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Background: We aim to use Natural Language Processing to automate the extraction and classification of thyroid cancer risk factors from pathology reports., Methods: We analyzed 1410 surgical pathology reports from adult papillary thyroid cancer patients from 2010 to 2019. Structured and nonstructured reports were used to create a consensus-based ground truth dictionary and categorized them into modified recurrence risk levels. Nonstructured reports were narrative, while structured reports followed standardized formats. We developed ThyroPath, a rule-based Natural Language Processing pipeline, to extract and classify thyroid cancer features into risk categories. Training involved 225 reports (150 structured, 75 unstructured), with testing on 170 reports (120 structured, 50 unstructured) for evaluation. The pipeline's performance was assessed using both strict and lenient criteria for accuracy, precision, recall, and F1-score; a metric that combines precision and recall evaluation., Results: In extraction tasks, ThyroPath achieved overall strict F-1 scores of 93% for structured reports and 90% for unstructured reports, covering 18 thyroid cancer pathology features. In classification tasks, ThyroPath-extracted information demonstrated an overall accuracy of 93% in categorizing reports based on their corresponding guideline-based risk of recurrence: 76.9% for high-risk, 86.8% for intermediate risk, and 100% for both low and very low-risk cases. However, ThyroPath achieved 100% accuracy across all risk categories with human extracted pathology information., Conclusions: ThyroPath shows promise in automating the extraction and risk recurrence classification of thyroid pathology reports at large scale. It offers a solution to laborious manual reviews and advancing virtual registries. However, it requires further validation before implementation., Competing Interests: Disclosure The authors have no conflicts of interest to disclose., (Copyright © 2024 AACE. Published by Elsevier Inc. All rights reserved.)

Objective: To evaluate the accuracy of thyroid imaging reporting and data system (ACR-TIRADS) and the Bethesda system for reporting cytopathology (TBSRCP) classifications for identifying or ruling out thyroid malignancy in relation to the gold standard (post-surgical pathology)., Methods: This cross-sectional study included 573 patients with single or multiple thyroid nodules. Patients were evaluated using the TIRADS and the TBSRCP classification. The data from a cohort of patients who underwent surgery (77/573, 13.4%) were correlated with post-operative pathology and the relevant clinical features of the patients., Results: Of 573 patients, 545 (95.1%) were euthyroid, 24 (4.1%) were hypothyroid, and 4 (0.8%) were hyperthyroid; 419 (73.1%) had benign nodules (Bethesda II), 115 (20.1%) had intermediate (Bethesda III, IV), and 39 (6.8%) had Bethesda V and VI nodules. Four-hundred twenty (73.3%) patients were categorized as TIRADS 2,3, and 153 (26.7%) were categorized as TIRADS 4,5. The Bethesda and TIRADS classifications concorded significantly in thyroid nodule diagnosis (K=14.9%, P<0.001).Thyroid malignancy was significantly associated with microcalcification and interrupted halo, while benign nodules were significantly associated with macrocalcification and complete halo type (P=0.041, P=0.005, respectively). The TBSRCP could significantly detect malignant thyroid nodules with a sensitivity, specificity, PPV, and NPV of 64.1%, 98.1%, 85.0%, and 94.1%, respectively (K=88.2%, P<0.001), while the respective values for the TIRADS classification were 63.5%, 76.0%, 84.6%, and 50.0% (K=34.8%, P=0.001)., Conclusion: The TIRADS and TBSRCP are essential primary steps for evaluating thyroid nodules and both are complimentary. Hence, each patient with thyroid nodules should be evaluated by both approaches before opting for surgery. Highly suspicious TIRADS categories TR4 and TR5 need further evaluation by fine needle aspiration cytology., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

The evaluation of thyroid lesions is common in the daily practice of cytology. While the majority of thyroid nodules are benign, in recent decades, there has been increased detection of small and well-differentiated thyroid cancers. Combining ultrasound evaluation with fine-needle aspiration cytology (FNAC) is extremely useful in the management of thyroid nodules. Furthermore, the adoption of specific terminology, introduced by different thyroid reporting systems, has helped effectively communicate thyroid FNAC diagnoses in a clear and understandable way. In 1996, the Papanicolaou Society thyroid cytological classification was introduced. This was followed in 2005 by the first Japanese and then in 2007 by the Bethesda System for Reporting Thyroid Cytopathology, which subsequently underwent two revisions. Other international thyroid terminology classifications include the British, Italian, Australasian and other Japanese cytology systems. This review covers similarities and differences among these cytology classification systems and highlights key points that unify these varied approaches to reporting thyroid FNAC diagnoses., (© 2024 The Author(s). Cytopathology published by John Wiley & Sons Ltd.)

Advances in Thyroid Pathology: WHO CLASSIFICATION 2022, BETHESDA SYSTEM 2023, MOLECULAR BIOLOGY AND MOLECULAR TESTING: Thyroid pathology has experienced significant advances with the publication of the 5th edition of the World Health Organization classification of endocrine tumors in 2022 and the third edition of the Bethesda system for thyroid cytopathology in 2023. At the same time, the availability of next-generation sequencing data coupled with numerous translational research projects have considerably increased our knowledge of the genomics and mechanics of thyroid cancers, enabling us to refine prognosis and propose new targeted therapies. In this review, we will take up the main new features of the WHO 2022 and Bethesda 2023 classifications, as well as molecular biology findings, with an emphasis on the practical implications for clinicians., Competing Interests: Liens d’intérêts S. Moog, M. Amine Bani, A. Al Ghuzlan et V. Suciu déclarent ne pas avoir de liens d’intérêts. L. Lamartina déclare des liens d’intérêts pour des financements pour participation à un congrès de la part des laboratoires AAA Novartis et Ipsen; pour participation à des tumor boards de la part des laboratoires Eisai et Ipsen; pour des honoraires perçus de la part des laboratoires Eisai, Lilly et Roche. Cet article fait partie du supplément Prise en charge des cancers thyroïdiens en 2024 : avancées diagnostiques et thérapeutiques réalisé avec le soutien institutionnel de Lilly., (Copyright © 2024 Elsevier Masson SAS. Tous droits réservés. Published by Elsevier Masson SAS. All rights reserved.)

Background: Papillary thyroid carcinoma (PTC) often extends to adjacent organs. According to the 8th Tumor-Node-Metastasis Classification, extension to the strap muscles was graded as T3b. We investigated the prognostic impact of T3b and the appropriateness of T3b in patients aged ≥55 years who were classified as stage II., Methods: We enrolled 7811 patients with M0 PTC who underwent initial surgery at the Kuma Hospital (Kobe, Japan) between January 2007 and December 2016. Tumor extension was divided into T3b, T4a1 (extension to the tracheal adventitia, tracheal cartilage, esophageal muscle layer, recurrent laryngeal nerve, cricothyroid, and inferior constrictor muscles), and sT4a2 (extension to the subcutaneous soft tissues, tracheal mucosa, esophageal mucosa, internal jugular vein, brachiocephalic vein, larynx, pharynx, and sternocleidomastoid muscle)., Results: In patients ≥55 years, the local recurrence-free survival (LR-FS), distant recurrence-free survival (DR-FS), and cause-specific survival (CSS) rates of T3bN0M0 were significantly poorer than those of T1/T2N0M0 but did not significantly differ from those of T3aN0M0. The LR-FS, DR-FS, and CSS rates of T3b stage II patients did not differ from those of T4a1 stage III patients but were significantly better than those of T4a2 stage III patients. T3b was an independent predictor of local recurrence and distant recurrence but not of death due to carcinoma in the multivariate analysis. In patients aged <55 years with M0 PTC, T3b had no prognostic value in both analyses., Conclusions: T3bM0 patients are appropriate to be classified as stage II in patients ≥55 years but be kept in stage I in patients <55 years., (© 2024 The Author(s). World Journal of Surgery published by John Wiley & Sons Ltd on behalf of International Society of Surgery/Société Internationale de Chirurgie (ISS/SIC).)

Purpose: This study aims to develop a deep learning-based computer-aided diagnosis (CAD) system for the automatic detection and classification of lateral cervical lymph nodes (LNs) on original ultrasound images of papillary thyroid carcinoma (PTC) patients., Methods: A retrospective data set of 1801 cervical LN ultrasound images from 1675 patients with PTC and a prospective test set including 185 images from 160 patients were collected. Four different deep leaning models were trained and validated in the retrospective data set. The best model was selected for CAD system development and compared with three sonographers in the retrospective and prospective test sets., Results: The Deformable Detection Transformer (DETR) model showed the highest diagnostic efficacy, with a mean average precision score of 86.3% in the retrospective test set, and was therefore used in constructing the CAD system. The detection performance of the CAD system was superior to the junior sonographer and intermediate sonographer with accuracies of 86.3% and 92.4% in the retrospective and prospective test sets, respectively. The classification performance of the CAD system was better than all sonographers with the areas under the curve (AUCs) of 94.4% and 95.2% in the retrospective and prospective test sets, respectively., Conclusions: This study developed a Deformable DETR model-based CAD system for automatically detecting and classifying lateral cervical LNs on original ultrasound images, which showed excellent diagnostic efficacy and clinical utility. It can be an important tool for assisting sonographers in the diagnosis process., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The 2023 Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) divides AUS diagnoses into two major subcategories: atypia of undetermined significance (AUS) nuclear atypia (AUS-N) and other (AUS-O). This study aims to compare the histological outcome and malignant rate of pediatric AUS thyroid nodules classified into AUS-N and AUS-O subcategories., Design: A search of our institutional electronic pathology database for the period from January 2012 to July 2023 was conducted to identify pediatric (<21 years old) thyroid nodules that were interpreted as AUS and subsequently had surgery. Cases were further divided into AUS-N and AUS-O subcategories. Results of follow-up surgical resections were collected. The malignant rate was calculated and compared between AUS-N and AUS-O groups., Results: The study identified 62 thyroid nodules from 58 pediatric patients. Among these nodules, 29 and 33 were subcategorized as AUS-N and AUS-O, respectively. Both groups exhibited a female predominance and displayed a similar nodule size distribution. Histological analysis revealed 15 carcinomas in AUS-N nodules, including 11 cases of classic papillary thyroid carcinoma (PTC) and four cases of follicular type of PTC. In contrast, in the AUS-O group, a total of five carcinomas were documented, including two PTCs and three oncocytic thyroid carcinomas. Notably, the malignant rate of AUS-N nodules (52%) is significantly higher than that of AUS-O nodules (15%) (p = .002)., Conclusion: In pediatric AUS thyroid nodules, the malignant risk in AUS-N is significantly higher than that in AUS-O. These findings may guide more appropriate clinical triage and/or improve management of pediatric patients with AUS thyroid nodules., (© 2024 The Authors. Cancer Cytopathology published by Wiley Periodicals LLC on behalf of American Cancer Society.)

Purpose: The present study aimed to analyze and compare sonographic features of papillary thyroid carcinoma (PTC) subtypes to determine whether ultrasound (US) may aid in differentiating particular subtypes., Methods: This retrospective study enrolled 133 patients diagnosed with 142 histopathologically proven PTCs as per the fifth edition of the World Health Organization classification of thyroid neoplasms between January 2013 and May 2023. US features based on the American College of Radiology and European Thyroid Imaging and Reporting Data Systems (TIRADS), and histopathological characteristics of nodules were assessed and compared., Results: Histopathological analysis yielded 55 (38.7%) classic PTC, 32 (22.5%) invasive encapsulated follicular variant (IEFV) PTC, 20 (14.1%) oncocytic subtype, 14 (9.9%) non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), 11 (7.8%) infiltrative follicular subtype, 7 (4.9%) tall cell subtype, 2 (1.4%) solid subtype, and 1 (0.7%) diffuse sclerosing subtype. The US findings indicating malignancy, such as taller-than-wide shape, irregular margins, echogenic foci, and higher TIRADS categories, were more frequently demonstrated in nodules with classic PTC and the tall cell subtype, in line with their histopathological features. Conversely, IEFV-PTC and NIFTP rarely exhibited these high-risk sonographic features. US appearance of the oncocytic subtype more frequently overlapped with IEFV-PTC, yet hypo/very hypoechoic nodules with larger nodular diameters and higher TIRADS scores may favor the diagnosis of this subtype., Conclusion: US features of certain subtypes may guide the differential diagnosis regarding shape, margin, echogenic foci, and TIRADS category of nodules; however, definitive subtyping is not yet possible using US images alone., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hekimsoy, Ertan, Serin, Karabulut and Özbek.)

Differentiated high-grade thyroid carcinoma (DHGTC) is a new subset within the spectrum of thyroid malignancies. This review aims to provide a comprehensive overview of DHGTC, focusing on its historical perspective, diagnosis, clinical characteristics, molecular profiles, management, and prognosis. DHGTC demonstrates an intermediate prognosis that falls between well-differentiated thyroid carcinoma and anaplastic thyroid carcinoma. Previously unenumerated, this entity is now recognized for its significant impact. Patients with DHGTC often present at an older age with advanced disease and exhibit aggressive clinical behavior. Molecularly, DHGTC shares similarities with other thyroid malignancies, harboring driver mutations such as BRAF V600E and RAS , along with additional late mutations. The unique behavior and histologic features of DHGTC underscore the necessity of precise classification for prognostication and treatment selection. This highlights the critical importance of accurate diagnosis and recognition by pathologists to enrich future research on this entity further.

In recent years, the incidence of thyroid cancer has rapidly increased. To address the issue of the inefficient diagnosis of thyroid cancer during surgery, we propose a rapid method for the diagnosis of benign and malignant thyroid nodules based on hyperspectral technology. Firstly, using our self-developed thyroid nodule hyperspectral acquisition system, data for a large number of diverse thyroid nodule samples were obtained, providing a foundation for subsequent diagnosis. Secondly, to better meet clinical practical needs, we address the current situation of medical hyperspectral image classification research being mainly focused on pixel-based region segmentation, by proposing a method for nodule classification as benign or malignant based on thyroid nodule hyperspectral data blocks. Using 3D CNN and VGG16 networks as a basis, we designed a neural network algorithm (V3Dnet) for classification based on three-dimensional hyperspectral data blocks. In the case of a dataset with a block size of 50 × 50 × 196, the classification accuracy for benign and malignant samples reaches 84.63%. We also investigated the impact of data block size on the classification performance and constructed a classification model that includes thyroid nodule sample acquisition, hyperspectral data preprocessing, and an algorithm for thyroid nodule classification as benign and malignant based on hyperspectral data blocks. The proposed model for thyroid nodule classification is expected to be applied in thyroid surgery, thereby improving surgical accuracy and providing strong support for scientific research in related fields.

The 5 th edition WHO classification of thyroid tumors proposed high-grade non-anaplastic thyroid carcinoma, which includes traditional poorly differentiated thyroid carcinoma (PDTC) and differentiated high-grade thyroid carcinoma (DHGTC), with a prognosis between highly differentiated thyroid carcinoma and anaplastic thyroid carcinoma (ATC), in which about 50% of patients do not take radioactive iodine. Therefore, this classification is of great clinical significance. This article interprets the diagnostic criteria and genetic features of high-grade non-anaplastic thyroid carcinoma in 5 th edition WHO classification, comparing with ATC.

Purpose: Our purposes were: 1) to estimate the prediction performance (PP) of cytology in identifying papillary thyroid carcinoma (PTC) subtypes; 2) to explore how the PTC subtypes distribute among the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) categories., Methods: Nodules were included if both the histology with the PTC subtype report and the cytology report with the possible PTC subtype were available. The PP was calculated by making the proportion of True positives/False positives+false negatives., Results: 309 cytologically "suspicious for malignancy" and "malignant" thyroid nodules with PTC histology were evaluated. ACR TI-RADS categorization for classical PTC was significantly different from non-classical PTC (p-value 0.02). For the whole cohort the PP of cytologically classical cases was 0.74, while that of cytologically non classical cases was 0.41. ACR TI-RADS categorization was not significantly different for aggressive vs non-aggressive PTC subtypes (p-value 0.1). When considering only aggressive or non-aggressive PTC subtypes, the PP of cytologically classical cases was respectively 0.86 and 0.87, while that of cytologically non classical cases was respectively 0.27 and 0.22. The PP of cytologically classical cases was 0.73 and 0.79, respectively for macroPTCs and microPTCs, while that of cytologically non classical cases was 0.55 and 0.33, respectively for macroPTCs and microPTCs., Conclusion: Cytology examination reliably performed in predicting classical PTC versus non classical PTC subtypes. ACR TI-RADS categorization was significantly different among classical PTC versus non classical PTC subtypes., (© 2023. The Author(s).)

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., (© 2023 International Society of Surgery/Société Internationale de Chirurgie (ISS/SIC).)

In accordance with the 2022 WHO classification of thyroid tumors there is a new group of high grade follicular cell-derived malignances which include both poorly differentiated as well as high grade differentiated thyroid carcinoma. This article describes two thyroid carcinomas with signs of high malignancy, characterised by the formation of their own fibrous capsule. We discuss a heterogeneous group of high grade tumors and possibility of indolent behavior some of this type of tumors.

The WHO classification of thyroid tumours enters its second half-century of development with the 5th edition. Compared to the previous 4th edition of the clas- sification, the permanent increase in information is mainly at the molecular biological level. This has changed the view of very traditional entities - the preferred name for polynodous goiter is (given the monoclonal nature of some nodules) follicular nodular thyroid disease. Some terminological relics have also been re- moved - Hürthle cells are definitively referred to as oncocytes. Follicular adenoma has a new subtype with papillary arrangement (and missing nuclear features of papillary carcinoma). In the already used NIFTP unit, subtypes smaller than 10 mm and oncocytic are newly defined. All oncocytic tumours have an arbitrarily set minimum proportion of oncocytes at 75 %. A multidisciplinary approach to the treatment of thyropathies and the stratification of therapeutic procedures according to risk brought about the introduction of grading into several nosological units of papillary, follicular, and medullary carcinomas. Grading using the number of mitoses determines their quantification at 2 mm² instead of the previously used non-uniform HPFs (high power fields of view). Clarification was made on the basis of genetic findings in a number of other, less frequent diagnoses (e.g. classification of squamous cell carcinoma among anaplastic). Among rare tumors a new category of salivary gland - type carcinomas is formulated with two representatives: mucoepidermoid and secretory carcinoma. Cribriform morular carcinoma previously classified as a variant of papillary carcinoma is newly separated on the basis of the immunological and genetic profile into the newly created category of tumors of uncertain histogenesis. This category also includes sclerosing mucoepidermoid carcinoma with eosinophilia. Microcarcino- ma as a separate entity is not included in the 5th edition. A tumor smaller than 10 mm must be characterized by the appropriate features of the corresponding category. Thyroblastoma replaces terminologically malignant teratoma from the previous classification. Part of the newly established diagnostic criteria is also applicable in FNAB diagnosis. The newly introduced grading in some nosological units can exceptionally change the diagnosis (NIFTP/EFVPTC/non-invasive HG FVPTC), but above all it will affect the choice of therapeutic procedures.

Background: Thyroid tumor is considered to be a very rare form of cancer. But recent researches and surveys highlight the fact that it is becoming prevalent these days because of various factors., Objectives: This paper proposes a novel hybrid classification system that is able to identify and classify the above said four different types of thyroid tumors using high end artificial intelligence techniques. The input data set is obtained from Digital Database of Thyroid Ultrasound Images through Kaggle repository and augmented for achieving a better classification performance using data warping mechanisms like flipping, rotation, cropping, scaling, and shifting., Methods: The input data after augmentation goes through preprocessing with the help of bilateral filter and is contrast enhanced using dynamic histogram equalization. The ultrasound images are then segmented using SegNet algorithm of convolutional neural network. The features needed for thyroid tumor classification are obtained from two different algorithms called CapsuleNet and EfficientNetB2 and both the features are fused together. This process of feature fusion is carried out to heighten the accuracy of classification., Results: A Multilayer Perceptron Classifier is used for classification and Bonobo optimizer is employed for optimizing the results produced. The classification performance of the proposed model is weighted using metrics like accuracy, sensitivity, specificity, F1-score, and Matthew's correlation coefficient., Conclusion: It can be observed from the results that the proposed multilayer perceptron based thyroid tumor type classification system works in an efficient manner than the existing classifiers like CANFES, Spatial Fuzzy C means, Deep Belief Networks, Thynet and Generative adversarial network and Long Short-Term memory.

The latest edition of the WHO Classification of thyroid tumors was released in 2022 and incorporates novel concepts vital to patient management. Thyroid follicular nodular disease is a term used to collectively represent a wide variety of benign and non-neoplastic lesions, including both clonal and non-clonal proliferations that manifest clinically as multinodular goiter. Thyroid neoplasms develop from follicular cells and can be either benign, low-risk, or malignant. To avoid classifying all lesions under 1 cm in diameter as low-risk illnesses, the new classification method highlights the need for subtyping papillary thyroid cancer based on histomorphologic indicators rather than tumor size. Formerly known as the cribriform-morular variety of papillary thyroid carcinoma, this tumor is now more commonly referred to by its more accurate name, cribriform-morular thyroid carcinoma. Its histogenesis is unknown. Similar to the traditional definition of 'poorly differentiated thyroid carcinoma' according to the Turin criteria, the newly defined 'differentiated high-grade thyroid carcinoma' encompasses papillary thyroid cancer, follicular thyroid carcinomas, and oncocytic carcinomas with high-grade characteristics linked to worse prognosis. The squamous cell subtype of anaplastic thyroid cancer has also recently been characterized as a distinct morphologic pattern. In this article, we will discuss the latest revision to the World Health Organization's classification system for thyroid cancer., Competing Interests: The authors declare no conflict of interest., (© 2024 by the authors.)

Objective: The study aimed to assess the predictive significance of inflammatory parameters as potential markers for malignancy in individuals with thyroid nodules., Method: Nine hundred and ninety-one patients with thyroid nodules who had undergone thyroid fine-needle aspiration biopsy were included and classified according to the Bethesda system. Neutrophil lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) values obtained from hemogram parameters were determined for each patient. The study examined the correlation between the Bethesda classification and NLR/SII levels. In addition, a comparison was made between the inflammatory parameters of the benign and malignant Bethesda groups., Results: Five hundred and seventy-three patients were classified as Bethesda 2 (benign), 34 as Bethesda 6 (malignant). A correlation was observed between the Bethesda classification and NLR and SII levels (r: 0.230, p < 0.001; r: 0.207 p < 0.001, respectively). NLR and SII values were significantly higher in the malignant group (p < 0.001). The cutoff value for SII in predicting benign and malignant thyroid nodules was 489.86 × 10 3 /mm 3 with a sensitivity of 88.2% and a specificity of 63.7%. The cutoff value for NLR for the same prediction was 2.06 with a sensitivity of 82.4% and a specificity of 83.4%., Conclusions: The findings of this study indicate that SII and NLR may be valuable prognostic markers for predicting the malignancy of thyroid nodules., (Copyright: © 2024 Permanyer.)

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.