Search

Artificial intelligence (AI) is of considerable interest in the healthcare community including its diagnostic applications for thyroid nodules in assisting both radiology and FNA assessment. Fine-needle aspiration (FNA) helps distinguishing benign from malignant thyroid nodules and is a crucial step in the initial diagnosis of cancer. The classification of some lesions can be challenging, and the use of AI in some cases may become essential in order not to give an indeterminate result to the lesion. In this review, we summarize the available evidence regarding the application of AI in thyroid imaging and cytopathology. There are now considerable applications in digital waiting to be approved that will save time and cut costs. The published literature to date has shown promising results. However, future work is required to better define how this technology can be exploited in routine cytopathology practice.

Objectives: The high incidence of prostate cancer causes prostatic samples to significantly affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging (WSI) and artificial intelligence (AI) have both gained approval for primary diagnosis in prostate pathology, providing physicians with novel tools for their daily routine. Methods: A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was carried out in electronic databases to gather the available evidence on the application of AI-based algorithms to prostate cancer. Results: Of 6290 articles, 80 were included, mostly (59%) dealing with biopsy specimens. Glass slides were digitized to WSI in most studies (89%), roughly two-thirds of which (66%) exploited convolutional neural networks for computational analysis. The algorithms achieved good to excellent results about cancer detection and grading, along with significantly reduced TATs. Furthermore, several studies showed a relevant correlation between AI-identified histologic features and prognostic predictive variables such as biochemical recurrence, extraprostatic extension, perineural invasion, and disease-free survival. Conclusions: The published evidence suggests that AI can be reliably used for prostate cancer detection and grading, assisting pathologists in the time-consuming screening of slides. Further technologic improvement would help widening AI's adoption in prostate pathology, as well as expanding its prognostic predictive potential.

01 februari 2023, Item does not contain fulltext, BACKGROUND: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. METHODS: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. FINDINGS: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. INTERPRETATION: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implemen

Objective: Despite an increase in thyroid fine needle aspiration (FNA) and advances in whole slide imaging (WSI) adoption, digital pathology is still considered inadequate for primary diagnosis of these cases. Herein, we aim to validate the utility of WSI in thyroid FNAs employing the Delphi method strategy. Methods: A panel of experts from seven reference cytology centres was recruited. The study consisted of two consecutive rounds: (1) an open-ended, free-response questionnaire generating a list of survey items; and (2) a consensus analysis of 80 selected shared WSIs from 80 cases by six investigators answering six morphological questions utilising a 1 to 5 Likert scale. Results: High consensus was achieved for all parameters, with an overall average score of 4.27. The broad majority of items (84%) were ranked either 4 or 5 by each physician. Two badly scanned cases were responsible for more than half of the low-ranked (≤2) values (57%). Good to excellent (≥3) diagnostic confidence was reached in more than 95.2% of cases. For most cases (78%) WSI assessment was not limited by technical issues linked to the image acquisition process. Conclusion: This systematic Delphi study indicates broad consensus among participating physicians on the application of DP to thyroid cytopathology, supporting expert opinion that WSI is reliable and safe for primary diagnostic purposes.

Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patient and public health management. Identification of many microbes still relies on manual microscopic examination, a time-consuming process requiring skilled staff. Thus, artificial intelligence (AI) has been exploited for identification of microorganisms. A systematic search was carried out using electronic databases looking for studies dealing with the application of AI to pathology microbiology specimens. Of 4596 retrieved articles, 110 were included. The main applications of AI regarded malaria (54 studies), bacteria (28), nematodes (14), and other protozoa (11). Most publications examined cytological material (95, 86%), mainly analyzing images acquired through microscope cameras (65, 59%) or coupled with smartphones (16, 15%). Various deep-learning strategies were used for the analysis of digital images, achieving highly satisfactory results. The published evidence suggests that AI can be reliably utilized for assisting pathologists in the detection of microorganisms. Further technologic improvement and availability of datasets for training AI-based algorithms would help expand this field and widen its adoption, especially for developing countries.

Immunohistochemical assessment with combined positive score (CPS) of programmed death-ligand 1 (PD-L1) is the prerequisite for administration of checkpoint inhibitor therapy in head and neck squamous cell carcinoma (HNSCC). Practicing pathologists are required to assess PD-L1 in routinary work and can be faced up with practical issues not always addressed in clinical trials or guidelines, such as choice of specimen to test, the intrinsic heterogeneity in PD-L1 expression in tumors and the potential impact of already administered therapy, given that patients’ material can be procured at several times of cancer natural history. In the present work, we review and discuss the recent literature regarding the assessment of PD-L1 in HNSCC from the perspective of the practicing pathologist, providing some evidence on the single issues. It emerges a general trend to an underestimation of PD-L1 expression in biopsies compared to resection specimens and to a higher degree of positivity in metastatic lymph nodes in respect to primary tumors. Moreover, therapy shows to have contrasting effect on PD-L1 expression. Although further studies are needed, taking into account the intrinsic heterogeneity in PD-L1 expression and the conflicting evidences, it may be speculated that the most recent material of patients in respect to the natural history of tumor can be the most reliable to evaluate PD-L1 expression.

Item does not contain fulltext

Contains fulltext : 283491.pdf (Publisher’s version ) (Open Access), BACKGROUND: Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ allocation and post-transplant graft biopsy for assessment of rejection or graft damage. The introduction of digital pathology with whole-slide imaging (WSI) in clinical research, trials and practice has catalyzed the application of artificial intelligence (AI) for histopathology, with development of novel machine-learning models for tissue interrogation and discovery. We aimed to review the literature for studies specifically applying AI algorithms to WSI-digitized pre-implantation kidney biopsy. METHODS: A systematic search was carried out in the electronic databases PubMed-MEDLINE and Embase until 25th September, 2021 with a combination of the key terms "kidney", "biopsy", "transplantation" and "artificial intelligence" and their aliases. Studies dealing with the application of AI algorithms coupled with WSI in pre-implantation kidney biopsies were included. The main theme addressed was detection and quantification of tissue components. Extracted data were: author, year and country of the study, type of biopsy features investigated, number of cases, type of algorithm deployed, main results of the study in terms of diagnostic outcome, and the main limitations of the study. RESULTS: Of 5761 retrieved articles, 7 met our inclusion criteria. All studies focused largely on AI-based detection and classification of glomerular structures and to a lesser extent on tubular and vascular structures. Performance of AI algorithms was excellent and promising. CONCLUSION: All studies highlighted the importance of expert pathologist annotation to reliably train models and the need to acknowledge clinical nuances of the pre-implantation setting. Close cooperation between computer scientists and practicing as well as expert renal pathologists is needed, helping to refine the performance of AI-based models for routine pre-implantation kidne

Item does not contain fulltext, The convergence of digital pathology and computer vision is increasingly enabling computers to perform tasks performed by humans. As a result, artificial intelligence (AI) is having an astoundingly positive effect on the field of pathology, including breast pathology. Research using machine learning and the development of algorithms that learn patterns from labeled digital data based on "deep learning" neural networks and feature-engineered approaches to analyze histology images have recently provided promising results. Thus far, image analysis and more complex AI-based tools have demonstrated excellent success performing tasks such as the quantification of breast biomarkers and Ki67, mitosis detection, lymph node metastasis recognition, tissue segmentation for diagnosing breast carcinoma, prognostication, computational assessment of tumor-infiltrating lymphocytes, and prediction of molecular expression as well as treatment response and benefit of therapy from routine H&E images. This review critically examines the literature regarding these applications of AI in the area of breast pathology.

Ki-67 assessment is a key step in the diagnosis of neuroendocrine neoplasms (NENs) from all anatomic locations. Several challenges exist related to quantifying the Ki-67 proliferation index due to lack of method standardization and inter-reader variability. The application of digital pathology coupled with machine learning has been shown to be highly accurate and reproducible for the evaluation of Ki-67 in NENs. We systematically reviewed all published studies on the subject of Ki-67 assessment in pancreatic NENs (PanNENs) employing digital image analysis (DIA). The most common advantages of DIA were improvement in the standardization and reliability of Ki-67 evaluation, as well as its speed and practicality, compared to the current gold standard approach of manual counts from captured images, which is cumbersome and time consuming. The main limitations were attributed to higher costs, lack of widespread availability (as of yet), operator qualification and training issues (if it is not done by pathologists), and most importantly, the drawback of image algorithms counting contaminating non-neoplastic cells and other signals like hemosiderin. However, solutions are rapidly developing for all of these challenging issues. A comparative meta-analysis for DIA versus manual counting shows very high concordance (global coefficient of concordance: 0.94, 95% CI: 0.83–0.98) between these two modalities. These findings support the widespread adoption of validated DIA methods for Ki-67 assessment in PanNENs, provided that measures are in place to ensure counting of only tumor cells either by software modifications or education of non-pathologist operators, as well as selection of standard regions of interest for analysis. NENs, being cellular and monotonous neoplasms, are naturally more amenable to Ki-67 assessment. However, lessons of this review may be applicable to other neoplasms where proliferation activity has become an integral part of theranostic evaluation including bre, This study is supported by Associazione Italiana Ricerca sul Cancro (AIRC IG n. 26343); Fondazione Cariverona: Oncology Biobank Project “Antonio Schiavi” (prot. 203885/2017); Fondazione Italiana Malattie Pancreas (FIMP-Ministero Salute J38D19000690001).

Mutational analysis contributes to the diagnosis and prognosis of thyroid nodules analyzed with fine-needle aspiration cytology (FNAC). Although several advanced molecular tests based on multiple molecular markers are available for clinical use and have increased their impact on clinical management of patients, they are not widely available. Among them is BRAF V600E, one of the most studied mutations. Other genetic alterations, such as TERT promoter mutations, may coexist in thyroid carcinomas. Previous studies have demonstrated that this duet might be involved in the aggressiveness of thyroid cancer, although its prognostic value related to mortality remains undefined. The detection of such genetic alterations in thyroid liquid-based cytology (LBC) thus may assist with patient management. METHODS: From January 2013 to June 2014, 356 thyroid FNAC samples were processed by LBC, including 174 surgical follow-up samples. BRAF V600E and TERT mutation analyses were performed on both LBC and histopathology. RESULTS: The study included 119 samples categorized as atypia of undetermined significance, 42 categorized as follicular neoplasms, 61 categorized as suspicious for malignancy, and 34 categorized as positive for malignancy. BRAF V600E mutation was detected in 10.4% of all cases, whereas TERT promoter mutations were identified in 1.1%. TERT-mutated cases belonged to the positive for malignancy category, with a histologic diagnosis of tall cell variant of papillary thyroid carcinoma. These genetic alterations correlated with lymph node metastases (P = .0349) and higher disease stage. CONCLUSIONS: BRAF V600E and TERT analysis can be performed on LBC. TERT mutations are rarely identified in well differentiated thyroid carcinoma but are associated with higher stage. Although a larger molecular panel may offer more information, analyzing these few point mutations is still likely to be useful for managing potentially more aggressive thyroid carcinomas. C

The e-learning event “PD-L1 Key learning in HNSCC” was organized by Global Studio SRL over several days (December 2019 to May 2020) and ended with a final webinar on June 12, 2020. There were 3 learning days with overall 28 sessions comprising both traditional lectures and interactive slide viewing sessions for overall 6 h of learning activity, with involvement of a mean of six lecturers of the faculty for each event. The final meeting was supported by Zoom videoconferencing software (Zoom Video Communications, Inc., San Jose, CA, USA). After subscription, all participants received a permanent link with meeting ID and password for all online material. The faculty included Albino Eccher (University and Hospital Trust of Verona, Verona), Gabriella Fontanini (University of Pisa, Pisa), Nicola Fusco (European Institute of Oncology, Milan), Paolo Graziano (Foundation IRCCS “Casa Sollievo della Sofferenza,” San Giovanni Rotondo, Foggia), Elena Guerini Rocco (European Institute of Oncology, Milan), Maurizio Martini (Catholic University-Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Rome), Patrizia Morbini (University of Pavia and IRCCS Policlinico S. Matteo, Pavia and Chief of Head and Neck Pathology Study Group for Italian Society for Anatomic Pathology and Cytology [SIAPEC]), Giancarlo Troncone (University of Naples Federico II, Naples), and Elena Vigliar (University of Naples Federico II, Naples). Attendees were 86 pathologists from all over Italy. All of the events were structured with lectures and interactive practical sessions involving case discussions.

Thyroid tumors can be classified into epithelial, nonepithelial, and nonprimary lesions. Nonepithelial thyroid tumors are rare. They can be of primary origin within the thyroid gland, arise secondary to contiguous growth from adjacent tissues, or represent metastatic disease. The incidence of nonepithelial tumors of the thyroid is only 1% to 2%, most of which are lymphomas; the remainder includes mesenchymal and histiocytic tumors. This review examines the cytohistological features of various nonepithelial and nonlymphoid tumors of the thyroid, including vascular lesions, neural tumors (including granular cell tumor and paraganglioma), smooth muscle tumors, solitary fibrous tumor, histiocytic neoplasms (eg, Langerhans cell histiocytosis and Rosai-Dorfman disease), and follicular dendritic cell sarcoma. Their differential diagnosis is discussed, including recommendations to prevent the pitfall of mistaking these rare tumors for more common epithelial thyroid neoplasms.

An overview about the role pof thryopid papillary carcinoma in the different countries

Background: Thyroid paragangliomas are extremely rare and often are misdiagnosed by preoperative fine-needle aspiration (FNA) because their cytologic features overlap with those of other thyroid neoplasms. The objective of this study was to review the cytomorphology in a series of thyroid paragangliomas and correlate the findings with histopathology. Methods: Five thyroid paraganglioma cases that underwent FNA were reviewed. Their clinical presentation, radiology features, cytomorphology, ancillary tests, and histopathology were analyzed. Results: All patients were women with an average age of 49 years (age range, 35-61 years) and presented with an asymptomatic, solitary thyroid nodule. Radiologically, these nodules (size range, 1.8-3.0 cm) were well circumscribed, hypoechoic, and hypervascular. FNA smears showed clusters of loosely cohesive, medium-to-large epithelioid cells with clear-to-eosinophilic and occasionally foamy cytoplasm that had indistinct cytoplasmic borders. The nuclei were round to oval with focal nuclear membrane irregularities, inconspicuous nucleoli, focal marked anisonucleosis, and occasional intranuclear pseudoinclusions. Naked nuclei, variable numbers of plasmacytoid cells, multinucleated giant cells, and sustentacular cells were present in the background along with blood vessels and lymphocytes. Cytology diagnoses were incorrect and included follicular neoplasm (n = 4) and follicular lesion of undetermined significance (n = 1). Final histopathology with immunohistochemistry revealed conventional paraganglioma (n = 3) or sclerosing paraganglioma with invasive features (n = 2). Conclusions: All thyroid paragangliomas were misdiagnosed on FNA as follicular neoplasms, in part because of the rarity of these tumors in this location and cytomorphology mimicking follicles. The absence of colloid, the presence of naked nuclei, focal marked anisonucleosis, and the presence of sustentacular cells are important cytology clues.

Contains fulltext : 220738.pdf (publisher's version ) (Open Access), The introduction of digital pathology is changing the practice of diagnostic anatomic pathology. Digital pathology offers numerous advantages over using a physical slide on a physical microscope, including more discriminative tools to render a more precise diagnostic report. The development of these tools is being facilitated by public challenges related to specific diagnostic tasks within anatomic pathology. To date, 24 public challenges related to pathology tasks have been published. This article discusses these public challenges and briefly reviews the underlying characteristics of public challenges and why they are helpful to the development of digital tools.

Background: Programmed death-ligand 1 (PD-L1) expression is emerging as an important predictive biomarker in anti–PD-L1 cancer immunotherapy. Its role has been clearly defined in various human cancers and is linked to a poor prognosis and resistance to anticancer therapies. The role of PD-L1 in thyroid cancers has not been well defined in fine-needle aspiration cytology (FNAC). The authors examined the performance of PD-L1 immunostaining in liquid-based cytology (LBC) to determine whether it could be a biomarker of malignancy or aggressive disease. Methods: From January 2018 to March 2019, 236 thyroid lesions, which had been diagnosed by FNAC as indeterminate lesions, suspicious for malignancy (SFM), and malignant, were enrolled. PD-L1 immunostaining was performed on both LBC and corresponding histology samples. Results: The FNAC cohort included 50 benign negative controls, 42 samples of atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS), 33 samples of follicular neoplasm/suspicious for follicular neoplasm (FN/SFN), 53 samples that were suspicious for malignancy (SFM), and 58 malignant samples. AUS/FLUS samples included 3 goiters, 32 follicular adenomas (FAs), 1 noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), 5 invasive follicular variants of papillary thyroid carcinoma (I-FVPTCs), and 1 follicular carcinoma; whereas FN/SFN samples included 24 FAs and 9 malignancies (4 I-FVPTCs, 1 NIFTP, 3 papillary thyroid carcinomas [PTCs], and 1 oncocytic follicular carcinoma). The 53 SFM samples were diagnosed on histopathology as 2 FAs, 5 NIFTPs, 15 I-FVPTCs, and 31 PTCs; whereas the 58 malignant specimens included 5 NIFTPs, 5 I-FVPTCs, and 48 PTCs. Increased plasma membrane and cytoplasmic PD-L1 expression was found in 79 cases (38.5%), including 61 PTCs (conventional and variants). Negative PD-L1 expression was found in NIFTPs and FAs. A BRAF V600E mutation was identified in 15% of PD-L1–positive

Introduction: The detection of rosette-like clusters (RLC) of follicular cells in thyroid carcinoma has been reported mostly in the columnar cell variant of papillary thyroid carcinoma (PTC). Despite the fact that diagnosing variants of PTC is no longer encouraged by The Bethesda System for Reporting Thyroid Cytopathology, the identification of cytomorphological features such as RLC linked with these tumours might help reduce possible misinterpretation in thyroid fine needle aspiration (FNA) cytology. We accordingly investigated the potential correlation of architectural patterns including RLC with PTC variants. Methods: We analysed 225 thyroid FNA cytology cases diagnosed as suspicious for malignancy (SFM) and positive for malignancy (M) over a 1-year time where all samples had corresponding histology. We also included 150 benign lesions from the same period. The presence of RLC vs similar appearing solid clusters, papillary structures and microfollicles were evaluated. We also performed immunocytochemistry and molecular testing for BRAFV600E. Results: We included 100 (44.4%) SFM favouring PTC and 125 (55.6%) M cases with cyto-histological correlation. On histology, all SFM and M cases showed malignancy including 140 (62.2%) classic PTC and 85 (37.8%) PTC variants. The cytomorphological patterns in all FNA samples included solid (74%), papillary (89%), microfollicular (70%), and pseudo-RLC morphology (25.7%). We identified only pseudo-RLC in 33 FNA specimens from PTC variant cases that included tall cell variant (42.4%), hobnail variant (21.2%) and miscellaneous variants (36.3%) of PTC. No definitive RLC were detected in our series. Immunocytochemistry and BRAFV600E were not specifically linked with an RLC pattern. Conclusions: These findings demonstrate that in our dataset the architectural pattern of RLC was not recognised within PTC variants. However, we did identify a pseudo-RLC pattern that was observed in association with tall cell variant and hobnail variant

Contains fulltext : 215198.pdf (publisher's version ) (Open Access)

Background: Hyalinizing trabecular tumors (HTTs) are rare, essentially benign, follicular cell–derived thyroid neoplasms characterized by a trabecular growth pattern and nuclear pseudoinclusions. Their cytological findings are misleading, because these tumors are often misinterpreted on fine needle aspirate cytology as malignant lesions, such as papillary thyroid cancer and/or medullary thyroid cancer, leading to unnecessary total thyroidectomy. The aim of this study was to analyze the cytomorphological features and application of ancillary techniques in a series of HTTs. Methods: Of 26 histological cases of HTT collected from September 2001 to December 2018, 18 cases had concomitant cytopathology. Cytological cases were processed with liquid-based cytology (LBC). Immunocytochemistry for HBME-1 and galectine-3 as well as molecular testing for BRAFV600E mutation were performed on both LBC and histological specimens. Results: The 18 lesions with fine needle aspirate cytology ranged in size from 5 to 45 mm. Cytological diagnoses included: 1 benign lesion favoring goiter (5.5%), 4 atypia of undetermined significance (22.2%), 6 follicular neoplasms (33.3%), 5 suspicious for malignancy favoring papillary thyroid cancer (28%), and 2 malignant (11%). Hence, 89% HTT had a negative concordant immunopanel, and they were 100% wild-type BRAFV600E. Conclusion: The majority of our HTTs (83.3%) were diagnosed in the indeterminate Bethesda categories, suggesting that their cytomorphological features pose issues for reaching a conclusive cytological diagnosis. The ancillary test results in our series support the fact that HTT is a benign neoplasm.

Certain carcinomas of the thyroid gland behave aggressively resulting in increased patient morbidity and poor patient prognosis. The diagnosis of these aggressive thyroid cancer subtypes is sometimes challenging and subject to increased interobserver variability. This review deals with the cytological features of such tumors including aggressive variants of papillary thyroid carcinoma, poorly differentiated thyroid carcinoma, and anaplastic thyroid carcinoma. These malignancies fall into 2 groups based on their cytomorphology: those that exhibit distinct microscopic features (eg, nuclear findings typical of classical papillary thyroid carcinoma or marked anaplasia) and those that present with more subtle cytologic features (eg, nuclear pseudostratification, “soap bubble” nuclei, supranuclear or subnuclear cytoplasmic vacuoles, rosette-like structures, hobnail cells). We review the literature regarding these aggressive thyroid cancers and highlight important phenotypic characteristics that can be useful for their diagnosis based on fine needle aspiration.

Background The Milan System for Reporting Salivary Gland Cytopathology (MSRSGC) is a 6-tier diagnostic category system with associated risks of malignancy (ROMs) and management recommendations. Submandibular gland fine-needle aspiration (FNA) is uncommon with a higher frequency of inflammatory lesions and a higher relative proportion of malignancy, and this may affect the ROM and subsequent management. This study evaluated the application of the MSRSGC and the ROM for each diagnostic category for 734 submandibular gland FNAs. Methods Submandibular gland FNA cytology specimens from 15 international institutions (2013-2017) were retrospectively assigned to an MSRSGC diagnostic category as follows: nondiagnostic, nonneoplastic, atypia of undetermined significance (AUS), benign neoplasm, salivary gland neoplasm of uncertain malignant potential (SUMP), suspicious for malignancy (SM), or malignant. A correlation with the available histopathologic follow-up was performed, and the ROM was calculated for each MSRSGC diagnostic category. Results The case cohort of 734 aspirates was reclassified according to the MSRSGC as follows: nondiagnostic, 21.4% (0%-50%); nonneoplastic, 24.2% (9.1%-53.6%); AUS, 6.7% (0%-14.3%); benign neoplasm, 18.3% (0%-52.5%); SUMP, 12% (0%-37.7%); SM, 3.5% (0%-12.5%); and malignant, 13.9% (2%-31.3%). The histopathologic follow-up was available for 333 cases (45.4%). The ROMs were as follows: nondiagnostic, 10.6%; nonneoplastic, 7.5%; AUS, 27.6%; benign neoplasm, 3.2%; SUMP, 41.9%; SM, 82.3%; and malignant, 93.6%. Conclusions This multi-institutional study shows that the ROM of each MSRSGC category for submandibular gland FNA is similar to that reported for parotid gland FNA, although the reported rates for the different MSRSGC categories were variable across institutions. Thus, the MSRSGC can be reliably applied to submandibular gland FNA.

BACKGROUND: Hyalinizing trabecular tumors (HTTs) are rare, essentially benign, follicular cell-derived thyroid neoplasms characterized by a trabecular growth pattern and nuclear pseudoinclusions. Their cytological findings are misleading, because these tumors are often misinterpreted on fine needle aspirate cytology as malignant lesions, such as papillary thyroid cancer and/or medullary thyroid cancer, leading to unnecessary total thyroidectomy. The aim of this study was to analyze the cytomorphological features and application of ancillary techniques in a series of HTTs. METHODS: Of 26 histological cases of HTT collected from September 2001 to December 2018, 18 cases had concomitant cytopathology. Cytological cases were processed with liquid-based cytology (LBC). Immunocytochemistry for HBME-1 and galectine-3 as well as molecular testing for BRAF(V600E) mutation were performed on both LBC and histological specimens. RESULTS: The 18 lesions with fine needle aspirate cytology ranged in size from 5 to 45 mm. Cytological diagnoses included: 1 benign lesion favoring goiter (5.5%), 4 atypia of undetermined significance (22.2%), 6 follicular neoplasms (33.3%), 5 suspicious for malignancy favoring papillary thyroid cancer (28%), and 2 malignant (11%). Hence, 89% HTT had a negative concordant immunopanel, and they were 100% wild-type BRAF(V600E). CONCLUSION: The majority of our HTTs (83.3%) were diagnosed in the indeterminate Bethesda categories, suggesting that their cytomorphological features pose issues for reaching a conclusive cytological diagnosis. The ancillary test results in our series support the fact that HTT is a benign neoplasm. (c) 2019 American Cancer Society.

Cytological specimens from thyroid nodules are increasingly being adopted as the first available material for cost effectively managing patients in the era of personalized medicine. Cytology aspirates not only play a central role in providing accurate diagnoses, but are also being collected for ancillary molecular testing. Molecular analysis, including the evaluation of somatic mutations and other genomic alterations, has accordingly become well integrated in the cytological workup of thyroid lesions. Appropriately handled thyroid cytology preparations provide well-preserved and adequately cellular material with improved DNA/RNA quantity. The recent publication of the 2nd edition of The Bethesda System for Reporting Thyroid Cytopathology and the American Thyroid Association guidelines confirm the relevant role of molecular testing in the management of the different subcategories of indeterminate thyroid lesions. This review discusses the role of molecular testing for indeterminate thyroid nodules, including the recent introduction of the noninvasive, encapsulated follicular variant of papillary thyroid carcinoma (FVPTC), known also as noninvasive follicular neoplasm with papillary-like nuclear features (NIFTP).