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BACKGROUND: This study evaluated the diagnostic effectiveness of the AIxURO platform, an artificial intelligence-based tool, to support urine cytology for bladder cancer management, which typically requires experienced cytopathologists and substantial diagnosis time. METHODS: One cytopathologist and two cytotechnologists reviewed 116 urine cytology slides and corresponding whole-slide images (WSIs) from urology patients. They used three diagnostic modalities: microscopy, WSI review, and AIxURO, per The Paris System for Reporting Urinary Cytology (TPS) criteria. Performance metrics, including TPS-guided and binary diagnosis, inter- and intraobserver agreement, and screening time, were compared across all methods and reviewers. RESULTS: AIxURO improved diagnostic accuracy by increasing sensitivity (from 25.0%-30.6% to 63.9%), positive predictive value (PPV; from 21.6%-24.3% to 31.1%), and negative predictive value (NPV; from 91.3%-91.6% to 95.3%) for atypical urothelial cell (AUC) cases. For suspicious for high-grade urothelial carcinoma (SHGUC) cases, it improved sensitivity (from 15.2%-27.3% to 33.3%), PPV (from 31.3%-47.4% to 61.1%), and NPV (from 91.6%-92.7% to 93.3%). Binary diagnoses exhibited an improvement in sensitivity (from 77.8%-82.2% to 90.0%) and NPV (from 91.7%-93.4% to 95.8%). Interobserver agreement across all methods showed moderate consistency (κ = 0.57-0.61), with the cytopathologist demonstrating higher intraobserver agreement than the two cytotechnologists across the methods (κ = 0.75-0.88). AIxURO significantly reduced screening time by 52.3%-83.2% from microscopy and 43.6%-86.7% from WSI review across all reviewers. Screening-positive (AUC+) cases required more time than negative cases across all methods and reviewers. CONCLUSIONS: AIxURO demonstrates the potential to improve both sensitivity and efficiency in bladder cancer diagnostics via urine cytology. Its integration into the cytopathological screening workflow could markedly decrease screening times, which would improve overall diagnostic processes.

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In today's medical landscape, social media (SoMe) platforms have expanded their reach beyond mere communication and entertainment, making a significant impact in the pathology field, including cytopathology. In recent years, SoMe platforms have become increasingly adopted by cytopathologists, facilitating continued education, professional networking, enhancing patient engagement, and entertainment. This adoption has influenced the professional growth of cytopathologists, and at its best, has led to the establishment of a robust professional online presence and ultimately contributed to leadership positions, fellowship opportunities, and academic promotions. Moreover, the integration of SoMe into the academic field has shown a profound impact on the visibility of academic journals and has provided a platform for lower-impact factor journals to expand their reach, ultimately increasing article citation rates and positively contributing to journal impact factor growth. SoMe platforms created a modern avenue for conference networking that has revolutionized knowledge dissemination and enhanced real-time engagement. The advantages of SoMe have extended to a global scale, positively enhancing professional expertise sharing, facilitating effective communication and teleconsultation worldwide, and reaching developing countries. Drawing insights from the recent medical literature and the practical insight from the experts' personal experience, this article provides a comprehensive review of how SoMe and cytopathology intersect to create new opportunities, facilitating informed discussions, global collaboration, and advancements in the field of cytopathology. This article also delves into the challenges surrounding SoMe platform navigation and addresses ethical and regulatory concerns, providing guidelines on what to post and what not to post on SoMe platforms.

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INTRODUCTION: Digitizing cytology slides presents challenges because of their three-dimensional features and uneven cell distribution. While multi-Z-plane scan is a prevalent solution, its adoption in clinical digital cytopathology is hindered by prolonged scanning times, increased image file sizes, and the requirement for cytopathologists to review multiple Z-plane images. METHODS: This study presents heuristic scan as a novel solution, using an artificial intelligence (AI)-based approach specifically designed for cytology slide scanning as an alternative to the multi-Z-plane scan. Both the 21 Z-plane scan and the heuristic scan simulation methods were used on 52 urine cytology slides from three distinct cytopreparations (Cytospin, ThinPrep, and BD CytoRich™ [SurePath]), generating whole-slide images (WSIs) via the Leica Aperio AT2 digital scanner. The AI algorithm inferred the WSI from 21 Z-planes to quantitate the total number of suspicious for high-grade urothelial carcinoma or more severe cells (SHGUC+) cells. The heuristic scan simulation calculated the total number of SHGUC+ cells from the 21 Z-plane scan data. Performance metrics including SHGUC+ cell coverage rates (calculated by dividing the number of SHGUC+ cells identified in multiple Z-planes or heuristic scan simulation by the total SHGUC+ cells in the 21 Z-planes for each WSI), scanning time, and file size were analyzed to compare the performance of each scanning method. The heuristic scan's metrics were linearly estimated from the 21 Z-plane scan data. Additionally, AI-aided interpretations of WSIs with scant SHGUC+ cells followed The Paris System guidelines and were compared with original diagnoses. RESULTS: The heuristic scan achieved median SHGUC+ cell coverage rates similar to 5 Z-plane scans across three cytopreparations (0.78-0.91 vs. 0.75-0.88, p = 0.451-0.578). Notably, it substantially reduced both scanning time (137.2-635.0 s vs. 332.6-1,278.8 s, p < 0.05) and image file size (0.51-2.10 GB vs. 1.16-3.10 GB, p < 0.05). Importantly, the heuristic scan yielded higher rates of accurate AI-aided interpretations compared to the single Z-plane scan (62.5% vs. 37.5%). CONCLUSION: We demonstrated that the heuristic scan offers a cost-effective alternative to the conventional multi-Z-plane scan in digital cytopathology. It achieves comparable SHGUC+ cell capture rates while reducing both scanning time and image file size, promising to aid digital urine cytology interpretations with a higher accuracy rate compared to the conventional single (optimal) plane scan. Further studies are needed to assess the integration of this new technology into compatible digital scanners for practical cytology slide scanning.

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Fine-needle aspiration cytology (FNAC) is a versatile diagnostic procedure uniquely suited for tissue biopsy of breast carcinomas and axillary metastases and/or recurrences. With the expanding treatment options and accompanying theragnostic tests, it is crucial to recognize the developments on ancillary testing and digital cytopathology techniques related to aspiration cytology of metastatic breast carcinoma. In this review, we aim to summarize and update the evidence of immunocytochemistry, for the detection of carcinoma cells (epithelial markers), confirmation of breast primary (breast-specific markers), assessment of surrogate immunostains (hormone receptors, ki-67 proliferative index and HER2) and theragnostic biomarkers, with discussion on potential diagnostic pitfalls, followed by the application of molecular tests, and digital cytopathologic techniques for assessing metastatic breast carcinoma in cytology.

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Background: Acquiring well-focused digital images of cytology slides with scanners can be challenging due to the 3-dimensional nature of the slides. This study evaluates performances of whole-slide images (WSIs) obtained from 2 different cytopreparations by 2 distinct scanners with 3 focus modes. Methods: Fourteen urine specimens were collected from patients with urothelial carcinoma. Each specimen was equally divided into 2 portions, prepared with Cytospin and ThinPrep methods and scanned for WSIs using Leica (Aperio AT2) and Hamamatsu (NanoZoomer S360) scanners, respectively. The scan settings included 3 focus modes (default, semi-auto, and manual) for single-layer scanning, along with a manual focus mode for 21 Z-layers scanning. Performance metrics were evaluated including scanning success rate, artificial intelligence (AI) algorithm-inferred atypical cell numbers and coverage rate (atypical cell numbers in single or multiple Z-layers divided by the total atypical cell numbers in 21 Z-layers), scanning time, and image file size. Results: The default mode had scanning success rates of 85.7% or 92.9%, depending on the scanner used. The semi-auto mode increased success to 92.9% or 100%, and manual even further to 100%. However, these changes did not affect the standardized median atypical cell numbers and coverage rates. The selection of scanners, cytopreparations, and Z-stacking influenced standardized median atypical cell numbers and coverage rates, scanning times, and image file sizes. Discussion: Both scanners showed satisfactory scanning. We recommend using semi-auto or manual focus modes to achieve a scanning success rate of up to 100%. Additionally, a minimum of 9-layer Z-stacking at 1 µm intervals is required to cover 80% of atypical cells. These advanced focus methods do not impact the number of atypical cells or their coverage rate. While Z-stacking enhances the AI algorithm's inferred quantity and coverage rates of atypical cells, it simultaneously results in longer scanning times and larger image file sizes.

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BACKGROUND: After a series of standardized reporting systems in cytopathology, the Sydney system was recently introduced to address the need for reproducibility and standardization in lymph node cytopathology. Since then, the risk of malignancy for the categories of the Sydney system has been explored by several studies, but no studies have yet examined the interobserver reproducibility of the Sydney system. METHODS: The authors assessed interobserver reproducibility of the Sydney system on 85 lymph node fine-needle aspiration cytology cases reviewed by 15 cytopathologists from 12 institutions in eight different countries, resulting in 1275 diagnoses. In total, 186 slides stained with Diff-Quik, Papanicolaou, and immunocytochemistry were scanned. A subset of the cases included clinical data and results from ultrasound examinations, flow cytometry immunophenotyping, and fluorescence in situ hybridization analysis. The study participants assessed the cases digitally using whole-slide images. RESULTS: Overall, the authors observed an almost perfect agreement of cytopathologists with the ground truth (median weighted Cohen κ = 0.887; interquartile range, κ = 0.210) and moderate overall interobserver concordance (Fleiss κ = 0.476). There was substantial agreement for the inadequate and malignant categories (κ = 0.794 and κ = 0.729, respectively), moderate agreement for the benign category (κ = 0.490), and very slight agreement for the suspicious (κ = 0.104) and atypical (κ = 0.075) categories. CONCLUSIONS: The Sydney system for reporting lymph node cytopathology shows adequate interobserver concordance. Digital microscopy is an adequate means to assess lymph node cytopathology specimens.

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INTRODUCTION: Many institutions have cytopathology case archives for education. Unfortunately, these slides deteriorate over time and have limited accessibility. Whole slide imaging (WSI) can overcome these limitations. However, suboptimal image quality and scanning effort are barriers. MATERIALS AND METHODS: We selected 123 slides from cytopathology study sets for WSI scanning at 400x magnification without z-stacking. The Ventana DP 200 scanner and Virtuoso software were used. Slides were scanned in 2 rounds: the first round of slides was prepared for scanning with light cleaning, and the second round was performed only on slides that had unacceptable WSI quality after thorough cleaning. Slides were assessed with a 4-tier grading system created by the authors. Time to scan each slide was recorded. RESULTS: Within the first round, 96 of 123 (78%) slides scanned were determined to be of acceptable quality. After the second round of scanning, in total, 118 of 123 (95.9%) slides were determined to be of acceptable quality. The average time needed to scan each slide was 213 seconds. CONCLUSIONS: The majority of slides scanned were of acceptable quality in the first round of scanning. After cleaning and rescanning, nearly every slide investigated was of acceptable quality. The primary objective is to provide other institutions that may be considering a similar project a benchmark so that they know what to expect in terms of slide scan success rate and the amount of time needed to digitize slides for educational archiving. This pilot study demonstrates the feasibility of using WSI for cytology education cases.

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BACKGROUND: High-risk human papilloma virus (HR HPV) testing and liquid-based cytology are used for primary cervical screening. Digital cytology, based on whole-slide scanned samples, is a promising technique for teaching and diagnostic purposes. The aim of our study was to evaluate the interobserver and intraobserver variation in low-grade squamous lesions, HR HPV status bias, and the use of whole-slide scanned digital cervical cytology slides. METHODS: Fifteen expert cytopathologists evaluated 71 digitalized ThinPrep slides (31 atypical squamous cells of undetermined significance [ASC-US], 21 negative for intraepithelial lesion or malignancy, and 19 low-grade squamous intraepithelial lesion cases). HR HPV data were accessible only in the second round. RESULTS: In interobserver analysis, Kendall's coefficient of concordance was 0.52 in the first round and 0.58 in the second round. Fleiss' kappa values were 0.29 in the first round and 0.31 in the second round. In the ASC-US category, Fleiss kappa increased from 0.19 to 0.22 in the second round and the increase was even higher expressed by Kendall's coefficient: from 0.42 to 0.52. In intraobserver analysis, personal scores were higher in the second round. CONCLUSIONS: The interobserver and intraobserver variability in low-grade squamous lesions was within fair agreement values in the present study, in line with previous works. The comparison of two rounds showed that expert cytopathologists are generally unbiased by the knowledge of HR HPV data, but that being informed of the HR HPV status leads to a better agreement. Stain quality and back discomfort were highlighted as factors affecting digital cytopathology use.

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This short article describes the method of digital cytopathology using Z-stack scanning with or without extended focusing. This technology is suitable to observe such thick clusters as adenocarcinoma on cytologic specimens. Artificial intelligence (AI) has been applied to histological images, but its application on cytologic images is still limited. This article describes our attempt to apply AI technology to cytologic digital images. For molecular analysis, cytologic materials, such as smear, LBC, and cell blocks, have been successfully used for targeted single gene detection and multiplex gene analysis with next-generation sequencing. As a future perspective, the system can be connected to full automation by combining digital cytopathology with AI application to detect target cancer cells and to perform molecular analysis. The literature review is updated according to the subjects.

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OBJECTIVE: The aim of this work was to raise awareness of problems using digital applications for examining, teaching, and applying telecytology at King Abdulaziz Medical City (KAMC), Riyadh, Saudi Arabia; University of Nebraska Medical Center (UNMC), Omaha, NE, USA; and University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, USA. The objective was to rationalize problems and propose alternative digital approaches. STUDY DESIGN: We sought to identify solutions to improve the following: (a) interpretive examination scores at KAMC for complex cytological templates (i.e., high-grade squamous intraepithelial lesions [HSIL]) when using static digital images (SDI) of cells in regions of interest (ROI); (b) visualization of cells in 3D clusters when teaching at UNMC using 2D and 3D whole-slide imaging (WSI); and (c) visualization of cells through streaming telecytology at UPMC. RESULTS: Composite SDI (CSDI) improved test scores for complex interpretations (i.e., HSIL) by converging diagnostic criteria from multiple ROI. Multiplane focusing through z-stacked WSI facilitated the teaching of cytological entities characterized by 3D cell clusters and consultative telecytology through robotic cell analysis. CONCLUSIONS: Adequately visualized cytomorphology and multiplane focusing are essential for virtual cytopathology examinations, teaching, or consultative telecytology. Visualization of diagnostic criteria through 2D or 3D imaging is critical. Panoptiq panoramic WSI with integrated z-stacked video clips enables optimal applied telecytology.

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The advancements in the fields of technology and networking have revolutionized the world including the fields of medicine and dentistry. Telemedicine and its various branches provide a broad platform to medical professionals for consultations and investigations and can also act as a valuable educational aid. This review highlights the components, methods employed, clinical applications, advantages, disadvantages of telepathology and telecytology.