Malignant Thyroid Nodules Research Articles

Distinguishing benign and malignant thyroid nodules using plasma trimethylamine N-oxide, carnitine, choline and betaine

PurposeTrimethylamine N-oxide (TMAO), a gut microbiome–derived metabolite, and its precursors (carnitine, choline, betaine) have not been fully examined in relation to thyroid cancer (TC) risk. The aim of this study was to assess the value of TMAO and its precursors in diagnosis of benign and malignant thyroid nodules.MethodsIn this study, high-performance liquid chromatography-tandem mass spectrometry was utilized to measure the levels of plasma TMAO and its precursors (choline, carnitine, and betaine) in 215 TC patients, 63 benign thyroid nodules (BTN) patients and 148 healthy controls (HC). The distribution of levels of TMAO and its precursors among the three groups were compared by the Kruskal–Wallis test. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the sensitivity, specificity, and the predictive accuracy of single and combined biomarkers.ResultsIn comparison to HC, TC showed higher levels of TMAO and lower levels of its precursors (carnitine, choline, and betaine) (all P < 0.001). Plasma choline (P < 0.01) and betaine (P < 0.05) were declined in BTN than HC. The levels of carnitine (P < 0.001) and choline (P < 0.05) were significantly higher in BTN than that in TC group. Plasma TMAO showed lower levels in TC with lymph node metastasis (101.5 (73.1–144.5) ng/ml) than those without lymph node metastasis (131 (84.8–201) ng/ml, P < 0.05). Combinations of these four metabolites achieved good performance in the differential diagnosis, with the area under the ROC curve of 0.703, 0.741, 0.793 when discriminating between TC and BTN, BTN and HC, TC and HC, respectively.ConclusionPlasma TMAO, along with its precursors could serve as new biomarkers for the diagnosis of benign and malignant thyroid nodules.

Somatostatin receptor imaging of thyroid tissue and differentiated thyroid cancer using gallium-68-labeled radiotracers-a review of clinical studies.

The rise in thyroid cancer incidence, especially papillary thyroid cancer (PTC), has underscored the need for improved diagnostic methods and management strategies. Herein, we aim to comprehensively review the evolving landscape in thyroid cancer diagnosis and the potential utility of Gallium-68 (Ga-68) based somatostatin receptor imaging. We reviewed the clinical studies involving Ga-68 based radiotracers by looking at the following literature databases -PUBMED, EMBASE, WEB OF SCIENCE and COCHRANE. We employed a detailed search strategy with the following search terms; PubMed: ("gallium Ga 68 dotatate" [Supplementary Concept]) AND ("Thyroid Gland"[Mesh] OR "Thyroid Nodule"[Mesh] OR "Thyroid Neoplasms"[Mesh]), Embase ("gallium 68" AND "Thyroid Disease"), Web of Science: ("Gallium 68 and Thyroid"). A comparison between Ga-68 DOTATATE and Ga-68 DOTANOC showed similar sensitivities but a higher uptake for Ga-68 DOTATATE. Studies comparing Ga-68-based SSTR PET with FDG PET highlighted the potential advantages of both approaches, with Ga-68-based SSTR PET being more specific in certain cases. Ga-68-based somatostatin receptor imaging displays clinical utility in RAI-R DTC, offering valuable insight into detecting skeletal lymph node metastases. Notably, it shows potential as a primary imaging tool, potentially augmenting the role of FDG PET. However, SSTR PET imaging's efficacy in distinguishing benign from malignant thyroid nodules varies, with a complex interplay of factors influencing its specificity, indicating its value as an adjunct to existing methods, warranting further research for a refined role in thyroid cancer management. Although study variations exist, Ga-based somatostatin receptor imaging holds potential as a complementary tool alongside diagnostic methods in thyroid cancer diagnosis, with particular relevance to RAI-R DTC. In carefully selected patients demonstrating the presence of Ga-68 DOTATATE avid lesions, further exploration, and investigation into the potential utilization of Lu177 DOTATATE are warranted.

Diagnostic Efficiency of ACR-TIRADS Score for Differentiating Benign and Malignant Thyroid Nodules of Various Pathological Types.

BACKGROUND Thyroid nodule prevalence reaches 65% in the general population. Hence, appropriate ultrasonic examination is key in disease monitoring and management. We investigated the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) score for diagnosis of benign and malignant thyroid nodules and pathological types. MATERIAL AND METHODS A retrospective study was conducted. According to ultrasound images, ultrasonic characteristics of benign and malignant thyroid nodules and different pathological types were analyzed using ACR-TIRADS score, and diagnostic value was determined. AUCs were compared for tumor diagnosis and differentiation. RESULTS Overall, 1675 thyroid nodules from 1614 patients were included. AUC value of papillary thyroid carcinoma (PTC) diagnosed with ACR-TIRADS was highest (0.955 [95% CI=0.946-0.965]), while that of follicular thyroid carcinoma (FTC) was lowest (0.877 [95% CI=0.843-0.912]). FTC had the highest sensitivity (95.1%) and lowest specificity (64.8%). When the cut-off value was 5.5 points, accuracy of diagnosing PTC and anaplastic thyroid carcinoma (ATC) was highest, 80.5% and 78.7% respectively. Comparison of the multi-index prediction model constructed by multivariable logistic regression analysis and prediction model constructed by ACR-TIRADS score showed, when evaluating PTC and ATC, the multi-index model was better: AUCs of PTC were 0.966 vs 0.955, and AUCs of ATC were 0.982 vs 0.952, respectively, (P<0.05). CONCLUSIONS ACR-TIRADS score-based ultrasound examination of thyroid nodules aids diagnosis of benign and malignant thyroid nodules. TIRADS criteria favor diagnosis of PTC (and ATC) over FTC. ACR-TIRADS score can help clinicians diagnose thyroid nodules quickly and earlier, exhibits good clinical value, and can prevent missed diagnoses.

DIAGNOSTIC ACCURACY OF TIRADS CLASSIFICATION IN DIFFERENTIATING BENIGN AND MALIGNANT THYROID NODULES KEEPING FINE NEEDLE ASPIRATION CYTOLOGY (FNAC) AS GOLD STANDARD

Thyroid nodules represent a joint clinical presentation of various benign and malignant thyroid diseases. Diagnostic ultrasound, particularly utilizing the Thyroid Imaging Reporting and Data System (TI-RADS), has emerged as a pivotal tool for stratifying the risk of malignancy in thyroid nodules and guiding decisions regarding fine-needle aspiration biopsy (FNAC). However, comprehensive validation studies are warranted to assess the diagnostic accuracy of ultrasound-based TI-RADS classification compared to FNAC as the gold standard. This cross-sectional validation study, conducted at the Department of Radiology, CPE Institute of Cardiology Multan from August 2, 2021, to February 1, 2022, enrolled 243 patients presenting with thyroid nodules, including multiple and solitary nodules. Baseline demographic variables, including age, gender, and nodule duration, were recorded for each participant. Ultrasonography was performed in all patients, and TI-RADS scores were calculated. Subsequently, fine-needle aspiration biopsies, guided by ultrasound, were obtained in the radiology department and sent to the histopathology department for confirmation of malignancy. The mean age of the cohort was 42.05 ± 12.27 years, with a mean nodule duration of 6.87 ± 3.56 months. The mean TI-RADS score was 3.46 ± 2.00. Of the participants, 176 (72.43%) were male and 67 (27.57%) were female. Malignancy was detected in 84 (34.57%) patients based on TI-RADS score, whereas FNAC confirmed malignancy in 50 (20.58%) patients. Evaluating diagnostic accuracy with FNAC as the gold standard, the TI-RADS score demonstrated a sensitivity of 84.0%, specificity of 78.2%, positive predictive value (PPV) of 50.0%, and negative predictive value (NPV) of 95.0%. Our findings indicate that the TI-RADS scoring system is reliable in predicting malignancy in patients with thyroid nodules. With a sensitivity of 84.0% and specificity of 78.2%, TI-RADS represents a valuable adjunctive tool in the diagnostic algorithm for thyroid nodules, offering considerable potential for improved clinical decision-making and patient management strategies.

Comparative evaluation of shear wave elastography elasticity values in thyroid nodules with cytology results and TI-RADS scoring in differentiation of benign–malignant nodules

PurposeThe aim of this prospective study was to investigate the diagnostic performance of shear wave elastography (SWE) in differentiating benign and malignant thyroid nodules and their correlation with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS).MethodsThis prospective study included 370 thyroid nodules in 308 patients aged 18–70 years. All the patients underwent B-mode ultrasound (US), Doppler examination, and SWE and were given an ACR TI-RADS risk score before fine needle aspiration biopsy (FNAB) and/or surgery. The correlation between SWE parameters and ACR TI-RADS categories was investigated statistically and compared with histopathologic results. Additionally, the diagnostic performance of SWE was evaluated to distinguish malignant and benign thyroid nodules.ResultsOne hundred and thirty-five of the 370 thyroid nodules were malignant, and 235 nodules were benign. The mean shear wave velocity (SWV) value of the malignant nodules (3.70 ± 0.98 m/s) was statistically higher than that of the benign nodules (2.70 ± 0.37 m/s). The best cutoff value of the mean SWV for differentiating benign and malignant nodules was found to be 2.94 m/s (sensitivity 90.4%, specificity 89.9%, positive predictive value 81.3%, negative predictive value 94.1%, p < 0.001). The average score of the nodules according to the ACR TI-RADS was 3.57 ± 1.83 in benign nodules and 7.38 ± 2.69 in malignant nodules (p ≤ 0.001).ConclusionThis study showed that combining SWE and TI-RADS improves the specificity of TI-RADS alone in differentiating benign and malignant nodules.

Correlation of ultrasound features in the TIRADS scoring system with cytological findings in the FNAC of thyroid nodules and their association with the metabolic status

BackgroundThyroid nodules were widely encountered in the population, and the selection of thyroid nodules for fine needle aspiration cytology (FNAC) remains confusing. It is essential to investigate the risk factors associated with thyroid nodules.Aim of workThis study aimed to evaluate the accuracy of the American College of Radiology-Thyroid Imaging Reporting and Data System (ACR-TIRADS) scoring system in distinguishing malignant thyroid nodules from benign ones and its association with cytological examination of the FNAC of the thyroid nodules. Additionally, we seek to investigate any potential association between thyroid nodules and some metabolic derangements.Patients and methodsThe study included 111 Egyptian patients with euthyroid nodules whom were subjected to history taking, clinical examination, and laboratory investigations including thyroid profile, fasting blood sugar (FBS), glycosylated hemoglobin A1c (HbA1c), and lipid profile. Thyroid ultrasound and FNAC were done for all patients. Categorization of each nodule was done according to the TIRADS. Cytopathological diagnosis was done by Bethesda system cytology classification.ResultsThere were 19 malignant and 92 benign nodules. There was a statistically significant difference between benign and malignant nodules regarding TIRADS classification, taller-than-wide shape, solidity, border, presence of peripheral calcifications, or punctuate echogenic foci (p < 0.05). Taller-than-wide shape had the highest specificity followed by irregular margin (94.6% and 92.6%, respectively). Sensitivity, specificity, PPV, and NPV for ACR-TIRADS versus cytopathology were 73.7%, 57.6%, 26.4%, and 91.4% respectively with overall accuracy of 60.4%. The high sensitivity and NPV of the US-based TIRADS classification system have excellent utility for correctly classifying nodules as positive for malignant disease. As regards risks for thyroid nodules, results showed that most of the study population were obese [Body Mass Index (BMI) = 31.6 ± 6.3, Waist circumference (WC) = 107.4 ± 13.9]. TSH and hypercholesterolemia did not show a significant association with thyroid malignancy.ConclusionACR-TIRADS classification is of high significant value in classifying nodules as positive for malignant disease and for predicting the absence of malignant disease, reducing unnecessary nodule FNAC. Hypercholesterolemia and TSH value were not significantly associated with malignant thyroid nodules.

Localization and Risk Stratification of Thyroid Nodules in Ultrasound Images Through Deep Learning

ObjectiveDeep learning algorithms have commonly been used for the differential diagnosis between benign and malignant thyroid nodules. In this study, we aimed to develop an integrated system that combines deep learning model and clinical standard thyroid imaging reporting and data system (TI-RADS) for the simultaneous segmentation and risk stratification of thyroid nodules. Methods304 ultrasound images from two independent sites with TI-RADS 4 thyroid nodules were collected. Edge-connection and Criminisi algorithm was used to remove manually-induced markers in ultrasound images. An integrated system based on TI-RADS and mask region-based convolution neural network (Mask R-CNN) was proposed to stratify subclasses of TI-RADS 4 thyroid nodules and to segment thyroid nodules in the ultrasound images. Accuracy and precision-recall curve were used to evaluate stratification performance, dice similarity coefficient (DSC) between the segmentation of Mask R-CNN and the radiologist's contour was used to evaluate segmentation performance of the model. ResultsThe combined approach could significantly enhance the performance of the proposed integrated system. Overall stratification accuracy of TI-RADS 4 thyroid nodules, mean average precision, and mean DSC of the proposed model in the independent test set were 90.79%, 0.8579, and 0.83, respectively. Specifically, stratification accuracy for TI-RADS 4a, 4b and 4c thyroid nodules were 95.83%, 84.21%, and 77.78%. ConclusionAn integrated system combining TI-RADS and deep learning model was developed. The system can provide clinicians with not only diagnostic assistance from TI-RADS, but also accurate segmentation of thyroid nodules, which improves the applicability of the system in clinical practice.

Outcomes of cytologically indeterminate thyroid nodules managed with Genomic Sequencing Classifier.

Molecular testing can refine the risk of malignancy in thyroid nodules with indeterminate cytology to decrease unnecessary diagnostic surgery. This study was performed to evaluate the outcomes of cytologically indeterminate thyroid nodules managed with Afirma genomic sequencing classifier (GSC) testing. Adult patients who underwent a biopsy at three major academic centers between July 2017 and June 2021 with Bethesda III or IV cytology were included. All patients had surgery or minimum follow-up of 1 year ultrasound surveillance. The primary outcomes were the sensitivity, specificity, PPV, and NPV of GSC in Bethesda III and IV nodules. The median nodule size of the 834 indeterminate nodules was 2.1 cm and the median follow-up was 23 months. GSC's sensitivity, specificity, PPV, and NPV across all institutions were 95%, 81%, 50%, and 99% for Bethesda III nodules and 94%, 82%, 65%, and 98% for Bethesda IV nodules, respectively. The overall false negative rate was 2%. The NPV of GSC in thyroid nodules with oncocytic predominance was 100% in Bethesda III nodules and 98% in Bethesda IV nodules. However, the PPV of oncocytic nodules was low (17% in Bethesda III nodules and 45% in Bethesda IV nodules). Only 22% of thyroid nodules with benign GSC results grew during surveillance. GSC is a key tool for managing patients with indeterminate cytology, including the higher-risk Bethesda IV category. GSC benign thyroid nodules can be observed similarly to thyroid nodules with benign cytology.

Sensitivity and Specificity Analysis of Fine Needle Aspiration Cytology (FNAC) for Thyroid Swelling.

Introduction Thyroid gland disorders, such as goiters or tumor masses, are the result of localized or systemic aberrations of the thyroid gland. The purpose of this research was to see how effective fine needle aspiration cytology (FNAC) was in detecting thyroid swelling in patients with thyroid swelling. It is critical to be able to differentiate between benign and malignant thyroid nodules to reduce unnecessary thyroid surgeries. It is hypothesized that FNAC is not a reliable diagnostic tool to detect thyroid nodules in patients with thyroid swelling and that there is a significant variation between the number of thyroid nodules detected by FNAC and the number of thyroid nodules that were eventually diagnosed as malignant by surgery. The significance of this research shows the effectiveness of diagnostic tests for thyroid nodules in patients with thyroid swelling can help reduce unnecessary surgeries and improve patient care. Methods This cross-sectional study was carried out at the Department of Pathology at a tertiary care hospital in central India, from March 1, 2022 to June 31, 2022. Fifty patients with thyroid swelling were covered in the study. All patients were chosen after an ultrasound revealed goiter on clinical grounds. Results The majority of patients in the age group 31-40 years (33.33%) were female (74.67%). About 54.67% of the patients had a single thyroid nodule. FNAC had a sensitivity of 95.38%, a specificity of 53.33%, a positive predictive value of 86.67% and a negative predictive value of 88.57%. Conclusion FNAC is a simple, economical, and commonly used first-line diagnostic method for thyroid cancer. A false negative or false positive cytological diagnosis may be produced as a result of thyroid cytology. The study emphasizes the need to improve basic healthcare in rural India by treating FNAC as a first-line diagnostic test for thyroid swellings to guide management, although it does not replace histopathology.

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

BackgroundThe 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.MethodsA retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively. Univariate and multivariate logistic regression were used to obtain β 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.Results572 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.ConclusionsThe 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.

Near-Infrared Spectroscopy for Distinguishing Malignancy in Thyroid Nodules.

Thyroid nodules are common clinical entities, with a significant proportion being malignant. Early, accurate, and non-invasive tools to differentiate benign and malignant nodules can optimize patient management and reduce unnecessary surgery. This study aimed to evaluate the efficacy and accuracy of near-infrared spectroscopy (NIRS) in distinguishing benign from malignant thyroid nodules. A diffuse reflectance spectrum for a total of 20 thyroid nodule samples (10 samples as colloid goiter and 10 samples as thyroid cancer), were acquired in the wavelength range from 1000 to 2500 nm. Spectral data from NIRS were analyzed by means of principal component analysis (PCA), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) to classify and differentiate thyroid nodule samples. The present study found that NIRS effectively distinguished colloid goiter and thyroid cancer using the first two principal components (PCs), explaining 90% and 10% of the variance, respectively. QDA discrimination plot displayed a clear separation between colloid goiter and thyroid cancer with minimal overlap, aligning with reported 95% accuracy. Additionally, applying LDA to seven PCs from PCA achieved a 100% accuracy rate in classifying colloid goiter and thyroid cancer from near-infrared spectral data. In conclusion, NIRS offers a promising, non-invasive complementing diagnostic tool for differentiating benign from malignant thyroid nodules with high accuracy. Future work should integrate these results into predictive model development, emphasizing external validation, alternative performance metrics, and protecting against potential overfitting translation of a machine learning model to a clinical setting.

Should there be a paradigm shift for the evaluation of isthmic thyroid nodules?

PurposeAlthough the thyroid isthmus seems like a rudimentary structure that connects bilateral lobes, it is an undiscovered area that needs to be explored. Currently, the data is evolving that the increase in the risk of malignancy is higher in the isthmic nodules, and extrathyroidal extensions and lymph node metastases are more common in isthmic-derived malignant thyroid nodules. Therefore, we aimed to compare the malignancy rate of isthmic and lobar nodules, the ultrasonographic features of isthmic and lobar nodules, and presence of lymph node metastases, distant metastases, and extrathyroidal invasions in malignant isthmic nodules.MethodsIn this retrospective study, we enrolled patients between the ages of 18–80 years, who had thyroid nodule/nodules cytology and/or pathology results from January 2009 to November 2022. 9504 nodules were selected for the analysis of US findings, cytopathology results, and malignancy rates.ResultsA mean ± SD age of 55.3 ± 13.0 years with a female to male ratio of [7618 (80.2%)/1886(19.8%)] were included in the study. 962 of the nodules were at isthmic localization; whereas 8542 nodules were at lobar localization. 1188 nodules were resulted as malignant from histopathological evaluation. Of the 1188 malignant nodules, 986 nodules were (83.0%) PTC, 114 nodules (9.6%) were FTC, 55 nodules were (4.6%) MTC, 16 nodules 1.3% were Hurtle cell carcinoma, 8 nodules (0.7%) were anaplastic thyroid carcinoma, and 9 nodules (0.8%) were thyroid tumors of uncertain malignant potential (TT-UMP). 156 of the malignant nodules (13.1%) were located in the isthmus, whereas the majority of the malignant nodules (n = 1032, 86.9%) were located at the lobar parts (right or left) of the thyroid. When the metastasis patterns of isthmic and lobar thyroid cancers were examined, no significant relationship was found between isthmic and lobar cancers in terms of capsule invasion (p = 0.435), muscle invasion (p = 0.294), and lymph node metastasis (p = 0.633). A significant relation was found between nodule localization (isthmus-upper-middle and lower lobes) and malignancy (p < 0.001). In our logistic regression analysis, isthmic and upper pole nodule localizations, age and TI-RADS were evaluated as independent risk factors for malignancy (p < 0.001 for all factors).ConclusionWe recommend nodule localization has to be considered an additional risk factor when performing a Fine Needle Aspiration Biopsy for the increased malignancy risk in this localization.

Integrated use of contrast-enhanced and grey-scale ultrasound in assigning American College of Radiology Thyroid Imaging-Reporting and Data System scores for characterisation of thyroid nodules: A prospective observational study.

The advent and increased use of high-resolution ultrasonography has resulted in improved detection of thyroid nodules. Even with the use of various Thyroid Imaging-Reporting and Data System, accurate imaging diagnosis of malignant thyroid nodules has been suboptimal, which necessitated use of newer modalities like contrast-enhanced ultrasonography alone and in combination for this purpose. Although the combined use of various Thyroid Imaging-Reporting and Data System and contrast-enhanced ultrasonography has turned out to be accurate in many studies, the ideal way to integrate contrast-enhanced ultrasonography into the Thyroid Imaging-Reporting and Data System algorithm is under-investigated. To estimate and compare the diagnostic accuracy of American College of Radiology Thyroid Imaging-Reporting and Data System and contrast-enhanced ultrasonography in differentiating benign and malignant nodules alone and in combination. To estimate the diagnostic accuracy of contrast-enhanced ultrasonography in re-categorisation of Thyroid Imaging-Reporting and Data System 3 and Thyroid Imaging-Reporting and Data System 4 thyroid nodules. This was a prospective cohort study performed in a tertiary care university-based hospital for 3 years. Adult patients with clinical or previous sonographic diagnosis of thyroid nodules were selected. Each of the nodules were assessed using ultrasonography and categorised using American College of Radiology Thyroid Imaging-Reporting and Data System criteria. The lesion was then assessed for contrast-enhanced ultrasonography features. The final diagnosis of the nodules was made using fine needle aspiration cytology. The diagnostic accuracy in diagnosis of malignant thyroid nodules for each of the American College of Radiology Thyroid Imaging-Reporting and Data System and contrast-enhanced ultrasonography alone and in combination was assessed. The diagnostic accuracy of contrast-enhanced ultrasonography in diagnosis of malignant thyroid nodules categorised as Thyroid Imaging-Reporting and Data System 3 and Thyroid Imaging-Reporting and Data System 4 was also assessed. American College of Radiology Thyroid Imaging-Reporting and Data System had a sensitivity, specificity, negative predictive value, positive predictive value and diagnostic accuracy of 86.6%, 54.5%, 17.4%, 97.3% and 57.7%, respectively, in diagnosis of malignant thyroid nodules. Contrast-enhanced ultrasonography had a sensitivity, specificity, negative predictive value, positive predictive value and diagnostic accuracy of 86.6%, 95.4%, 67.9%, 98.4% and 94.4%, respectively, in diagnosis of malignant thyroid nodules. Contrast-enhanced ultrasonography had sensitivity, specificity, negative predictive value, positive predictive value and diagnostic accuracy of 93.3%, 100.0%, 100.0%, 99.2% and 99.3%, respectively, in re-categorisation of Thyroid Imaging-Reporting and Data System 3 and Thyroid Imaging-Reporting and Data System 4 nodules. Contrast-enhanced ultrasonography can play a key role in diagnosis of malignant thyroid nodules which are categorised as indeterminate on grey-scale ultrasound.

Nonoperative, Active Surveillance of Larger Malignant and Suspicious Thyroid Nodules.

Active surveillance for papillary thyroid cancer (PTC) meeting criteria for surgical resection is uncommon. Which patients may prove reasonable candidates for this approach is not well defined. This work aimed to examine the feasibility and safety of active surveillance for patients with known or suspected intrathyroidal PTC up to 4 cm in diameter. A retrospective review was conducted of all consecutive patients who underwent nonoperative active surveillance of suspicious or malignant thyroid nodules over a 20-year period from 2001 to 2021. We included patients with an initial ultrasound-fine-needle aspiration confirming either (a) Bethesda 5 or 6 cytology or (b) a "suspicious" Afirma molecular test. The primary outcomes and measures included the rate of adverse oncologic outcomes (mortality and recurrence), as well as the cumulative incidence of size/volume growth. Sixty-nine patients were followed with active surveillance for 1 year or longer (average 55 months), with 26 patients (38%) having nodules 2 cm or larger. No patients were found to develop new-incident occurrence of lymph node or distant metastasis. One patient, however, demonstrated concern for progression to a dedifferentiated cancer on repeat core biopsy 17 years after initial start of nonoperative selection. A total of 21% of patients had an increase in maximum diameter more than 3 mm, while volume increase of 50% or greater was noted in 25% of patients. Thirteen patients ultimately underwent delayed (rescue) surgery, and no disease recurrence was noted after such treatment. Age and initial nodule size were not predictors of nodule growth. These data expand consideration of active surveillance of PTC in select patients with intrathyroidal suspected malignancy greater than 1 cm in diameter. Rescue surgery, if required at a later time point, appears effective.

Diagnostic value of colour Doppler ultrasound in differentiating malignant and benign nodules in thyroiditis background.

Differentiating malignant thyroid nodules from benign ones is challenging. Sonography is a non-invasive modality that can be helpful in this regard and is far better than invasive methods like fine needle aspiration (FNA). This study aimed to assess the diagnostic value of colour Doppler ultrasonography in distinguishing malignant and benign nodules of thyroid gland. The study involved patients with thyroiditis and thyroid nodules, who underwent sonography. Ultrasound findings were assessed. All the nodules were classified according to the FNA into malignant, follicular nodules and lymphatic. Then, sonography findings were compared between these three groups. There were 216 nodules, including 108 (50%) malignant nodules, 80 (37%) benign and 28 (13%) lymphatic follicles, were evaluated. Micro-calcification was present in 50 (46.3%) malignant cases, 11 (13.7%) benign cases and 2 (2.1%) lymphatic follicles. Decreased or mixed vascularity was reported in 43 (69%) malignant nodules, 4 (5%) benign cases and 7 (25%) lymphatic follicles. Also, 9.7% and 42% of malignant and benign nodules had peripheral circular vascularity, respectively; however, none of the lymphatic follicles had this finding. With 89% specificity, 49% sensitivity and 73.5% accuracy, calcification with or without decreased or mixed vascularity could differentiate benign and malignant nodules. Decreased or mixed vascularity with or without calcification shows high sensitivity in differentiating malignant and benign nodules.

Improved cancer risk stratification of isoechoic thyroid nodules to reduce unnecessary biopsies using quantitative ultrasound.

Gray-scale ultrasound (US) is the standard-of-care for evaluating thyroid nodules (TNs). However, the performance is better for the identification of hypoechoic malignant TNs (such as classic papillary thyroid cancer) than isoechoic malignant TNs. Quantitative ultrasound (QUS) utilizes information from raw ultrasonic radiofrequency (RF) echo signal to assess properties of tissue microarchitecture. The purpose of this study is to determine if QUS can improve the cancer risk stratification of isoechoic TNs. Patients scheduled for TN fine needle biopsy (FNB) were recruited from the Thyroid Health Clinic at Boston Medical Center. B-mode US and RF data (to generate QUS parameters) were collected in 274 TNs (163 isoechoic, 111 hypoechoic). A linear combination of QUS parameters (CQP) was trained and tested for isoechoic [CQP(i)] and hypoechoic [CQP(h)] TNs separately and compared with the performance of conventional B-mode US risk stratification systems. CQP(i) produced an ROC AUC value of 0.937+/- 0.043 compared to a value of 0.717 +/- 0.145 (p >0.05) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.589 +/- 0.173 (p >0.05) for the American Thyroid Association (ATA) risk stratification system. In this study, CQP(i) avoids unnecessary FNBs in 73% of TNs compared to 55.8% and 11.8% when using ACR TI-RADS and ATA classification system. This data supports that a unique QUS-based classifier may be superior to conventional US stratification systems to evaluate isoechoic TNs for cancer and should be explored further in larger studies.

TSE-GAN: strain elastography using generative adversarial network for thyroid disease diagnosis.

Over the past 35years, studies conducted worldwide have revealed a threefold increase in the incidence of thyroid cancer. Strain elastography is a new imaging technique to identify benign and malignant thyroid nodules due to its sensitivity to tissue stiffness. However, there are certain limitations of this technique, particularly in terms of standardization of the compression process, evaluation of results and several assumptions used in commercial strain elastography modes for the purpose of simplifying imaging analysis. In this work, we propose a novel conditional generative adversarial network (TSE-GAN) for automatically generating thyroid strain elastograms, which adopts a global-to-local architecture to improve the ability of extracting multi-scale features and develops an adaptive deformable U-net structure in the sub-generator to apply effective deformation. Furthermore, we introduce a Lab-based loss function to induce the networks to generate realistic thyroid elastograms that conform to the probability distribution of the target domain. Qualitative and quantitative assessments are conducted on a clinical dataset provided by Shanghai Sixth People's Hospital. Experimental results demonstrate that thyroid elastograms generated by the proposed TSE-GAN outperform state-of-the-art image translation methods in meeting the needs of clinical diagnostic applications and providing practical value.

Clinical value of multi-gene testing in distinguishing benign and malignant thyroid nodules.

The newly released 2022 WHO Classification of Neuroendocrine Neoplasms (version 5) and a recent update on thyroid tumor classifications have emphasized genetic testing to an unprecedented level. Fine needle aspiration (FNA) has been widely applied for the preoperative diagnosis of thyroid nodules. However, it is limited mainly to testing for a single gene-BRAFV600E, whereas multi-gene testing data are scarce, especially in the Asian population. This study aimed to explore the clinical value of multi-gene testing in the differential diagnosis of benign and malignant thyroid nodules based on the 2023 Bethesda System for Reporting Thyroid Cytopathology (BSRTC). A total of 615 thyroid nodules underwent ultrasound-guided fine-needle aspiration cytology (FNAC) were collected from Sir Run Run Shaw Hospital, Zhejiang University School of Medicine. The next-generation sequencing platform was applied for multi-gene testing. A panel of well-recognized commonly mutated genes in thyroid cancer were analyzed, including BRAFV600E, KRAS, NRAS, HRAS, TERT, TP53, PAX8/PPARG, CCDC6/ RET and NCOA4/ RET. Gene mutations were identified in 324 nodules (52.7%), with BRAFV600E being the most prevalent driver gene alteration observed in this cohort (233/324; 79.1%), followed by RAS (77/324, 23.8%). The overall malignancy rate of gene mutations was 89.7% in our cohort, of which the lymph node metastasis rate was 45.3%. The combination of multi-gene testing and cytology resulted in 89.3% sensitivity, 95.2% specificity, 98.9% positive predictive value, 64.5% negative predictive value and 90.3% accuracy, which were significantly higher than those from mere cytology (sensitivity 68.6%, specificity 87.5%, positive predictive value 95.9%, negative predictive value 39.8%, accuracy 72.2%). Multi-gene testing could substantially enhance the detection rate of malignant thyroid nodules and protect patients with benign nodules from unnecessary surgeries. Multi-gene testing provides a valuable reference for individualized preoperative decision-making, which may serve as a crucial method for postoperative treatment and prognosis assessment.

Ultrasound microflow patterns help in distinguishing malignant from benign thyroid nodules

BackgroundVascular features are not commonly used to evaluate thyroid nodules by conventional ultrasound due to the low sensitivity. Superb Microvascular Imaging (SMI) is a new ultrasonic Doppler technology that specializes in depicting microvessels and low-speed flow. The objective of this study was to explore the value of microflow features on SMI in differentiating malignant from benign thyroid nodules.MethodsOne hundred and seventy-seven adult patients with thyroid nodules in our center from October 2021 to June 2022 with available histopathological results were recruited, including 125 malignant nodules and 123 benign nodules. Preoperative ultrasound was performed using greyscale, Color Doppler Flow Imaging (CDFI), monochrome SMI (mSMI) and color SMI (cSMI). Vascular features such as flow richness, microflow distribution and microflow patterns of malignant thyroid nodules were compared with those of benign nodules.ResultsPenetrating vessel ≥ 1 (82.4% in the malignant group vs. 30.9% in the benign group, P < 0.001), the crab claw-like pattern (64.0% vs. 10.6%, P < 0.001) and the root hair-like pattern (8.0% vs. 2.4%, P = 0.049) were common in malignant thyroid nodules, among which the crab claw-like pattern was an independent risk factor for malignant thyroid nodules. The wheel-like pattern (1.6% in the malignant group vs. 33.3% in the benign group, P < 0.001) and the arborescent pattern (0 vs. 19.5%, P < 0.001) were more likely to appear in benign nodules. The diagnostic specificities of the crab claw-like pattern and the root hair-like pattern for malignant thyroid nodules were 0.894, 0.976, and the positive predictive values were 0.860, 0.769. The diagnostic specificities of the wheel-like pattern and the arborescent pattern for benign thyroid nodules were 0.984, 1.000, and the positive predictive values were 0.953, 1.000.ConclusionsThe crab claw-like pattern and the root hair-like pattern were microflow characteristics of malignant thyroid nodules. The wheel-like pattern and the arborescent pattern could help exclude the diagnosis of thyroid cancer.

Diagnostic models for predicting malignancy in thyroid nodules classified as Bethesda Category III in an endemic region.

This study aims to develop a diagnostic model to help physicians determine whether thyroid nodules categorized as atypia of undetermined significance (AUS) in category III of the Bethesda system are benign or malignant preoperatively. To create a diagnostic model for predicting thyroid nodules' benign or malignant with AUS cytology based on clinical, ultrasonographic, and cytopathological findings. This is a retrospective cohort study involving patients (>19) at risk of thyroid cancer who had thyroidectomy after an AUS cytology. The dataset consists of 53 variables 204 nodules from 183 patients. Binary logistic regression and factor analysis methods were used to identify risk factors for malignancy. Finally, four prediction models were developed using different approaches, based on clinical, pathological clinical + pathological, and the factors. A total of 88 (48.1%) of 183 patients diagnosed with AUS were benign and 95 (51.9%) the malignant. After determining risk factors, four prediction models were developed based on different approaches to assist physicians in deciding to detect AUS nodules early. It was seen that bilaterality was found to be a risk factor for malignancy in the clinical model (pbilaterality = .03) and it was also seen that the pathological variables pale chromatin and irregular contours in the oncocyte variables were risk factors for malignancy (ppalechromatin = .02, pirregularcontoursintheoncocyte = .04). The best model obtained sensitivity and specificity values are 73% and 87% based on clinical and pathological variables. This comprehensive study may provide a more in-depth understanding of AUS and make a notable contribution to healthcare professionals before surgery.