tumor size, multiple tumors, and US-based CLNM status were included as independent predictors in the personalized nomogram. The nomogram showed good calibration and discrimination in the training and validation datasets. The addition of the BRAF V600E mutation status did not improve the performance of the nomogram. The decision curve analysis showed the nomogram to have clinical feasibility.

Conclusions

A nomogram that integrates US characteristics with patients' clinical features was built. This US-based nomogram can be expediently applied to promote the personalized preoperative prediction of CLNM and to develop surgical strategies, such as tailored central compartment neck dissection, in patients with PTC.

Ultrasound validation of predictive model for central cervical lymph node metastasis in papillary thyroid cancer on BRAF

Aim: To compare the value of predictive power of the models for central cervical lymph node metastasis (CLNM) in papillary thyroid carcinomas (PTCs). Patients & methods: 220 PTCs were prospectively enrolled into the study with pathological examination. We established a new risk model with univariate and multivariate analyses and receiver-operating characteristic curves were plotted. Z-test was performed to compare the area under two curves and validated the predictive model for central CLNM in PTCs. The comparison of previous and new predictive model was analyzed. Results: Microcalcification, capsule contact or involvement, internal flow and BRAF^V600E mutation were four independent risk factors for PTCs with central CLNMs. The area under the curves for the new and the previous model were 0.948 and 0.934 (p = 0.572), respectively. Conclusion: Two predictive models showed strong consistency in predicting central CLNM in PTCs. The predictive model may be helpful in selecting appropriate treatment method in PTCs.

Nomogram Based on Shear-Wave Elastography Radiomics Can Improve Preoperative Cervical Lymph Node Staging for Papillary Thyroid Carcinoma

Background: Accurate preoperative prediction of cervical lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC) provides a basis for surgical decision-making and the extent of tumor resection. This study aimed to develop and validate an ultrasound radiomics nomogram for the preoperative assessment of LN status. Methods: Data from 147 PTC patients at the Wuhan Tongji Hospital and 90 cases at the Hunan Provincial Tumor Hospital between January 2017 and September 2019 were included in our study. They were grouped as the training and external validation set. Radiomics features were extracted from shear-wave elastography (SWE) images and corresponding B-mode ultrasound (BMUS) images. Then, the minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator regression were used to select LN status-related features and construct the SWE and BMUS radiomics score (Rad-score). Multivariate logistic regression was performed using the two radiomics scores together with clinical data, and a nomogram was subsequently developed. The performance of the nomogram was assessed with respect to discrimination, calibration, and clinical usefulness in the training and external validation set. Results: Both the SWE and BMUS Rad-scores were significantly higher in patients with cervical LN metastasis. Multivariate analysis indicated that the SWE Rad-scores, multifocality, and ultrasound (US)-reported LN status were independent risk factors associated with LN status. The radiomics nomogram, which incorporated the three variables, showed good calibration and discrimination in the training set (area under the receiver operator characteristic curve [AUC] 0.851 [CI 0.791-0.912]) and the validation set (AUC 0.832 [CI 0.749-0.916]). The significantly improved net reclassification improvement and index-integrated discrimination improvement demonstrated that SWE radiomics signature was a very useful marker to predict the LN metastasis in PTC. Decision curve analysis indicated that the SWE radiomics nomogram was clinically useful. Furthermore, the nomogram also showed favorable discriminatory efficacy in the US-reported LN-negative (cN0) subgroup (AUC 0.812 [CI 0.745-0.860]). Conclusions: The presented radiomics nomogram, which is based on the SWE radiomics signature, shows a favorable predictive value for LN staging in patients with PTC.

Predictive Factors for Level V Lymph Node Metastases in Papillary Thyroid Carcinoma with BRAFV600E Mutation and Clinicopathological Features

Background

Therapeutic lateral neck dissection (LND) is recommended in papillary thyroid carcinoma (PTC) patients with clinically lateral lymph node metastasis (LLNM), whether underwent level V LND remains controversial for lacking of sensitive predicting system. BRAF^V600E mutation is associated with aggressive tumor behavior, recurrence, and disease-specific mortality of PTC. However, the relationship between BRAF^V600E mutation and level V LNM is unclear.

Methods

Univariate and multivariate analyses were retrospectively conducted on the potential predictive factors of 252 PTC patients who underwent initial treatment of neck lymph node dissection from September 2015 to October 2018 in our institute. BRAF^V600E mutation and the clinicopathological characteristics of the two groups were compared.

Results

LLNM was presented in 208 (82.5%) patients and level II-V LNM was present in 42.8%, 71.2%, 85.1%, 17.8% patients, respectively. BRAF^V600E mutation was observed in 188 (74.6%) patients and was significantly associated with patients' age, lymphocytic thyroiditis, capsule invasion, bilateral central lymph node metastasis (CLNM) and level V LNM in PTC. Univariate analysis revealed that lymphocytic thyroiditis, tumor size, number of CLNM, Level II LNM, Level III LNM, simultaneous Level II+III, simultaneous Level III+IV and simultaneous Level II+III+IV were significantly correlated with Level V LNM. In addition, multivariate analysis revealed that tumor size ≥2.5 cm, number of CLNM≥3, level II metastases and BRAF^V600E mutation were independent Level V LNM predictors (odds ratio 3.910, 3.660, 8.410, 0.439; 95% CI 1.737-10.135, 1.054-12.713, 1.233-57.355, 0.280-0.827, respectively).

Conclusion

In summary, we presented several independent predictive factors for level V LNM in PTC patients. We constructed a risk prediction model consisting of tumor size ≥2.5 cm, number of CLNM≥3 and level II metastases and BRAF^V600E mutation that may guide surgeons to evaluate the nodal status in PTC and perform tailored therapeutic LND.

Suspicious ultrasound and clinicopathological features of papillary thyroid carcinoma predict the status of TERT promoter

PURPOSE

To investigate the value of ultrasound (US) and clinicopathological features of papillary thyroid cancer (PTC) in predicting Telomerase Reverse Transcriptase (TERT) promoter mutations.

METHODS

Preoperative US images of 351 surgically confirmed PTCs were evaluated in terms of PTCs size and US features. The basic clinicopathological features were also retrieved. Univariate and multivariate analyses were performed to identify the risk factors for TERT promoter mutations. A scoring system was developed based on the cumulative number of risk factors. The area under the receiver operating characteristic curve (AUC) and cut-off value were calculated to evaluate the diagnostic performance of the scoring system for predicting TERT promoter mutations.

RESULTS

TERT promoter mutations were found in 4.84% (17/351) of patients with PTCs. Patient age >50 years (OR: 6.244, P = 0.006), multifocality (OR: 21.071, P = 0.022), taller-than-wide shape (OR: 4.934, P = 0.029), microlobulated margin (OR: 4786, P = 0.032), and capsule contact or involvement (OR: 4.668, P = 0.030) were independent risk factors for TERT promoter mutations. TERT promoter mutations were relevant to more suspicious US and clinicopathological features than TERT promoter wild-type PTC (median, 4 vs. 1, P < 0.001). The cut-off value was 2.5 and the associated AUC was 0.908 (P < 0.001).

CONCLUSIONS

The probability of TERT promoter mutations increases along with the suspicious US features and clinicopathological characteristics, which may help to recognize patients who deserve a different approach, in terms of management and follow-up, in view of the worst outcome associated to this mutation.

A meta-analysis evaluating the relationship between B-type Raf kinase mutation and cervical lymphatic metastasis in papillary thyroid cancer

BACKGROUND

B-type Raf kinase (BRAF) mutation is proved to be a critical predictive factor in papillary thyroid cancer (PTC) with aggressive characteristics. However, the association between BRAF mutation and cervical lymphatic metastasis in PTC is controversial.

METHODS

We searched papers on the study of BRAF mutation and cervical lymphatic metastasis in PTC patients through PubMed, Web of Science, Embase, and Cochranelibrary. The BRAF (+) cases, BRAF (-) cases, and cervical lymphphatic metastatic cases in both BRAF (+) and BRAF (-) groups were collected. After Quality assessment, statistical Analysis (funnel plot and Harbord evaluation, Random-effect model, heterogeneity, subgroup analysis, sensitivity analysis, and metacum analysis) were done by the Review Manager (RevMan) 5.3 and stata14 statistical software.

RESULTS

There were 78 cross-section studies which met our inclusion criteria. And all of them had no selection bias, publication bias, or any other bias. A significant association existed between BRAF mutation and cervical lymph node metastasis (LNM) (odds ratio [OR] = 1.63; 95% confidence interval [CI]: 1.44-1.84; P < .05). Overall, 46 studies were conducted among East Asians. Twenty four articles had provided the data of central lymph node metastasis (CLNM), 11 articles with the data of lateral lymph node metastasis (LLNM), and classic/conventional PTC (CPTC) was analyzed in 10 studies. Subgroup analyses were performed based on ethnicity, metastatic site, and subtype of PTC. Significant association between BRAF (+) mutation and cervical LNM were indicated in East Asians (OR = 1.73; 95% CI: 1.49-2.02; P < .05), in non-East Asians (OR = 1.57; 95% CI: 1.26-1.96; P < .05), and in CLNM (OR = 1.80; 95% CI: 1.56-2.07; P < .05). While no significant association was found in LLNM (OR = 1.37; 95% CI: 0.76-2.48; P = .29 > .05) and in CPTC (OR = 1.32; 95% CI: 0.97-1.80; P = .08 > .05). We did not find any other major changes when sensitivity analysis was performed. The metacum analysis showed no significant association existed before 2012. While a significant association began to exist between BRAF mutation and LNM from 2012, and this association became stable from 2017.

CONCLUSIONS

We consider that a significant association exists between BRAF mutation and cervical LNM. Further meta-analysis on subgroup may reveal some valuable factors between BRAF gene mutation and LNM. And we do not recommend that BRAF (+) as the biomarker for LNM in PTC.

Petal-Like Calcifications in Thyroid Nodules on Ultrasonography: A Rare Morphologic Characteristic of Calcification Associated With Aggressive Biological Behavior

This study investigated a rare ultrasonographically detected thyroid petal-like calcification and its relationship with thyroid carcinoma and biological behavior. We described the clinical and ultrasonographical features of thyroid nodules with petal-like calcifications in 18 patients undergoing thyroid surgery and cervical lymph node dissection. All of the thyroid nodules with petal-like calcifications were papillary thyroid carcinomas (PTCs). Of the 18 patients, 13 (72.2%) had cervical central lymph node metastasis, and five (27.8%) had cervical lateral lymph node metastasis. Petal-like calcifications occurred in malignant thyroid nodules with a high incidence of lymph node metastasis, which may be a specific ultrasonographic feature associated with the aggressive biological behavior of PTC.

Suspicious ultrasound characteristics correlate with multiple factors that predict central lymph node metastasis of papillary thyroid carcinoma: Significant role of HBME-1

PURPOSE

Papillary thyroid carcinoma (PTC) is frequently associated with central lymph node metastasis (CLNM). In the present study, we aimed to identify possible risk factors for CLNM in PTC, including suspicious ultrasound (US) features coexisting with thyroid diseases, immunohistochemical markers, and BRAF_V600E. These were used to establish a model to predict the risk of CLNM.

METHODS

From January 2016 to March 2018, we identified a cohort of patients with classic PTC who underwent cervical US and were diagnosed by postoperative pathology. Fine-needle aspiration biopsies were analyzed for the presence ofBRAF_V600E, and immunohistochemistry was used to detect tumor markers. US imaging was performed in accordance with a standardized protocol. A model to determine the risk of CLNM was established using the outcomes of univariate and multivariate analyses.

RESULTS

Age of ≥45 years, male sex, mean tumor diameter of ≥1.0 cm, taller-than-wide tumor shape, multiple PTCs, capsule contact, and HBME-1 expression were significant independent risk predictors of CLNM. Hashimoto's thyroiditis, nodular goiter, andBRAF_V600E were not significantly associated with CLNM. The cutoff value (area under the curve = 0.760) for predicting risk was determined from receiver operating characteristic curves (sensitivity, 75.6 %; specificity, 60.7 %).

CONCLUSIONS

Male sex, age of ≥45 years, mean tumor diameter of ≥1.0 cm, taller-than-wide shape, multiple tumors, capsule contact, and HBME-1 expression were independent predictors of the risk of CLNM in patients with PTC. The risk model may be useful for evaluating patients' prognoses and selecting optimal surgical strategies.

Overexpression of B7H5/CD28H is associated with worse survival in human gastric cancer

Gastric cancer (GC) is a common malignancy with low 5‐year overall survival (OS). Recently, immune therapy has been used to treat cancer. B7H5 and CD28H are novel immune checkpoint molecules. However, the prognostic value of B7H5/CD28H expression in patients with GC remains unclear. In this study, seventy‐one patients diagnosed with GC were included in this study. Patients' GC tissues and matched adjacent tissue constructed a tissue microarray. The expression levels of B7H5 and CD28H were examined using immunohistochemistry. Correlations between the expression of B7H5 and CD28H and the clinical data were evaluated. We found that the expression of B7H5 and CD28H (both P = .001) were higher in GC tumour tissues than in adjacent noncancerous tissues. B7H5/CD28H expression acted as an independent predictive factor in the OS of patients with GC. High expression of B7H5 and CD28H predicted poor outcome. Patients in the B7H5+CD28H+ group had a lower 5‐year OS compared with patients in the B7H5−CD28− group (4.5% vs 55.6%, P = .001). A significant difference was found in the 5‐year OS between patients in the B7H5+CD28H− and B7H5+CD28H+ groups (33.5% vs 4.5%, P = .006). However, there was no correlation between B7H5 and CD28H expression (P = .844). Therefore, B7H5 and CD28H expression are up‐regulated in GC and are independent prognostic factors for overall survival in patients with GC. Although there was no correlation between B7H5 and CD28H expression, high expression of B7H5 and CD28H predicts poor prognosis, especially when both are highly expressed.

BRAFV600E mutation analysis in fine-needle aspiration cytology specimens for diagnosis of thyroid nodules: The influence of false-positive and false-negative results

Background

The accurate evaluation of BRAF^V600E mutation in preoperative fine‐needle aspiration cytology (FNAC) specimens is important for making management decisions in thyroid nodules (TNs). The aim of this study was to assess the false‐positive and false‐negative BRAF^V600E mutations in thyroid FNAC specimens and their influence on diagnosis of TN.

Methods

This prospective study enrolled 292 nodules in 269 patients who underwent BRAF^V600E mutation analysis using amplification refractory mutation system‐quantitative real‐time polymerase chain reaction (ARMS‐qPCR) both in FNAC specimens and formalin‐fixed, paraffin‐embedded (FFPE) tissue samples after surgery. The false‐positive and false‐negative mutations for BRAF^V600E analysis using ARMS‐qPCR in FNAC specimens were recorded, with reference to the results of BRAF^V600E mutation analysis using ARMS‐qPCR in FFPE tissue sample. Diagnostic performances of FNAC, BRAF^V600E mutation analysis in FNAC specimens, BRAF^V600E mutation analysis in FFPE tissue sample, and the combination of FNAC and BRAF^V600E mutation analysis for predicting thyroid malignancy were assessed.

Results

The false‐positive and false‐negative mutations for BRAF^V600E analysis using ARMS‐qPCR in FNAC specimens were 10.1% (19/189) and 7.1% (7/98), respectively. FNAC combined with preoperative BRAF^V600E mutation analysis significantly increased the diagnostic sensitivity from 75.7% to 92.3%, and accuracy from 78.7% to 90.6% in comparison with FNAC alone (both P < .001). No significant differences were found between the combination of FNAC and BRAF^V600E mutation analysis in FNAC specimens and the combination of FNAC and BRAF^V600E mutation analysis in FFPE tissue sample (sensitivity: 92.3% vs 91.9%; accuracy: 90.6% vs 91.3%; both P > .05).

Conclusions

FNAC combined with preoperative BRAF^V600E mutation analysis can significantly increase the diagnostic performance in comparison with FNAC alone. False‐positive and false‐negative BRAF^V600E mutation results are found in preoperative FNAC specimens, whereas it does not affect the overall auxiliary diagnosis of TNs.