Acta Cytologica最新文献

Introduction: The International Serous Fluid Cytopathology Reporting System (TIS) was developed to standardize communication among health professionals reporting analyses of serous fluid samples. The categories include non-diagnosis (ND), negative for malignancy (NFM), atypia of undetermined significance (AUS), suspected malignancy (SFM), and malignant (MAL). Each category was characterized by a risk of malignancy (ROM).

Methods: We performed a literature review to analyze studies related to TIS using several sources, including PubMed, followed by a search of relevant cytopathology journal websites (American Cancer Society, Diagnostic Cytopathology, Journal of the American Society of Cytopathology, and Acta Cytologica and Cytopathology). The search included articles published between January 2020 and December 2023, using the terms "international AND serous fluid system."

Results: We identified 257 articles, of which 20 addressed the inclusion and exclusion criteria. The overall ROMs for each category were 23.55% for ND, 16.46% for NFM, 50.78% for AUS, 91.34% for SFM, and 98.21% for MAL.

Conclusion: Considering the TIS-recommended ROM rates, the ND category was between the suggested intervals, while the SFM category rate was bigger than expected. The other categories (NFM, AUS, and MAL) were below expected values. SFM and MAL had a stronger association with MAL results. New studies are needed to determine each category's ROM rate from TIS accurately.

Introduction: Liquid-based cytology (LBC) has replaced conventional smear (CS) in the world. In this study, through a series with a large number of cases, we aimed to make a comparison and general evaluation in all groups, primarily epithelial abnormalities, according to LBC and CS methods. This study was carried out in a private pathology laboratory located in a metropolitan city, where cytological materials sent from many clinics were examined.

Material and methods: There were 165,915 cases whose smears were examined between 2012 and 2020, most of them conventional (131,224 CS, 34,691 LBC). Cases were evaluated on the basis of the Bethesda 2014 classification and divided into sub-diagnostic categories after they were divided into two main groups as "with epithelial abnormalities" and "without." χ2 and Fischer's precision statistical tests were conducted using SPSS 23.0 package. In the CS process, cervical samples were obtained using an endocervical brush and a spatula. Cells were directly spread onto the slides and promptly fixed in 95% ethanol, followed by staining with the standard Papanicolaou stain. For LBC ThinPrep, cervical specimens were gathered using a cervix brush. The brush was washed in a vial and discarded. Finally, cells were isolated through vacuum filtration and transferred to the slide using air pressure.

Results: Squamous cell abnormalities (atypical squamous cells of undetermined significance [ASC-US], atypical squamous cells - cannot exclude high-grade squamous intraepithelial lesion [ASC-H], low-grade squamous intraepithelial lesion [LSIL], high-grade squamous intraepithelial lesion [HSIL], squamous cell carcinoma, atypical glandular cells of undetermined significance) were reported in 5,696 (3.43%) cases. ASC (ASC-US + ASC-H)/SIL ratio (1.36/2.04) was found to be 0.67 (recommended Bethesda ratio is <3). ASC-US (p < 0.001), ASC-H (p < 0.001), and HSIL(p < 0.001) detection rate of LBC was found to be significantly higher than CS. ASC-US (1.8/1.2), ASC-H (0.08/0.008), and HSIL (0.6/0.3) case ratios of LBC/CS were found to be significantly higher in LBC. LSIL (1.72/1.66) rate was similar.

Conclusion: LBC is superior to CS in detecting epithelial lesions. In addition to being used as a screening method, it is clear that it makes a great contribution to reducing cervical carcinomas due to HPV typing. Definitive comments regarding comparison of methods on reactive changes and microorganism detection are challenging. Preanalytical factors might account for these situations.

Background: Thyroid nodules are prevalent among the general population, thus imposing substantial demands upon healthcare providers to establish effective management paradigms when investigating these lesions. A pivotal component in the diagnostic process involves the cytomorphological evaluation of fine-needle aspiration (FNA) specimens extracted from the nodule under scrutiny. This examination serves the critical purpose of enabling a comprehensive assessment for the risk of either a neoplasm or malignancy, thereby providing the clinical team with the requisite information to render decisions regarding potential surgical intervention and/or a structured clinical follow-up. A subset of FNA specimens obtained from the thyroid gland present a vexing challenge for interpretation and cannot be classified based on cytomorphology as either benign or malignant and are classified as "indeterminate" for neoplasm or malignancy. The indeterminate thyroid FNA diagnosis in the third iteration of the Bethesda classification is termed as "atypia of undetermined significance" (AUS).

Summary: The thyroid FNA specimens classified as "atypical" constitute a perplexing category, necessitating considerations such as repeated cytological evaluations, supplementary molecular analyses, diagnostic lobectomy, or vigilant surveillance. This review article draws upon the most recent Bethesda classification guidelines and delineates various potential pitfalls encountered during the interpretation of atypia observed in thyroid fine-needle aspiration and histopathologic counterparts. Additionally, it proffers strategic algorithms devised to effectively navigate these diagnostic challenges.

Key messages: It is important to recognize the value of an integrated approach when triaging AUS lesions, considering various clinical, morphological, and sometimes also immunocytochemical or molecular features.

Background: Fine-needle aspiration cytology (FNAC) is a cornerstone technique for the initial assessment of breast lesions, offering a rapid and minimally invasive option for cytological evaluation. While FNACs can forego the need for core needle biopsies (CNBs), variations in technique, subjective interpretation, and intrinsic limitations present diagnostic challenges. The International Academy of Cytology (IAC) established the Yokohama system and is developing the WHO Reporting System for Breast Cytopathology jointly with IARC, to standardize diagnostic criteria, aiming to enhance diagnostic precision and consistency. Due to the preference for CNBs, expertise in breast FNAC is low in the developed world.

Summary: This review assesses common pitfalls in breast cytopathology. These common and uncommon entities may easily lead to false-negative or false-positive diagnoses, due to morphological overlap or misleading clinical and radiological contexts. For instance, pauci-cellular lesions, such as lobular carcinomas, often lead to false-negative diagnoses, whereas complex sclerosing lesions, fibroadenomas, and papillary lesions may show concerning features, resulting in a false positive. The same is true for some benign inflammatory pathologies, such as steatonecrosis, and uncommon lesions, such as collagenous spherulosis. Ductal carcinoma in situ can lead to both false-negative and false-positive diagnoses, and high-grade lesions are impossible to tell apart from invasive carcinomas. These are discussed in detail. Procedural and preanalytical conditions, and the role of ancillary testing, are also briefly addressed.

Key messages: Breast FNAB is a powerful diagnostic technique, fast and minimally invasive. Even in contexts which lack expertise, this technique can be successfully adopted with a cautious approach and as long as pitfalls are kept in mind, benefiting patients and healthcare systems.

Introduction: The diagnosis of salivary gland secretory carcinoma (SC) in fine-needle aspiration specimens is challenging because its low-grade nature makes it difficult to differentiate it from various benign or malignant salivary gland neoplasms. Currently, the gold standard is demonstration of ETV6-NTRK3 fusion gene. However, the decision for ordering this costly molecular testing can be facilitated by the correct recognition of its cytomorphological features. The aim of the review was to determine the accuracy of fine-needle aspiration cytology (FNAC) in diagnosis of salivary gland SC. The secondary objective was to recognize varied cytomorphological patterns, characteristic features of SC and differentiate it from other neoplasms.

Methods: PubMed/MEDLINE, Science Direct, Embase, Cochrane review, and PROSPERO databases were searched for studies having the following key search terms: ("secretory carcinoma of salivary gland" OR "mammary analogue secretory carcinoma of salivary gland") AND ("Cytology" OR "Cytological features" OR "aspirate" OR "cytodiagnosis") published in the time frame of 2010 to June 2023. Studies reporting cytological features of the salivary gland tumors which were confirmed/diagnosed as SC on molecular investigation, were included in the systematic review. Finally, seventeen studies reporting a total of 45 cases were included in the metanalysis.

Results: The sensitivity of the FNAC in diagnosing SC in salivary gland is 27.7% (95% CI: 16.6-42.5%). The LR+ (positive likelihood ratio) was 0.654 (0.344-1.245), LR- (negative likelihood ratio) was 1.023 (0.538-1.946), and diagnostic odds ratio was 0.421 (0.129-1.374). The molecular testing and/or immunohistochemistry performed on cell block increased the diagnostic accuracy.

Conclusion: Recognition of subtle cytomorphological patterns, i.e., papillary formation, clusters, and singly dispersed cells along with presence of fine intracytoplasmic vacuolations were the characteristic findings in majority of cases, confirmed with diagnostic molecular profiling. This may be helpful in identification of this rare entity with limited published literature and help in increasing diagnostic accuracy.

Background: Salivary gland lesions possess diagnostic challenges on fine-needle aspiration (FNA) material. They are relatively uncommon, yet present with a wide spectrum of cytomorphology. Herein, we review common salivary gland neoplasms, their cytomorphologic features, their diagnostic pitfalls, and ancillary studies helpful in achieving an accurate diagnosis.

Summary: There are many cytomorphologic overlaps between benign and malignant salivary gland entities. Moreover, metaplasia, cystic changes, and degenerative changes are common findings adding to diagnostic dilemmas. These complicating factors contribute to a minute risk of malignancy in salivary gland lesions that are interpreted as benign on FNA. In rare cases, even malignant salivary gland neoplasms are misinterpreted as benign on aspirated material due to the many cytomorphologic overlaps. For example, benign and malignant neoplasms containing stroma such as myoepithelioma and adenoid cystic carcinoma may be misinterpreted as pleomorphic adenoma. Moreover, diagnosis of salivary gland neoplasms with basal cell features can be confusing on FNA materials; for example, basal cell adenoma can be misinterpreted as adenoid cystic carcinoma. Mucoepidermoid carcinomas have many different appearances on aspirated material due to variable amounts of mucin, degree of nuclear atypia, cellular content, and squamous metaplasia. Acinic cell carcinoma exhibits large cells with abundant cytoplasm on FNA, which can be mistaken for oncocytic cells in oncocytoma or Warthin tumor. Salivary duct carcinoma shows distinct features of malignancy and thus can be mistaken for secondary tumors involving the salivary glands or other malignant salivary gland tumors. The presence of tumor-associated lymphocytes is another underlying cause of misdiagnosis, especially when considering the differential diagnosis of an intraparotid lymph node. Ancillary studies such as immunohistochemistry and molecular studies are gaining more attention to be utilized on FNA cases. PLAG1 immunostaining, CD117, DOG1, mammaglobin, and androgen receptor (AR) are examples of commonly used immunostains in diagnosis of salivary gland lesions. MYB gene fusion, rearrangements of the MAML2 gene, and ERBB2/HER2 are examples of molecular alterations useful in diagnosis of salivary gland neoplasms. In conclusion, the aim of salivary gland cytology is to differentiate benign entities from the malignant ones and to prevent unnecessary aggressive treatments.

Key messages: The diagnostic pitfalls are enormous in salivary gland cytology. Familiarity with cytomorphology of different entities and their cytomorphologic overlaps, and application of ancillary studies improves the diagnostic yield, patient management and prevents unnecessary aggressive procedures.

Introduction: Standardized basic morphology and the algorithmic approach make the Paris System (TPS) for Reporting Urinary Cytology understandable and applicable. This study examined how well the TPS categories are understood by pathology residents and how well these criteria are enabling them reaching accurate diagnosis.

Materials/methods: A hundred consecutive cases representing all categories were selected. Authors reevaluated slides using TPS regardless of their original diagnosis. In the next step, the TPS was explained to four residents and trained them by five optimal urine cytology samples from each category. Then they were asked to diagnose the selected slides according to the TPS. The diagnoses were compared to authors. The agreement was assessed using kappa. Discordant diagnoses were classified as high and low impact based on potential on clinical practice.

Results: The sensitivity of authors was 62.8%, and residents' were 24-31.8%. The specificity of authors was 98.8%, and residents' were 82.3-92.8%. Reproducibility of TPS was 40-46%. Kappa values were below 0.40 except for one resident. The highest rate of concordance was for negative for high-grade urothelial carcinoma (NHGUC): authors assigned 38 NHGUC (35 biopsy-proven benign cases). Twenty to twenty-six of them were assigned as NHGUC by residents. While authors assigned 42 cases as suspicious for high-grade urothelial carcinoma (SHGUC) or high-grade urothelial carcinoma (HGUC) (35 biopsy-proven malignant cases), residents assigned 22-29 of them. Discordant diagnosis with high clinical implication was 56-63%.

Conclusion: Diagnostic accuracy rates of junior pathology residents using the TPS were unsatisfactory. The best agreement was observed in NHGUC and HGUC categories. Combining HGUC and SHGUC doubled the sensitivity of residents.

Introduction: This study conducts the first meta-analysis to evaluate the diagnostic accuracy and the aggregated risk of malignancy associated with each category of the Papanicolaou Society of Cytopathology (PSC) system for reporting respiratory cytology.

Methods: A systematic search was conducted in PubMed, Scopus, and Web of Science using the keywords "(Lung, Respiratory specimens) AND (Papanicolaou Society of Cytopathology System)." Articles were assessed for risk of bias using the QUADAS-2 tool. After excluding inadequate samples, sensitivity and specificity for various cut-off points. Summary receiver operating characteristic curves and diagnostic odds ratios were pooled to assess diagnostic accuracy.

Results: Five studies, totaling 3,489 cases, were included. Sensitivity and specificity for the "Atypical and higher risk categories" considered positive were 60% (95% CI, 51-68%) and 87% (95% CI, 81-92%), respectively. For the "Suspicious for malignancy and higher risk categories" considered positive, sensitivity and specificity were 49% (95% CI, 40-58%) and 95% (95% CI, 92-97%), respectively. Sensitivity and specificity for the "Malignant" category considered positive for malignancy were 42% (95% CI, 33-52%) and 97% (95% CI, 92-99%), respectively. The pooled area under the curve ranged from 68 to 75% for each cut-off.

Conclusion: This meta-analysis underscores the PSC system's accuracy in reporting respiratory cytology. It highlights the diagnostic importance of the "Suspicious" and "Malignant" categories in identifying malignancy, and the utility of the "Atypical" category for initial screening. These findings support the PSC system's role in enhancing diagnostic accuracy and clinical decision-making in respiratory cytology.

Introduction: The application of artificial intelligence (AI) algorithms in serous fluid cytology is lacking due to the deficiency in standardized publicly available datasets. Here, we develop a novel public serous effusion cytology dataset. Furthermore, we apply AI algorithms on it to test its diagnostic utility and safety in clinical practice.

Methods: The work is divided into three phases. Phase 1 entails building the dataset based on the multitiered evidence-based classification system proposed by the International System (TIS) of serous fluid cytology along with ground-truth tissue diagnosis for malignancy. To ensure reliable results of future AI research on this dataset, we carefully consider all the steps of the preparation and staining from a real-world cytopathology perspective. In phase 2, we pay special consideration to the image acquisition pipeline to ensure image integrity. Then we utilize the power of transfer learning using the convolutional layers of the VGG16 deep learning model for feature extraction. Finally, in phase 3, we apply the random forest classifier on the constructed dataset.

Results: The dataset comprises 3,731 images distributed among the four TIS diagnostic categories. The model achieves 74% accuracy in this multiclass classification problem. Using a one-versus-all classifier, the fallout rate for images that are misclassified as negative for malignancy despite being a higher risk diagnosis is 0.13. Most of these misclassified images (77%) belong to the atypia of undetermined significance category in concordance with real-life statistics.

Conclusion: This is the first and largest publicly available serous fluid cytology dataset based on a standardized diagnostic system. It is also the first dataset to include various types of effusions and pericardial fluid specimens. In addition, it is the first dataset to include the diagnostically challenging atypical categories. AI algorithms applied on this novel dataset show reliable results that can be incorporated into actual clinical practice with minimal risk of missing a diagnosis of malignancy. This work provides a foundation for researchers to develop and test further AI algorithms for the diagnosis of serous effusions.