The utility of routine preoperative cervical ultrasonography in patients undergoing thyroidectomy for differentiated thyroid cancer

Cervical lymph node metastasis prediction from papillary thyroid carcinoma US videos: a prospective multicenter study

BACKGROUND

Prediction of lymph node metastasis (LNM) is critical for individualized management of papillary thyroid carcinoma (PTC) patients to avoid unnecessary overtreatment as well as undesired under-treatment. Artificial intelligence (AI) trained by thyroid ultrasound (US) may improve prediction performance.

METHODS

From September 2017 to December 2018, patients with suspicious PTC from the first medical center of the Chinese PLA general hospital were retrospectively enrolled to pre-train the multi-scale, multi-frame, and dual-direction deep learning (MMD-DL) model. From January 2019 to July 2021, PTC patients from four different centers were prospectively enrolled to fine-tune and independently validate MMD-DL. Its diagnostic performance and auxiliary effect on radiologists were analyzed in terms of receiver operating characteristic (ROC) curves, areas under the ROC curve (AUC), accuracy, sensitivity, and specificity.

RESULTS

In total, 488 PTC patients were enrolled in the pre-training cohort, and 218 PTC patients were included for model fine-tuning (n = 109), internal test (n = 39), and external validation (n = 70). Diagnostic performances of MMD-DL achieved AUCs of 0.85 (95% CI: 0.73, 0.97) and 0.81 (95% CI: 0.73, 0.89) in the test and validation cohorts, respectively, and US radiologists significantly improved their average diagnostic accuracy (57% vs. 60%, P = 0.001) and sensitivity (62% vs. 65%, P < 0.001) by using the AI model for assistance.

CONCLUSIONS

The AI model using US videos can provide accurate and reproducible prediction of cervical lymph node metastasis in papillary thyroid carcinoma patients preoperatively, and it can be used as an effective assisting tool to improve diagnostic performance of US radiologists.

TRIAL REGISTRATION

We registered on the Chinese Clinical Trial Registry website with the number ChiCTR1900025592.

Predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma using deep learning

Background

The aim of this study is to design a deep learning (DL) model to preoperatively predict the occurrence of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC).

Methods

This research collected preoperative ultrasound (US) images and clinical factors of 611 PTMC patients. The clinical factors were analyzed using multivariate regression. Then, a DL model based on US images and clinical factors was developed to preoperatively predict CLNM. The model's efficacy was evaluated using the receiver operating characteristic (ROC) curve, along with accuracy, sensitivity, specificity, and the F1 score.

Results

The multivariate analysis indicated an independent correlation factors including age ≥55 (OR = 0.309, p < 0.001), tumor diameter (OR = 2.551, p = 0.010), macrocalcifications (OR = 1.832, p = 0.002), and capsular invasion (OR = 1.977, p = 0.005). The suggested DL model utilized US images achieved an average area under the curve (AUC) of 0.65, slightly outperforming the model that employed traditional clinical factors (AUC = 0.64). Nevertheless, the model that incorporated both of them did not enhance prediction accuracy (AUC = 0.63).

Conclusions

The suggested approach offers a reference for the treatment and supervision of PTMC. Among three models used in this study, the deep model relied generally more on image modalities than the data modality of clinic records when making the predictions.

Artificial intelligence-based prediction of cervical lymph node metastasis in papillary thyroid cancer with CT

OBJECTIVES

To develop an artificial intelligence (AI) system for predicting cervical lymph node metastasis (CLNM) preoperatively in patients with papillary thyroid cancer (PTC) based on CT images.

METHODS

This multicenter retrospective study included the preoperative CT of PTC patients who were divided into the development, internal, and external test sets. The region of interest of the primary tumor was outlined manually on the CT images by a radiologist who has eight years of experience. With the use of the CT images and lesions masks, the deep learning (DL) signature was developed by the DenseNet combined with convolutional block attention module. One-way analysis of variance and least absolute shrinkage and selection operator were used to select features, and a support vector machine was used to construct the radiomics signature. Random forest was used to combine the DL, radiomics, and clinical signature to perform the final prediction. The receiver operating characteristic curve, sensitivity, specificity, and accuracy were used by two radiologists (R1 and R2) to evaluate and compare the AI system.

RESULTS

For the internal and external test set, the AI system achieved excellent performance with AUCs of 0.84 and 0.81, higher than the DL (p = .03, .82), radiomics (p < .001, .04), and clinical model (p < .001, .006). With the aid of the AI system, the specificities of radiologists were improved by 9% and 15% for R1 and 13% and 9% for R2, respectively.

CONCLUSIONS

The AI system can help predict CLNM in patients with PTC, and the radiologists' performance improved with AI assistance.

CLINICAL RELEVANCE STATEMENT

This study developed an AI system for preoperative prediction of CLNM in PTC patients based on CT images, and the radiologists' performance improved with AI assistance, which could improve the effectiveness of individual clinical decision-making.

KEY POINTS

• This multicenter retrospective study showed that the preoperative CT image-based AI system has the potential for predicting the CLNM of PTC. • The AI system was superior to the radiomics and clinical model in predicting the CLNM of PTC. • The radiologists' diagnostic performance improved when they received the AI system assistance.

Construction and validation of nomograms to reduce completion thyroidectomy by predicting lymph node metastasis in low-risk papillary thyroid carcinoma

CONTEXT

More than 5 central lymph nodes metastases (CLNM) or lateral lymph node metastasis (LLNM) indicates a higher risk of recurrence in low-risk papillary thyroid carcinoma (PTC) and may lead to completion thyroidectomy (CTx) in patients initially undergoing lobectomy.

OBJECTIVE

To screen potentially high-risk patients from low-risk patients by using preoperative and intraoperative clinicopathological features to predict lymph node status.

METHODS

A retrospective analysis of 8301 PTC patients in Wuhan Union Hospital database (2009-2021) was performed according to the 2015 American Thyroid Association (ATA) and 2021 National Comprehensive Cancer Network (NCCN) guidelines, respectively. Logistic regression and best subsets regression were used to identify risk factors. Nomograms were established and externally validated using the Differentiated Thyroid Cancer in China cohort.

RESULTS

More than 5 CLNM or LLNM was detected in 1648 (19.9%) patients. Two predictive models containing age, gender, maximum tumor size, free thyroxine (FT4) and palpable node (all p < 0.05) were established. The nomogram based on NCCN criteria showed better discriminative power and consistency with a specificity of 0.706 and a sensitivity of 0.725, and external validation indicated that 76% of potentially high-risk patients could achieve preoperative conversion of surgical strategy.

CONCLUSIONS

Models based on large cohorts with good predictive performance were constructed and validated. Preoperative low-risk (T1-2N0M0) patients with age younger than 40 years, male gender, large tumor size, low FT4 and palpable nodes may be at high risk of LLNM or more than 5 CLNM, and they should receive more aggressive initial therapy to reduce CTx.

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

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.

Surgeon-performed ultrasound changes surgical management in patients with thyroid cancer

BACKGROUND

A comprehensive neck ultrasound (US) is essential in the operative planning of patients with thyroid disease. Recent literature has shown surgeon-performed US (SUS) can be more accurate than radiology-performed US for the purpose of surgical planning. Missed findings on radiology-performed ultrasound may lead to inadequate surgical management.

METHODS

A retrospective cohort study of patients undergoing total thyroidectomy with lateral neck dissection for thyroid cancer, with both radiology-performed US and SUS performed by a Head and Neck surgeon. Ultrasound findings and adherence to American Thyroid Association (ATA) guidelines were compared, and changes in management based on SUS findings were identified.

RESULTS

A total of 26 patients who underwent total thyroidectomy with lateral neck dissection met the inclusion criteria. Preconsultation US investigations fulfilled criteria as recommended by the American Thyroid Association (ATA) guidelines in 57.7%% of cases. The central and lateral neck compartments were assessed in 57.7% and 84.6% of preconsultation US investigations respectively. Central and lateral metastatic neck metastases were incorrectly reported or not reported in 78.6% and 42.3% of cases. The SUS findings prompted a change in surgical management in 65.4% of cases.

CONCLUSION

SUS changed surgical management in two thirds (65.4%) of patients. Reliance on radiology-performed ultrasound alone may result in incorrect staging. Awareness of the additional benefits of SUS is important for surgeons treating patients with thyroid disease to prevent inadequate surgery being performed.

Clinical Value of Ultrasonography and Serum Markers in Preoperative N Staging of Thyroid Cancer

We aimed to determine factors influencing lymph node metastasis (LNM) and develop a more effective method to assess preoperative N staging. Overall, data of 2130 patients who underwent thyroidectomy for thyroid cancer between 2018 and 2021 were retrospectively analysed. Patients were divided into groups according to pN0, pN1a, and pN1b stages. Pathology was used to analyse the correlation between preoperative serum marker indicators and LNM. Receiver operating characteristic curves were used to compare the diagnostic value of ultrasound (US) examination alone, serum thyroglobulin, age, and combined method for LNM. A significant moderate agreement was observed between preoperative US and postoperative pathology for N staging. Between the pN0 and pN1 (pN1a + pN1b) groups, the differences in free triiodothyronine, anti-thyroid peroxidase antibody, and serum thyroglobulin levels were statistically significant. Among the indicators, serum thyroglobulin was an independent predictor of LNM. The area under the receiver operating characteristic curve was 0.610 for serum thyroglobulin level for predicting LNM, 0.689 for US alone, and 0.742 for the combined method. Both preoperative US and serum thyroglobulin level provide a specific value when evaluating the N staging of thyroid cancer, and the combined method is more valuable in the diagnosis of LNM than US alone.

Machine Learning-Based Shear Wave Elastography Elastic Index (SWEEI) in Predicting Cervical Lymph Node Metastasis of Papillary Thyroid Microcarcinoma: A Comparative Analysis of Five Practical Prediction Models

Purpose

Although many factors determine the prognosis of papillary thyroid carcinoma (PTC), cervical lymph node metastasis (CLNM) is one of the most terrible factors. In view of this, this study aimed to build a CLNM prediction model for papillary thyroid microcarcinoma (PTMC) with the help of machine learning algorithm.

Methods

We retrospectively analyzed 387 PTMC patients hospitalized in the Department of Medical Oncology, Enshi Tujia and Miao Autonomous Prefecture Central Hospital from January 1, 2015, to January 31, 2022. Based on supervised learning algorithms, namely random forest classifier (RFC), artificial neural network(ANN), support vector machine(SVM), decision tree(DT), and extreme gradient boosting gradient(XGboost) algorithm, the LNM prediction model was constructed, and the prediction efficiency of ML-based model was evaluated via receiver operating characteristic curve(ROC) and decision curve analysis(DCA).

Results

Finally, a total of 24 baseline variables were included in the supervised learning algorithm. According to the iterative analysis results, the pulsatility index(PI), resistance index(RI), peak systolic blood flow velocity(PSBV), systolic acceleration time(SAT), and shear wave elastography elastic index(SWEEI), such as average value(Emean), maximum value(Emax), and minimum value(Emix) were candidate predictors. Among the five supervised learning models, RFC had the strongest prediction efficiency with area under curve(AUC) of 0.889 (95% CI: 0.838–0.940) and 0.878 (95% CI: 0.821–0.935) in the training set and testing set, respectively. While ANN, DT, SVM and XGboost had prediction efficiency between 0.767 (95% CI: 0.716–0.818) and 0.854 (95% CI: 0.803–0.905) in the training set, and ranged from 0.762 (95% CI: 0.705–0.819) to 0.861 (95% CI: 0.804–0.918) in the testing set.

Conclusion

We have successfully constructed an ML-based prediction model, which can accurately classify the LNM risk of patients with PTMC. In particular, the RFC model can help tailor clinical decisions of treatment and surveillance.

Diagnostic accuracy of ultrasound, CT and their combination in detecting cervical lymph node metastasis in patients with papillary thyroid cancer: a systematic review and meta-analysis

OBJECTIVES

To determine the diagnostic accuracy of ultrasound (US), CT and their combination in detecting cervical lymph node metastasis (CLNM) in patients with papillary thyroid cancer (PTC).

METHODS

Medline (via PubMed), Web of Science, Embase were searched to identify studies published till 5 December 2021 that used US and CT to detect CLNM in patients with PTC. The primary outcomes were sensitivity, specificity and diagnostic ORs in neck-level-based (lymph nodes are analysed by neck level) or patient-based (lymph nodes are analysed by patient) analysis. Secondary outcomes were sensitivity, specificity and DORs in the central and lateral compartments.

RESULTS

Fourteen studies (6167 patients with 11 601 neck lymph nodes) met the inclusion criteria. Based on the neck-level-based analysis, the pooled sensitivity, specificity and DORs were 0.35 (95% CI 0.34 to 0.37), 0.95 (95% CI 0.94 to 0.95) and 13.94 (95% CI 9.34 to 20.82) for US, were 0.46 (95% CI 0.44 to 0.47), 0.88 (95% CI 0.87 to 0.89) and 7.24 (95% CI 5.46 to 9.62) for CT, were 0.51 (95% CI 0.49 to 0.52), 0.85 (95% CI 0.84 to 0.86), 6.01 (95% CI 3.84 to 9.40) for the combination of US and CT. In the patient-based analysis, the pooled estimates of sensitivity, specificity and DOR were 0.41 (95% CI 0.36 to 0.46), 0.92 (95% CI 0.89 to 0.94) and 7.56 (95% CI 4.08 to 14.01) for US, were 0.49 (0.44 to 0.54), 0.91 (0.89 to 0.94), 9.40 (5.79 to 15.27) for CT, and were 0.64 (95% CI 0.57 to 0.71), 0.83 (95% CI 0.77 to 0.88), 8.59 (95% CI 5.37 to 13.76) for the combination of US and CT.

DISCUSSION

These findings suggest US, with a DOR almost twice that of CT in the neck-level-based analysis, was superior to CT in detecting CLNM in patients with PTC, especially in the lateral compartment. The combination of US and CT increased the sensitivity from 41%-49% for the individual modalities to 64% for combined modalities in the patient-based analysis.

Preoperative Evaluation of Central Lymph Nodes in Papillary Thyroid Carcinoma Using High-Resolution Ultrasound and Shear-Wave Elastography

ABSTRACT

The aim of this study was to discuss the diagnostic value of high-resolution ultrasound and virtual touch tissue imaging quantification (VTIQ) for distinguishing metastatic and benign central lymph nodes (CLNs) in patients with papillary thyroid carcinoma. This retrospective study involved 86 pathologically proven benign lymph nodes (LNs) and 118 metastatic LNs in patients with papillary thyroid carcinoma. We analyzed the sonographic features of CLNs (size, shape, distribution, hilum, echogenicity, cystic change, calcification, vascularity, shear-wave velocity [SWV]). The prevalence of sonographic features and the SWV was compared between metastatic and benign CLNs. The size, shape, margin, distribution, presence of hilum, echogenicity, calcification, and vascularity were significantly different between benign and metastatic CLNs (P < 0.05 for all). The mean maximum SWV for malignant CLNs was 3.139 ± 0.408 m/s, whereas that of benign CLNs was 2.418 ± 0.369 m/s (P < 0.05). The cutoff point of the SWV for differentiating benign and malignant LNs was 2.675 m/s. Logistic regression analysis showed that round or irregular shape, aggregation or fusion, calcification, and VTIQ value greater than 2.675 m/s of CLNs were independent risk factors for malignancy, with an odds ratio of 5.77, 3.05, 3.23, and 62.85, respectively. High-resolution ultrasound and VTIQ can provide valuable information for distinguishing metastatic from benign CLNs.

2020 Imaging Guidelines for Thyroid Nodules and Differentiated Thyroid Cancer: Korean Society of Thyroid Radiology

Imaging plays a key role in the diagnosis and characterization of thyroid diseases, and the information provided by imaging studies is essential for management planning. A referral guideline for imaging studies may help physicians make reasonable decisions and minimize the number of unnecessary examinations. The Korean Society of Thyroid Radiology (KSThR) developed imaging guidelines for thyroid nodules and differentiated thyroid cancer using an adaptation process through a collaboration between the National Evidence-based Healthcare Collaborating Agency and the working group of KSThR, which is composed of radiologists specializing in thyroid imaging. When evidence is either insufficient or equivocal, expert opinion may supplement the available evidence for recommending imaging. Therefore, we suggest rating the appropriateness of imaging for specific clinical situations in this guideline.

Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study

OBJECTIVES

This study aimed to develop a computed tomography (CT)-based radiomics model to predict central lymph node metastases (CLNM) preoperatively in patients with papillary thyroid carcinoma (PTC).

METHODS

In this retrospective study, 678 patients with PTC were enrolled from Yantai Yuhuangding Hot3spital (n=605) and the Affiliated Hospital of Binzhou Medical University (n=73) within August 2010 to December 2020. The patients were randomly divided into a training set (n=423), an internal test set (n=182), and an external test set (n=73). Radiomics features of each patient were extracted from preoperative plain scan and contrast-enhanced CT images (arterial and venous phases). One-way analysis of variance (ANOVA) and least absolute shrinkage and selection operator algorithm were used for feature selection. The K-nearest neighbor, logistics regression, decision tree, linear-support vector machine (linear-SVM), Gaussian-SVM, and polynomial-SVM algorithms were used to establish radiomics models for CLNM prediction. The clinical risk factors were selected by ANOVA and multivariate logistic regression. Incorporated with clinical risk factors, a combined radiomics model was established for the preoperative prediction of CLNM in patients with PTCs. The performance of the combined radiomics model was evaluated using the receiver operating characteristic (ROC) and calibration curves in the training and test sets. The clinical usefulness was evaluated through decision curve analysis (DCA).

RESULTS

A total of 4227 radiomic features were extracted from the CT images of each patient, and 14 non-zero coefficient features associated with CLNM were selected. Four clinical variables (sex, age, tumor diameter, and CT-reported lymph node status) were significantly associated with CLNM. Linear-SVM led to the best prediction model, which incorporated radiomic features and clinical risk factors. Areas under the ROC curves of 0.747 (95% confidence interval [CI] 0.706-0.782), 0.710 (95% CI 0.634-0.786), and 0.764 (95% CI 0.654-0.875) were obtained in the training, internal, and external test sets, respectively. The linear-SVM algorithm also showed better sensitivity (0.702 [95% CI 0.600-0.790] vs. 0.477 [95% CI 0.409-0.545]) and accuracy (0.670 [95% CI 0.600-0.738] vs. 0.642 [95% CI 0.569-0.712]) than an experienced radiologist in the internal test set in the combined radiomics model. The calibration plot reflected a favorable agreement between the actual and estimated probabilities of CLNM. The DCA indicated the clinical usefulness of the combined radiomics model.

CONCLUSION

The combined radiomics model is a non-invasive preoperative tool that incorporates radiomic features and clinical risk factors to predict CLNM in patients with PTC.

Preoperative Prediction of Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma via Conventional and Contrast-Enhanced Ultrasound

OBJECTIVES

To investigate the independent risk factors for cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) and establish a prediction model via conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS).

METHODS

A total of 275 patients with single PTC, who were admitted to our hospital from January 2016 to December 2018, were enrolled in this study. The clinical characteristics and features of the tumor on conventional US and CEUS were retrospectively analyzed. A binary logistic regression model was established, and the diagnostic efficacy of conventional US and CEUS was compared.

RESULTS

The binary logistic regression analysis showed that age younger than 38 years, size of 10.0 mm or greater, solid composition, peak of the nodule interior of 28.3750 or greater, and area under the curve (AUC) of the peripheral ring of less than 3.2500 were independent risk factors of CLNM (P < .05, for all). Prediction model: Logit (p) = -4.135 + 1.040 (age) + 1.920 (size) + 1.769 (composition) + 1.230 (peak of nodule interior) + 0.812 (AUC of peripheral ring). The model positively predicted CLNM at a value of L > -0.199. The AUC, sensitivity, and negative predictive value of the receiver operating characteristic curve for the model were 0.727, 71.7%, and 75.2%, respectively, which were significantly higher than those of conventional US (Z = -2.403; P = .016; Z = -5.330; P < .001; and Z = -2.390; P = .017). The specificity of the model was 73.7%, which was lower than that of conventional US (Z = 3.508; P < .001).

CONCLUSIONS

The preoperative prediction model established via conventional US and CEUS may be helpful to evaluate CLNM in patients with PTC and determine the appropriate treatment options.

Lymph node metastasis prediction of papillary thyroid carcinoma based on transfer learning radiomics

Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) is of great value for the treatment option selection. The purpose of this paper is to develop a transfer learning radiomics (TLR) model for preoperative prediction of LNM in PTC patients in a multicenter, cross-machine, multi-operator scenario. Here we report the TLR model produces a stable LNM prediction. In the experiments of cross-validation and independent testing of the main cohort according to diagnostic time, machine, and operator, the TLR achieves an average area under the curve (AUC) of 0.90. In the other two independent cohorts, TLR also achieves 0.93 AUC, and this performance is statistically better than the other three methods according to Delong test. Decision curve analysis also proves that the TLR model brings more benefit to PTC patients than other methods.

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.

SEOM clinical guideline thyroid cancer (2019)

Thyroid carcinoma is the most frequent endocrine malignancy and accounts for around 3% of global cancer incidence. Different histologies and clinical scenarios make necessary a multidisciplinary approach that includes new diagnostic methods and surgical, radiopharmaceutical and systemic therapies. This guideline updates several aspects of management of thyroid cancer.

Preoperative Ultrasonographic Staging of Papillary Thyroid Carcinoma With the Eighth American Joint Committee on Cancer Tumor-Node-Metastasis Staging System

OBJECTIVE

The purpose of this study was to evaluate the performance of preoperative ultrasonography (US) in the staging of papillary thyroid carcinoma (PTC) according to the eighth AJCC TNM classification system, to determine the effect of the preoperative US staging in the management of PTC.

PATIENTS AND METHODS

Preoperative US was performed by 2 highly trained sonographers in 665 consecutive patients with PTC, and the T and N categories were determined preoperatively. The accuracy of preoperative US in clinical staging was evaluated based on the histopathological specimens according to the eighth AJCC TNM classification. Further analysis was performed to identify the high-risk factors of N1b stage.

RESULTS

Overall accuracy of preoperative US for T stage was 92.5% (615/665). The accuracy of sonographic evaluation for T was high except for the T4a. Overall accuracy of preoperative US for N stage was 59% (426/655). The accuracies of sonographic evaluation for N0, N1a, and N1b were 81.8% (274/335), 33.3% (70/250), and 87.5% (70/80), respectively. Of 250 N1a patients, 164 (65.6%) were underestimated by US. Univariate and multivariate analyses showed that larger tumor diameter, multifocality, and higher T stage significantly increase the risk of N1b stage (P < 0.01).

CONCLUSIONS

Preoperative US was useful for the evaluation in staging of PTC, but some limitations still existed. For higher-risk patients of N1b (larger tumor size, multifocality, and higher T stage), preoperative US examination for lateral neck region should be further emphasized, and prophylactic lateral nodal dissection should be determined based on both preoperative imaging results and intraoperative evaluation.

Controversial Issues in Thyroid Cancer Management

The lack of prospective randomized clinical trials for most management topics in differentiated thyroid cancer forces us to make management recommendations based on retrospective observational data, which are often incomplete, subject to selection bias, and conflicting. Therefore, it is not surprising that many aspects of thyroid cancer management remain controversial and not well defined. This review will examine the controversies surrounding 3 important topics in thyroid cancer management: the option of thyroid lobectomy as initial therapy, the use of preoperative neck imaging to optimize the completeness of the initial surgery, and the selective use of radioactive iodine for remnant ablation, adjuvant treatment, or treatment for known persistent or recurrent disease. As thyroid cancer management moves toward a much more risk-adapted approach to personalized recommendations, clinicians and patients must balance the risks and benefits of the potential options to arrive at a plan that is optimized regarding both patient preferences/values and the philosophy/experience of the local disease management team.

Risk of recurrence in a homogeneously managed pT3-differentiated thyroid carcinoma population

BACKGROUND

International guidelines for the management of differentiated thyroid cancers are based on the 7th TNM classification: pT3 tumors are defined as differentiated thyroid cancers (DTCs) measuring more than 4 cm in their greatest dimension that are limited to the thyroid or any tumor with minimal extrathyroidal extension (ETE; sternothyroid muscle or perithyroid soft tissues). Differences in clinicohistological features and prognosis among patients with pT3 tumors remain controversial, and studies regarding pT3 subgroups are lacking.

OBJECTIVE

To analyze the prognosis of four subgroups of pT3 DTCs (papillary, PTC; or follicular, FTC).

DESIGN AND SETTING

The data of patients who underwent surgery for pT3 DTC between 1978 and 2015 in a surgical department specialized in endocrine surgery were reviewed. Patients were classified into four groups as follows: the pT3a (≤ 10 mm with ETE), pT3b (10-40 mm with ETE), pT3c (> 40 mm without ETE), and pT3d groups (> 40 mm with ETE). Recurrence-free survival (RFS) was analyzed using the Kaplan-Meier method.

RESULTS

One thousand eighty-eight patients with pT3 DTC were included, of whom 311 (29%) had pT3a; 548 (50%), pT3b; 165 (15%), pT3c; and 64 (6%), pT3d. For the 916 patients with lymph node (LN) dissection, metastatic LNs were more frequent in the pT3b and pT3d groups (61 and 61%, respectively) than in the other groups (44% pT3a and 10% pT3c; p < 0.001). During the median follow-up period of 9 years (range, 2-38 years), recurrence occurred in 169 patients with T3 tumors (16%), including 18 with pT3a (6%), 100 with pT3b (18%), 20 with pT3c (12%), and 31 with pT3d (48%). In a multivariate analysis, LN metastases (< 0.0001), extranodal extension (p = 0.03), FTC (vs. PTC) (p = 0.006), pT3b (p = 0.016), and pT3d (p = 0.047) were associated with an increased risk of recurrence. The 5-year RFS rates were 94.5, 82.2, 91.1, and 50.3% for the pT3a, pT3b, pT3c, and pT3d groups, respectively (p < 0.01).

CONCLUSION

Except for microcarcinoma, the risk of LN involvement is high and similar for the DTC patients with minimal ETE, regardless of the size of the tumor. The association of a tumor size of > 4 cm and ETE are associated with a poor prognosis and should justify the classification of these cases as a high-risk group. Other pT3 patients with no LN metastases could be individualized as a low-risk group.

Latero-cervical lymph node metastases (N1b) represent an additional risk factor for papillary thyroid cancer outcome

PURPOSE

Papillary thyroid carcinoma (PTC), the most common thyroid cancer histotype, has a good prognosis even when spread to the neck lymph node (LN). The prognostic role of LN metastases' location is still controversial. The aim of the present study was to evaluate the clinical relevance of the number and location of LN metastases at presentation in PTCs.

METHODS

This retrospective study included a consecutive series of 1653 PTC patients followed for a mean period of 5.9 years in a referral thyroid cancer clinic. All patients have undergone thyroidectomy with the dissection of at least six LNs. According to the LN status, patients were subdivided into 569 N0 (34.4%), 644 N1a (39.0%, central compartment) and 440 N1b (26.6%, latero-cervical compartment).

RESULTS

Age at diagnosis was significantly lower in N1b (39.8, IQR 30.7-51.6) and N1a (40.1, IQR 31.3-50.1) than in N0 (44.7, IQR 36.6-55.0 yrs). The male gender was more prevalent in N1b than in N1a and N0 (F/M = 1.9/1, 4.0/1 and 5.5/1, respectively). Persistent/recurrent disease at last control was significantly more frequent in N1b (29.8%) than in N1a (14.3%), and in N1a than in N0 (4.2%) (p < 0.01 for all). Also, distant metastases were significantly (p < 0.001) more frequent in N1b (14.1%) than in N1a (4.3%) and N0 (1.6%). LN metastases' number (>5) was a significant risk factor for persistent/recurrent disease only for N1a patients.

CONCLUSIONS

These data indicate that persistent/recurrent disease and distant metastases are significantly more frequent in patients with latero-cervical LN (N1b) metastases and that the LN location should be used for a better postsurgical risk stratification.

Thyroid cancer

Thyroid cancer is the fifth most common cancer in women in the USA, and an estimated over 62 000 new cases occurred in men and women in 2015. The incidence continues to rise worldwide. Differentiated thyroid cancer is the most frequent subtype of thyroid cancer and in most patients the standard treatment (surgery followed by either radioactive iodine or observation) is effective. Patients with other, more rare subtypes of thyroid cancer-medullary and anaplastic-are ideally treated by physicians with experience managing these malignancies. Targeted treatments that are approved for differentiated and medullary thyroid cancers have prolonged progression-free survival, but these drugs are not curative and therefore are reserved for patients with progressive or symptomatic disease.

Why Thyroid Surgeons Are Frustrated with Radiologists: Lessons Learned from Pre- and Postoperative US

Optimal treatment of thyroid cancer is highly dependent on accurate staging of the extent of disease at presentation. Preoperative ultrasonography (US) is the most sensitive method for detecting metastatic lymph nodes and is recommended as part of the standard preoperative workup. Missed findings on preoperative scans may lead to understaging and inadequate surgical management, which subsequently predispose these patients to residual disease postoperatively and a higher risk for recurrence, possibly requiring repeat surgery. Traditionally, thyroid US for pre- and postoperative staging has been performed by radiologists. However, there is a growing trend away from radiologist-performed US in favor of surgeon-performed US. Recent surgical and endocrinology literature has shown that, when compared with surgeon-performed US, radiologist-performed preoperative staging US is less accurate and is inadequate for presurgical planning, with higher local recurrence rates. This review highlights the importance of accurate preoperative US for patients with differentiated thyroid cancer, with specific attention to deficiencies that exist in general radiology department thyroid US reports. We present a standardized approach to neck US reporting that incorporates the newly updated 2015 recommendations from the American Thyroid Association and also addresses the pertinent questions for thyroid surgeons. By ensuring comprehensive preoperative assessment and improving thyroid US reporting, we seek to improve patient access to optimized care. ^©RSNA, 2016.

Recurrence rate in regional lymph nodes in 737 patients with follicular or Hürthle cell neoplasms

BACKGROUND

Preoperative ultrasound (US) evaluation of central and lateral neck compartments is recommended for all patients undergoing a thyroidectomy for malignant or suspicious for malignancy cytologic or molecular findings. Our aim was to find out how frequent was recurrence in regional lymph nodes in patients with follicular or Hürthle cell neoplasm and usefulness of preoperative neck US investigation in patients with neoplasm.

PATIENTS AND METHODS

Altogether 737 patients were surgically treated because of follicular or Hürthle cell neoplasms from 1995 to 2014 at our cancer comprehensive center, among them 207 patients (163 females, 44 males; mean age 52 years) had thyroid carcinoma.

RESULTS

Carcinoma was diagnosed in follicular and Hürthle cell neoplasm in 143/428 and 64/309 of cases, respectively. A recurrence in regional lymph nodes occurred in 12/207 patients (6%) during a median follow-up of 55 months. Among patients with carcinoma a recurrence in regional lymph nodes was diagnosed in follicular and Hürthle cell neoplasms in 2% and 14%, respectively (p = 0.002). Recurrence in regional lymph nodes was diagnosed in 3/428 of all patients with follicular neoplasm and 9/309 of all patients with Hürthle cell neoplasm.

CONCLUSIONS

Recurrence in lymph nodes was diagnosed in 0.7% of patients with a preoperative diagnosis of follicular neoplasm and 3% of patients with a Hürthle cell neoplasm. A recurrence in regional lymph nodes is rare in patients with carcinoma and preoperative diagnosis of follicular neoplasm. Preoperative neck ultrasound examination in patients with a follicular neoplasm is probably not useful, but in patients with Hurtle cell neoplasm it may be useful.

2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer

BACKGROUND

Thyroid nodules are a common clinical problem, and differentiated thyroid cancer is becoming increasingly prevalent. Since the American Thyroid Association's (ATA's) guidelines for the management of these disorders were revised in 2009, significant scientific advances have occurred in the field. The aim of these guidelines is to inform clinicians, patients, researchers, and health policy makers on published evidence relating to the diagnosis and management of thyroid nodules and differentiated thyroid cancer.

METHODS

The specific clinical questions addressed in these guidelines were based on prior versions of the guidelines, stakeholder input, and input of task force members. Task force panel members were educated on knowledge synthesis methods, including electronic database searching, review and selection of relevant citations, and critical appraisal of selected studies. Published English language articles on adults were eligible for inclusion. The American College of Physicians Guideline Grading System was used for critical appraisal of evidence and grading strength of recommendations for therapeutic interventions. We developed a similarly formatted system to appraise the quality of such studies and resultant recommendations. The guideline panel had complete editorial independence from the ATA. Competing interests of guideline task force members were regularly updated, managed, and communicated to the ATA and task force members.

RESULTS

The revised guidelines for the management of thyroid nodules include recommendations regarding initial evaluation, clinical and ultrasound criteria for fine-needle aspiration biopsy, interpretation of fine-needle aspiration biopsy results, use of molecular markers, and management of benign thyroid nodules. Recommendations regarding the initial management of thyroid cancer include those relating to screening for thyroid cancer, staging and risk assessment, surgical management, radioiodine remnant ablation and therapy, and thyrotropin suppression therapy using levothyroxine. Recommendations related to long-term management of differentiated thyroid cancer include those related to surveillance for recurrent disease using imaging and serum thyroglobulin, thyroid hormone therapy, management of recurrent and metastatic disease, consideration for clinical trials and targeted therapy, as well as directions for future research.

CONCLUSIONS

We have developed evidence-based recommendations to inform clinical decision-making in the management of thyroid nodules and differentiated thyroid cancer. They represent, in our opinion, contemporary optimal care for patients with these disorders.

Preoperative High-Resolution Ultrasound for the Assessment of Malignant Central Compartment Lymph Nodes in Papillary Thyroid Cancer

BACKGROUND

The identification and removal of malignant central compartment lymph nodes (MCLN) is important to minimize the risk of persistent or recurrent local disease in patients with papillary thyroid cancer (PTC). While the diagnostic accuracy of preoperative ultrasound for the assessment of lateral compartment node metastases is well recognized, its role in the identification of central compartment node metastases in patients with PTC is less established. This study delineates the utility of high-resolution ultrasound (HUS) for the assessment of MCLN in patients with PTC.

METHODS

A retrospective chart review was performed of 227 consecutive patients who underwent total thyroidectomy for biopsy-proven PTC by a single endocrine surgeon in an academic tertiary care center between 2004 and 2014. Preoperative sonographic results were compared to postoperative pathology reports to determine the accuracy of HUS for the assessment of MCLN. Statistical analysis also included sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

HUS identified abnormal central compartment nodes in 51 (22.5%) patients. All 227 patients underwent a careful central compartment node exploration. One hundred and four (45.8%) patients had MCLN identified by surgery, of whom 65 (62.5%) had a negative preoperative central compartment HUS. The sensitivity and specificity of preoperative HUS for the assessment of MCLN were 0.38 and 0.90, respectively. The PPV and NPV were 0.76 and 0.63, with an accuracy of 0.66.

CONCLUSION

Preoperative HUS is quite specific for the identification of MCLN in patients with PTC. The present findings emphasize, however, that a negative HUS does not obviate the need for careful exploration of the central compartment to minimize the risk of persistent or recurrent local disease.

Recent Changes in the Clinical Outcome of Papillary Thyroid Carcinoma With Cervical Lymph Node Metastasis

CONTEXT

The prognosis of papillary thyroid cancer (PTC) with cervical lymph node (LN) metastasis has changed with increased detection of subclinical metastatic LNs. The number and size of metastatic LNs were proposed as new prognostic factors in PTC with cervical LN metastasis (N1).

OBJECTIVE

The objective of the study was to evaluate changes in N1 PTC characteristics and clinical outcome over time and to confirm the prognostic value of the number and size of metastatic LNs.

DESIGN AND PATIENTS

This study included 1815 N1 PTC patients diagnosed between 1997 and 2011. Patients were classified into three risk groups according to the number and size of metastatic LNs: very low risk, five or fewer and 0.2 cm or less; low risk, five or fewer and 0.2 cm or greater; and high risk, more than five.

MAIN OUTCOME MEASURES

Response to initial therapy and disease-free survival (DFS) was measured.

RESULTS

Metastatic LNs became smaller, and the ratio of metastatic LNs, which represents the extent of LN involvement and the completeness of surgery, decreased significantly over time. The proportion of patients with excellent response significantly increased from 33% to 67% over time (P < .001). These improvements were more evident in the low- and high-risk groups than in the very low-risk group. The DFS 5 years after initial surgery was also significantly increased from 73% to 91% over time (P < .001). The new LN classification was strongly associated with outcome. Patients in the very low-risk group had longer DFS than those in the low- and high-risk groups during the study period.

CONCLUSIONS

The clinical outcome of N1 PTC has significantly changed over time with the earlier detection of thyroid cancers with less extensive LN involvement. More complete surgical neck dissection also might be responsible for these changes. The number and size of metastatic LNs are important prognostic factors of recurrence in N1 PTC.