Discriminating Interpatient Variabilities of RAS Gene Variants for Precision Detection of Thyroid Cancer.

Importance: Interpatient variabilities in genomic variants may reflect differences in tumor statuses among individuals. Objectives: To delineate interpatient variabilities in RAS variants in thyroid tumors based on the fifth World Health Organization classification of thyroid neoplasms and assess their diagnostic significance in cancer detection among patients with thyroid nodules. Design, Setting, and Participants: This prospective diagnostic study analyzed surgically resected thyroid tumors obtained from February 2016 to April 2022 and residual thyroid fine-needle aspiration (FNA) biopsies obtained from January 2020 to March 2021, at Mount Sinai Hospital, Toronto, Ontario, Canada. Data were analyzed from June 20, 2022, to October 15, 2023. Exposures: Quantitative detection of interpatient disparities of RAS variants (ie, NRAS, HRAS, and KRAS) was performed along with assessment of BRAF V600E and TERT promoter variants (C228T and C250T) by detecting their variant allele fractions (VAFs) using digital polymerase chain reaction assays. Main Outcomes and Measures: Interpatient differences in RAS, BRAF V600E, and TERT promoter variants were analyzed and compared with surgical histopathologic diagnoses. Malignancy rates, sensitivity, specificity, positive predictive values, and negative predictive values were calculated. Results: A total of 438 surgically resected thyroid tumor tissues and 249 thyroid nodule FNA biopsies were obtained from 620 patients (470 [75.8%] female; mean [SD] age, 50.7 [15.9] years). Median (IQR) follow-up for patients who underwent FNA biopsy analysis and subsequent resection was 88 (50-156) days. Of 438 tumors, 89 (20.3%) were identified with the presence of RAS variants, including 51 (11.6%) with NRAS, 29 (6.6%) with HRAS, and 9 (2.1%) with KRAS. The interpatient differences in these variants were discriminated at VAF levels ranging from 0.15% to 51.53%. The mean (SD) VAF of RAS variants exhibited no significant differences among benign nodules (39.2% [11.2%]), noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs) (25.4% [14.3%]), and malignant neoplasms (33.4% [13.8%]) (P = .28), although their distribution was found in 41.7% of NIFTPs and 50.7% of invasive encapsulated follicular variant papillary thyroid carcinomas (P < .001). RAS variants alone, regardless of a low or high VAF, were significantly associated with neoplasms at low risk of tumor recurrence (60.7% of RAS variants vs 26.9% of samples negative for RAS variants; P < .001). Compared with the sensitivity of 54.2% (95% CI, 48.8%-59.4%) and specificity of 100% (95% CI, 94.8%-100%) for BRAF V600E and TERT promoter variant assays, the inclusion of RAS variants into BRAF and TERT promoter variant assays improved sensitivity to 70.5% (95% CI, 65.4%-75.2%), albeit with a reduction in specificity to 88.8% (95% CI, 79.8%-94.1%) in distinguishing malignant neoplasms from benign and NIFTP tumors. Furthermore, interpatient differences in 5 gene variants (NRAS, HRAS, KRAS, BRAF, and TERT) were discriminated in 54 of 126 indeterminate FNAs (42.9%) and 18 of 76 nondiagnostic FNAs (23.7%), and all tumors with follow-up surgical pathology confirmed malignancy. Conclusions and Relevance: This diagnostic study delineated interpatient differences in RAS variants present in thyroid tumors with a variety of histopathological diagnoses. Discrimination of interpatient variabilities in RAS in combination with BRAF V600E and TERT promoter variants could facilitate cytology examinations in preoperative precision malignancy diagnosis among patients with thyroid nodules.

Machine learning to predict the occurrence of thyroid nodules: towards a quantitative approach for judicious utilization of thyroid ultrasonography.

Introduction: Ultrasound is instrumental in the early detection of thyroid nodules, which is crucial for appropriate management and favorable outcomes. However, there is a lack of clinical guidelines for the judicious use of thyroid ultrasonography in routine screening. Machine learning (ML) has been increasingly used on big data to predict clinical outcomes. This study aims to leverage the ML approach in assessing the risk of thyroid nodules based on common clinical features. Methods: Data were sourced from a Chinese cohort undergoing routine physical examinations including thyroid ultrasonography between 2013 and 2023. Models were established to predict the 3-year risk of thyroid nodules based on patients' baseline characteristics and laboratory tests. Four ML algorithms, including logistic regression, random forest, extreme gradient boosting, and light gradient boosting machine, were trained and tested using fivefold cross-validation. The importance of each feature was measured by the permutation score. A nomogram was established to facilitate risk assessment in the clinical settings. Results: The final dataset comprised 4,386 eligible subjects. Thyroid nodules were detected in 54.8% (n=2,404) individuals within the 3-year observation period. All ML models significantly outperformed the baseline regression model, successfully predicting the occurrence of thyroid nodules in approximately two-thirds of individuals. Age, high-density lipoprotein, fasting blood glucose and creatinine levels exhibited the highest impact on the outcome in these models. The nomogram showed consistency and validity, providing greater net benefits for clinical decision-making than other strategies. Conclusion: This study demonstrates the viability of an ML-based approach in predicting the occurrence of thyroid nodules. The findings highlight the potential of ML models in identifying high-risk individuals for personalized screening, thereby guiding the judicious use of ultrasound in this context.

Changes in thyroid cytology reporting in the 3rd edition of the Bethesda system.

Reporting fine-needle aspiration of thyroid nodules in the Bethesda classification is a practice widely used internationally and by us. The revised third edition of the Bethesda System of Reporting Thyroid Cytopathology brings changes in terminology, content, and new chapters. In terms of terminology, an obvious change is the removal of the two-word names of three categories while maintaining the six diagnostic categories of the previous versions - new: BI - non-diag- nostic, BIII - atypia of undetermined significance, BIV - follicular neoplasia. In the detailed description of the findings within the individual categories, the ter- minological changes adopted by the fifth edition of the WHO classification of thyroid neoplasia are respected - in particular, the recommended name follicular thyroid nodular disease for the most frequently represented category BII - benign. In the evaluation itself, the diagnostic specifications accepted by the current WHO classification of histopathological findings are reflected in the individual categories - if they are applicable at the cytological level. Targeted attention will need to be paid to high grade features. The revised version brings new chapters dedicated to molecular testing and evaluation of the paediatric population.

Differential diagnosis of thyroid nodules using heterogeneity quantification software on ultrasound images: correlation with the Bethesda system and surgical pathology.

Ultrasonography (US)-guided fine-needle aspiration cytology (FNAC) is the primary modality for evaluating thyroid nodules. However, in cases of atypia of undetermined significance (AUS) or follicular lesion of undetermined significance (FLUS), supplemental tests are necessary for a definitive diagnosis. Accordingly, we aimed to develop a non-invasive quantification software using the heterogeneity scores of thyroid nodules. This cross-sectional study retrospectively enrolled 188 patients who were categorized into four groups according to their diagnostic classification in the Bethesda system and surgical pathology [II-benign (B) (n = 24); III-B (n = 52); III-malignant (M) (n = 54); V/VI-M (n = 58)]. Heterogeneity scores were derived using an image pixel-based heterogeneity index, utilized as a coefficient of variation (CV) value, and analyzed across all US images. Differences in heterogeneity scores were compared using one-way analysis of variance with Tukey's test. Diagnostic accuracy was determined by calculating the area under the receiver operating characteristic (AUROC) curve. The results of this study indicated significant differences in mean heterogeneity scores between benign and malignant thyroid nodules, except in the comparison between III-M and V/VI-M nodules. Among malignant nodules, the Bethesda classification was not observed to be associated with mean heterogeneity scores. Moreover, there was a positive correlation between heterogeneity scores and the combined diagnostic category, which was based on the Bethesda system and surgical cytology grades (R = 0.639, p < 0.001). AUROC for heterogeneity scores showed the highest diagnostic performance (0.818; cut-off: 30.22% CV value) for differentiating the benign group (normal/II-B/III-B) from the malignant group (III-M/V&VI-M), with a diagnostic accuracy of 72.5% (161/122). Quantitative heterogeneity measurement of US images is a valuable non-invasive diagnostic tool for predicting the likelihood of malignancy in thyroid nodules, including AUS or FLUS.

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.

Deciphering the progression of fine-needle aspiration: A bibliometric analysis of thyroid nodule research.

This study aims to dissect the evolution and pivotal shifts in Fine-Needle Aspiration (FNA) research for thyroid nodules over the past 2 decades, focusing on delineating key technological advancements and their impact on clinical practice. A comprehensive bibliometric analysis was conducted on 5418 publications from the Web of Science Core Collection database (2000-2023). Publications were rigorously selected based on their contributions to the advancement of FNA techniques and their influence on thyroid nodule management practices. Our analysis uncovered significant breakthroughs, most notably the incorporation of ultrasound and molecular diagnostics in FNA, which have markedly elevated diagnostic accuracy. A pivotal shift was identified towards minimally invasive post-FNA treatments, such as Radiofrequency Ablation, attributable to these diagnostic advancements. Additionally, the emergence of AI-assisted cytology represents a frontier in precision diagnostics, promising enhanced disease identification. The geographical analysis pinpointed the United States, Italy, and China as key contributors, with the United States leading in both publication volume and citation impact. This bibliometric analysis sheds light on the transformative progression in FNA practices for thyroid nodules, characterized by innovative diagnostic technologies and a trend towards patient-centric treatment approaches. The findings underscore the need for further research into AI integration and global practice standardization. Future explorations should focus on the practical application of these advancements in diverse healthcare settings and their implications for global thyroid nodule management.

A fully autonomous robotic ultrasound system for thyroid scanning.

The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasound system, which is able to scan thyroid regions without human assistance and identify malignant nod- ules. In this system, human skeleton point recognition, reinforcement learning, and force feedback are used to deal with the difficulties in locating thyroid targets. The orientation of the ultrasound probe is adjusted dynamically via Bayesian optimization. Experimental results on human participants demonstrated that this system can perform high-quality ultrasound scans, close to manual scans obtained by clinicians. Additionally, it has the potential to detect thyroid nodules and provide data on nodule characteristics for American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) calculation.

Incidental 68Ga-DOTATATE uptake in thyroid nodules: Is guideline-directed management still appropriate?

BACKGROUND: Fluorodeoxyglucose uptake on positron emission tomography imaging has been shown to be an independent risk factor for malignancy in thyroid nodules. More recently, a new positron emission tomography radiotracer-Gallium-68 DOTATATE-has gained popularity as a sensitive method to detect neuroendocrine tumors. With greater availability of this imaging, incidental Gallium-68 DOTATATE uptake in the thyroid gland has increased. It is unclear whether current guideline-directed management of thyroid nodules remains appropriate in those that are Gallium-68 DOTATATE avid. METHODS: We retrospectively reviewed Gallium-68 DOTATATE positron emission tomography scans performed at our institution from 2012 to 2022. Patients with incidental focal Gallium-68 DOTATATE uptake in the thyroid gland were included. Fine needle aspiration biopsies were characterized via the Bethesda System for Reporting Thyroid Cytopathology. Bethesda III/IV nodules underwent molecular testing (ThyroSeq v3), and malignancy risk ≥50% was considered positive. RESULTS: In total, 1,176 Gallium-68 DOTATATE PET scans were reviewed across 837 unique patients. Fifty-three (6.3%) patients demonstrated focal Gallium-68 DOTATATE thyroid uptake. Nine patients were imaged for known medullary thyroid cancer. Forty-four patients had incidental radiotracer uptake in the thyroid and were included in our study. Patients included in the study were predominantly female sex (75%), with an average age of 62.9 ± 13.9 years and a maximum standardized uptake value in the thyroid of 7.3 ± 5.3. Frequent indications for imaging included neuroendocrine tumors of the small bowel (n = 17), lung (n = 8), and pancreas (n = 7). Thirty-three patients underwent subsequent thyroid ultrasound. Sonographic findings warranted biopsy in 24 patients, of which 3 were lost to follow-up. Cytopathology and molecular testing results are as follows: 12 Bethesda II (57.1%), 6 Bethesda III/ThyroSeq-negative (28.6%), 1 Bethesda III/ThyroSeq-positive (4.8%), 2 Bethesda V/VI (9.5%). Four nodules were resected, revealing 2 papillary thyroid cancers, 1 neoplasm with papillary-like nuclear features, and 1 follicular adenoma. There was no difference in maximum standardized uptake value between benign and malignant nodules (7.0 ± 4.6 vs 13.1 ± 5.7, P = .106). Overall, the malignancy rate among patients with sonography and appropriate follow-up was 6.7% (2/30). Among patients with cyto- or histopathology, the malignancy rate was 9.5% (2/21). There were no incidental cases of medullary thyroid cancer. CONCLUSION: The malignancy rate among thyroid nodules with incidental Gallium-68 DOTATATE uptake is comparable to rates reported among thyroid nodules in the general population. Guideline-directed management of thyroid nodules remains appropriate in those with incidental Gallium-68 DOTATATE uptake.

Comparison of Cytological Adequacy between 23- and 25-Gauge in Ultrasound-Guided Fine-Needle Aspiration of Thyroid Nodules: A Single-Center Prospective Study.

INTRODUCTION: Approximately 15% of fine-needle aspiration (FNA) of thyroid nodules are considered nondiagnostic. Several factors are potentially involved, including clinical and nodule features but also the gauge (G) of the needle used. However, few studies have compared the cytological adequacy obtained with different gauge needles and the data are controversial. We aimed to evaluate cytological adequacy results using 23- or 25-G needles. METHODS: This study is an observational and prospective study of thyroid nodules submitted to ultrasound-guided FNA. The procedure was performed randomly using 23- or 25-G needles. The samples were reported by different cytopathologists who were blinded to the information of the gauge of the needle used. Statistical analysis was performed to compare cytological adequacy of FNA between the two groups. RESULTS: A total of 177 thyroid nodules were included - 98 (55.4%) using 23-G and 79 (44.6%) using 25-G needles. The 23-G group presented a higher rate of cytological adequacy (69.4% [68/98] vs. 46.8% [37/79], p = 0.002). No differences were found between the two groups regarding patient or nodule characteristics. On logistic regression, 23-G needles correlated with better cytological adequacy (unadjusted OR 2.57 [95% CI: 1.39-4.77]), even after adjusting for nodule dimension, location, and type of cytology (slides +/- additional liquid-based cytology) (adjusted OR 2.44 [95% CI: 1.23-4.84]). CONCLUSION: The gauge of the needle used was found to be an independent predictor of cytological adequacy, with 23-G needles providing more adequate samples. Further investigation is needed to confirm our results in order to stablish the optimal diagnosis technique.

Predictive values of ultrasound characters associated with malignant thyroid nodules in Yaoundé: a cross-sectional study.

Introduction: most ultrasound criteria are defined in developed countries and commonly used in practice to assess the malignancy risk of thyroid nodules. This practice does not take into consideration some aspects of our context as delay of consultation and insufficient iodine intake. The objective of this study was to determine the predictive values of ultrasound characters associated with malignant thyroid nodules in our environment. Methods: we conducted a cross-sectional, prospective, and analytical study in three hospitals in Yaoundé over a six-month period in 2022. Our sample consisted of thyroid nodules with ultrasound, cytopathological, and histopathological data. The ultrasound characters and histology status of category III thyroid nodules and higher in Bethesda score were analysed in univariate and multivariate statistics to determine their predictive values. Results: eighty-nine nodules were obtained according to our inclusion criteria. The sex ratio was 0.46 and the average age of the patients was 46 years (IQR=42-59). The cancer prevalence in our sample was 22.47%. On ultrasound assessment, the characters associated to malignant histology (p<0.05) were nodules count, echogenicity, echostructure, presence or absence of microcalcifications, margins, and type of vascularization. Positive predictive values ranged from 26.15 to 57.14%, while negative predictive values ranged from 12.5 to 33.3%. Conclusion: taken alone, the ultrasound characters of suspected thyroid nodules have poor predictive values. There was a high variability in sensitivity but that was generally good (60-95%) while specificity was low. The prediction of malignant thyroid nodules is correlated with the association of at least two ultrasound criteria supported by clinical arguments.

The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules.

Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant. The American College of Radiology has developed the Thyroid Imaging Reporting and Data System (TI-RADS) to standardize the interpretation and reporting of thyroid ultrasound results. Within TI-RADS, a category 4 designation signifies a thyroid nodule with an intermediate level of suspicion for malignancy. Accurate classification of these nodules is crucial for proper management, as it can potentially reduce unnecessary surgeries and improve patient outcomes. This study utilized deep learning techniques to effectively classify TI-RADS category 4 thyroid nodules as either benign or malignant. A total of 500 patients were included in the study and randomly divided into a training group (350 patients) and a test group (150 patients). The YOLOv3 model was constructed and evaluated using various metrics, achieving an 84% accuracy in the classification of TI-RADS category 4 thyroid nodules. Based on the predictions of the model, along with clinical and ultrasound data, a nomogram was developed. The performance of the nomogram was superior in both the training and testing groups. Furthermore, the calibration curve demonstrated good agreement between predicted probabilities and actual outcomes. Decision curve analysis further confirmed that the nomogram provided greater net benefits. Ultimately, the YOLOv3 model and nomogram successfully improved the accuracy of distinguishing between benign and malignant TI-RADS category 4 thyroid nodules, which is crucial for proper management and improved patient outcomes.

Applying machine-learning models to differentiate benign and malignant thyroid nodules classified as C-TIRADS 4 based on 2D-ultrasound combined with five contrast-enhanced ultrasound key frames.

Objectives: To apply machine learning to extract radiomics features from thyroid two-dimensional ultrasound (2D-US) combined with contrast-enhanced ultrasound (CEUS) images to classify and predict benign and malignant thyroid nodules, classified according to the Chinese version of the thyroid imaging reporting and data system (C-TIRADS) as category 4. Materials and methods: This retrospective study included 313 pathologically diagnosed thyroid nodules (203 malignant and 110 benign). Two 2D-US images and five CEUS key frames ("2nd second after the arrival time" frame, "time to peak" frame, "2nd second after peak" frame, "first-flash" frame, and "second-flash" frame) were selected to manually label the region of interest using the "Labelme" tool. A total of 7 images of each nodule and their annotates were imported into the Darwin Research Platform for radiomics analysis. The datasets were randomly split into training and test cohorts in a 9:1 ratio. Six classifiers, namely, support vector machine, logistic regression, decision tree, random forest (RF), gradient boosting decision tree and extreme gradient boosting, were used to construct and test the models. Performance was evaluated using a receiver operating characteristic curve analysis. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy (ACC), and F1-score were calculated. One junior radiologist and one senior radiologist reviewed the 2D-US image and CEUS videos of each nodule and made a diagnosis. We then compared their AUC and ACC with those of our best model. Results: The AUC of the diagnosis of US, CEUS and US combined CEUS by junior radiologist and senior radiologist were 0.755, 0.750, 0.784, 0.800, 0.873, 0.890, respectively. The RF classifier performed better than the other five, with an AUC of 1 for the training cohort and 0.94 (95% confidence interval 0.88-1) for the test cohort. The sensitivity, specificity, accuracy, PPV, NPV, and F1-score of the RF model in the test cohort were 0.82, 0.93, 0.90, 0.85, 0.92, and 0.84, respectively. The RF model with 2D-US combined with CEUS key frames achieved equivalent performance as the senior radiologist (AUC: 0.94 vs. 0.92, P = 0.798; ACC: 0.90 vs. 0.92) and outperformed the junior radiologist (AUC: 0.94 vs. 0.80, P = 0.039, ACC: 0.90 vs. 0.81) in the test cohort. Conclusions: Our model, based on 2D-US and CEUS key frames radiomics features, had good diagnostic efficacy for thyroid nodules, which are classified as C-TIRADS 4. It shows promising potential in assisting less experienced junior radiologists.

Radiofrequency ablation is an effective treatment for Bethesda III thyroid nodules without genetic alterations.

Background: Radiofrequency ablation (RFA) is effective in the treatment of thyroid nodules, leading to a 50-90% reduction with respect to baseline. Current guidelines indicate the need for a benign cytology prior to RFA, though, on the other side, this procedure is also successfully used for the treatment of papillary microcarcinomas. No specific indications are available for nodules with an indeterminate cytology (Bethesda III/IV). Aim: To evaluate the efficacy of RFA in Bethesda III nodules without genetic alterations as verified by means of a custom panel. Methods: We have treated 33 patients (mean delivered energy 1069 ± 1201 J/mL of basal volume) with Bethesda III cytology, EU-TIRADS 3-4, and negative genetic panel. The mean basal nodular volume was 17.3 ± 10.7 mL. Results: Considering the whole series, the mean volume reduction rate (VRR) was 36.8 ± 16.5% at 1 month, 59.9 ± 15.5% at 6 months, and 62 ± 15.7% at 1-year follow-up. The sub-analysis done in patients with 1 and 2 years follow-up data available (n = 20 and n = 5, respectively) confirmed a progressive nodular volume decrease. At all-time points, the rate of reduction was statistically significant (P < 0.0001), without significant correlation between the VRR and the basal volume. Neither cytological changes nor complications were observed after the procedure. Conclusion: RFA is effective in Bethesda III, oncogene-negative nodules, with reduction rates similar to those obtained in confirmed benign lesions. This procedure represents a good alternative to surgery or active surveillance in this particular class of nodules, regardless of their initial volume. A longer follow-up will allow to evaluate further reduction or possible regrowth.

Accuracy and diagnostic performance of the Bethesda system for reporting thyroid cytopathology in a tertiary endocrine surgical referral center in Belgium.

BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology is a commonly used classification for fine needle aspiration (FNA) cytology of suspicious thyroid nodules. The risk of malignancy (ROM) for each category has recently been analyzed in three international databases. This paper compares the diagnostic performance of the Bethesda classification in a high-volume referral center in Belgium. METHODS: All consecutive thyroid procedures were registered in a prospective database from January 2010 till August 2022. Patient and surgical characteristics, preoperative Bethesda categories, and postoperative pathology results were analyzed. RESULTS: Out of 2219 consecutive thyroid procedures, 1226 patients underwent preoperative FNA. Papillary thyroid cancer was the most prevalent malignancy (N = 119, 70.4%), followed by follicular (N = 17, 10.1%) and medullary thyroid cancer (N = 15, 8.9%). Micropapillary thyroid cancer was incidentally found in 46 (3.8%) patients. Bethesda categories I, II, III, IV, V, and VI, respectively, represented 250 (20.4%; ROM 4.4%), 546 (44.5%; ROM 3.8%), 96 (7.8%; ROM 20.8%), 231 (18.8%; ROM 15.2%), 62 (5.1%; ROM 72.6%), and 41 (3.3%; ROM 90.2%) patients. Overall ROM was 13.8%. An negative predictive value (NPV) of 96.2% was found. Overall specificity was 64.2% with a positive predictive value (PPV) of 31.9%. Diagnostic accuracy was 67.8%. Compared to international databases (CESQIP, EUROCRINE, and UKRETS), ROM in this study appeared lower for Bethesda category IV (15.2 vs. 26.7% and p = 0.612). CONCLUSION: Despite being validated in numerous studies, ROM based on preoperative FNA cytology classified according to the Bethesda classification may vary among surgical centers and countries as this study reveals a higher NPV and lower PPV.

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

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

Multimodal ultrasonography evaluation in thyroid nodule characterization: what is the ideal algorithm?

AIMS: The aim of this study is to investigate the diagnostic performances of Ultrasonography (US), Shear-wave Elastography (SWE), and Superb Microvascular Imaging (SMI) findings in the diagnosis of malignant thyroid nodules (MTNs) and to determine the US algorithm with the best diagnostic performance. MATERIAL AND METHODS: Eighty-one nodules in 77 patients who had underwent multimodal US with biopsy results, were evaluated. Echogenicity, nodule components, contours, presence and type of calcification, and size were analyzed with US. Nodule stiffness and vascular index (VI) measurements were performed via SWE and SMI. The power of the US algorithm in predicting malignancy was evaluated. RESULTS: Hypoechogenicity, irregular contour, aspect ratio (anteroposterior (AP)/transvers diameter) >1, and >43.9 kPa were the characteristicshad significant efficacy in the diagnosis of MTNs. Sensitivity, specificity, and AUC values were respectively 100%, 48.5%, and 0.742 for hypoechogenicity; 80%, 90.1%, and 0.855 for irregular contour; 60%, 71.2%, and 0.656 for aspect ratio >1; 60%, 72.7%, and 0.671 for >43.9 kPa; and 93.3%, 90.9%, and 0.921 for the US algorithm. VI did not show significant efficacy in diagnosis. CONCLUSION: Some B-mode and SWE findings showed sufficient efficacy in differentiating benign and malign nodules on their own. However, diagnostic accuracy increased significantly when the US algorithm was applied.

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

PURPOSE: The 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). METHODS: This 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. RESULTS: One 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). CONCLUSION: This study showed that combining SWE and TI-RADS improves the specificity of TI-RADS alone in differentiating benign and malignant nodules.