The incidental thyroid nodule.

Incidental thyroid nodules that are found on an imaging study performed for reasons other than thyroid pathology represent a common scenario encountered by health care providers. The initial workup for these nodules comprises a thorough history and physical examination, thyroid function tests, a dedicated thyroid ultrasound, and fine-needle aspiration of any suspicious lesions. Management ranges from observation and reassurance to surgical resection and depends on the cytologic diagnosis. In cases of cytologically indeterminate or discordant nodules, surgical excision (lobectomy) offers a definitive diagnosis, although molecular testing or a reasonable period of observation may be useful as less invasive adjuncts. CA Cancer J Clin 2018;68:97-105. © 2018 American Cancer Society.

Contemporary Management of Thyroid Nodules.

Thyroid nodules are common in the general population, with higher prevalence in women and with advancing age. Approximately 5% of thyroid nodules are malignant; the majority of this subset represents papillary thyroid cancer. Ultrasonography is the standard technique to assess the underlying thyroid parenchyma, characterize the features of thyroid nodules, and evaluate for abnormal cervical lymphadenopathy. Various risk stratification systems exist to categorize the risk of malignancy based on the ultrasound appearance of a thyroid nodule. Nodules are selected for fine-needle aspiration biopsy on the basis of ultrasound features, size, and high-risk clinical history. Cytology results are classified by the Bethesda system into six categories ranging from benign to malignant. When cytology is indeterminate, molecular testing can further risk-stratify patients for observation or surgery. Surveillance is indicated for nodules with benign cytology, indeterminate cytology with reassuring molecular testing, or non-biopsied nodules without a benign sonographic appearance.

Blood leukocytes as a non-invasive diagnostic tool for thyroid nodules: a prospective cohort study.

BACKGROUND: Thyroid nodule (TN) patients in China are subject to overdiagnosis and overtreatment. The implementation of existing technologies such as thyroid ultrasonography has indeed contributed to the improved diagnostic accuracy of TNs. However, a significant issue persists, where many patients undergo unnecessary biopsies, and patients with malignant thyroid nodules (MTNs) are advised to undergo surgery therapy. METHODS: This study included a total of 293 patients diagnosed with TNs. Differential methylation haplotype blocks (MHBs) in blood leukocytes between MTNs and benign thyroid nodules (BTNs) were detected using reduced representation bisulfite sequencing (RRBS). Subsequently, an artificial intelligence blood leukocyte DNA methylation (BLDM) model was designed to optimize the management and treatment of patients with TNs for more effective outcomes. RESULTS: The DNA methylation profiles of peripheral blood leukocytes exhibited distinctions between MTNs and BTNs. The BLDM model we developed for diagnosing TNs achieved an area under the curve (AUC) of 0.858 in the validation cohort and 0.863 in the independent test cohort. Its specificity reached 90.91% and 88.68% in the validation and independent test cohorts, respectively, outperforming the specificity of ultrasonography (43.64% in the validation cohort and 47.17% in the independent test cohort), albeit with a slightly lower sensitivity (83.33% in the validation cohort and 82.86% in the independent test cohort) compared to ultrasonography (97.62% in the validation cohort and 100.00% in the independent test cohort). The BLDM model could correctly identify 89.83% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. In micronodules, the model displayed higher specificity (93.33% in the validation cohort and 92.00% in the independent test cohort) and accuracy (88.24% in the validation cohort and 87.50% in the independent test cohort) for diagnosing TNs. This performance surpassed the specificity and accuracy observed with ultrasonography. A TN diagnostic and treatment framework that prioritizes patients is provided, with fine-needle aspiration (FNA) biopsy performed only on patients with indications of MTNs in both BLDM and ultrasonography results, thus avoiding unnecessary biopsies. CONCLUSIONS: This is the first study to demonstrate the potential of non-invasive blood leukocytes in diagnosing TNs, thereby making TN diagnosis and treatment more efficient in China.

The clinical value of artificial intelligence in assisting junior radiologists in thyroid ultrasound: a multicenter prospective study from real clinical practice.

BACKGROUND: This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histopathology, and to explore whether artificial intelligence (AI) can provide precise assistance for clinical decision-making in the real-world prospective scenario. METHODS: In this prospective study, we enrolled 1036 patients with a total of 2296 thyroid nodules from three medical centers. The diagnostic performance of the AI system, radiologists with different levels of experience, and AI-assisted radiologists with different levels of experience in diagnosing thyroid nodules were evaluated against our proposed 2e diagnostic criteria, with the first being an arbitration committee consisting of 3 senior specialists and the second being cyto- or histopathology. RESULTS: According to the 2e diagnostic criteria, 1543 nodules were classified by the arbitration committee, and the benign and malignant nature of 753 nodules was determined by pathological examinations. Taking pathological results as the evaluation standard, the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of the AI systems were 0.826, 0.815, 0.821, and 0.821. For those cases where diagnosis by the Arbitration Committee were taken as the evaluation standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.946, 0.966, 0.964, and 0.956. Taking the global 2e diagnostic criteria as the gold standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.868, 0.934, 0.917, and 0.901, respectively. Under different criteria, AI was comparable to the diagnostic performance of senior radiologists and outperformed junior radiologists (all P < 0.05). Furthermore, AI assistance significantly improved the performance of junior radiologists in the diagnosis of thyroid nodules, and their diagnostic performance was comparable to that of senior radiologists when pathological results were taken as the gold standard (all p > 0.05). CONCLUSIONS: The proposed 2e diagnostic criteria are consistent with real-world clinical evaluations and affirm the applicability of the AI system. Under the 2e criteria, the diagnostic performance of the AI system is comparable to that of senior radiologists and significantly improves the diagnostic capabilities of junior radiologists. This has the potential to reduce unnecessary invasive diagnostic procedures in real-world clinical practice.

Molecular testing for thyroid nodules: Where are we now?

Approximately 25% of the fine needle aspiration samples (FNAB) of thyroid nodules are classified as "indeterminate samples", that means, Bethesda III and IV categories. Until the last decade, most of these cases underwent diagnostic surgery, although only a minority (13-34%) confirmed malignancy postoperatively. In view of this, with the objective of improving the preoperative diagnosis in these cases, the molecular tests emerged, which are validated from the diagnostic point of view, presenting good performance, with good diagnostic accuracy, being able to avoid diagnostic surgeries. With the advancement of knowledge of the role of each of the mutations and gene rearrangements in thyroid oncogenesis, molecular markers have left to play only a diagnostic role and have been gaining more and more space both in defining the prognostic role of the tumor, as well as in the indication of target therapy. Thus, the objective of this review is to show how to use the tool of molecular tests, now commercially available in the world, in the management of indeterminate cytological nodules, assessing the pre-test malignancy risk of the nodule, through clinical, ultrasonographic and cytological characteristics, and decide on the benefit of molecular testing for each patient. In addition, to discuss its new and promising prognostic and therapeutic role in thyroid cancer.

Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules.

BACKGROUND: The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity. METHODS: A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively. Univariate and multivariate logistic regression were used to obtain ß coefficients, construct predictive models and nomogram incorporating MRI morphological features in the training cohort, and validated in the validation cohort. The discrimination, calibration, and decision curve analysis of the nomogram were performed. The diagnosis efficacy, area under the curve (AUC) and net reclassification index (NRI) were calculated and compared with TI-RADS. RESULTS: 572 thyroid nodules were included (training cohort: n = 397, validation cohort: n = 175). Age, low signal intensity on T2WI, restricted diffusion, reversed halo sign in delay phase, cystic degeneration and wash-out pattern were independent predictors of malignancy. The nomogram demonstrated good discrimination and calibration both in the training cohort (AUC = 0.972) and the validation cohort (AUC = 0.968). The accuracy, sensitivity, specificity, PPV, NPV and AUC of MRI-based prediction were 94.4%, 96.0%, 93.4%, 89.9%, 96.5% and 0.947, respectively. The MRI-based prediction model exhibited enhanced accuracy (NRI>0) in comparison to TI-RADSs. CONCLUSIONS: The prediction model for diagnosis of benign and malignant thyroid nodules demonstrated a more notable diagnostic efficacy than TI-RADS. Compared with the TI-RADSs, predictive model had better specificity along with a high sensitivity and can reduce overdiagnosis and unnecessary biopsies.

US of thyroid nodules: can AI-assisted diagnostic system compete with fine needle aspiration?

OBJECTIVES: Artificial intelligence (AI) systems can diagnose thyroid nodules with similar or better performance than radiologists. Little is known about how this performance compares with that achieved through fine needle aspiration (FNA). This study aims to compare the diagnostic yields of FNA cytopathology alone and combined with BRAFV600E mutation analysis and an AI diagnostic system. METHODS: The ultrasound images of 637 thyroid nodules were collected in three hospitals. The diagnostic efficacies of an AI diagnostic system, FNA-based cytopathology, and BRAFV600E mutation analysis were evaluated in terms of sensitivity, specificity, accuracy, and the κ coefficient with respect to the gold standard, defined by postsurgical pathology and consistent benign outcomes from two combined FNA and mutation analysis examinations performed with a half-year interval. RESULTS: The malignancy threshold for the AI system was selected according to the Youden index from a retrospective cohort of 346 nodules and then applied to a prospective cohort of 291 nodules. The combination of FNA cytopathology according to the Bethesda criteria and BRAFV600E mutation analysis showed no significant difference from the AI system in terms of accuracy for either cohort in our multicenter study. In addition, for 45 included indeterminate Bethesda category III and IV nodules, the accuracy, sensitivity, and specificity of the AI system were 84.44%, 95.45%, and 73.91%, respectively. CONCLUSIONS: The AI diagnostic system showed similar diagnostic performance to FNA cytopathology combined with BRAFV600E mutation analysis. Given its advantages in terms of operability, time efficiency, non-invasiveness, and the wide availability of ultrasonography, it provides a new alternative for thyroid nodule diagnosis. CLINICAL RELEVANCE STATEMENT: Thyroid ultrasonic artificial intelligence shows statistically equivalent performance for thyroid nodule diagnosis to FNA cytopathology combined with BRAFV600E mutation analysis. It can be widely applied in hospitals and clinics to assist radiologists in thyroid nodule screening and is expected to reduce the need for relatively invasive FNA biopsies. KEY POINTS: • In a retrospective cohort of 346 nodules, the evaluated artificial intelligence (AI) system did not significantly differ from fine needle aspiration (FNA) cytopathology alone and combined with gene mutation analysis in accuracy. • In a prospective multicenter cohort of 291 nodules, the accuracy of the AI diagnostic system was not significantly different from that of FNA cytopathology either alone or combined with gene mutation analysis. • For 45 indeterminate Bethesda category III and IV nodules, the AI system did not perform significantly differently from BRAFV600E mutation analysis.

Efficacy of HIFU for the treatment of benign thyroid nodules: a systematic review and meta-analysis.

OBJECTIVE: Thyroid nodules are common and sometimes associated with cosmetic issues. Surgical treatment has several disadvantages, including visible scarring. High-intensity focused ultrasound (HIFU) is a recent noninvasive treatment for thyroid nodules. The present study aims to evaluate the effectiveness and safety of HIFU for the treatment of benign thyroid nodules. METHODS: We searched PubMed, Embase, and Cochrane Library for studies evaluating the outcomes of HIFU for patients with benign thyroid nodules. We conducted a meta-analysis by using a random effects model and evaluated the volume reduction ratio, treatment success rate, and incidence of treatment-related complications. RESULTS: Thirty-two studies were included in the systematic review. Only 14 studies were used in the meta-analysis because the other 18 involved data collected during overlapping periods. The average volume reduction ratios at 3, 6, and 12 months after treatment were 39.02% (95% CI: 27.57 to 50.47%, I2: 97.9%), 48.55% (95% CI: 35.53 to 61.57%, I2: 98.2%), and 55.02% (95% CI: 41.55 to 68.48%, I2: 99%), respectively. Regarding complications, the incidences of vocal cord paresis and Horner's syndrome after HIFU were 2.1% (95% CI: 0.2 to 4.1%, I2: 14.6%) and 0.7% (95% CI: 0 to 1.9%, I2: 0%), respectively. CONCLUSIONS: HIFU is an effective and safe treatment option for patients with benign thyroid nodules. However, the effects of HIFU on nodules of large sizes and with different properties require further investigation. Additional studies, particularly randomized controlled trials involving long-term follow-up, are warranted. CLINICAL RELEVANCE STATEMENT: Surgical treatment for thyroid nodules often results in permanent visible scars and is associated with a risk of bleeding, nerve injury, and hypothyroidism. High-intensity focused ultrasound may be an alternative for patients with benign thyroid nodules. KEY POINTS: • The success rate of HIFU treatment for thyroid nodules is 75.8% at 6 months. Average volume reduction ratios are 48.55% and 55.02% at 6 and 12 months. • The incidence of complications such as vocal fold paresis, Horner's syndrome, recurrent laryngeal nerve palsy, hypothyroidism, and skin redness is low. • HIFU is both effective and safe as a treatment for benign thyroid nodules.

Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.

OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk. METHODS: We conducted a retrospective multicenter study using ultrasound images from four hospitals. Convolutional neural network (CNN) models were constructed to classify ultrasound images of thyroid nodules into solid and non-solid, as well as benign and malignant. A total of 11,201 images of 6784 nodules were used for training, validation, and testing. The area under the receiver-operating characteristic curve (AUC) was employed as the primary evaluation index. RESULTS: The models had AUCs higher than 0.91 in the benign and malignant grading of solid thyroid nodules, with the Inception-ResNet AUC being the highest at 0.94. In the test set, the best algorithm for identifying benign and malignant thyroid nodules had a sensitivity of 0.88, and a specificity of 0.86. In the human vs. DL test set, the best algorithm had a sensitivity of 0.93, and a specificity of 0.86. The Inception-ResNet model performed better than the senior physicians (p < 0.001). The sensitivity and specificity of the optimal model based on the external test set were 0.90 and 0.75, respectively. CONCLUSIONS: This research demonstrates that CNNs can assist thyroid nodule diagnosis and reduce the rate of unnecessary fine-needle aspiration (FNA). CLINICAL RELEVANCE STATEMENT: High-resolution ultrasound has led to increased detection of thyroid nodules. This results in unnecessary fine-needle aspiration and anxiety for patients whose nodules are benign. Deep learning can solve these problems to some extent. KEY POINTS: • Thyroid solid nodules have a high probability of malignancy. • Our models can improve the differentiation between benign and malignant solid thyroid nodules. • The differential performance of one model was superior to that of senior radiologists. Applying this could reduce the rate of unnecessary fine-needle aspiration of solid thyroid nodules.

Volume reduction rate of radiofrequency ablation in ≤ 2 cm Bethesda IV thyroid nodules.

OBJECTIVE: This prospective observational study aimed to evaluate the efficacy of radiofrequency ablation (RFA) in treating ≤ 2 cm thyroid nodules with Bethesda IV cytology and C-TIRADS 4A categorization. Additionally, the factors influencing the completed absorption of ablation (CAA) were examined. METHODS: A total of 62 cases with 62 nodules underwent ultrasound-guided RFA and were included in the study. The volume reduction rate (VRR), CAA, and incomplete absorption of ablation (IAA) were assessed at the 1st, 3rd, 6th, and subsequent 6-month follow-ups. Clinical and ultrasound features were compared between the CAA and IAA groups at the 12th month follow-up. RESULTS: The average VRR at the 1st, 3rd, 6th, 12th month, and last follow-up were -88.6%, 16.0%, 59.7%, 82.0%, and 98.2%, respectively. More than half of the nodules achieved a 90% VRR after 1 year of RFA, with 88.7% demonstrating CAA at the end of the study (follow-up duration of 14 to 63 months). Nodules with grade 3 vascularity and those associated with chronic thyroiditis showed delayed CAA at the 12th month follow-up (p = 0.036 and 0.003, respectively). CONCLUSION: RFA is an effective technique for treating ≤ 2 cm thyroid nodules with Bethesda IV cytology and C-TIRADS 4A categorization. Nodules with grade 3 blood supply and patients with chronic thyroiditis exhibited an impact on the completed absorption following RFA. CLINICAL RELEVANCE STATEMENT: Our study has shown that radiofrequency ablation is an effective treatment for ≤ 2 cm thyroid nodules classified as Bethesda IV cytology. However, we identified that high vascularity of the nodule and chronic thyroiditis are adverse factors affecting the completed absorption of the ablation. KEY POINTS: •Radiofrequency ablation (RFA) is an effective technique for treatment of ≤ 2 cm Bethesda IV category thyroid nodules. •Higher blood supply and chronic thyroiditis influence the completed absorption after RFA.

CT-Based Radiomics Models for Differentiation of Benign and Malignant Thyroid Nodules: A Multicenter Development and Validation Study.

BACKGROUND. CT is increasingly detecting thyroid nodules. Prior studies indicated a potential role of CT-based radiomics models in characterizing thyroid nodules, although these studies lacked external validation. OBJECTIVE. The purpose of this study was to develop and validate a CT-based radiomics model for the differentiation of benign and malignant thyroid nodules. METHODS. This retrospective study included 378 patients (mean age, 46.3 ± 13.9 [SD] years; 86 men, 292 women) with 408 resected thyroid nodules (145 benign, 263 malignant) from two centers (center 1: 293 nodules, January 2018 to December 2022; center 2: 115 nodules, January 2020 to December 2022) who underwent preoperative multiphase neck CT (noncontrast, arterial, and venous phases). Nodules from center 1 were divided into training (n = 206) and internal validation (n = 87) sets; all nodules from center 2 formed an external validation set. Radiologists assessed nodules for morphologic CT features. Nodules were manually segmented on all phases, and radiomic features were extracted. Conventional (clinical and morphologic CT), noncontrast CT radiomics, arterial phase CT radiomics, venous phase CT radiomics, multiphase CT radiomics, and combined (clinical, morphologic CT, and multiphase CT radiomics) models were established using feature selection methods and evaluated by ROC curve analysis, calibration-curve analysis, and decision-curve analysis. RESULTS. The combined model included patient age, three morphologic features (cystic change, "edge interruption" sign, abnormal cervical lymph nodes), and 28 radiomic features (from all three phases). In the external validation set, the combined model had an AUC of 0.923, and, at an optimal threshold derived in the training set, sensitivity of 84.0%, specificity of 94.1%, and accuracy of 87.0%. In the external validation set, the AUC was significantly higher for the combined model than for the conventional model (0.827), noncontrast CT radiomics model (0.847), arterial phase CT radiomics model (0.826), venous phase CT radiomics model (0.773), and multiphase CT radiomics model (0.824) (all p < .05). In the external validation set, the calibration curves indicated the lowest (i.e., best) Brier score for the combined model; in the decision-curve analysis, the combined model had the highest net benefit for most of the range of threshold probabilities. CONCLUSION. A combined model incorporating clinical, morphologic CT, and multiphase CT radiomics features exhibited robust performance in differentiating benign and malignant thyroid nodules. CLINICAL IMPACT. The combined radiomics model may help guide further management for thyroid nodules detected on CT.

Molecular Profiling for Bethesda III to VI Nodules: Results of a Multicenter International Retrospective Study.

OBJECTIVE: Molecular testing is a well-established tool that assists in the management of thyroid nodules. We describe our experience using molecular testing of thyroid nodules with Bethesda III to VI cytology. METHODS: This is a retrospective multicenter, multinational study of thyroid nodules that underwent preoperative molecular profiling with ThyGenX/ThyGeNEXT or ThyroSeq V3 between 2015 and 2022. The clinical characteristics and mutational profiles of tumors were compared. Collected data included demographics, cytology results, surgical pathology, and molecular alterations. Molecular alterations were categorized into 3 main phenotypes: BRAF-like, RAS-like, and non-BRAF-non-RAS (NBNR). RESULTS: Overall, 784 patients who had surgery were included, of which 603 (76.2%) were females. The most common histologic type was papillary thyroid cancer (PTC) with 727 (91.9%) cases. In total, 205 (28.2%) cases showed an aggressive subtype of PTC (eg, tall cell and hobnail). BRAF-like alterations were most likely to be found in Bethesda V and VI nodules and show extrathyroidal extension (ETE), nodal disease, and/or aggressive subtypes of PTC (P < .001 for all). RAS-like alterations were more commonly found in Bethesda III and IV nodules and were less likely to show ETE, nodal disease, and/or aggressive histology (P < .001 for all). NBNR alterations were more commonly found in Bethesda III and IV nodules and were less likely to show ETE, nodal disease, and/or aggressive subtypes of PTC. However, they were rarely but significantly associated with poorly differentiated thyroid cancer (P < .005). CONCLUSION: Molecular testing of thyroid nodules can help determine the likelihood of malignancy and classify nodules into several tumor phenotypes, predicting their behaviors and potentially allowing for a more tailored treatment. NBNR alterations should be managed with caution.

Thyroid Nodules: Past, Present, and Future.

BACKGROUND: Over the past millennia, the evaluation and management of thyroid nodules has essentially remained the same with thyroidectomy as the only reliable method to identify malignancy. However, in the last 30 years, technological advances have significantly improved diagnostic management of thyroid nodules. Advances in imaging have allowed development of a reliable risk- based stratification system to identify nodules at increased risk of malignancy. At the same time, sensitive imaging has caused collateral damage to the degree that we are now identifying and treating many small, low risk nodules with little to no clinical relevance. OBJECTIVE: To review the history of thyroid nodule evaluation with emphasis on recent changes and future pathways. METHODS: Literature review and discussion. RESULTS: Thyroid ultrasound remains the best initial method to evaluate the thyroid gland for nodules. Different risk-of-malignancy protocols have been developed and introduced by different societies, reporting methods have been developed and improved each, with goals of improving the ability to recognize nodules requiring further intervention and minimizing excessive monitoring of those who do not. Once identified, cytological evaluation of nodules further enhances malignancy identification with molecular markers assisting in ruling out malignancies in indeterminate nodules preventing unneeded intervention. And all societies have urged avoidance of overdiagnosis and overtreatment of low-risk cancers of little to no clinical relevance. CONCLUSION: In this review, we describe advancements in nodule evaluation and management, while emphasizing caution in overdiagnosing and overtreating low-risk lesions without clinical importance.

Assessing the Frequency of Deferrable Thyroid Nodule Biopsies to De-escalate Low-Value Care.

OBJECTIVE: Thyroid nodules are common, yet fewer than 1 in 10 harbors malignancy. When present, thyroid cancer is typically indolent with excellent survival. Therefore, patients who are not candidates for thyroid cancer treatment due to comorbid disease may not require further thyroid nodule evaluation. The goal of this study was to determine the rate of deferrable thyroid nodule biopsies in patients with limited life expectancy. METHODS: We identified patients who underwent thyroid fine needle aspiration (FNA) between 2015 and 2018 at our institution. The primary outcome was the number of deferrable FNAs, defined as FNAs performed in patients who died within 2 years after biopsy. Secondary outcomes included cytologic Bethesda score, procedure costs, and final diagnosis on surgical pathology. Multivariable logistic and Cox proportional hazards regressions were used to evaluate factors associated with FNA in patients with limited life expectancy. RESULTS: A total of 2565 FNAs were performed. Most patients were female (79%), and 37 (1.5%) patients died within 2 years. Nonthyroid specialists were significantly more likely to order deferrable FNAs (odds ratio 4.13, P < .001). Of the patients who died within 2 years, most (78%) had a concomitant diagnosis of nonthyroid cancer, and 4 went on to have thyroid surgery (Bethesda scores: 3, 4, 4, and 6). Spending associated with deferrable FNAs and subsequent surgery totaled over $98 000. CONCLUSIONS: Overall, the rate of deferrable thyroid nodule biopsies was low. However, there is an opportunity to reduce low-value biopsies in patients with a concurrent nonthyroid cancer by partnering with oncology providers.

Prevalence of thyroid nodule and relationship with physiological and psychosocial factors among adults in Zhejiang Province, China: a baseline survey of a cohort study.

BACKGROUND: Thyroid nodules have attracted much attention due to their high incidence and potential for malignant transformation. Compared with the clinical assessment and diagnosis of thyroid nodules, there are relatively few studies on the epidemiological risk factors for thyroid nodules. The aim of this study was to investigate the prevalence of thyroid nodule among adults in Zhejiang province and to explore their relationship with physiological and psychosocial factors. METHODS: The data used in this study were obtained from the baseline survey of the Zhejiang Provincial Cohort Study on Environment and Health. From June 2022 to December 2023, a total of 21,712 participants from five representative cities in Zhejiang were recruited for the baseline survey. Based on the inclusion and exclusion criteria, 15,595 adults were included in the analysis. The data were collected via self-report questionnaires and physical examinations. Multivariate logistic regression analysis was subsequently performed. RESULTS: The detection rate of thyroid nodules was 50.98% among adults in Zhejiang province. Age, gender, education level, BMI, tea and alcohol consumption all had a statistically significant association with thyroid nodules (p < 0.05). After adjusting for sociodemographic factors, results of logistic regression analysis showed that good life satisfaction (OR = 0.854, 95% CI: 0.780-0.934) had a lower risk of thyroid nodules, however, poor life satisfaction (OR = 1.406, 95% CI: 1.014-1.951), social isolation (OR = 1.294, 95% CI: 1.089-1.538) and a family history of thyroid nodules (OR = 1.334, 95% CI: 1.064-1.672) had a greater risk of thyroid nodules. CONCLUSION: The detection rate of thyroid nodules in adults of Zhejiang province was an increasing trend compared with that in previous years. In addition to the sensitive thyroid nodule screening technology, influencing factors mentioned in this study might also represent credible candidates for this increase. As variable influence factors, weight management, good interpersonal relationships and life satisfaction should be the focus of health interventions.

Comparison of the diagnostic effectiveness of ultrasound imaging coupled with three mathematical models for discriminating thyroid nodules.

BACKGROUND: The overlapping nature of thyroid lesions visualized on ultrasound (US) images could result in misdiagnosis and missed diagnoses in clinical practice. PURPOSE: To compare the diagnostic effectiveness of US coupled with three mathematical models, namely logistic regression (Logistics), partial least-squares discriminant analysis (PLS-DA), and support vector machine (SVM), in discriminating between malignant and benign thyroid nodules. MATERIAL AND METHODS: A total of 588 thyroid nodules (287 benign and 301 malignant) were collected, among which 80% were utilized for constructing the mathematical models and the remaining 20% were used for internal validation. In addition, an external validation cohort comprising 160 nodules (80 benign and 80 malignant) was employed to validate the accuracy of these mathematical models. RESULTS: Our study demonstrated that all three models exhibited effective predictive capabilities for distinguishing between benign and malignant nodules, whose diagnostic effectiveness surpassed that of the TI-RADS classification, particularly in terms of true negative diagnoses. SVM achieved a higher diagnostic rate for malignant thyroid nodules (93.8%) compared to Logistics (91.5%) and PLS-DA (91.6%). PLS-DA exhibited higher diagnostic rates for benign thyroid nodules (91.9%) compared to Logistics (86.7%) and SVM (88.7%). Both the area under the receiver operating characteristic curve (AUC) values of PLS-DA (0.917) and SVM (0.913) were higher than that of Logistics (0.891). CONCLUSION: Our findings indicate that SVM had significantly higher rates of true positive diagnoses and PLS-DA exhibited significantly higher rates of true negative diagnoses. All three models outperformed the TI-RADS classification in discriminating between malignant and benign thyroid nodules.

An Improved k-Nearest Neighbor Algorithm for Recognition and Classification of Thyroid Nodules.

OBJECTIVES: To complete the task of automatic recognition and classification of thyroid nodules and solve the problem of high classification error rates when the samples are imbalanced. METHODS: An improved k-nearest neighbor (KNN) algorithm is proposed and a method for automatic thyroid nodule classification based on the improved KNN algorithm is established. In the improved KNN algorithm, we consider not only the number of class labels for various classes of data in KNNs, but also the corresponding weights. And we use the Minkowski distance measure instead of the Euclidean distance measure. RESULTS: A total of 508 ultrasound images of thyroid nodules, including 415 benign nodules and 93 malignant nodules, were used in the paper. Experimental results show the improved KNN has 0.872549 accuracy, 0.867347 precision, 1 recall, and 0.928962 F1-score. At the same time, we also considered the influence of different distance weights, the value of k, different distance measures on the classification results. CONCLUSIONS: A comparison result shows that our method has a better performance than the traditional KNN and other classical machine learning methods.

Evaluation and application of American College of Radiology Thyroid Imaging Reporting and Data System for improved malignancy detection in paediatric thyroid nodules.

OBJECTIVE: The American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) is a widely used method for the management of adult thyroid nodules. However, its use in paediatric patients is controversial because adult fine needle aspiration biopsy (FNAB) recommendations may lead to delayed diagnoses of cancer in children. The objectives of this study were to evaluate the performance of TI-RADS in paediatric thyroid nodules and to tailor FNAB recommendations for children. METHODS: Consecutive surgically resected paediatric thyroid nodules from two tertiary care centres between 2003 and 2021 were reviewed. Ultrasounds were blindly scored by radiologists according to TI-RADS. Management recommendations based on TI-RADS were evaluated. Various modelling methodologies were used to determine the optimal cutoff for FNAB in children. RESULTS: Of the 96 patients, 79 (82%) were female and the median age at surgery was 16.1 years. Fifty (52%) nodules were malignant on surgical pathology. The area under the receiver operating characteristic curve of TI-RADS for predicting malignancy was 0.78. Adult TI-RADS recommendations would have resulted in 4% of cancerous nodules being lost to follow-up. Modifications to TI-RADS (FNAB of all TR3 nodules ≥1.5 cm, FNAB of TR4 and TR5 nodules ≥0.5 cm, surveillance of nodules ≥1 cm, consider surgery for nodules >4 cm) reduced this missed malignancy rate to 0%. CONCLUSIONS: TI-RADS can risk-stratify paediatric thyroid nodules. However, the system requires modifications to reduce the missed malignancy rate in paediatric thyroid nodules. Our data suggest that lower size thresholds for FNAB are warranted in children.

Assessment of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS™) with modification of the management recommendations for pediatric thyroid nodules.

BACKGROUND: Thyroid nodules are unusual in children, but when present, they carry a higher risk for malignancy, as compared to adults. Several guidelines have been created to address the risk stratification for malignancy of thyroid nodules in adults, but none has been completely validated in children. A few authors have proposed lowering the size threshold to the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS™) management guidelines to decrease missed carcinomas at presentation in children; however, little information is known regarding their accuracy. OBJECTIVE: To assess the performance of proposed modifications of the ACR TI-RADS™ size criteria to guide management decisions in pediatric thyroid nodules and to assess the associated increase in number of fine needle aspiration (FNA) and follow-up exams. MATERIALS AND METHODS: This is a retrospective study of children under 18 years old who underwent ultrasound assessment of a thyroid nodule at a tertiary care pediatric institution between January 2006 and August 2021. The largest dimension, maximum ACR TI-RADS™ score, and final thyroid nodules' diagnoses were documented. The course of action based on the adult ACR TI-RADS™ and after modifying the size threshold for management recommendations was documented and compared. Statistics included descriptive analysis, weighted Kappa statistics, sensitivity, specificity, accuracy, and positive/negative predictive values of the ACR TI-RADS™ presented with 95% confidence intervals (CI) using either Clopper-Pearson or standard logit methods. RESULTS: Of 116 nodules, 18 (15.5%) were malignant. Most malignant nodules (94.4%, n = 17) were ACR TI-RADS™ 4 and ACR TI-RADS™ 5 categories. Based on the adult ACR TI-RADS™ criteria, 24 (24.5%) benign and 15 (83.3%) malignant nodules would have undergone FNA; 14 (14.3%) benign and 3 (16.7%) malignant nodules would have been followed up; and 60 (61.2%) benign and none of malignant nodules would have been dismissed. Three (16.7%) malignant nodules would not have been recommended FNA at presentation, delaying their diagnoses. By lowering the size-threshold criteria of the ACR TI-RADS™ guidelines, no malignancy would have been missed at presentation, but this also resulted in a higher number of FNA from 24 (24.5%) to 36 (36.7%) and follow-up ultrasound exams from 14 (14.3%) to 62 (63.3%). CONCLUSION: Applying potential modifications to the ACR TI-RADS™ guideline lowering the size threshold criteria of the thyroid nodule to guide management decisions for pediatric thyroid nodules can lead to early detection of malignant nodules in children, but at the cost of a significantly increased number of biopsies or ultrasound exams. Further tailoring of the guideline with larger multicentric studies is needed, before warranting its acceptance and general use in the pediatric population.

Thyroid US-guided FNA techniques: A prospective,randomized controlled study.

BACKGROUND: Thyroid nodules are common in the general population. Ultrasonography is the most efficient diagnostic approach to evaluate thyroid nodules. The US FNAC procedure can be performed using either the short axis (perpendicular), or a long axis (parallel) approach to visualize the needle as it is advanced toward the desired nodule. The main aim of this study was to compare the percentage of non-diagnostic results between the long and short axis approach. METHODS: A prospective study that included a randomized controlled trial and was divided into two arms-the short axis and the long axis-was conducted. A total of 245 thyroid nodules were collected through the fine needle aspiration cytology, performed with ultrasound, from march 2021 to march 2022. The patient's demographic information were collected and also nodules characteristics. RESULTS: Of 245 nodules sampled, 122 were sampled with the long axis method, while 123 with the short axis method. There is not significantly less non diagnostic approach with either method compared to the other (11.5 % vs 16.3 % respectively). DISCUSSION: Previous studies came to the conclusion that the long axis method yields fewer non diagnostic samples. This study evaluated the two FNA approaches which were proceeded by the same physician who is expert in both techniques. CONCLUSION: The US FNAC performed in the long axis approach will not produce more conclusive results and less non diagnostic results (Bethesda category 1) than the short axis approach one.