CLINICAL PRACTICE. Thyroid Nodules

High-Performance Metabolic Profiling of High-Risk Thyroid Nodules by ZrMOF Hybrids

Thyroid nodules (TNs) have emerged as the most prevalent endocrine disorder in China. Fine-needle aspiration (FNA) remains the standard diagnostic method for assessing TN malignancy, although a majority of FNA results indicate benign conditions. Balancing diagnostic accuracy while mitigating overdiagnosis in patients with benign nodules poses a significant clinical challenge. Precise, noninvasive, and high-throughput screening methods for high-risk TN diagnosis are highly desired but remain less explored. Developing such approaches can improve the accuracy of noninvasive methods like ultrasound imaging and reduce overdiagnosis of benign nodule patients caused by invasive procedures. Herein, we investigate the application of gold-doped zirconium-based metal-organic framework (ZrMOF/Au) nanostructures for metabolic profiling of thyroid diseases. This approach enables the efficient extraction of urine metabolite fingerprints with high throughput, low background noise, and reproducibility. Utilizing partial least-squares discriminant analysis and four machine learning models, including neural network (NN), random forest (RF), logistic regression (LR), and support vector machine (SVM), we achieved an enhanced diagnostic accuracy (98.6%) for discriminating thyroid cancer (TC) from low-risk TNs by using a diagnostic panel. Through the analysis of metabolic differences, potential pathway changes between benign nodule and malignancy are identified. This work explores the potential of rapid thyroid disease screening using the ZrMOF/Au-assisted LDI-MS platform, providing a potential method for noninvasive screening of thyroid malignant tumors. Integrating this approach with imaging technologies such as ultrasound can enhance the reliability of noninvasive diagnostic methods for malignant tumor screening, helping to prevent unnecessary invasive procedures and reducing the risk of overdiagnosis and overtreatment in patients with benign nodules.

Reinforced Computer-Aided Framework for Diagnosing Thyroid Cancer

Thyroid cancer is the most pervasive disease in the endocrine system and is getting extensive attention. The most prevalent method for an early check is ultrasound examination. Traditional research mainly concentrates on promoting the performance of processing a single ultrasound image using deep learning. However, the complex situation of patients and nodules often makes the model dissatisfactory in terms of accuracy and generalization. Imitating the diagnosis process in reality, a practical diagnosis-oriented computer-aided diagnosis (CAD) framework towards thyroid nodules is proposed, using collaborative deep learning and reinforcement learning. Under the framework, the deep learning model is trained collaboratively with multiparty data; afterward classification results are fused by a reinforcement learning agent to decide the final diagnosis result. Within the architecture, multiparty collaborative learning with privacy-preserving on large-scale medical data brings robustness and generalization, and diagnostic information is modeled as a Markov decision process (MDP) to get final precise diagnosis results. Moreover, the framework is scalable and capable of containing more diagnostic information and multiple sources to pursue a precise diagnosis. A practical dataset of two thousand thyroid ultrasound images is collected and labeled for collaborative training on classification tasks. The simulated experiments have shown the advancement of the framework in promising performance.

Clinical risk factors and cancer risk of thyroid imaging reporting and data system category 4 A thyroid nodules

PURPOSE

Beyond the Thyroid Imaging Reporting and Data System (TIRADS) classification of thyroid nodules, additional factors must be weighed in the decision to perform fine needle aspiration (FNA). In this study, we aimed to identify risk factors for malignancy in patients with ultrasound-classified Chinese-TIRADS (C-TIRADS) 4 A nodules.

METHODS

Patients who underwent thyroid FNA at our institution between May 2021 and September 2022 were enrolled. We collected demographic data, including age, sex, previous radiation exposure, and family history. An in-person questionnaire was used to collect lifestyle data, such as smoking habits and alcohol consumption. Body mass index (BMI) was calculated. The serum levels of thyroid stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb), and thyroglobulin antibody (TGAb) were measured. Prior to FNA, ultrasonic inspection reports were reviewed. The cytologic diagnoses for FNA of thyroid nodules followed the Bethesda System for Reporting Thyroid Cytopathology (2017).

RESULTS

Among the 252 C-TIRADS 4 A nodules, 103 were malignant. Compared to those in the benign group, the patients in the malignant group had a younger age (42.2 ± 13.6 vs. 51.5 ± 14.0 years, P < 0.001). Logistic regression showed that advanced age was associated with a lower risk of malignancy in C-TIRADS 4 A nodules (OR = 0.95, 95% CI 0.93 ~ 0.97, P < 0.001). We demonstrated a decreased risk of malignancy in patients with 48.5 years or older.

CONCLUSION

Advanced age was associated with a decreased risk of malignancy in patients with C-TIRADS 4 A nodules. This study indicated that in addition to sonographic characteristics, patient age should be considered when assessing the risk of malignancy.

A nationwide registry-based observational study of thyroid disease incidence in the Faroe Islands

OBJECTIVE

The occurrence of thyroid disease varies among populations. While the iodine nutrition level of the Faroese seems to have been decreasing over the past decades, there is no systematic evaluation of the thyroid disease pattern in the Faroe Islands. Such knowledge of thyroid disease occurrence in the North Atlantic region may support healthcare planning and prevention. To investigate incidence rates, including subtypes of thyroid diseases, and demographic characteristics of thyroid disease patients in the Faroe Islands, to improve understanding of the patterns and trends of these disorders.

DESIGN AND METHOD

A registry-based observational study was conducted over 10 years, encompassing all adult Faroese individuals.

PATIENTS AND MEASUREMENTS

Health records from general practitioners and hospitals were used to identify incident cases of thyroid diseases. Validation was performed using multiple data sources. The incidence rates were standardised using population data from the middle of the study period 2006-2018.

RESULTS

Among the 1152 individuals diagnosed with thyroid disease, the standardised incidence rates per 100,000 person-years were 55 for hyperthyroidism and 112 for hypothyroidism, and around four times higher in women than in men. Hashimoto's thyroiditis was the dominant cause of hypothyroidism, while Graves' disease was the leading cause of hyperthyroidism. The incidence of hypothyroidism increases with age. A decreasing trend was observed over time for both hypothyroidism and hyperthyroidism.

CONCLUSION

Considering the decrease in iodine nutrition levels over the past decades, we were surprised by the high incidence of autoimmune thyroid disease. The findings highlight the need for continuous monitoring of thyroid disease occurrence in coastal areas of the North Atlantic Ocean.

IRX5's influence on macrophage polarization and outcome in papillary thyroid cancer

Background

With a rise in recent years, thyroid cancer (TC) is the most prevalent hormonal cancer worldwide. It is essential to investigate the inherent variability at the molecular level and the immune environment within tumors of various thyroid cancer subtypes in order to identify potential targets for therapy and provide precise treatment for patients with thyroid adenocarcinoma.

Methods

First, we analyzed the expression of IRX5 in pan-cancer and papillary thyroid carcinoma by bioinformatics methods and collected paired samples from our center for validation. Subsequently, we analyzed the significance of IRX5 on the prognosis and diagnosis of PTC. Next, we explored the possible mechanisms by which IRX5 affects the prognosis of thyroid cancer patients by GO/KEGG enrichment analysis, and further investigated the effect of IRX5 on immune infiltration of thyroid cancer. Ultimately, by conducting experiments on cells and animals, we were able to show how IRX5 impacts the aggressive characteristics of thyroid cancer cells and its influence on macrophages within the immune system of thyroid cancer.

Results

In 11 malignant tumors, including PTC, IRX5 is overexpressed and associated with a poor prognosis. IRX5 may affect the prognosis of PTC through embryonic organ development, ossification, mesenchyme development, etc. Increased IRX5 expression decreases the presence of cytotoxic and Th17 cells in papillary thyroid cancer. IRX5 was highly expressed in different PTC cell lines, such as K-1 and TPC-1. Silencing IRX5 effectively halted the growth and movement of PTC cells while also decreasing M2 polarization and enhancing M1 polarization in tumor-associated macrophages.

Conclusion

IRX5 could impact the outlook of individuals with PTC by stimulating the shift of macrophages to M2 in the immune surroundings of thyroid cancer growths, suggesting a potential new focus for treating thyroid cancer, particularly through immunotherapy.

Traditional Chinese medicine treatment for benign thyroid nodules: Literature review

Thyroid nodules (TNs) are pathological changes characterized by abnormal proliferation of thyroid gland tissue. Approximately 19% to 67% of asymptomatic individuals are diagnosed with TNs, with the majority being benign nodules and 4% to 6.5% being thyroid cancer nodules. Western medicine recommends regular examinations and surgery, while traditional Chinese medicine (TCM) provides an alternative choice to maintain thyroid function and reduce the need for surgery. However, in Taiwan, research on TCM treatment for benign TNs is primarily limited to case reports, lacking large-scale and systematic clinical studies. We conducted a search of electronic databases including PubMed, Google Scholar, Wanfang Data, and China National Knowledge Infrastructure to collect clinical trials related to TCM treatment for TNs. Our goal is to provide new treatment options, further validate the value of TCM in the treatment of TNs, and lay a foundation for future clinical research.

Correlation of TIRADS scoring in thyroid nodules with preoperative fine needle aspiration biopsy and postoperative specimen pathology

INTRODUCTION

The aim of our study is to determine the value of Thyroid Imaging Reporting and Data Systems (TIRADS) scoring in predicting malignancy in thyroid nodules by examining its relationship with fine needle aspiration biopsy and postoperative histopathological results.

MATERIALS AND METHODS

In this study, patients who underwent surgery after ultrasonographic examination and fine needle aspiration biopsy for thyroid nodules at the General Surgery Clinic of Çukurova University Faculty of Medicine between January 2014 and November 2021 were retrospectively analyzed. The thyroid ultrasonography and fine needle aspiration biopsy of the included patients were performed by a clinician with 15 years of experience. The ultrasonographic features of the nodules were re-evaluated by the same clinician, and the American College of Radiology (ACR) TIRADS score was determined. Fine needle aspiration biopsy results were grouped according to Bethesda criteria. Postoperative histopathological examination results were divided into two groups: benign and malignant. The ACR TIRADS score was compared with fine needle aspiration biopsy and histopathological results. The performance of the ACR TIRADS score in predicting malignancy was determined.

RESULTS

79.8% of the 397 patients were female, and the mean age was 50.9 ± 12.8 years. The mean diameter of the nodules was 27.4 ± 15.8 mm. There was a significant, positive, but weak correlation between ACR TIRADS and Bethesda (p < 0.001) (r = 0.33). When the ACR TIRADS score was compared with histopathological results, it was found that the rate of malignancy increased as the TIRADS score increased (p < 0.001). The rates of malignancy diagnosis were 0% for TR1, 13.2% for TR2, 21.7% for TR3, 50.3% for TR4, and 72.4% for TR5. The area under the receiver operating characteristic curve for TIRADS in predicting malignancy was 0.747 (95% CI: 0.699-0.796, p < 0.001). TIRADS can distinguish malignancy with 75% accuracy. The optimal cutoff point was determined as TR4 with 80.3% sensitivity and 60.8% specificity.

CONCLUSION

The ACR TIRADS scoring system is an effective risk classification system for thyroid nodules, providing 75% accuracy in predicting malignancy, with 80.3% sensitivity and 60.8% specificity values.

Associations of Combined Exposure to Metabolic and Inflammatory Indicators with Thyroid Nodules in Adults: A Nested Case-Control Study

Objective

To explore associations of combined exposure to metabolic/inflammatory indicators with thyroid nodules.

Methods

We reviewed personal data for health screenings from 2020 to 2021. A propensity score matching method was used to match 931 adults recently diagnosed with thyroid nodules in a 1 : 4 ratio based on age and gender. Conditional logistic regression and Bayesian kernel machine regression (BKMR) were used to explore the associations of single metabolic/inflammatory indicators and the mixture with thyroid nodules, respectively.

Results

In the adjusted models, five indicators (ORQ4 vs. Q1: 1.30, 95% CI: 1.07-1.58 for fasting blood glucose; ORQ4 vs. Q1: 1.30, 95% CI: 1.08-1.57 for systolic blood pressure; ORQ4 vs. Q1: 1.26, 95% CI: 1.04-1.53 for diastolic blood pressure; ORQ4 vs. Q1: 1.23, 95% CI: 1.02-1.48 for white blood cell; ORQ4 vs. Q1: 1.28, 95% CI: 1.07-1.55 for neutrophil) were positively associated with the risk of thyroid nodules, while high-density lipoproteins (ORQ3 vs. Q1: 0.75, 95% CI: 0.61-0.91) were negatively associated with the risk of thyroid nodules. Univariate exposure-response functions from BKMR models showed similar results. Moreover, the metabolic and inflammatory mixture exhibited a significant positive association with thyroid nodules in a dose-response pattern, with systolic blood pressure being the greatest contributor within the mixture (conditional posterior inclusion probability of 0.82). No interaction effects were found among the five indicators. These associations were more prominent in males, participants with higher age (≥40 years old), and individuals with abnormal body mass index status.

Conclusions

Levels of the metabolic and inflammatory mixture have a linear dose-response relationship with the risk of developing thyroid nodules, with systolic blood pressure levels being the most important contributor.

Ultrasound Features and Performance of Afirma Gene Sequencing Classifier in Cytologically Indeterminate Thyroid Nodules

Background

Cytologically indeterminate thyroid nodules (ITN) pose a management challenge. Here we analyze if adding ultrasound characteristics to Afirma Genome Sequence Classifier (GSC) results increases GSC diagnostic performance.

Methods

We retrospectively analyzed 237 GSC-tested Bethesda III/IV ITNs between July 2017 and December 2019 and classified them by American Thyroid Association (ATA) and the Thyroid Imaging Reporting and Data System (TIRADS) of the American College of Radiology.

Results

The benign call rate was higher in Bethesda III ITNs with TIRADS <5 vs TIRADS 5 (89% vs 68%. P = .015). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of GSC in ATA high-risk Bethesda III ITNs vs lower were 100% vs 80% (P = 1), 89.5% vs 91.5% (P = .67), 66.7% vs 25% (P = .13), and 100% vs 99.2% (P = 1), respectively, and for TIRADS 5 vs <5 were 100% vs 80% (P = 1), 88.2% vs 91.4% (P = .65), 71.4% vs 23.5% (P = .06), and 100% vs 99.3% (P = 1). The sensitivity, specificity, PPV, and NPV of GSC in high-risk ATA Bethesda IV ITNs vs lower were 66.7% vs 100% (P = .42), 83.3% vs 85.7% (P = 1), 66.7% vs 64.3% (P = 1), and 83.3% vs 100% (P = .3), respectively, and for TIRADS 5 vs <5 were 66.7% vs 90% (P = .42), 88.9% vs 83.8% (P = 1), 66.7% vs 60% (P = 1), and 88.9% vs 96.9% (P = .39).

Conclusion

Sensitivity, specificity, NPV, and PPV of GSC were not significantly different in ATA high-risk and TIRADS 5 ITNs compared to ATA < high-risk and TIRADS 1-4 ITNs.

Malignancy in a Solitary Thyroid Nodule: A Retrospective Histopathological Evaluation

Objective

This study aimed to assess the presence and type of malignancy in patients who underwent thyroid surgery for solitary thyroid nodules.

Methods

A retrospective review was performed of the case notes of all adult patients with solitary thyroid nodules who underwent thyroid surgery from 1 January 2019 to 31 October 2022. All patients had solitary thyroid nodules identified by ultrasonography. The electronic records of our pathology department were used to determine the pathological diagnosis.

Results

Forty-two patients with solitary thyroid nodules underwent thyroid surgery. The mean age at presentation was 39.1 ± 12.6 years, and 76.2% of patients were female. The malignancy rate was 31%. Further histopathological analysis found that malignant solitary thyroid nodules were mostly papillary carcinoma.

Conclusion

This study indicates that solitary thyroid nodules should be evaluated thoroughly and treated with a high index of suspicion because they have a high chance (31%) of being malignant.

The role of primary cilia in thyroid diseases

Primary cilia (PC) are non-motile and microtube-based organelles protruding from the surface of almost all thyroid follicle cells. They maintain homeostasis in thyrocytes and loss of PC can result in diverse thyroid diseases. The dysfunction of structure and function of PC are found in many patients with common thyroid diseases. The alterations are associated with the cause, development, and recovery of the diseases and are regulated by PC-mediated signals. Restoring normal PC structure and function in thyrocytes is a promising therapeutic strategy to treat thyroid diseases. This review explores the function of PC in normal thyroid glands. It summarizes the pathology caused by PC alterations in thyroid cancer (TC), autoimmune thyroid diseases (AITD), hypothyroidism, and thyroid nodules (TN) to provide comprehensive references for further study.

Pathology and new insights in thyroid neoplasms in the 2022 WHO classification

PURPOSE OF REVIEW

The assessment of thyroid nodules is a common clinical problem, linked to the high incidence of thyroid nodules in the population and the low incidence of aggressive thyroid carcinoma. The screening is therefore one of the strengths of our patient care. Recently, the 2023 Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) and 2022 WHO classification of thyroid neoplasms have been released based on the definition of new entities and the growing impact of molecular testing. The aim of this review is to analyze how these upgrades can help us in the daily routine practice diagnosis of thyroid cancer.

RECENT FINDINGS

Our review is focused on the most frequent thyroid tumors derived from thyroid follicular cell. Fine needle aspiration (FNA) is the gold standard for the screening of thyroid nodules with very high levels of sensitivity and specificity. These sensitivity and specificity are improved by molecular testing, which refines the risk of malignancy. The 2023 TBSRTC integrates molecular data and the upgrades integrated in the 2022 WHO classification such as the 'low-risk neoplasms' and the 'high-grade follicular-cells derived carcinoma'. The morphological examination remains crucial since the capsular and/or vascular invasion are key features of malignancy in the follicular thyroid neoplasms. Low-risk neoplasms represent a clinical challenge since no specific guidelines are available. Challenges remain regarding oncocytic thyroid lesions, which are not associated with specific diagnostic molecular biomarkers. Molecular testing can help not only in deciphering the prognosis but also in the targeted therapeutic strategy.

SUMMARY

While molecular testing has succeeded to substantially improve the pre and postoperative diagnosis and risk stratification of thyroid tumors, the morphological examination is still central in the daily routine diagnosis of thyroid pathology. Future is the integrated diagnosis of clinical, morphological, molecular and epigenetic features with the help of artificial intelligence algorithms.

Comparative analysis of machine learning-based ultrasound radiomics in predicting malignancy of partially cystic thyroid nodules

OBJECTIVE

To investigate the application of machine learning (ML) model-based thyroid ultrasound radiomics in the evaluation of malignancy in partially cystic thyroid nodules (PCTNs).

METHODS

One hundred and ninety-two patients with 197 nodules PCTNs from January 2020 to December 2020 were retrospectively analyzed. Radiomics features were extracted based on hand-crafted features from the ultrasound images, and machine learning methods were used to build a classification model by radiomics features. The least absolute shrinkage and selection operator regression was applied to select the features of nonzero coefficients from radiomics features. The prediction performance of the established model was mainly evaluated by the area under the curve (AUC) and accuracy, sensitivity, and specificity.

RESULTS

Nineteen radiomics features were extracted from the original images for each nodule. Eight ML classifiers were able to differentiate malignancy in PCTNs. The AUC, accuracy, sensitivity, and specificity of k-Nearest Neighbor (KNN) model were 0.909, 82.95%, 83.33%, and 89.90%, respectively, on the test cohort. The comparative result showed statistically equivalent performance for thyroid nodule diagnosis based on image fusion and single image. In addition, the ML-Based ultrasound radiomics system showed a better AUC as compared with ACR TI-RADS model and the ultrasound features model.

CONCLUSION

The novel ultrasonic-based ML model has an important clinical value for predicting malignancy in PCTNs. It can provide clinicians with a preoperative non-invasive primary screening method for PCTN diagnosis to avoid unnecessary medical investment and improve treatment outcomes.

Thyroid Nodules: Emerging Trends in Detection and Visualization based on Citespace

BACKGROUND

Thyroid nodule (TN) is a highly prevalent clinical endocrine disease. Many countries have formed guidelines on the prevention and treatment of TN based on extensive research. However, there is a scarcity of TN-related literature based on bibliometrics.

OBJECTIVES

This study aimed to evaluate the scientific achievements and progress of TN research from a global perspective by investigating the literature for 20 years through bibliometrics.

METHODS

We searched the literature on TN in the core collection of the Web of Science database from 2002 to 2021 and used the Citespace software to analyze the co-authorship, co-citation, and co-occurrence of countries, institutions, authors, keywords, and co-cited literature.

RESULTS

We retrieved 12319 documents related to TN. The literature on TN has been growing since 2002. The United States has contributed the largest proportion of TN papers (20.64%), followed by China, Italy, and South Korea. The United States ranked first in terms of centrality (0.38). Haugen BR, Gharib H, and Cibas ES are the top three most cited authors. The papers published in Thyroid were cited most frequently (7952 times). The most prominent keywords were management, cancer, fine needle aspiration, diagnosis, malignant tumor, thyroid cancer, ultrasound, biopsy, benign, surgery, ablation, and cytology. All keywords could be divided into three categories: diagnosis stratification, treatment, and cancer. As far as potential hot spots are concerned, the keywords that have recently burst strongly and are still continuing are: "Association Guideline" (2018-2021), "Radiofrequency Ablation" (2017-2021), "Classification" (2019-2021), and "Data System" (2017-2021).

CONCLUSION

Based on the current trends, the number of publications on TN will continue to increase. The United States is the most active contributor to research in this field. Previous literature focused on stratification, cancer, surgery, and ablation, and there were different opinions on the stratification of diagnosis. There were relatively few studies on pathogenesis and treatment using medicine. More focus will be placed on association guidelines, radiofrequency ablation, classification, and data system, which may be the next popular topics in TN research.

Integrated proteomic and metabolomic analysis of plasma reveals regulatory pathways and key elements in thyroid cancer

Thyroid cancer (TC) is the most common endocrine malignancy with increasing incidence in recent years. Fine-needle aspiration biopsy (FNAB), as a gold standard for the initial evaluation of thyroid nodules, fails to cover all the cytopathologic conditions resulting in overdiagnosis. There is an urgent need for a better classification of thyroid cancer from benign thyroid nodules (BTNs). Here, data independent acquisition (DIA)-based proteomics and untargeted metabolomics in plasma samples of 10 patients with TC and 15 patients with BTNs were performed. Key proteins and metabolites were identified specific to TC, and an independent cohort was used to validate the potential biomarkers using enzyme-linked immunosorbent assay (ELISA). In total, 1429 proteins and 1172 metabolites were identified. Principal component analysis showed a strong overlap at the proteomic level and a significant discrimination at the metabolomic level between the two groups, indicating a more drastic disturbance in the metabolome of thyroid cancer. Integrated analysis of proteomics and metabolomics shows glycerophospholipid metabolism and arachidonic acid metabolism as key regulatory pathways. Furthermore, a multi-omics biomarker panel was developed consisting of LCAT, GPX3 and leukotriene B4. Based on the AUC value for the discovery set, the classification performance was 0.960. The AUC value of the external validation set was 0.930. Altogether, our results will contribute to the clinical application of potential biomarkers in the diagnosis of thyroid cancer.

TS-DSANN: Texture and shape focused dual-stream attention neural network for benign-malignant diagnosis of thyroid nodules in ultrasound images

Recently, accurate diagnosis of thyroid nodules has played a critical role in precision medicine and healthcare system management. Due to complicated changes in ultrasound features of texture, and similar visual appearance of benign-malignant nodules, the identification of cancerous thyroid lesions from a given ultrasound image still faces challenges for even experienced radiologists. Learning-based computer-aided diagnosis (CAD) systems have accordingly attracted more and more attention recently. However, little research is committed to developing a deep learning-based CAD system that has greater conformity with radiologists' diagnostic decision-making. In this study, we devise a texture and shape focused dual-stream attention neural network, dubbed TS-DSANN. Specifically, in the texture focused stream, we utilize the ImageNet pre-trained ResNet34 to guide the network to recognize texture-related nodule attributes. Meanwhile, in the shape focused stream, in addition to using ResNet34 backbone, jointly learning from scratch with the contour obtained by contour detection module to enhance the extraction of shape features. Afterward, we employ a concatenation operation to aggregate the abovementioned two stream networks for capturing richer and more representative features. Finally, we further utilize an online class activation mapping mechanism to assist the dual-stream network in generating a localization heatmap to obtain more visualization attention to the nodule from the whole image, and supervise classifier's attention in decision-making. Experimental results conducted on the two-center thyroid nodule ultrasound datasets verify that our proposed method has improved the classification performance, superior to the state-of-the-art methods.

Can Thyroid Nodules be Managed with Radiofrequency Ablation?

Radiofrequency ablation (RFA) is an established and growing minimally-invasive technique with an impressive safety profile used to manage thyroid nodules. Beyond shorter operative and recovery times, the main advantages of RFA include the lack of an incisional scar as well as maximizing the potential for maintenance of normal thyroid function. RFA can significantly reduce nodular volume, achieving rates of 60% to 95% in a breadth of thyroid disease, including benign nodules, primary carcinomas, and recurrent malignancies. Thorough patient counselling is imperative for RFA candidates, including a discussant of complications, nodule regrowth, and the potential for a subsequent ablation session.

An update on the management of thyroid nodules: rationalising the guidelines

BACKGROUND

Guidance for the management of thyroid nodules has evolved over time, from initial evaluation based predominantly on clinical grounds to now including the established role of ultrasound and fine needle aspiration cytology in their assessment. There is, however, significant variation in the management of thyroid nodules depending on which national guidelines are followed. In addition, there are certain clinical situations such as pregnancy and paediatric thyroid nodules that have differing evaluation priorities.

OBJECTIVES

This review aimed to provide an overview of currently accepted practices for the initial investigation and subsequent management of patients with thyroid nodules for the non-specialist. The review also addresses areas of variance between the systems in common clinical use, as well as newer, evolving technologies, including molecular testing in the evaluation of malignancy in thyroid nodules.

Automated diagnosis and management of follicular thyroid nodules based on the devised small-dataset interpretable foreground optimization network deep learning: a multicenter diagnostic study

BACKGROUND

Currently, follicular thyroid carcinoma (FTC) has a relatively low incidence with a lack of effective preoperative diagnostic means. To reduce the need for invasive diagnostic procedures and to address information deficiencies inherent in a small dataset, we utilized interpretable foreground optimization network deep learning to develop a reliable preoperative FTC detection system.

METHODS

In this study, a deep learning model (FThyNet) was established using preoperative ultrasound images. Data on patients in the training and internal validation cohort ( n =432) were obtained from Ruijin Hospital, China. Data on patients in the external validation cohort ( n =71) were obtained from four other clinical centers. We evaluated the predictive performance of FThyNet and its ability to generalize across multiple external centers and compared the results yielded with assessments from physicians directly predicting FTC outcomes. In addition, the influence of texture information around the nodule edge on the prediction results was evaluated.

RESULTS

FThyNet had a consistently high accuracy in predicting FTC with an area under the receiver operating characteristic curve (AUC) of 89.0% [95% CI 87.0-90.9]. Particularly, the AUC for grossly invasive FTC reached 90.3%, which was significantly higher than that of the radiologists (56.1% [95% CI 51.8-60.3]). The parametric visualization study found that those nodules with blurred edges and relatively distorted surrounding textures were more likely to have FTC. Furthermore, edge texture information played an important role in FTC prediction with an AUC of 68.3% [95% CI 61.5-75.5], and highly invasive malignancies had the highest texture complexity.

CONCLUSION

FThyNet could effectively predict FTC, provide explanations consistent with pathological knowledge, and improve clinical understanding of the disease.

A Combination of BRAF and EZH1/SPOP/ZNF148 Three-Gene Mutational Classifier Improves Benign Call Rate in Indeterminate Thyroid Nodules

Reliable preoperative diagnosis of thyroid nodules remained challenging because of the inconclusiveness of fine-needle aspiration (FNA) cytology. In the present study, 583 formalin-fixed paraffin embedded (FFPE) thyroid nodule tissues and 161 FNA specimens were enrolled retrospectively. Then BRAF V600E, EZH1 Q571R, SPOP P94R, and ZNF148 mutations among these samples were identified using Sanger sequencing. Based on this four-gene genomic classifier, we proposed a two-step modality to diagnose thyroid nodules to differentiate benign and malignant thyroid nodules. In the FFPE group, thyroid cancers were effectively diagnosed in 37.7% (220/583) of neoplasms by the primary BRAF V600E testing, and 15.7% (57/363) of thyroid nodules could be further determined as benign by subsequent EZH1 Q571R, SPOP P94R, and ZNF148 (we called them "ESZ") mutation testing. In the FNA group, 161 BRAF wild-type specimens were classified according to The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). A total of 7 mutated samples fell within Bethesda categories III-IV, and the mutation rate of "ESZ" in Bethesda III-IV categories was 8.4%. The two-step genomic classifier could further improve thyroid nodule diagnosis, which may inform more optimal patient management.

An adaptive multi-modal hybrid model for classifying thyroid nodules by combining ultrasound and infrared thermal images

BACKGROUND

Two types of non-invasive, radiation-free, and inexpensive imaging technologies that are widely employed in medical applications are ultrasound (US) and infrared thermography (IRT). The ultrasound image obtained by ultrasound imaging primarily expresses the size, shape, contour boundary, echo, and other morphological information of the lesion, while the infrared thermal image obtained by infrared thermography imaging primarily describes its thermodynamic function information. Although distinguishing between benign and malignant thyroid nodules requires both morphological and functional information, present deep learning models are only based on US images, making it possible that some malignant nodules with insignificant morphological changes but significant functional changes will go undetected.

RESULTS

Given the US and IRT images present thyroid nodules through distinct modalities, we proposed an Adaptive multi-modal Hybrid (AmmH) classification model that can leverage the amalgamation of these two image types to achieve superior classification performance. The AmmH approach involves the construction of a hybrid single-modal encoder module for each modal data, which facilitates the extraction of both local and global features by integrating a CNN module and a Transformer module. The extracted features from the two modalities are then weighted adaptively using an adaptive modality-weight generation network and fused using an adaptive cross-modal encoder module. The fused features are subsequently utilized for the classification of thyroid nodules through the use of MLP. On the collected dataset, our AmmH model respectively achieved 97.17% and 97.38% of F1 and F2 scores, which significantly outperformed the single-modal models. The results of four ablation experiments further show the superiority of our proposed method.

CONCLUSIONS

The proposed multi-modal model extracts features from various modal images, thereby enhancing the comprehensiveness of thyroid nodules descriptions. The adaptive modality-weight generation network enables adaptive attention to different modalities, facilitating the fusion of features using adaptive weights through the adaptive cross-modal encoder. Consequently, the model has demonstrated promising classification performance, indicating its potential as a non-invasive, radiation-free, and cost-effective screening tool for distinguishing between benign and malignant thyroid nodules. The source code is available at https://github.com/wuliZN2020/AmmH .

Indeterminate thyroid nodules (Thy3): malignancy rate and characteristics in a study of 118 patients

INTRODUCTION

Thyroid nodules are common, and the combined use of ultrasound and fine needle aspiration cytology provides useful information on their malignancy risk. The Thy reporting system is widely used in the United Kingdom, with malignancy rates for Thy3 cytology being quoted between 5% and 30%. This study aims to establish the risk of thyroid cancer in operated patients with Thy3 cytology and correlate it with patient demographics and nodule size.

METHODS

This is a retrospective observational study of all thyroidectomies that took place in a single institution over a 3-year period (2019-2022). Those with a preoperative cytology of Thy3 were analysed further and in particular, nodule size, final histology and patients' demographics were documented.

RESULTS

Some 260 thyroidectomies were performed during the study period. Of these, 118 patients had Thy3 cytology. In the Thy3a group (n = 70), the malignancy rate was 27.1%. The average age of those with thyroid cancer was 51.4 vs 51.2 years for those with benign disease. The nodule size was under 40mm for both groups (36mm vs 39.7mm). In the Thy3f group (n = 48), the malignancy rate was 43.8%. The average age of those with thyroid cancer was 53.5 vs 56.2 years for those with benign disease. The nodule size was similar (24.5mm vs 27.6mm).

CONCLUSIONS

In this study, one in three patients with Thy3 cytology was diagnosed with thyroid cancer. We urge local units to analyse their data, to aid patients' informed decision-making. Within the subgroups, there was no significant difference in average nodule size or patients' age.

Differentiating Thyroid Follicular Adenoma from Follicular Carcinoma via G-Protein Coupled Receptor-Associated Sorting Protein 1 (GASP-1)

Follicular neoplasms are classified as benign or malignant depending on the presence or absence of capsular and/or vascular invasion. Due to incomplete capsular penetration or equivocal vascular invasion, the evaluation of these features can be challenging using histologic examination. In the current study, we analyzed the involvement of G-protein coupled receptor-associated sorting protein 1 (GASP-1) in the development and progression of thyroid neoplasms. Affinity-purified anti-GASP-1 polyclonal antibodies were used for routine immunohistochemistry (IHC) analysis. Thyroid tissue microarrays containing normal thyroid tissue, follicular adenoma, follicular carcinoma, papillary thyroid carcinoma, and anaplastic carcinoma were analyzed. We found that the level of GASP-1 expression can differentiate follicular adenoma from follicular carcinoma. When numerous cases were scored for GASP-1 expression by a board-certified pathologist, we found that GASP-1 expression is 7-fold higher in thyroid malignant neoplasms compared to normal thyroid tissue, and about 4-fold higher in follicular carcinoma compared to follicular adenoma. In follicular adenoma tissues, we observed the presence of many mini-glands that are enriched in GASP-1 and some mini-glands contain as few as three cells. GASP-1 IHC also possesses several advantages over the conventional H&E and can be used to identify early thyroid cancer and monitor cancer progression.

Identifying and Predicting Diverse Patterns of Benign Nodule Growth

CONTEXT

The natural history of benign thyroid nodules is typically characterized by slow growth and minimal risk of malignant transformation. Available data have, to date, been unable to elucidate the diversity of benign nodule growth patterns over time nor predictive of which patients follow which pattern.

OBJECTIVE

We aimed to better define the diverse patterns of benign nodule behavior and their predictors.

METHODS

We prospectively studied 389 consecutive patients with solitary, solid, cytologically benign thyroid nodules ≥1 cm and follow-up ultrasound for at least 4 years. Demographic, sonographic, biochemical data were collected at initial evaluation, and subsequent growth patterns were identified over the follow-up. Predictors of growth at initial evaluation and 3 years of follow-up were defined.

RESULTS

The mean (±SD) follow-up was 7.7 (±2.7) years. Three distinct growth patterns were identified: A) stagnant nodules with average growth rate < 0.2 mm/year; B) slow-growing nodules with a rate 0.2 to 1.0 mm/year; and C) fast-growing nodules increasing > 1.0 mm/year. Fast-growing nodules represented 17.2% of the cohort, and were more frequent in patients younger than 50 years (OR 2.2 [1.2-4.1], P = 0.016), and in larger nodules (2.0-2.9 cm, OR 3.5 [1.7-7.1], P = 0.001; >3.0 cm, OR 4.4 [1.8-10.4], P = 0.001 vs reference 1-1.9 cm). In a multiple regression model, nodule growth at 3 years at an average growth rate over 0.2 mm/year over 3 years since initial evaluation was an independent predictor of longer-term fast nodule growth, even after adjusting for age, biological sex, TSH level, and nodule size (P < 0.001).

CONCLUSION

The natural history of benign nodule growth is diverse, with over 80% of nodules demonstrating minimal to no growth long-term. Nearly 20% of cytologically benign nodules may exhibit a fast, continued growth pattern, which can be predicted by the 3-year growth rate pattern. These findings can help inform decision making for tailored benign nodule follow-up and monitoring.

Detection of Thyroid Nodule Prevalence and Associated Risk Factors in Southwest China: A Study of 45,023 Individuals Undergoing Physical Examinations

Background

Thyroid nodules (TNs) are among the most common thyroid lesions, and rates of these nodules have risen over the past three decades. As the majority of TN patients remain asymptomatic when these nodules are in the early stages of development, malignant nodules may continue to develop into thyroid cancer when not detected. As such, early screening and diagnosis-based strategies represent the most promising means of preventing or treating TNs and associated cancers. The present study was thus developed to explore TN prevalence among individuals in Luzhou, China.

Methods

Here, thyroid ultrasonography and metabolic-related indicators from 45,023 adults undergoing routine physical examinations in the Health Management Center of a large Grade A hospital in Luzhou over the last three years were retrospectively reviewed in an effort to identify factors associated with TN risk and the detection of these nodules through univariate and multivariate logistic regression analyses.

Results

In total, 13,437 TNs were detected in these 45,023 healthy adults for an overall 29.8% detection rate. This TN detection rate rose with age, and multivariate logistic regression analyses revealed that independent risk factors associated with TNs included greater age (≥31 years old), female (OR = 2.283, 95% CI: 2.177-2.393), central obesity (OR = 1.115, 95% CI: 1.051-1.183), impaired fasting glucose (OR = 1.203, 95% CI: 1.063-1.360), overweight status (OR = 1.085, 95% CI: 1.026-1.147), and obesity (OR = 1.156, 95% CI: 1.054-1.268), while low BMI was a protective factor associated with lower rates of TN incidence (OR = 0.789, 95% CI: 0.706-0.882). When results were stratified by gender, impaired fasting glucose was not an independent predictor of TN risk among males, while high LDL levels were an independent predictor of TNs among females, and other risk factors were not significantly changed.

Conclusion

TN detection rates were high among adults in Southwestern China. Female, elderly individuals, individuals exhibiting central obesity, and those with high levels of fasting plasma glucose are more likely to develop TN.

Accuracy of fine-needle aspiration cytopathology to differentiate malignant and benign thyroid nodules with ≥4 cm diameter: A retrospective study

BACKGROUND

Thyroid nodules (TN) are commonly present in the general population and are usually pathologically benign. An initial diagnosis with fine-needle aspiration (FNA) cytopathology could help clinical decision-making with fewer complications. As the previous studies suggest surgical procedures for >4 cm TNs, we aimed to investigate the accuracy of preoperative FNA cytology to predict malignancy risk in these nodules in a sample of the Iranian population.

METHODS

Patients with ≥4 cm TNs who had preoperative FNA cytology, underwent nodulectomy and had a histopathological report were included. Each patient's preoperative demographic, ultrasonographic, and cytology data were gathered. After surgery, resected samples were assessed pathologically and diagnosed as benign or malignant. Finally, data were analyzed to evaluate the presurgical accuracy of the FNA cytology.

RESULTS

We identified 41 (51.25%) patients with malignant legions among our study population (N = 80). The pathology reports were indeterminate in 3 patients with follicular neoplasm. Bethesda scores were substantially higher in patients with malignancy. The sensitivity, specificity, and false-negative rate of FNA cytology reports using the Bethesda system were 73.7%, 74.2%, and 26.3%, respectively. There was no association between malignancy and TNs' size, neither their volume nor their highest diameter.

CONCLUSION

FNA cytology is not as sensitive and specific in nodules>4 cm as in smaller ones. However, it can still be used alongside other diagnostic procedures in malignancy screening. Clinicians should make more complex decisions considering various influential factors to avoid missing malignant lesions and reduce diverse probable complications of highly invasive diagnostic surgery. Further prospective research on >4 cm TNs and their multiple features' association with malignancy is required for more precise judgment.

A prospective comparison of ACR-TIRADS and EU-TIRADS in thyroid nodule assessment for FNA-US

OBJECTIVE

Prospective data on the accuracy of ultrasound (US) classification systems in thyroid nodules are still scarce. The aim of this study is to compare the accuracy of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) and European (EU)-TIRADS classification systems.

DESIGN AND PATIENTS

Consecutive patients with one or more thyroid nodule(s) who underwent fine-needle aspiration (FNA) under ultrasonographic guidance (FNA-US) were prospectively evaluated.

MEASUREMENTS

Clinical evaluation and US data were collected. The reference standard used for this study was FNA-US cytology and histopathological diagnosis.

RESULTS

A total of 186 thyroid nodules in 166 patients were evaluated, resulting in 168 nodules from 149 patients with conclusive benign or malignant results. Sensitivity, specificity, negative predictive value (NPV) and false negative (FN) were 100.0%, 28.7%, 100.0% and 0.0%, respectively, for ACR-TIRADS; and 90.0%, 19.1%, 96.8% and 9.1% (n = 1), respectively, for EU-TIRADS. The number of unnecessary FNA-US indicated by ACR-TIRADS was lower than EU-TIRADS (71.3% vs. 80.9%, p = .017), and the number of possibly avoided FNA-US was higher (26.7% vs. 17.8%). Using the same threshold of ACR-TIRADS to indicate FNA-US in EU-TIRADS 3 nodules (2.5 cm), there was an improvement in specificity (30.6%) and avoided FNA-US (28.6%). The best performance of both systems was demonstrated when FNA-US would be indicated only in highly suspicious nodules and/or in the presence of lymphadenopathy, with 85.7% and 89.3% of possibly avoided FNA-US for ACR-TIRADS and EU-TIRADS, respectively, without increasing FN.

CONCLUSION

Both systems presented high sensitivity, but low specificity in selecting nodules for FNA-US. The use of nodular size for FNA-US selection is questioned.

Ultrasound-Based Risk Stratification System for the Assessment of Partially Cystic Thyroid Nodules

OBJECTIVE

To develop and validate a risk stratification system for the prediction of malignancy in Partially Cystic Thyroid Nodules (PCTNs).

METHODS

From January 2020 to December 2021, we retrospectively reviewed the sonography data of PCTNs patients from Hangzhou TCM Hospital, Hangzhou First People's Hospital two medical centers. The independent risk factors of malignant PCTNs were evaluated using univariate and multivariate logistic regression analysis. The nomogram prediction efficiency was assessed using Area Under the Curve (AUC) and calibration curves. To determine the clinic value of the predictive model, Decision Curve Analysis (DCA) was used.

RESULTS

In this retrospective study, a total of 285 patients (301 PCTNs) were enrolled, 242 nodules were benign, and 59 nodules were malignant. Younger age, hypoechoic, irregular margin and microcalcifications were found to be the independent risk factors associated with malignant PCTNs. The AUC, sensitivity, and specificity were 0.860, 77.1%, and 84.7% in the training set and 0.897, 91.7%, and 87.0% in the external validation set, respectively. The total point of nomogram is greater than 161, which shows the best to predict the malignancy of PCTNs.

CONCLUSIONS

Our findings demonstrated that the risk stratification system for the assessment of PTCNs showed good prediction capacities.

Ultrasound imaging in thyroid nodule diagnosis, therapy, and follow-up: Current status and future trends

Ultrasound, the primary imaging modality in thyroid nodule management, suffers from drawbacks including: high inter- and intra-observer variability, limited field-of-view and limited functional imaging. Developments in ultrasound technologies are taking place to overcome these limitations, including three-dimensional-Doppler, -elastography, -nodule characteristics-extraction, and novel machine-learning algorithms. For thyroid ablative treatments and biopsies, perioperative use of three-dimensional ultrasound opens a new field of research. This review provides an overview of the current and future applications of ultrasound, and discusses the potential of new developments and trends that may improve the diagnosis, therapy, and follow-up of thyroid nodules.

Exploring the research landscape of the past, present, and future of thyroid nodules

Introduction

The purpose of this study was to assess the landscape of thyroid nodules research during the last 22 years using machine learning and text analysis.

Methods

In November 2021, we obtained from PubMed all works indexed under the Medical Subject Headings (MeSH) subject line "thyroid nodules." The entire set of search results was retrieved in XML format, and metadata such as title, abstract, keywords, MeSH words, and year of publication were extracted for bibliometric evaluation from the original XML files. To increase the specificity of the investigation, the Latent Dirichlet allocation (LDA) topic modeling method was applied.

Results

Our study included 5,770 research papers. By using frequency analysis of MeSH terms, research on thyroid nodules was divided into two categories: clinical and basic. The proportion of clinical research is nearing 89% and is dominated by the differential diagnosis of thyroid nodules. In contrast, the proportion of MeSH terms relating to basic research was just 11%, with DNA mutation analysis being the most common topic. Following this, LDA analysis revealed the thyroid nodule study had three clusters: Imaging Studies, Biopsy and Diagnosis, and Epidemiology and Screening of Thyroid Cancer. The result suggests that current thyroid nodule research appears to have focused on ultrasonography and histological diagnosis, which are tightly correlated. Molecular biomarker research has increased, therefore enhancing the diagnostic precision of thyroid nodules. However, inflammation, anxiety, and mental health disorders related to thyroid nodules have received little attention.

Conclusion

Basic research on thyroid nodules has unmet research requirements. Future research could focus on developing strategies to more efficiently identify malignant nodules, exploring the mechanism of thyroid nodule development, and enhancing the quality of life of thyroid patients.

Patients undergoing endocrine consultation and first diagnosis of nodular disease: Indications of thyroid ultrasound and completeness of ultrasound reports

PURPOSE

To evaluate reasons for performing ultrasonography (US) and completeness of US reports in patients undergoing endocrine consultation with the first diagnosis of nodular disease.

METHODS

Since January 1 to June 30, 2021, we prospectively collected patient data (age and thyroid-stimulating hormone concentrations), reasons for performing thyroid US, and completeness of reports regarding the description of the thyroid gland and nodules. In the case of multiple nodules, we considered the nodule suspected of malignancy and the largest one. To evaluate the accuracy of thyroid nodule description, we referred to the five characteristics suggested by the ACR TI-RADS system.

RESULTS

A total of 341 patients with thyroid nodules received endocrine consultation (female, 78%). The most frequent reasons for performing thyroid US were unrelated to a suspected thyroid disease (31.7%), followed by incidentaloma (23.5%), dysfunction or positivity for thyroid antibodies (19.1%), symptomatic or visible nodules (17.6%), and family history of any thyroid disease (8.2%). Gland texture was not reported in 41.9%. The depth of the lobes was the dimension reported most frequently (42.2%), but any diameter was not reported in 57.8% of the cases. As regards the description of the most relevant nodule, length was reported more frequently (75.9%). Margins and echogenicity were more frequently described (54.5% and 44.3%, respectively) than other characteristics (composition: 27%; shape: 8.8%; echogenic foci: 6.7%). No reports had indicated the malignancy risk stratification.

CONCLUSIONS

The results of the study demonstrate that in patients undergoing endocrine consultation with first detected thyroid nodules, US was mostly performed in asymptomatic cases, US reports were incomplete, and no risk stratification system was reported.

Comparison of S-Detect and thyroid imaging reporting and data system classifications in the diagnosis of cytologically indeterminate thyroid nodules

PURPOSE

The aim of this study was to investigate the value of S-Detect for predicting the malignant risk of cytologically indeterminate thyroid nodules (CITNs).

METHODS

The preoperative prediction of 159 CITNs (Bethesda III, IV and V) were performed using S-Detect, Thyroid Imaging Reporting and Data System of American College of Radiology (ACR TI-RADS) and Chinese TI-RADS (C-TIRADS). First, Linear-by-Linear Association test and chi-square test were used to analyze the malignant risk of CITNs. McNemar's test and receiver operating characteristic curve were used to compare the diagnostic efficacy of S-Detect and the two TI-RADS classifications for CITNs. In addition, the McNemar's test was used to compare the diagnostic accuracy of the above three methods for different pathological types of nodules.

RESULTS

The maximum diameter of the benign nodules was significantly larger than that of malignant nodules [0.88(0.57-1.42) vs 0.57(0.46-0.81), P=0.002]. The risk of malignant CITNs in Bethesda system and the two TI-RADS classifications increased with grade (all P for trend<0.001). In all the enrolled CITNs, the diagnostic results of S-Detect were significantly different from those of ACR TI-RADS and C-TIRADS, respectively (P=0.021 and P=0.007). The sensitivity and accuracy of S-Detect [95.9%(90.1%-98.5%) and 88.1%(81.7%-92.5%)] were higher than those of ACR TI-RADS [87.6%(80.1%-92.7%) and 81.8%(74.7%-87.3%)] (P=0.006 and P=0.021) and C-TIRADS [84.3%(76.3%-90.0%) and 78.6%(71.3%-84.5%)] (P=0.001 and P=0.001). Moreover, the negative predictive value and the area under curve value of S-Detect [82.8% (63.5%-93.5%) and 0.795%(0.724%-0.855%)] was higher than that of C-TIRADS [54.8%(38.8%-69.8%) and 0.724%(0.648%-0.792%] (P=0.024 and P=0.035). However, the specificity and positive predictive value of S-Detect were similar to those of ACR TI-RADS (P=1.000 and P=0.154) and C-TIRADS (P=1.000 and P=0.072). There was no significant difference in all the evaluated indicators between ACR TI-RADS and C-TIRADS (all P>0.05). The diagnostic accuracy of S-Detect (97.4%) for papillary thyroid carcinoma (PTC) was higher than that of ACR TI-RADS (90.4%) and C-TIRADS (87.8%) (P=0.021 and P=0.003).

CONCLUSION

The diagnostic performance of S-Detect in differentiating CITNs was similar to ACR TI-RADS and superior to C-TIRADS, especially for PTC.

ACR TI-RADS classification combined with number of nodules, halo features optimizes diagnosis and prediction of follicular thyroid cancer

OBJECTIVES

To investigate the application value of The American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) category combined with other ultrasound features of nodules in distinguishing follicular thyroid carcinoma (FTC) from thyroid follicular adenoma (FTA).

METHODS

We collected and retrospectively analyzed clinical and ultrasound data for 118 and 459 patients with FTCs and FTAs, respectively, at our hospital. Next, we used ACR TI-RADS classification combined with other ultrasound features of nodules to distinguish FTC from FTA. Multivariate Logistic regression was used to screen independent risk factors for FTC, which were subsequently used to construct a nomogram for predicting FTC.

RESULTS

ACR TI-RADS categories 4 and 5, unilateral multiple nodules, and halo thickness≥2 mm were independent risk factors for FTC. ACR TI-RADS category combined with number of nodules, halo features of the nodule was a significantly better prediction model for FTC diagnosis (AUC = 0.869) than that of ACR TI-RADS classification alone (AUC = 0.756).

CONCLUTIONS

Clinicians need to pay attention to the halo of nodules when distinguishing FTA from FTC. Notably, ACR TI-RADS combined with other nodule ultrasound features has superior predictive performance in diagnosis of FTC compared to ACR TI-RADS classification alone, thus can provide an important reference value for preoperative diagnosis of FTC.

Incorporation of a machine learning pathological diagnosis algorithm into the thyroid ultrasound imaging data improves the diagnosis risk of malignant thyroid nodules

Objective

This study aimed at establishing a new model to predict malignant thyroid nodules using machine learning algorithms.

Methods

A retrospective study was performed on 274 patients with thyroid nodules who underwent fine-needle aspiration (FNA) cytology or surgery from October 2018 to 2020 in Xianyang Central Hospital. The least absolute shrinkage and selection operator (lasso) regression analysis and logistic analysis were applied to screen and identified variables. Six machine learning algorithms, including Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Naive Bayes Classifier (NBC), Random Forest (RF), and Logistic Regression (LR), were employed and compared in constructing the predictive model, coupled with preoperative clinical characteristics and ultrasound features. Internal validation was performed by using 10-fold cross-validation. The performance of the model was measured by the area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, F1 score, Shapley additive explanations (SHAP) plot, feature importance, and correlation of features. The best cutoff value for risk stratification was identified by probability density function (PDF) and clinical utility curve (CUC).

Results

The malignant rate of thyroid nodules in the study cohort was 53.2%. The predictive models are constructed by age, margin, shape, echogenic foci, echogenicity, and lymph nodes. The XGBoost model was significantly superior to any one of the machine learning models, with an AUC value of 0.829. According to the PDF and CUC, we recommended that 51% probability be used as a threshold for determining the risk stratification of malignant nodules, where about 85.6% of patients with malignant nodules could be detected. Meanwhile, approximately 89.8% of unnecessary biopsy procedures would be saved. Finally, an online web risk calculator has been built to estimate the personal likelihood of malignant thyroid nodules based on the best-performing ML-ed model of XGBoost.

Conclusions

Combining clinical characteristics and features of ultrasound images, ML algorithms can achieve reliable prediction of malignant thyroid nodules. The online web risk calculator based on the XGBoost model can easily identify in real-time the probability of malignant thyroid nodules, which can assist clinicians to formulate individualized management strategies for patients.

Artificial intelligence defines protein-based classification of thyroid nodules

Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue samples from a retrospective cohort. This classifier achieved over 91% accuracy in the discovery set for classifying malignant thyroid nodules. The classifier was externally validated by blinded analyses in a retrospective cohort of 288 nodules (89% accuracy; FFPE) and a prospective cohort of 294 FNA biopsies (85% accuracy) from twelve independent clinical centers. This study shows that integrating high-throughput proteomics and AI technology in multi-center retrospective and prospective clinical cohorts facilitates precise disease diagnosis which is otherwise difficult to achieve by other methods.

Prevalence of thyroid nodules and its association with water iodine among Chinese men and women

BACKGROUND

Because of the large change in iodine nutrition and other lifestyle in China, there is concern that thyroid nodules (TNs) may become epidemic. However, few data are currently available on the national prevalence of TNs. In addition, whether excess iodine in drinking water is associated with an increased risk of TNs, following universal salt iodization, has been less studied. We aim to estimate a national prevalence of TNs and its association with drinking water iodine.

METHODS

We conducted a national survey of 9,381,032 adults, aged 18 years or older, from 30 provinces and municipalities in China, who underwent a thyroid ultrasound test from January 2018 to December 2018. Crude and standardized prevalence of TNs were estimated. We further evaluated the ecological association between province- or city-specific iodine levels in drinking water and the prevalence of TNs using linear regression.

RESULTS

The age-standardized prevalence of TNs in men, women, and both sexes were 29.8%, 44.7%, and 37.1%, respectively. The prevalence increased with age from 22.7% (18-30 years) to 71.5% (≥70 years), and body mass index from 26.1% (<18.5 kg/m2) to 40.8% (≥28 kg/m2). Participants living in the eastern, northern, and northeastern regions had a higher prevalence of TNs (ranged from 38.7% to 43.7%) than those in other regions (ranged from 30.1% to 35.5%). The coastal residents (40.1%) had a higher prevalence of TNs than those in inlanders (35.4%). Higher levels of iodine in drinking water were linearly associated with increased prevalence of TNs, with Pearson correlation coefficients of 0.47 (P < 0.01) in men, 0.40 (P = 0.03) in women, and 0.46 (P = 0.01) in overall participants.

CONCLUSION

This was a nationwide prevalence study of TNs in China, showing that TNs were common health problems, and increased concentration of iodine in drinking water was associated with a higher prevalence of TNs.

Role of echogenic foci in ultrasonographic risk stratification of thyroid nodules: Echogenic focus scoring in the American College of Radiology Thyroid Imaging Reporting and Data System

Background

Although echogenic foci may raise malignancy rates in thyroid nodules, the association between peripheral calcification or macrocalcification and thyroid carcinoma is controversial. We evaluated the malignancy probability of various echogenic foci and explored whether the method of determining a thyroid nodule’s point score in the echogenic focus category of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) is reasonable.

Methods

We retrospectively evaluated 819 patients with 852 nodules. The patterns of echogenic foci on ultrasonography were classified into the following four categories: punctate echogenic foci, macrocalcification, peripheral calcification, and multiple different types of echogenic foci. The core needle biopsy results were divided into two groups: benign and malignant or suspicious for malignancy.

Results

Among the 852 nodules, 471 (55.3%) had echogenic foci on ultrasonography. Of these nodules, there was no significant statistical difference in the malignant or suspicious for malignancy rate between nodules with peripheral calcification and those with macrocalcification [40.0% (8/20) vs. 30.6% (11/36), respectively; p = 0.474]. The incidence of malignancy or suspicious for malignancy for nodules with peripheral calcification, macrocalcification, or multiple different types of echogenic foci was significantly lower than the incidence for punctate echogenic foci alone, with odds ratios of 0.265 [95% confidence interval (CI): 0.105–0.667; p = 0.005], 0.175 (95% CI: 0.083–0.368; p = 0.000), and 0.256 (95% CI: 0.136–0.482; p = 0.000), respectively.

Conclusion

We found no significant statistical difference in the risk of malignancy or suspicious for malignancy rate between peripheral calcification and macrocalcification in thyroid nodules. We observed that nodules with multiple different types of echogenic foci were not associated with higher malignant or suspicious for malignancy rates compared with nodules with punctate echogenic foci alone.

Saliva microbiome changes in thyroid cancer and thyroid nodules patients

Objective

Thyroid disease has been reported to associate with gut microbiota, but the effects of thyroid cancer and thyroid nodules on the oral microbiota are still largely unknown. This study aimed to identify the variation in salivary microbiota and their potential association with thyroid cancer and thyroid nodules.

Methods

We used 16S rRNA high-throughput sequencing to examine the salivary microbiota of thyroid cancer patients (n = 14), thyroid nodules patients (n = 9), and healthy controls (n = 15).

Results

The alpha-diversity indices Chao1 and ACE were found to be relatively higher in patients with thyroid cancer and thyroid nodules compared to healthy controls. The beta diversity in both the thyroid cancer and thyroid nodules groups was divergent from the healthy control group. The genera Alloprevotella, Anaeroglobus, Acinetobacter, unclassified Bacteroidales, and unclassified Cyanobacteriales were significantly enriched in the thyroid cancer group compared with the healthy control group. In contrast, the microbiome of the healthy controls was mainly composed of the genera Haemophilus, Lautropia, Allorhizobium Neorhizobium Pararhizobium Rhizobium, Escherichia Shigella, and unclassified Rhodobacteraceae. The thyroid nodules group was dominated by genre uncultured Candidatus Saccharibacteria bacterium, unclassified Clostridiales bacterium feline oral taxon 148, Treponema, unclassified Prevotellaceae, Mobiluncus, and Acholeplasma. In contrast, the genera unclassified Rhodobacteraceae and Aggregatibacter dominated the healthy control group. The study also found that clinical indicators were correlated with the saliva microbiome.

Conclusion

The salivary microbiota variation may be connected with thyroid cancer and thyroid nodules.

Association of Ozone Exposures with the risk of thyroid nodules in Hunan Province: a population-based cohort study

BACKGROUND

Increasing evidence associates air pollution with thyroid dysfunction, whereas the potential relationship between exposure to ozone (O₃) and Thyroid Nodules (TNs) is unclear.

METHODS

This retrospective cohort study investigated the association between O₃ exposure and TNs in Hunan province, enrolling 191,357 Chinese adults who lived in Hunan province from January 2009 to December 2019 and received voluntary medical examinations. Individual exposure levels to O₃ from 2010 to 2019 were measured on account of participants' residential addresses at the district level. Associations of O₃ exposure with the risk of incidental TNs were assessed by restricted cubic splines and surveyed as odds ratios after adjusting for demographic factors.

RESULTS

In total, 81,900 adults were newly diagnosed with TNs during the study period. Age-standardized TNs detection rate in Hunan province increased from 25.9 to 46.3% between 2010 and 2019, with the greatest annual percent change being 8.1 [95% CI, 7.3-8.8]. A similar trend has been found in all tumor sizes, ages, and both sexes. O₃ exposure presented a statistically significant dose-dependent positive correlation (greater than 0.036 ppm) with TNs. Similarly, long-term exposure to high levels of O₃ (1-year average O₃ concentrations exceeding 0.0417 ppm) was found positively associated with increased TSH levels.

CONCLUSIONS

High-level O₃ exposure in the long term was associated with an increase in TSH. Consequently, increased TSH was related to the increased risk of TNs. Being exposed to high-level O₃ in the long term was related to the increased detection rates of TNs in Hunan province, which could be mediated by TSH.

The application value of CDFI and SMI combined with serological markers in distinguishing benign and malignant thyroid nodules

PURPOSE

The purpose of this study is to explore the application value of CDFI and SMI combined with serological markers in distinguishing benign and malignant thyroid nodules.

METHOD

A total of 192 patients with thyroid nodules admitted to our hospital from July 2019 to December 2020 were selected as subjects. Color Doppler blood flow imaging (CDFI) and supermicro blood flow imaging (SMI) methods are used to detect the blood flow of patients and the levels of serum thyroglobulin antibody (TgAb), thyroid peroxidase antibody (TPOAb), and thyroid stimulating hormone (TSH). The receiver operating characteristic curve (ROC curve) was used to observe the sensitivity and specificity of serological markers for distinguishing benign and malignant thyroid nodules, and combined with CDFI and SMI to observe the sensitivity and specificity for distinguishing benign and malignant thyroid nodules.

RESULTS

The levels of TgAb, TPOAb and TSH in benign thyroid nodules were lower than those of the malignant group, and the difference was statistically significant (P < 0.01). There was no statistically significant difference between benign and malignant thyroid nodules in the presence or absence of the capsule and the presence or absence of vocal halo (P > 0.05), while the differences in the nodule morphology, boundary, internal echo and internal calcification were statistically significant (P < 0.01).

CONCLUSION

CDFI and SMI combined with serological index detection have higher value in the differential diagnosis of thyroid cancer, which can significantly improve the sensitivity and specificity of differential diagnosis.

Ultrasound for the assessment of thyroid nodules: an overview for non-radiologists

Upon discovery of a thyroid nodule (or nodules), a patient is usually referred for evaluation by ultrasound, which is typically performed by a trained radiologist or sonographer. More recently, this technology has been used intraoperatively by endocrine surgeons and also by endocrinologists, often in the context of ‘one-stop shops’ or point of care ultrasound in the outpatient setting. Although thyroid nodules are common and most will be benign, the subsequent work up of these can cause anxiety for patients and place a burden on radiologists. In the UK, sonographic features of benign, suspicious or malignant nodules are classified by the British Thyroid Association U1–U5 criteria, which decide whether to biopsy the nodule (typically U3 and above). This article provides an overview of ultrasound in assessing the thyroid nodule in the context of this classification. This can be used as a guide to interpretation of thyroid ultrasonography for non-radiologists.

SuperSonic shear imaging for the differentiation between benign and malignant thyroid nodules: a meta-analysis

PURPOSE

To assess the diagnostic value of SuperSonic shear imaging (SSI) for the differentiation between benign and malignant thyroid nodules through meta-analysis.

METHODS

Online database searches were performed on PubMed, EMBASE, the Cochrane Library, and the Web of Science until 31 July 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to assess the quality of the included studies. Three measures of diagnostic test performance were used to examine the value of SSI, including the summary area under the receiver operating characteristic curve (AUROC), the summary diagnostic odds ratio (DOR), and the summary sensitivity and specificity. Heterogeneity was explored using meta-regression and subgroup analyses.

RESULTS

Finally, 21 studies with 3376 patients were included in this study. There were a total of 4296 thyroid nodules, in which 1806 malignant nodules and 2490 benign ones were involved. Thyroid nodules exhibited a malignancy rate of 42.0% (range 5.6-79.8%), 95.1% of which were of papillary variant. SSI showed a summary sensitivity of 74% [95% confidence interval (CI) 67-79%], specificity of 82% (95% CI 77-87%) and AUROC of 0.85 (95% CI 0.82-0.88) for the differentiation between benign and malignant thyroid nodules. The summary positive likelihood ratio (LR), negative LR, and DOR were 4.2 (95% CI 3.3-5.3), 0.32 (95% CI 0.26-0.40), and 13 (95% CI 9-18), respectively.

CONCLUSIONS

SSI showed high accuracy in the diagnostic differentiation between benign and malignant thyroid nodules and can be served as a noninvasive and important adjunct for thyroid nodule evaluation.

A Case-Based Comparison of the American Thyroid Association and Thyroid Imaging Reporting & Data System Guidelines

Thyroid nodules are a common clinical finding. Approximately 4-7% of the population have a palpable nodule on physical exam,1 while up to 70% of the population have a nodule detected incidentally on ultrasound.2 The vast majority of nodules are benign, however, approximately 5-13% of thyroid nodules detected on imaging are at risk of malignancy.3 Some malignant nodules, especially those smaller than 1 cm, can exhibit indolent behavior and do not require aggressive treatment.4 Therefore, thyroid nodules need to be accurately assessed to avoid overdiagnosis and overtreatment of nodules which would not otherwise affect patient morbidity. The American Thyroid Association (ATA) addressed this challenge by developing a set of ultrasound pattern-based guidelines for thyroid nodule management in 2009, which were updated in 2015.5 Other societies have since published similar guidelines, such as the Thyroid Imaging Reporting & Data System (TI-RADS) by the American College of Radiology in 2017. TI-RADS was similarly intended to risk-stratify nodules based on ultrasound appearance, but uses a points-based approach. The purpose of this review is to provide an overview of thyroid nodule evaluation and management through a case-based comparison using the ATA and TI-RADS guidelines.

Epidemiological, Clinical, Ultrasonographic and Cytological Characteristics of Thyroid Nodules in an Afro-Caribbean Population: A Series of 420 Patients

Simple Summary

This study describes the epidemiological, clinical and ultrasound characteristics of malignancy in thyroid nodules and evaluates the value of cytology in the diagnosis of malignancy in an Afro-Caribbean population. Our results revealed that none of the standard ultrasound criteria of malignancy were significantly predictive of cancer, but hypoechogenicity and central vascularity were frequently found in malignant nodules. These results could increase awareness and guide practitioners in their diagnostic approach and management of thyroid nodules in Afro-Caribbean populations. Bethesda system-based cytology revealed low sensitivity in analyzing the risk of malignancy in this population. The high prevalence of papillary microcarcinomas may explain the inconclusive ultrasound and cytological results.

Abstract

The incidence of thyroid cancer is increasing worldwide. The aim of this study is to describe the epidemiological, clinical and ultrasound characteristics of malignancy in thyroid nodules and to evaluate the predictive value of the Bethesda system for thyroid cytology in the diagnosis of malignancy in an Afro-Caribbean population. We conducted a retrospective study in Martinique involving 420 patients with a diagnosis of thyroid nodules between 2011 and 2014. Of the 192/420 (45.7%) patients operated on for thyroid nodules, 9% had thyroid cancer. All patients with thyroid cancer were obese women with a mean age of 50 years. The final histological examination revealed papillary microcarcinomas in 61% of cases and papillary carcinomas in 39% of cases. Thyroid cytology alone had a low sensitivity (22.2%) and positive predictive value (15.4%) for the diagnosis of malignancy, with a good specificity (91.1%) and negative predictive value (94.2%). None of the standard ultrasound criteria of malignancy were significantly predictive of cancer, but hypoechogenicity and central vascularity were frequently found in malignant nodules. These epidemiological, clinical and ultrasound results could increase awareness and guide practitioners in their diagnostic approach and management of thyroid nodules in an Afro-Caribbean population. Bethesda system-based cytology revealed lower sensitivity in analyzing the risk of malignancy in this population. The high prevalence of papillary microcarcinomas may explain the inconclusive ultrasound and cytological results.

The Association of Thyroid Nodules With Blood Trace Elements Identified in a Cross-Section Study

Background

The association between occurrence of thyroid nodules (TNs) and trace elements detectable in blood are still inconclusive. The present study sought to determine the relationship between selected trace elements and TNs in the iodine-adequate area of Guangdong, China.

Methods

A total of 1,048 participants from four communities were enrolled. A number of medical checkups were conducted to collect relevant data on anthropometric parameters, blood pressure, glucose blood levels and lipid profiles, as well as data on thyroid function, presence of thyroid autoantibodies, and trace elements. Presence of TN was diagnosed by ultrasonography.

Results

Of the 1048 participants (49.5 ± 14.4 years old), 543 participants (51.8%) had TNs. Serum copper, magnesium and zinc levels are associated with the presence of TNs among healthy subjects. Subjects with higher levels of zinc, magnesium and copper had 1.23-fold, 1.04-fold, and 1.007-fold increased risks of the prevalence of TNs (P = 0.013, 0.017, and < 0.001, resp). Compared with the first quartile of copper content in serum, participants in the fourth quartile had the highest prevalence of TNs with an odds ratio of 8.90 (95% confidence interval (CI) 5.41, 14.94) among all participants. Women in the third quartile of magnesium level had a 1.86-fold (95%CI 1.05, 3.31) risk of the prevalence of TNs. Subjects in the highest quartile of zinc level had a 1.82-fold (95%CI 1.06, 3.16) risk of the prevalence of TNs in females.

Conclusion

TNs were found highly prevalent in females in the investigated population from an iodine-adequate area of Guangdong, China. The imbalance of selected trace elements (copper, magnesium and zinc) in the body is related to the presence of TNs among healthy subjects. The observed correlation of copper on TNs warrants further studies.

Integrative metabolomic characterization identifies plasma metabolomic signature in the diagnosis of papillary thyroid cancer

Discrimination of malignancy from thyroid nodules poses challenges in clinical practice. We aimed to identify the plasma metabolomic biomarkers in discriminating papillary thyroid cancer (PTC) from benign thyroid nodule (BTN). Metabolomics profiling of plasma was performed in two independent cohorts of 651 subjects of PTC (n = 215), BTN (n = 230), and healthy controls (n = 206). In addition, 132 patients with thyroid micronodules (<1 cm) and 44 patients with BTN suspected malignancy by ultrasound were used for biomarker validation. Recursive feature elimination algorithm was used for metabolic biomarkers selecting. Significant differential metabolites were demonstrated in patients with thyroid nodules (PTC and BTN) from healthy controls (P = 0.0001). A metabolic biomarker panel (17 differential metabolites) was identified to discriminate PTC from BTN with an AUC of 97.03% (95% CI: 95.28-98.79%), 91.89% sensitivity, and 92.63% specificity in discovery cohort. The panel had an AUC of 92.72% (95% CI: 87.46-97.99%), 86.57% sensitivity, and 92.50% specificity in validation cohort. The metabolic biomarker signature could correctly identify 84.09% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. Moreover, high accuracy of 87.88% for diagnosis of papillary thyroid microcarcinoma was displayed by this panel and showed significant improvement in accuracy, AUC and specificity when compared with ultrasound. We identified a novel metabolic biomarker signature to discriminate PTC from BTN. The clinical use of this biomarker panel would have improved diagnosis stratification of thyroid microcarcinoma in comparison to ultrasound.

Synchronous tele-ultrasonography is helpful for a naive operator to perform high-quality thyroid ultrasound examinations

Purpose

This study investigated the value of synchronous tele-ultrasonography (TUS) for naive operators in thyroid ultrasonography (US) examinations.

Methods

Ninety-seven patients were included in this prospective, parallel-controlled trial. Thyroid scanning and diagnosis were completed by resident A independently, resident B with guidance from a US expert through synchronous TUS, and an on-site US expert. The on-site expert’s findings constituted the reference standard. Two other off-site US experts analyzed all data in a blind manner. Inter-operator consistency between the two residents and the on-site US expert for thyroid size measurements, nodule measurements, nodule features, American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) categories, and image quality was compared. Two questionnaires were completed to evaluate the clinical benefit.

Results

Resident B detected more nodules consistent with the on-site expert than resident A did (89.4% vs. 56.5%, P<0.001). Resident B achieved excellent consistency with the on-site expert in terms of ACR TI-RADS categories, nodule composition, shape, echogenic foci, and vascularity (all intra-class correlation coefficients [ICCs] >0.75), while resident A achieved lower consistency in ACR TI-RADS categories, composition, echogenicity, margin, echogenic foci, and vascularity (all ICCs 0.40-0.75). Residents A and B had excellent consistency in target nodule measurements (all ICCs >0.75). Resident B achieved better performance than resident A for gray values, time gain compensation, depth, color Doppler adjustment, and the visibility of key information (all P<0.05). Furthermore, 61.9% (60/97) of patients accepted synchronous TUS, and 59.8% (58/97) patients were willing to pay for it.

Conclusion

Synchronous TUS can help inexperienced residents achieve comparable thyroid diagnostic capability to a US expert.

Stratification of follicular thyroid tumors using data-independent acquisition proteomics and a comprehensive thyroid tissue spectral library

Thyroid nodules occur in about 60% of the population. A major challenge in thyroid nodule diagnosis is to distinguish between follicular adenoma (FA) and carcinoma (FTC). Here, we present a comprehensive thyroid spectral library covering five types of thyroid tissues. This library includes 121 960 peptides and 9941 protein groups. This spectral library can be used to quantify up to 7863 proteins from thyroid tissues, and can also be used to develop parallel reaction monitoring (PRM) assays for targeted protein quantification. Next, to stratify follicular thyroid tumours, we compared the proteomes of 24 FA and 22 FTC samples, and identified 204 differentially expressed proteins (DEPs). Our data suggest altered ferroptosis pathways in malignant follicular carcinoma. In all, 31 selected proteins effectively distinguished follicular tumours. Of those DEPs, nine proteins were further verified by PRM in an independent cohort of 18 FA and 19 FTC. Together, we present a comprehensive spectral library for DIA and targeted proteomics analysis of thyroid tissue specimens, and identified nine proteins that could potentially distinguish FA and FTC.

Construction of the Classification Model Using Key Genes Identified Between Benign and Malignant Thyroid Nodules From Comprehensive Transcriptomic Data

Thyroid nodules are present in upto 50% of the population worldwide, and thyroid malignancy occurs in only 5–15% of nodules. Until now, fine-needle biopsy with cytologic evaluation remains the diagnostic choice to determine the risk of malignancy, yet it fails to discriminate as benign or malignant in one-third of cases. In order to improve the diagnostic accuracy and reliability, molecular testing based on transcriptomic data has developed rapidly. However, gene signatures of thyroid nodules identified in a plenty of transcriptomic studies are highly inconsistent and extremely difficult to be applied in clinical application. Therefore, it is highly necessary to identify consistent signatures to discriminate benign or malignant thyroid nodules. In this study, five independent transcriptomic studies were combined to discover the gene signature between benign and malignant thyroid nodules. This combined dataset comprises 150 malignant and 93 benign thyroid samples. Then, there were 279 differentially expressed genes (DEGs) discovered by the feature selection method (Student’s t test and fold change). And the weighted gene co-expression network analysis (WGCNA) was performed to identify the modules of highly co-expressed genes, and 454 genes in the gray module were discovered as the hub genes. The intersection between DEGs by the feature selection method and hub genes in the WGCNA model was identified as the key genes for thyroid nodules. Finally, four key genes (ST3GAL5, NRCAM, MT1F, and PROS1) participated in the pathogenesis of malignant thyroid nodules were validated using an independent dataset. Moreover, a high-performance classification model for discriminating thyroid nodules was constructed using these key genes. All in all, this study might provide a new insight into the key differentiation of benign and malignant thyroid nodules.