Risk of malignancy in thyroid nodules with increased 11C-Choline uptake detected incidentally on PET/CT: A diagnostic accuracy study.

PURPOSE: The purpose was to evaluate the pathological nature of focal thyroid uptake seen in 11C-Choline PET/CT performed for prostate cancer. MATERIAL AND METHODS: The study was IRB-approved. All 11C-Choline PET/CT exam reports for studies performed between January 01, 2018, and July 30, 2021, in male patients with prostate cancer in our institution were retrospectively reviewed. Exams with "focal thyroid uptake" on their final report were selected. Patients with surgery or ablation in the thyroid prior to the PET/CT, proven parathyroid adenomas or absent thyroid ultrasound were excluded. Repeated PET/CT exams of same patient were excluded. PET images were analyzed visually and semi-quantitatively by measuring the maximum standardized uptake value (SUVmax) of the focal thyroid uptake. Available thyroid ultrasound images, cytology and pathology reports were reviewed. Statistical analyses were performed. RESULTS: Out of 10,047 sequential 11C-Choline PET/CT studies, 318 reports included "focal thyroid uptake." About 128 of these studies were repeat exams and were excluded. Additional 87 patients were excluded, because the uptake was determined to be adjacent, rather than confined to the thyroid gland. Out of the remaining 103 patients, 74 patients had focal thyroid uptake and concurrent thyroid sonographic evaluation. Out of the 74 focal uptakes evaluated with ultrasound, 21 were presumed benign thyroid nodules based on the ultrasound and 53 had further evaluation with biopsy. Sixty three nodules were benign (21 presumed benign on ultrasound and 42 cytology or surgical pathology-proven), 9 nodules were malignant and 2 remained indeterminate. There was no significant difference between the SUVs of the benign and malignant groups (P > .3). CONCLUSION: In this retrospective study of patients with prostate cancer who underwent 11C-Choline PET/CT, we identified a group of patients who underwent thyroid ultrasound for incidental finding of focal 11C-Choline thyroid uptake. Incidence of malignancy in this group was 12%. Therefore, further investigation with ultrasound and possibly ultrasound-guided biopsy may be warranted when a choline avid thyroid nodule is found incidentally on choline PET.

Construction of thyroid cancer classification and iodine metabolism related diagnostic model using thyroid differentiation score and bioinformation.

To more accurately diagnose and treat patients with different subtypes of thyroid cancer, we constructed a diagnostic model related to the iodine metabolism of THCA subtypes. THCA expression profiles, corresponding clinicopathological information, and single-cell RNA-seq were downloaded from TCGA and GEO databases. Genes related to thyroid differentiation score were obtained by GSVA. Through logistic analyses, the diagnostic model was finally constructed. DCA curve, ROC curve, machine learning, and K-M analysis were used to verify the accuracy of the model. qRT-PCR was used to verify the expression of hub genes in vitro. There were 104 crossover genes between different TDS and THCA subtypes. Finally, 5 genes (ABAT, CHEK1, GPX3, NME5, and PRKCQ) that could independently predict the TDS subpopulation were obtained, and a diagnostic model was constructed. ROC, DCA, and RCS curves exhibited that the model has accurate prediction ability. K-M and subgroup analysis results showed that low model scores were strongly associated with poor PFI in THCA patients. The model score was significantly negatively correlated with T cell follicular helper. In addition, the diagnostic model was significantly negatively correlated with immune scores. Finally, the results of qRT-PCR corresponded with bioinformatics results. This diagnostic model has good diagnostic and prognostic value for THCA patients, and can be used as an independent prognostic indicator for THCA patients.

Next generation sequence-based targeted somatic mutation analysis in thyroid nodules with pathologically diagnosed as indeterminate cytology.

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.

Oncocytic cell carcinoma of the thyroid with TERT promoter mutation presenting as asphyxia in an elderly: a case report.

Introduction: The prevalence of thyroid nodules and malignancies in the elderly is a growing concern. Thyroid nodules in this population have unique characteristics, requiring careful treatment strategies that balance risks and benefits. Oncocytic carcinoma of the thyroid (OCA) is a rare, aggressive subtype with diagnostic challenges. Methods: This case features an 84-year-old patient who presented with a neck mass and symptoms of asphyxia. Clinical evaluation, imaging studies, and biopsy were conducted to assess the nature of the thyroid lesion. Molecular testing, including genetic analysis, was performed to identify specific mutations associated with OCA and guide treatment decisions. Results: The patient was diagnosed with oncocytic carcinoma of the thyroid. The molecular testing revealed specific genetic mutations indicative of OCA, confirming the diagnosis. The presence of these mutations guided the treatment plan, emphasizing the importance of molecular diagnostics in managing thyroid malignancies, especially in the elderly. Discussion: This case illustrates the complexities of diagnosing and treating thyroid malignancies in the elderly. Biopsy and molecular testing provided diagnostic accuracy and informed treatment. Individualized approaches are essential for better outcomes, especially in aggressive subtypes, balancing the risks and benefits of intervention.

Primary schwannoma of the thyroid gland: analysis of case characteristics and review of the literature.

BACKGROUND: To improve the characteristics of primary thyroid schwannomas (PTS) and to provide reference basis for clinical diagnosis and treatment. METHODS: PubMed was searched for case reports of PTS up to December 2022 using the search terms "Thyroid nerve sheath tumor" or "Thyroid schwannoma" or "Thyroid Neurilemmoma", respectively. 34 cases were screened. RESULTS: PTS can occur at any age, nodules averaged 3.9 cm. The most common symptoms were voice change and dysphagia. Fine needle aspiration cytology showing spindle-shaped cells should be considered for schwannoma. Most cases underwent thyroid lobectomy or nodule removal with a good prognosis. Tissue types with both Antoni A and Antoni B features are common. Positive immunohistochemical staining for S-100 protein, CD34 and waveform proteins helped confirm the diagnosis. CONCLUSIONS: Positive immunohistochemistry for S-100 and wave proteins helps confirm the diagnosis. Preoperative diagnosis is challenging, but pathology and immunohistochemical staining are the gold standard for diagnosis. The first choice of treatment is surgical resection of the nodules, the prognosis is good.

Solitary fibrous tumor of thyroid: Case report.

Solitary fibrous tumour is a relatively rare soft tissue fibroblastic tumour, accounting for approximately 2% of soft tissue tumours. It has been described primarily as a tumour of the pleural cavity; however, up to 70% of cases occur elsewhere, in any anatomical location, which can make diagnosis difficult. If this is the diagnosis being considered, the STAT6 antibody is currently available with high sensitivity and specificity. In this paper we describe the case of a 72-year-old female patient, followed up and treated by an outpatient endocrinologist for a multinodular euthyroid goitre for several years. Due to complete nodular remodelling of the left lobe of the thyroid gland and sonographic findings of several small nodules in the right lobe of the thyroid gland, total thyroidectomy was recommended to the patient. The operation was performed at the ENT department in Jindrichuv Hradec Hospital. Material from the operation was subsequently sent for histopathological examination. Several hyperplastic colloid nodules and a small oncocytic adenoma were detected microscopically in the right lobe of the thyroid gland. In the left lobe, an imprecisely delineated, greyish-white lesion measuring 2 x 1.8 x 1.5 cm was observed on the section. Microscopically, the tumour consisted of spindle-shaped cells in a focally hyalinised stroma. In the immunohistochemical examination, tumour cells reacted positively with the CD34 antibody, and negatively with antibodies against thyroglobulin, cytokeratins (CK AE1/AE3) and S100 protein. Further immunohistochemical examinations (Bcl2, CD99, STAT6) with positive results were supplemented upon consultation at a higher facility. Based on morphology and the results of the immunohistochemical examinations, the tumour was diagnosed as a solitary fibrous tumour of the thyroid gland. This is a relatively unusual finding in this location; according to literature, only a few dozen cases have been described.

A practical nomogram for preoperatively predicting lateral cervical lymph node metastasis in medullary thyroid carcinoma: a dual-center retrospective study.

Purpose: Lateral lymph node metastasis (LLNM) is very common in medullary thyroid carcinoma (MTC), but there is still controversy about how to manage cervical lateral lymph nodes, especially for clinically negative MTC. The aim of this study is to develop and validate a nomogram for predicting LLNM risk in MTC. Materials and methods: A total of 234 patients from two hospitals were retrospectively enrolled in this study and divided into LLNM positive group and LLNM negative group based on the pathology. The correlation between LLNM and preoperative clinical and ultrasound variables were evaluated by univariable and multivariable logistic regression analysis. A nomogram was generated to predict the risk of the LLNM of MTC patients, validated by external dataset, and evaluated in terms of discrimination, calibration, and clinical usefulness. Results: The training, internal, and external validation datasets included 152, 51, and 31 MTC patients, respectively. According to the multivariable logistic regression analysis, gender (male), relationship to thyroid capsule and serum calcitonin were independently associated with LLNM in the training dataset. The predictive nomogram model developed with the aforementioned variables showed favorable performance in estimating risk of LLNM, with the area under the ROC curve (AUC) of 0.826 in the training dataset, 0.816 in the internal validation dataset, and 0.846 in the external validation dataset. Conclusion: We developed and validated a model named MTC nomogram, utilizing available preoperative variables to predict the probability of LLNM in patients with MTC. This nomogram will be of great value for guiding the clinical diagnosis and treatment process of MTC patients.

Plasma miRNA-146b-3p, -222-3p, -221-5p, -21a-3p Expression Levels and TSHR Methylation: Diagnostic Potential and Association with Clinical and Pathological Features in Papillary Thyroid Cancer.

This study aimed to investigate the expression of microRNAs (miRNAs) -146b-3p, -221-5p, -222-3p, and -21a-3p and the methylation pattern of the thyroid-stimulating hormone receptor (TSHR) gene in blood plasma samples from papillary thyroid cancer (PTC) patients before and after thyroidectomy compared to healthy controls (HCs). This study included 103 participants, 46 PTC patients and 57 HCs, matched for gender and age. Significantly higher preoperative expression levels of miRNAs and TSHR methylation were determined in the PTC patients compared to HCs. Post-surgery, there was a notable decrease in these biomarkers. Elevated TSHR methylation was linked to larger tumor sizes and lymphovascular invasion, while increased miRNA-222-3p levels correlated with multifocality. Receiver operating characteristic (ROC) analysis showed AUCs below 0.8 for all candidate biomarkers. However, significant changes in the expression of all analyzed miRNAs and TSHR methylation levels indicate their potential to differentiate PTC patients from healthy individuals. These findings suggest that miRNAs and TSHR methylation levels may serve as candidate biomarkers for early diagnosis and monitoring of PTC, with the potential to distinguish PTC patients from healthy individuals. Further research is needed to validate these biomarkers for clinical application.

Thyroid Fine-Needle Aspiration: The Current and Future Landscape of Cytopathology.

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.

Label-Free Surface-Enhanced Raman Spectroscopy with Machine Learning for the Diagnosis of Thyroid Cancer by Using Fine-Needle Aspiration Liquid Samples.

The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk of false-negative results. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms holds promise for cancer diagnosis. In this study, we develop a label-free SERS liquid biopsy method with machine learning for the rapid and accurate diagnosis of thyroid cancer by using thyroid FNA washout fluids. These liquid supernatants are mixed with silver nanoparticle colloids, and dispersed in quartz capillary for SERS measurements to discriminate between healthy and malignant samples. We collect Raman spectra of 36 thyroid FNA samples (18 malignant and 18 benign) and compare four classification models: Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). The results show that the CNN algorithm is the most precise, with a high accuracy of 88.1%, sensitivity of 87.8%, and the area under the receiver operating characteristic curve of 0.953. Our approach is simple, convenient, and cost-effective. This study indicates that label-free SERS liquid biopsy assisted by deep learning models holds great promise for the early detection and screening of thyroid cancer.

Detection of RAS p.Q61R by Immunohistochemistry in Practice: A Clinicopathologic Study of 217 Thyroid Nodules with Molecular Correlates.

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.

Spindle epithelial tumor with thymus-like elements (SETTLE): a diagnostic challenge with distinct therapeutic implication; case report.

Spindle epithelial tumor with thymus-like elements (SETTLE) is a rare malignant neoplasm of the thyroid gland which is believed to arise from intrathyroidal thymic tissue. It predominantly affects young adults and children presenting with a thyroid mass of variable duration and rarely occurs in adults. It has a high overall survival with a tendency for delayed metastasis. SETTLE is a biphasic lobulated tumor composed of spindle shaped cells along with glandular formations seen on histopathological examination. Despite its typical morphology it is commonly misdiagnosed on histopathology due to its rarity and overlapping morphology with other close mimics such as a carcinoma, synovial sarcoma and thymoma. Herein we report such a case occurring in a middle aged female presenting with a neck mass. She had an initial diagnosis of metastatic poorly differentiated squamous cell carcinoma possibly with an orophayngeal primary in view of co expression of CK, p40 and p16 on immunohistochemistry. The patient underwent surgical resection with modified neck dissection. On review at our hospital it was diagnosed as SETTLE and she remains disease free after a follow-up period of 1 year. Diligent histopathological examination espoused with a judicious panel of IHC markers in conjunction with clinicoradiological findings forms the mainstay of diagnosis. Diffuse and strong p16 immunoexpression has not been documented or evaluated in literature so far, and needs to be explored for its diagnostic utility in this rare entity.

Schizophrenia and papillary thyroid carcinoma in an adolescent female with 22q11.2 deletion syndrome.

22q11.2 deletion syndrome is a condition with complex multisystem involvement, and many clinicians will encounter patients living with the condition. 22q11.2 deletion syndrome is known to significantly increase the risk of psychosis, and there is some emerging evidence that 22q11.2 deletion syndrome may be associated with an increased risk of malignancy. We report on a case of an adolescent female who had a delayed diagnosis of 22q11.2 deletion syndrome after she developed severe psychosis at an early age. She was subsequently diagnosed in late adolescence with papillary thyroid carcinoma. This case contributes to the limited body of evidence regarding the treatment of psychosis secondary to 22q11.2 deletion syndrome and the potential increased risk of malignancy associated with the genetic condition.

Pathology diagnosis of intraoperative frozen thyroid lesions assisted by deep learning.

BACKGROUND: Thyroid cancer is a common thyroid malignancy. The majority of thyroid lesion needs intraoperative frozen pathology diagnosis, which provides important information for precision operation. As digital whole slide images (WSIs) develop, deep learning methods for histopathological classification of the thyroid gland (paraffin sections) have achieved outstanding results. Our current study is to clarify whether deep learning assists pathology diagnosis for intraoperative frozen thyroid lesions or not. METHODS: We propose an artificial intelligence-assisted diagnostic system for frozen thyroid lesions that applies prior knowledge in tandem with a dichotomous judgment of whether the lesion is cancerous or not and a quadratic judgment of the type of cancerous lesion to categorize the frozen thyroid lesions into five categories: papillary thyroid carcinoma, medullary thyroid carcinoma, anaplastic thyroid carcinoma, follicular thyroid tumor, and non-cancerous lesion. We obtained 4409 frozen digital pathology sections (WSI) of thyroid from the First Affiliated Hospital of Sun Yat-sen University (SYSUFH) to train and test the model, and the performance was validated by a six-fold cross validation, 101 papillary microcarcinoma sections of thyroid were used to validate the system's sensitivity, and 1388 WSIs of thyroid were used for the evaluation of the external dataset. The deep learning models were compared in terms of several metrics such as accuracy, F1 score, recall, precision and AUC (Area Under Curve). RESULTS: We developed the first deep learning-based frozen thyroid diagnostic classifier for histopathological WSI classification of papillary carcinoma, medullary carcinoma, follicular tumor, anaplastic carcinoma, and non-carcinoma lesion. On test slides, the system had an accuracy of 0.9459, a precision of 0.9475, and an AUC of 0.9955. In the papillary carcinoma test slides, the system was able to accurately predict even lesions as small as 2 mm in diameter. Tested with the acceleration component, the cut processing can be performed in 346.12 s and the visual inference prediction results can be obtained in 98.61 s, thus meeting the time requirements for intraoperative diagnosis. Our study employs a deep learning approach for high-precision classification of intraoperative frozen thyroid lesion distribution in the clinical setting, which has potential clinical implications for assisting pathologists and precision surgery of thyroid lesions.

Combining radiomics and molecular biomarkers: a novel economic tool to improve diagnostic ability in papillary thyroid cancer.

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.

Epidemiologic changes in thyroid disease.

PURPOSE OF REVIEW: To analyze the evolving epidemiologic trends in thyroid disease, focusing on risk factors, underlying drivers of these changes, and their implications on clinical practice and research priorities. RECENT FINDINGS: Thyroid disease remains one of the most prevalent groups of disorders globally, and the shift in its frequency and distribution is multifactorial. The prevalence of hypothyroidism increases with age, although normal thyrotropin ranges appear to be age-dependent, raising concern for potentially inappropriate levothyroxine use. Hyperthyroidism and Graves' disease continue to be predominant in reproductive-age women but exhibit a milder phenotype at diagnosis. Thyroid nodules are increasingly found in asymptomatic patients, likely from more widespread use of neck and chest imaging. Thyroid cancer incidence has risen exponentially over the years, mostly driven by overdiagnosis of low-risk tumors; however, a small rise in incidence of higher risk tumors has been noted. Obesity appears to be a risk factor for thyroid cancer occurrence and more aggressive forms of the disease. SUMMARY: Understanding epidemiologic trends in thyroid disease is crucial for guiding clinical practice and research efforts, aiming to optimize patient outcomes while preventing unnecessary and potentially harmful interventions.

Clues for Early Diagnosis of MEN2B Syndrome Before Medullary Thyroid Carcinoma.

Early onset medullary thyroid carcinoma, later pheochromocytomas, and nonspecific extra-endocrine features (hypermobility and persistent constipation) are part of the clinical phenotype of Multiple Endocrine Neoplasia type 2B (MEN2B). A de novo pathogenic M918T variant in the rearranged during transfection proto-oncogene is usually identified. Affected children are often seen by multiple clinicians over a long period before consideration of a diagnosis of MEN2B, with metastatic medullary thyroid carcinoma often the precipitator. We describe the clinical presentation and course of 5 children ultimately diagnosed with MEN2B in New South Wales and the Australian Capital Territory, Australia between 1989 and 2021. All cases had intestinal ganglioneuromatosis that could have prompted an earlier diagnosis. Population wide newborn genomic screening for rare diseases is on the horizon. We propose that MEN2B genomic screening should be included in newborn screening programs and that careful exclusion of intestinal ganglioneuromatosis would allow earlier identification leading to improved clinical outcomes.

Development and Multicenter, Multiprotocol Validation of Neural Network for Aberrant Right Subclavian Artery Detection.

PURPOSE: This study aimed to develop and validate a convolutional neural network (CNN) that automatically detects an aberrant right subclavian artery (ARSA) on preoperative computed tomography (CT) for thyroid cancer evaluation. MATERIALS AND METHODS: A total of 556 CT with ARSA and 312 CT with normal aortic arch from one institution were used as the training set for model development. A deep learning model for the classification of patch images for ARSA was developed using two-dimension CNN from EfficientNet. The diagnostic performance of our model was evaluated using external test sets (112 and 126 CT) from two institutions. The performance of the model was compared with that of radiologists for detecting ARSA using an independent dataset of 1683 consecutive neck CT. RESULTS: The performance of the model was achieved using two external datasets with an area under the curve of 0.97 and 0.99, and accuracy of 97% and 99%, respectively. In the temporal validation set, which included a total of 20 patients with ARSA and 1663 patients without ARSA, radiologists overlooked 13 ARSA cases. In contrast, the CNN model successfully detected all the 20 patients with ARSA. CONCLUSION: We developed a CNN-based deep learning model that detects ARSA using CT. Our model showed high performance in the multicenter validation.

Multiple Endocrine Neoplasia Type 1, Type 2A, and Type 2B.

Multiple endocrine neoplasia type 1 is a rare genetic neuroendocrine syndrome caused by over 1500 different germline mutations. It can cause 20 different endocrine tumors affecting primarily the parathyroid glands, gastroenteropancreatic tract, and the anterior pituitary gland. Multiple endocrine neoplasia type 2A (MEN2A) and Multiple endocrine neoplasia type 2B (MEN2B) are autosomal dominant genetic syndromes because of a germline variant in the 'rearranged during transfection' (RET) proto-oncogene. There are common RET mutations causing receptor hyperactivation and induction of downstream signals that cause oncogenesis. Common conditions with MEN2A are medullary thyroid cancer (MTC), pheochromocytoma, and primary hyperparathyroidism. Common conditions with MEN2B include MTC, pheochromocytomas, and benign ganglioneuromas.

[Rethinking on the epidemic situation and standardized diagnosis and treatment of low risk differentiated thyroid cancer].

Thyroid cancer is a malignant tumor originating from thyroid epithelial or parafollicular epithelial cells. It is also the most common malignant tumor in the head and neck. At present, the incidence of thyroid cancer ranks ninth among all common malignant tumors, and has become one of the top ten common malignant tumors. In recent years, with the release of various guidelines, the diagnosis and treatment of thyroid cancer around the world is gradually standardized. Meanwhile, China has also begun to implement quality control of diagnosis and treatment, standardize diagnosis and treatment behavior, and promote the standardization of diagnosis and treatment of thyroid tumors nationwide, in order to ultimately improve patient's survival rate and quality of life. Based on the current changes in the diagnosis and treatment of thyroid cancer at home and abroad, the article discusses the epidemic situation, diagnosis and treatment status, new concept and progress of standardized diagnosis and treatment of thyroid cancer.