RESUMEN

PURPOSE: The management of indeterminate thyroid nodules remains a topic of ongoing debate, particularly regarding the differentiation of malignancy. Somatic mutation analysis offers crucial insights into tumor characteristics. This study aimed to assist the clinical management of indeterminate nodules with somatic mutation analysis. METHODS: Aspiration samples from 20 indeterminate thyroid nodules were included in the study. A next-generation sequencing panel containing 67 genes was used for molecular profiling. The results were compared with pathology data from surgical material, which is considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS: Variants in six genes (NRAS, BRAF, TP53, TERT, PTEN, PIK3CA) were detected in 10 out of 20 samples. We identified nine Tier 1 or 2 variants in 10 (67 %) out of 15 malignant nodules (NRAS, BRAF, TP53, TERT, PTEN, PIK3CA) and one Tier 2 (PIK3CA) variant in one out of five benign nodules. The study demonstrated an NPV of 40 %, a PPV of 90 %, a specificity of 80 %, and a sensitivity of 60 %. CONCLUSION: Based on the detected molecular markers, at least nine patients (45 %) could be managed correctly without needing a repeat FNAB attempt. This study underscores the clinical practicality of molecular tests in managing nodules with indeterminate cytology. Additionally, this study emphasizes the importance of considering the patient's age when determining the DNA- or RNA-based genetic testing method. Finally, we discussed the significance of the somatic mutation profile and its impact on the current pathological classification.

Asunto(s)

Secuenciación de Nucleótidos de Alto Rendimiento , Mutación , Nódulo Tiroideo , Humanos , Nódulo Tiroideo/genética , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico , Femenino , Persona de Mediana Edad , Masculino , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Adulto , Análisis Mutacional de ADN/métodos , Anciano , Neoplasias de la Tiroides/genética , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico , Biomarcadores de Tumor/genética , Sensibilidad y Especificidad , Biopsia con Aguja Fina , Citología

RESUMEN

Objectives: This study aimed to evaluate the effectiveness of thyroid fine needle aspiration cytology (FNAC) using a novel-cell preserving matrix called Cytomatrix in improving diagnostic accuracy for thyroid nodules. Materials and methods: Fifty patients undergoing thyroidectomy were enrolled and FNAC was performed on the excised thyroid glands, with the collected sample being placed on the Cytomatrix. The results were compared with histopathological analysis, and diagnostic performance was assessed statistically. Results: Cytomatrix demonstrated an accuracy of 96%, sensitivity of 84.61%, and specificity of 100%. Concordance between cytological and histopathological findings highlighted Cytomatrix's potential to enhance thyroid FNAC accuracy. Conclusion: FNAC using Cytomatrix shows promise in improving diagnostic accuracy for thyroid nodules. Its application, marked by faster processing and efficient resource utilization, coupled with the preservation of cellular architecture, holds considerable potential in enhancing cytological diagnosis, thus optimizing patient management strategies.

Asunto(s)

Nódulo Tiroideo , Humanos , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/cirugía , Biopsia con Aguja Fina/métodos , Femenino , Masculino , Persona de Mediana Edad , Adulto , Tiroidectomía/métodos , Citodiagnóstico/métodos , Anciano , Glándula Tiroides/patología , Glándula Tiroides/cirugía , Sensibilidad y Especificidad , Adulto Joven , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico , Neoplasias de la Tiroides/cirugía , Citología

RESUMEN

Background: A preoperative diagnosis to distinguish malignant from benign thyroid nodules accurately and sensitively is urgently important. However, existing clinical methods cannot solve this problem satisfactorily. The aim of this study is to establish a simple, economic approach for preoperative diagnosis in eastern population. Methods: Our retrospective study included 86 patients with papillary thyroid cancer and 29 benign cases. The ITK-SNAP software was used to draw the outline of the area of interest (ROI), and Ultrosomics was used to extract radiomic features. Whole-transcriptome sequencing and bioinformatic analysis were used to identify candidate genes for thyroid nodule diagnosis. RT-qPCR was used to evaluate the expression levels of candidate genes. SVM diagnostic model was established based on the METLAB 2022 platform and LibSVM 3.2 language package. Results: The radiomic model was first established. The accuracy is 73.0%, the sensitivity is 86.1%, the specificity is 17.6%, the PPV is 81.6%, and the NPV is 23.1%. Then, CLDN10, HMGA2, and LAMB3 were finally screened for model building. All three genes showed significant differential expressions between papillary thyroid cancer and normal tissue both in our cohort and TCGA cohort. The molecular model was established based on these genetic data and partial clinical information. The accuracy is 85.9%, the sensitivity is 86.1%, the specificity is 84.6%, the PPV is 96.9%, and the NPV is 52.4%. Considering that the above two models are not very effective, We integrated and optimized the two models to construct the final diagnostic model (C-thyroid model). In the training set, the accuracy is 96.7%, the sensitivity is 100%, the specificity is 93.8%, the PPV is 93.3%, and the NPV is 100%. In the validation set, the accuracy is 97.6%, the sensitivity remains 100%, the specificity is 84.6%, the PPV is 97.3%, and the NPV is 100%. Discussion: A diagnostic panel is successfully established for eastern population through a simple, economic approach using only four genes and clinical data.

Asunto(s)

Biomarcadores de Tumor , Cáncer Papilar Tiroideo , Neoplasias de la Tiroides , Humanos , Cáncer Papilar Tiroideo/genética , Cáncer Papilar Tiroideo/diagnóstico , Femenino , Estudios Retrospectivos , Masculino , Neoplasias de la Tiroides/genética , Neoplasias de la Tiroides/diagnóstico , Biomarcadores de Tumor/genética , Persona de Mediana Edad , Adulto , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/genética , Radiómica

RESUMEN

Thyroid cytology is a rapidly evolving field that has seen significant advances in recent years. Its main goal is to accurately diagnose thyroid nodules, differentiate between benign and malignant lesions, and risk stratify nodules when a definitive diagnosis is not possible. The current landscape of thyroid cytology includes the use of fine-needle aspiration for the diagnosis of thyroid nodules with the use of uniform, tiered reporting systems such as the Bethesda System for Reporting Thyroid Cytopathology. In recent years, molecular testing has emerged as a reliable preoperative diagnostic tool that stratifies patients into different risk categories (low, intermediate, or high) with varying probabilities of malignancy and helps guide patient treatment.

Asunto(s)

Glándula Tiroides , Neoplasias de la Tiroides , Nódulo Tiroideo , Humanos , Biopsia con Aguja Fina/métodos , Biopsia con Aguja Fina/tendencias , Diagnóstico Diferencial , Glándula Tiroides/patología , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico

RESUMEN

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.

Asunto(s)

Nódulo Tiroideo , Circonio , Nódulo Tiroideo/diagnóstico por imagen , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/patología , Humanos , Circonio/química , Oro/química , Metabolómica , Femenino

RESUMEN

CONTEXT: Fine-needle aspiration cytology (FNAC) is widely utilized for thyroid lesion diagnosis but faces challenges such as sample inadequacy and overlapping cytological features. This study examines how accurately these patterns correlate with histopathological diagnoses, shedding light on FNAC's limitations and diagnostic potential. AIMS: To study the application of the architectural pattern of follicular cells in the interpretation of thyroid lesions and to demonstrate the diagnostic accuracy (DA) of FNAC. SETTINGS AND DESIGN: Cross-sectional study carried over 1 year. SUBJECTS AND METHODS: A total of 110 cases were reviewed by the cytopathologists. The prominent follicular cell architecture, namely macrofollicular, microfollicular, papillary, trabecular, three-dimensional clusters, and dispersed cells, was described in each case. In addition to these patterns, cellular morphology and background features were also noted, and a final cytological diagnosis was established. The cytology diagnosis was correlated with the histopathological diagnosis. STATISTICAL ANALYSIS USED: Sensitivity, specificity, positive predictive value, negative predictive value, DA of FNAC in diagnosing nonneoplastic and neoplastic lesions. RESULTS: Macrofollicular pattern was seen in 80.26% of colloid goiter cases. Microfollicular pattern was observed in 72.2% of follicular neoplasm. About 62.5% of papillary thyroid carcinomas showed a papillary pattern. The trabecular pattern was seen in 42.86% of chronic lymphocytic thyroiditis and 16.67% of follicular neoplasms. The sensitivity and specificity of FNAC in diagnosing neoplastic lesions was 92.59% and 97.59%, respectively. CONCLUSIONS: FNAC is a simple, rapid, definite, and cost-effective primary diagnostic tool for thyroid evaluation. Cell architecture pattern is a simple and appropriate approach that complements cell morphology and background details in arriving at the final cytological diagnosis of thyroid lesions.

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Résumé Contexte:La cytologie par aspiration à l'aiguille fine (FNAC) est largement utilisée pour le diagnostic des lésions thyroïdiennes, mais elle est confrontée à des défis tels que l'insuffisance des échantillons et des caractéristiques cytologiques qui se chevauchent. Cette étude examine avec quelle précision ces modèles sont en corrélation avec les diagnostics histopathologiques, l'excrétion lumière sur les limites et le potentiel diagnostique de la FNAC.Objectifs:Étudier l'application du modèle architectural des cellules folliculaires dans le interprétation des lésions thyroïdiennes et démontrer la précision diagnostique (DA) de la FNAC.Paramètres et conception:étude transversale réalisée sur 1 an.Sujets et méthodes:Au total, 110 cas ont été examinés par les cytopathologistes. L'architecture cellulaire folliculaire proéminente, à savoir des amas macrofolliculaires, microfolliculaires, papillaires, trabéculaires, tridimensionnels et des cellules dispersées, ont été décrits dans chaque cas. Dans En plus de ces modèles, la morphologie cellulaire et les caractéristiques de fond ont également été notées, et un diagnostic cytologique final a été établi. Le Le diagnostic cytologique était corrélé au diagnostic histopathologique.Analyse statistique utilisée:sensibilité, spécificité, prédictif positif valeur, valeur prédictive négative, DA de la FNAC dans le diagnostic des lésions non néoplasiques et néoplasiques.Résultats:un schéma macrofolliculaire a été observé dans 80,26 % des cas de goitre colloïde. Un profil microfolliculaire a été observé dans 72,2 % des néoplasmes folliculaires. Environ 62,5 % de la thyroïde papillaire les carcinomes présentaient un aspect papillaire. L'aspect trabéculaire a été observé dans 42,86 % des thyroïdites lymphoïdes chroniques et 16,67 % des cas folliculaires néoplasmes. La sensibilité et la spécificité du FNAC dans le diagnostic des lésions néoplasiques étaient respectivement de 92,59 % et 97,59 %.Conclusions:FNAC est un outil de diagnostic primaire simple, rapide, précis et rentable pour l'évaluation de la thyroïde. Le modèle d'architecture cellulaire est simple et approprié approche qui complète la morphologie cellulaire et les détails de base pour parvenir au diagnostic cytologique final des lésions thyroïdiennes.

Asunto(s)

Sensibilidad y Especificidad , Glándula Tiroides , Neoplasias de la Tiroides , Humanos , Biopsia con Aguja Fina/métodos , Estudios Transversales , Femenino , Masculino , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico , Persona de Mediana Edad , Adulto , Glándula Tiroides/patología , Adenocarcinoma Folicular/patología , Adenocarcinoma Folicular/diagnóstico , Anciano , Valor Predictivo de las Pruebas , Citodiagnóstico/métodos , Adolescente , Carcinoma Papilar/patología , Carcinoma Papilar/diagnóstico , Adulto Joven , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico , Citología

RESUMEN

RAS p.Q61R is the most prevalent hot-spot mutation in RAS and RAS-like mutated thyroid nodules. A few studies evaluated RAS p.Q61R by immunohistochemistry (RASQ61R-IHC). We performed a retrospective study of an institutional cohort of 150 patients with 217 thyroid lesions tested for RASQ61R-IHC, including clinical, cytologic and molecular data. RASQ61R-IHC was performed on 217 nodules (18% positive, 80% negative, and 2% equivocal). RAS p.Q61R was identified in 76% (n = 42), followed by RAS p.Q61K (15%; n = 8), and RAS p.G13R (5%; n = 3). NRAS p.Q61R isoform was the most common (44%; n = 15), followed by NRAS p.Q61K (17%; n = 6), KRAS p.Q61R (12%; n = 4), HRAS p.Q61R (12%; n = 4), HRAS p.Q61K (6%; n = 2), HRAS p.G13R (6%; n = 2), and NRAS p.G13R (3%; n = 1). RASQ61R-IHC was positive in 47% of noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP; 17/36), 22% of follicular thyroid carcinomas (FTC; 5/23), 10% of follicular thyroid adenomas (FTA; 4/40), and 8% of papillary thyroid carcinomas (PTC; 9/112). Of PTC studied (n = 112), invasive encapsulated follicular variant (IEFVPTC; n = 16) was the only subtype with positive RASQ61R-IHC (56%; 9/16). Overall, 31% of RAS-mutated nodules were carcinomas (17/54); and of the carcinomas, 94% (16/17) were low-risk per American Thyroid Associated (ATA) criteria, with only a single case (6%; 1/17) considered ATA high-risk. No RAS-mutated tumors recurred, and none showed local or distant metastasis (with a follow-up of 0-10 months). We found that most RAS-mutated tumors are low-grade neoplasms. RASQ61R-IHC is a quick, cost-effective, and reliable way to detect RAS p.Q61R in follicular-patterned thyroid neoplasia and, when malignant, guide surveillance.

Asunto(s)

Inmunohistoquímica , Nódulo Tiroideo , Humanos , Femenino , Masculino , Nódulo Tiroideo/patología , Nódulo Tiroideo/genética , Nódulo Tiroideo/metabolismo , Nódulo Tiroideo/diagnóstico , Persona de Mediana Edad , Adulto , Estudios Retrospectivos , Anciano , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/metabolismo , Neoplasias de la Tiroides/genética , Neoplasias de la Tiroides/diagnóstico , Adulto Joven , Mutación , Anciano de 80 o más Años , Adolescente , Proteínas de la Membrana/genética , GTP Fosfohidrolasas/genética , Proteínas Proto-Oncogénicas p21(ras)

RESUMEN

Introduction: Samples classified as indeterminate correspond to 10-20% of cytologies obtained by fine needle biopsy of thyroid nodules, preventing an adequate distinction between benign and malignant lesions and leading to diagnostic thyroidectomies that often prove unnecessary, as most cases are benign. Furthermore, although the vast majority of patients with differentiated thyroid cancer (DTC) have such a good prognosis that active surveillance is permitted as an initial therapeutic option, relapses are not rare, and a non-negligible number of patients experience poor outcomes. MicroRNAs (miR) emerge as potential biomarkers capable of helping to define more precise management of patients in all these situations. Methods: Aiming to investigate the clinical utility of miR-146b-5p in the diagnostic of thyroid nodules and evaluating its prognostic potential in a realworld setting, we studied 89 thyroid nodule samples, correlating miR-146b-5p expression with clinical tools such as the 8th edition from the American Joint Committee on Cancer (AJCC/UICC) and the American Thyroid Association Guideline Stratification Systems for the rate of recurrence (RR). Results: miR-146b-5p expression levels distinguished benign from malignant thyroid FNA samples (p< 0.0001). For indeterminate nodules, overexpression of miR-146b-5p with a cut-off of 0.497 was able to diagnose malignancy with a 90% accuracy; specificity=87.5%; sensitivity=100%. An increased expression of miR-146b-5p was associated with greater RR (p=0.015). A cut-off of 2.21 identified cases with more vascular involvement (p=0.013) and a cut-off of 2.420 was associated with a more advanced TNM stage (p-value=0.047). Discussion: We demonstrated that miR-146b5p expression in FNA samples is able to differentiate benign from malignant indeterminate nodules and is associated with an increased risk of recurrence and mortality, suggesting that this single miRNA may be a useful diagnostic and prognostic marker in the personalized management of DTC patients.

Asunto(s)

Biomarcadores de Tumor , MicroARNs , Neoplasias de la Tiroides , Humanos , MicroARNs/genética , MicroARNs/metabolismo , Neoplasias de la Tiroides/genética , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico , Neoplasias de la Tiroides/metabolismo , Femenino , Pronóstico , Masculino , Persona de Mediana Edad , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Adulto , Anciano , Biopsia con Aguja Fina , Nódulo Tiroideo/genética , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/metabolismo , Recurrencia Local de Neoplasia/genética , Recurrencia Local de Neoplasia/patología , Recurrencia Local de Neoplasia/diagnóstico

RESUMEN

Background: Data-driven digital learning could improve the diagnostic performance of novice students for thyroid nodules. Objective: To evaluate the efficacy of digital self-learning and artificial intelligence-based computer-assisted diagnosis (AI-CAD) for inexperienced readers to diagnose thyroid nodules. Methods: Between February and August 2023, a total of 26 readers (less than 1 year of experience in thyroid US from various departments) from 6 hospitals participated in this study. Readers completed an online learning session comprising 3,000 thyroid nodules annotated as benign or malignant independently. They were asked to assess a test set consisting of 120 thyroid nodules with known surgical pathology before and after a learning session. Then, they referred to AI-CAD and made their final decisions on the thyroid nodules. Diagnostic performances before and after self-training and with AI-CAD assistance were evaluated and compared between radiology residents and readers from different specialties. Results: AUC (area under the receiver operating characteristic curve) improved after the self-learning session, and it improved further after radiologists referred to AI-CAD (0.679 vs 0.713 vs 0.758, p<0.05). Although the 18 radiology residents showed improved AUC (0.7 to 0.743, p=0.016) and accuracy (69.9% to 74.2%, p=0.013) after self-learning, the readers from other departments did not. With AI-CAD assistance, sensitivity (radiology 70.3% to 74.9%, others 67.9% to 82.3%, all p<0.05) and accuracy (radiology 74.2% to 77.1%, others 64.4% to 72.8%, all p <0.05) improved in all readers. Conclusion: While AI-CAD assistance helps improve the diagnostic performance of all inexperienced readers for thyroid nodules, self-learning was only effective for radiology residents with more background knowledge of ultrasonography. Clinical Impact: Online self-learning, along with AI-CAD assistance, can effectively enhance the diagnostic performance of radiology residents in thyroid cancer.

Asunto(s)

Inteligencia Artificial , Diagnóstico por Computador , Nódulo Tiroideo , Humanos , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/diagnóstico por imagen , Femenino , Masculino , Diagnóstico por Computador/métodos , Competencia Clínica , Adulto , Ultrasonografía/métodos , Radiología/educación , Curva ROC , Internado y Residencia/métodos , Persona de Mediana Edad

RESUMEN

Background: Thyroid nodules, increasingly prevalent globally, pose a risk of malignant transformation. Early screening is crucial for management, yet current models focus mainly on ultrasound features. This study explores machine learning for screening using demographic and biochemical indicators. Methods: Analyzing data from 6,102 individuals and 61 variables, we identified 17 key variables to construct models using six machine learning classifiers: Logistic Regression, SVM, Multilayer Perceptron, Random Forest, XGBoost, and LightGBM. Performance was evaluated by accuracy, precision, recall, F1 score, specificity, kappa statistic, and AUC, with internal and external validations assessing generalizability. Shapley values determined feature importance, and Decision Curve Analysis evaluated clinical benefits. Results: Random Forest showed the highest internal validation accuracy (78.3%) and AUC (89.1%). LightGBM demonstrated robust external validation performance. Key factors included age, gender, and urinary iodine levels, with significant clinical benefits at various thresholds. Clinical benefits were observed across various risk thresholds, particularly in ensemble models. Conclusion: Machine learning, particularly ensemble methods, accurately predicts thyroid nodule presence using demographic and biochemical data. This cost-effective strategy offers valuable insights for thyroid health management, aiding in early detection and potentially improving clinical outcomes. These findings enhance our understanding of the key predictors of thyroid nodules and underscore the potential of machine learning in public health applications for early disease screening and prevention.

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Aprendizaje Automático , Nódulo Tiroideo , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/epidemiología , Nódulo Tiroideo/diagnóstico por imagen , Humanos , Femenino , Masculino , China/epidemiología , Estudios Transversales , Persona de Mediana Edad , Adulto , Detección Precoz del Cáncer/métodos , Anciano , Tamizaje Masivo/métodos , Ultrasonografía/métodos

RESUMEN

BACKGROUND: Thyroid Imaging Reporting and Data Systems (TIRADSs) have demonstrated high performance in risk stratification of thyroid nodules (TNs). However, further improvements are needed in view of the ongoing project of an international TIRADS. Even if thyroid-stimulating hormone (TSH) measurement is traditionally used to assess the thyroid function, several papers have reported that higher TSH levels are associated with the presence of differentiated thyroid carcinoma (DTC). The present study aimed to investigate the role of TSH levels as improvement factor of American College of Radiology (ACR-), European Thyroid Association (EU-), and Korean Society (K-)TIRADS. METHODS: Patients undergoing thyroidectomy were reviewed and TNs were re-assessed according to TIRADSs. Different TSH subgroups were attained. Histology was the reference standard. DTC risk of relapse was assessed according to American Thyroid Association guidelines. RESULTS: The study series included 97 patients with 39.2% cancer prevalence. ACR-, EU-, and K-TIRADS indicated fine-needle aspiration cytology (FNAC) in 78.9%, 81.6%, and 92.1% of cases, respectively. All high-risk DTC had FNAC indication according to the three TIRADSs. The cancer rate was significantly lower in patients with TSH<0.4 mIU/L (P=0.04). The receiver operating characteristic (ROC) curve analysis showed that the best TSH cut-off to detect DTC patient was >1.3 mIU/L with Area Under the Curve (AUC)=0.70. Combining TSH data with TIRADS, the sensitivity of ACR-, EU-, and K-TIRADS increased to 92.1% 89.5%, and 94.7%, respectively. Conversely, the rate of unnecessary FNAC raised. At multivariate analysis, gender, TSH, and TIRADS were independent predictors of cancer. CONCLUSIONS: Even if TIRADSs are strongly reliable to stratify the risk of malignancy of TNs, measuring TSH can further improve our sensitivity in detecting DTC.

Asunto(s)

Neoplasias de la Tiroides , Nódulo Tiroideo , Tiroidectomía , Tirotropina , Humanos , Neoplasias de la Tiroides/sangre , Neoplasias de la Tiroides/diagnóstico , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/cirugía , Tirotropina/sangre , Masculino , Femenino , Persona de Mediana Edad , Adulto , Nódulo Tiroideo/sangre , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/cirugía , Nódulo Tiroideo/diagnóstico por imagen , Biopsia con Aguja Fina , Anciano , Estudios Retrospectivos , Medición de Riesgo/métodos , Sensibilidad y Especificidad

Asunto(s)

Nódulo Tiroideo , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/patología , Humanos

Asunto(s)

Biomarcadores , ADN Circular , Humanos , Biomarcadores/sangre , ADN Circular/sangre , ADN Circular/análisis , ADN Circular/genética , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/sangre , Nódulo Tiroideo/genética , Femenino , Masculino , Persona de Mediana Edad , Adulto

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BACKGROUND: Renal cell carcinoma (RCC) is one of the most common and prevalent cancers all around the world with a prevalence of 3%. Approximately twenty percent of patients present with metastasis at the time of diagnosis, while late metastasis in renal cell carcinoma is a quite familiar phenomenon. Head and neck and particularly thyroid metastasis from RCC are rare events. CASE: We present a case of a 75-year-old woman who developed thyroid nodules 13 years after nephrectomy for RCC. Diagnosis confirmed metastatic RCC through clinical history, histomorphology, and immunohistochemistry. Imaging studies revealed thyroid lesions without metastasis in other organs. The patient underwent total thyroidectomy and remains symptom-free after 2 years of follow-up. CONCLUSION: This case highlights the importance of considering metastatic lesions is crucial in managing thyroid nodules in patients with a history of cancer, particularly RCC.

Asunto(s)

Carcinoma de Células Renales , Neoplasias Renales , Nódulo Tiroideo , Tiroidectomía , Humanos , Carcinoma de Células Renales/secundario , Carcinoma de Células Renales/patología , Carcinoma de Células Renales/diagnóstico , Carcinoma de Células Renales/cirugía , Femenino , Anciano , Neoplasias Renales/patología , Neoplasias Renales/cirugía , Neoplasias Renales/diagnóstico , Nódulo Tiroideo/patología , Nódulo Tiroideo/cirugía , Nódulo Tiroideo/diagnóstico , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/secundario , Neoplasias de la Tiroides/cirugía , Neoplasias de la Tiroides/diagnóstico , Nefrectomía

RESUMEN

Elevated immunoglobulin G4 (IgG4) serum antibodies are an important feature of IgG4-related disease. However, IgG4 antibodies can play a role in autoimmune thyroid disorders. In this study, we aimed to evaluate the impact of serum IgG4 levels on clinical features of Graves' disease (GD). We recruited 60 patients with GD (48 patients without thyroid eye disease, 12 patients with moderate-to-severe Graves' orbitopathy [GO], and 25 healthy control subjects). The prevalence of high IgG4 serum concentration was 4.2% among GD patients without GO and 33.33% in patients with moderate-to-severe GO. The group with GO had significantly higher median IgG4 levels (87.9 mg/dL) than the control group (41.2 mg/dL, P = 0.034) and the GD without GO group (30.75 mg/dL, P < 0.001). Patients with thyroid nodules had lower IgG4 levels than patients without thyroid nodules, but the difference was not statistically significant (35.7 [24.8; 41.53] mg/dL vs. 43 [30.1; 92.7] mg/dL, P = 0.064). IgG4 as a diagnostic tool for moderate-to-severe GO had the following parameters: area under the curve (AUC): 0.851 (P < 0.001), at the cut-off value of 49 mg/dL, negative predictive value: 100%, positive predictive value: 48%, sensitivity: 100%, specificity: 73%. There were no significant differences between the high and normal IgG4 groups in thyroid hormones, antithyroid antibodies, and ultrasound features. Serum IgG4 levels are associated with some of the clinical features of GD and can help in the diagnostic process of the disease. More research is needed to better understand the pathophysiology of IgG4 involvement in GD.

Asunto(s)

Enfermedad de Graves , Oftalmopatía de Graves , Inmunoglobulina G , Humanos , Inmunoglobulina G/sangre , Inmunoglobulina G/inmunología , Masculino , Femenino , Enfermedad de Graves/sangre , Enfermedad de Graves/diagnóstico , Enfermedad de Graves/inmunología , Persona de Mediana Edad , Adulto , Oftalmopatía de Graves/sangre , Oftalmopatía de Graves/diagnóstico , Oftalmopatía de Graves/inmunología , Biomarcadores/sangre , Índice de Severidad de la Enfermedad , Anciano , Sensibilidad y Especificidad , Estudios de Casos y Controles , Nódulo Tiroideo/sangre , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/inmunología , Relevancia Clínica

RESUMEN

Objective. The intend of the present study was to assess the diagnostic performance of strain elastography in investigating the thyroid nodule malignancy taking the surgical biopsy as a gold standard reference test. Methods. The study included 120 patients with 123 thyroid nodules, of which 67 had total thyroidectomy. The American College of Radiology Thyroid Imaging Reporting and Data Systems (ACR-TIRADS) were evaluated for all nodules. All suspicious nodules were referred for a fine needle aspiration cytology (FNAC) if they fulfilled the required size. Strain elastography was performed for each suspicious nodule. Ultrasound-guided FNAC was performed for all suspicious nodules. Total thyroidectomy was performed in those whom the suspicious nodules were proven by FNAC. Results. Strain ratio had a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of 84%, 81%, 95%, 85%, and 84%, respectively, with a cut point 1.96. Elasticity score had a sensitivity, specificity, PPV, NPV, and diagnostic accuracy of 100%, 80%, 95%, 85% and 87%, respectively, with a cut point 0.96. The elasticity score had a statistically significantly odds ratio for detecting the benignity 3.9 C. I (1.6-9.3). Conclusion. Strain elastography has a high diagnostic performance in detecting the malignant as well as benign nodules, thus it can limit the rate of unneeded FNAC or surgery especially among B3 and B4 groups with indeterminate cytology.

Asunto(s)

Diagnóstico por Imagen de Elasticidad , Sensibilidad y Especificidad , Neoplasias de la Tiroides , Nódulo Tiroideo , Humanos , Diagnóstico por Imagen de Elasticidad/métodos , Masculino , Femenino , Persona de Mediana Edad , Adulto , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico por imagen , Neoplasias de la Tiroides/cirugía , Neoplasias de la Tiroides/diagnóstico , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico por imagen , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/cirugía , Biopsia con Aguja Fina , Anciano , Glándula Tiroides/patología , Glándula Tiroides/diagnóstico por imagen , Tiroidectomía , Biopsia Guiada por Imagen/métodos , Adulto Joven , Valor Predictivo de las Pruebas , Citología

RESUMEN

Background: Droplet digital (dd)PCR is a new-generation PCR technique with high precision and sensitivity; however, the positive and negative droplets are not always effectively separated because of the "rain" phenomenon. We aimed to develop a practical optimization and evaluation process for the ddPCR assay and to apply it to the detection of BRAF V600E in fine-needle aspiration (FNA) specimens of thyroid nodules, as an example. Methods: We optimized seven ddPCR parameters that can affect "rain." Analytical and clinical performance were analyzed based on histological diagnosis after thyroidectomy using a consecutive prospective series of 242 FNA specimens. Results: The annealing time and temperature, number of PCR cycles, and primer and probe concentrations were found to be more important considerations for assay optimization than the denaturation time and ramp rate. The limit of blank and 95% limit of detection were 0% and 0.027%, respectively. The sensitivity of ddPCR for histological papillary thyroid carcinoma (PTC) was 82.4% (95% confidence interval [CI], 73.6%-89.2%). The pooled sensitivity of BRAF V600E in FNA specimens for histological PTC was 78.6% (95% CI, 75.9%-81.2%, I2=60.6%). Conclusions: We present a practical approach for optimizing ddPCR parameters that affect the separation of positive and negative droplets to reduce rain. Our approach to optimizing ddPCR parameters can be expanded to general ddPCR assays for specific mutations in clinical laboratories. The highly sensitive ddPCR can compensate for uncertainty in cytological diagnosis by detecting low levels of BRAF V600E.

Asunto(s)

Reacción en Cadena de la Polimerasa , Proteínas Proto-Oncogénicas B-raf , Nódulo Tiroideo , Proteínas Proto-Oncogénicas B-raf/genética , Humanos , Biopsia con Aguja Fina , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/patología , Nódulo Tiroideo/genética , Neoplasias de la Tiroides/diagnóstico , Neoplasias de la Tiroides/genética , Neoplasias de la Tiroides/patología , Sensibilidad y Especificidad , Cáncer Papilar Tiroideo/genética , Cáncer Papilar Tiroideo/diagnóstico , Cáncer Papilar Tiroideo/patología , Mutación , Límite de Detección , Persona de Mediana Edad , Femenino , Adulto , Masculino , Carcinoma Papilar/patología , Carcinoma Papilar/diagnóstico , Carcinoma Papilar/genética , Estudios Prospectivos , Anciano , Cartilla de ADN/metabolismo , Cartilla de ADN/química

RESUMEN

BACKGROUND: Accurately distinguishing between malignant and benign thyroid nodules through fine-needle aspiration cytopathology is crucial for appropriate therapeutic intervention. However, cytopathologic diagnosis is time consuming and hindered by the shortage of experienced cytopathologists. Reliable assistive tools could improve cytopathologic diagnosis efficiency and accuracy. We aimed to develop and test an artificial intelligence (AI)-assistive system for thyroid cytopathologic diagnosis according to the Thyroid Bethesda Reporting System. METHODS: 11 254 whole-slide images (WSIs) from 4037 patients were used to train deep learning models. Among the selected WSIs, cell level was manually annotated by cytopathologists according to The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) guidelines of the second edition (2017 version). A retrospective dataset of 5638 WSIs of 2914 patients from four medical centres was used for validation. 469 patients were recruited for the prospective study of the performance of AI models and their 537 thyroid nodule samples were used. Cohorts for training and validation were enrolled between Jan 1, 2016, and Aug 1, 2022, and the prospective dataset was recruited between Aug 1, 2022, and Jan 1, 2023. The performance of our AI models was estimated as the area under the receiver operating characteristic (AUROC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. The primary outcomes were the prediction sensitivity and specificity of the model to assist cyto-diagnosis of thyroid nodules. FINDINGS: The AUROC of TBSRTC III+ (which distinguishes benign from TBSRTC classes III, IV, V, and VI) was 0·930 (95% CI 0·921-0·939) for Sun Yat-sen Memorial Hospital of Sun Yat-sen University (SYSMH) internal validation and 0·944 (0·929 - 0·959), 0·939 (0·924-0·955), 0·971 (0·938-1·000) for The First People's Hospital of Foshan (FPHF), Sichuan Cancer Hospital & Institute (SCHI), and The Third Affiliated Hospital of Guangzhou Medical University (TAHGMU) medical centres, respectively. The AUROC of TBSRTC V+ (which distinguishes benign from TBSRTC classes V and VI) was 0·990 (95% CI 0·986-0·995) for SYSMH internal validation and 0·988 (0·980-0·995), 0·965 (0·953-0·977), and 0·991 (0·972-1·000) for FPHF, SCHI, and TAHGMU medical centres, respectively. For the prospective study at SYSMH, the AUROC of TBSRTC III+ and TBSRTC V+ was 0·977 and 0·981, respectively. With the assistance of AI, the specificity of junior cytopathologists was boosted from 0·887 (95% CI 0·8440-0·922) to 0·993 (0·974-0·999) and the accuracy was improved from 0·877 (0·846-0·904) to 0·948 (0·926-0·965). 186 atypia of undetermined significance samples from 186 patients with BRAF mutation information were collected; 43 of them harbour the BRAFV600E mutation. 91% (39/43) of BRAFV600E-positive atypia of undetermined significance samples were identified as malignant by the AI models. INTERPRETATION: In this study, we developed an AI-assisted model named the Thyroid Patch-Oriented WSI Ensemble Recognition (ThyroPower) system, which facilitates rapid and robust cyto-diagnosis of thyroid nodules, potentially enhancing the diagnostic capabilities of cytopathologists. Moreover, it serves as a potential solution to mitigate the scarcity of cytopathologists. FUNDING: Guangdong Science and Technology Department. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Asunto(s)

Aprendizaje Profundo , Nódulo Tiroideo , Humanos , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/patología , China , Estudios Retrospectivos , Biopsia con Aguja Fina , Estudios Prospectivos , Femenino , Masculino , Persona de Mediana Edad , Adulto , Sensibilidad y Especificidad , Glándula Tiroides/patología , Anciano , Neoplasias de la Tiroides/diagnóstico , Neoplasias de la Tiroides/patología

RESUMEN

Thyroid nodules are widely prevalent, and often discovered incidentally. Malignancy rates are low for incidental thyroid nodules, and overall outcomes are favorable regardless of diagnosis. Patients with thyroid nodules should be evaluated with TSH levels followed by ultrasound of the thyroid and cervical lymph nodes. It is important to recognize sonographic features suspicious for thyroid malignancy and obtain biopsies when indicated according to major society guidelines. The Bethesda System for Reporting Thyroid Cytopathology along with molecular testing can help guide management decisions regarding thyroid nodules. Surgical resection and other emerging technologies are safe and effective for the treatment of thyroid nodules needing intervention.

Asunto(s)

Hallazgos Incidentales , Nódulo Tiroideo , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/terapia , Nódulo Tiroideo/patología , Humanos , Tiroidectomía/métodos , Neoplasias de la Tiroides/diagnóstico , Neoplasias de la Tiroides/terapia , Ultrasonografía , Biopsia con Aguja Fina , Glándula Tiroides/patología , Glándula Tiroides/diagnóstico por imagen

RESUMEN

Background: Artificial intelligence (AI) is increasingly being applied in pathology and cytology, showing promising results. We collected a large dataset of whole slide images (WSIs) of thyroid fine-needle aspiration cytology (FNA), incorporating z-stacking, from institutions across the nation to develop an AI model. Methods: We conducted a multicenter retrospective diagnostic accuracy study using thyroid FNA dataset from the Open AI Dataset Project that consists of digitalized images samples collected from 3 university hospitals and 215 Korean institutions through extensive quality check during the case selection, scanning, labeling, and reviewing process. Multiple z-layer images were captured using three different scanners and image patches were extracted from WSIs and resized after focus fusion and color normalization. We pretested six AI models, determining Inception ResNet v2 as the best model using a subset of dataset, and subsequently tested the final model with total datasets. Additionally, we compared the performance of AI and cytopathologists using randomly selected 1031 image patches and reevaluated the cytopathologists' performance after reference to AI results. Results: A total of 10,332 image patches from 306 thyroid FNAs, comprising 78 malignant (papillary thyroid carcinoma) and 228 benign from 86 institutions were used for the AI training. Inception ResNet v2 achieved highest accuracy of 99.7%, 97.7%, and 94.9% for training, validation, and test dataset, respectively (sensitivity 99.9%, 99.6%, and 100% and specificity 99.6%, 96.4%, and 90.4% for training, validation, and test dataset, respectively). In the comparison between AI and human, AI model showed higher accuracy and specificity than the average expert cytopathologists beyond the two-standard deviation (accuracy 99.71% [95% confidence interval (CI), 99.38-100.00%] vs. 88.91% [95% CI, 86.99-90.83%], sensitivity 99.81% [95% CI, 99.54-100.00%] vs. 87.26% [95% CI, 85.22-89.30%], and specificity 99.61% [95% CI, 99.23-99.99%] vs. 90.58% [95% CI, 88.80-92.36%]). Moreover, after referring to the AI results, the performance of all the experts (accuracy 96%, 95%, and 96%, respectively) and the diagnostic agreement (from 0.64 to 0.84) increased. Conclusions: These results suggest that the application of AI technology to thyroid FNA cytology may improve the diagnostic accuracy as well as intra- and inter-observer variability among pathologists. Further confirmatory research is needed.

Asunto(s)

Inteligencia Artificial , Neoplasias de la Tiroides , Humanos , Biopsia con Aguja Fina/métodos , Neoplasias de la Tiroides/patología , Neoplasias de la Tiroides/diagnóstico , Estudios Retrospectivos , Glándula Tiroides/patología , Cáncer Papilar Tiroideo/patología , Cáncer Papilar Tiroideo/diagnóstico , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Nódulo Tiroideo/patología , Nódulo Tiroideo/diagnóstico , Citología