Interobserver variability in cytopathology: How much do we agree?

Interobserver variability remains a major challenge for cytopathologists despite the development of standardized reporting and classification systems. Indeed, whereas moderate-to-good interobserver agreement is generally achievable when the differential diagnosis between benign and malignant entities is straightforward, high levels of variability make the diagnostic interpretation of atypical and suspicious samples not consistent. This review explores the landscape of interobserver agreement in cytopathology across different anatomical sites.

[What contribution can make artificial intelligence to urinary cytology?]

Urinary cytology using the Paris system is still the method of choice for screening high-grade urothelial carcinomas. However, the use of the objective criteria described in this terminology shows a lack of inter- and intra-observer reproducibility. Moreover, if its sensitivity is excellent on instrumented urine, it remains insufficient on voided urine samples. Urinary cytology appears to be an excellent model for the application of artificial intelligence to improve performance, since the objective criteria of the Paris system are defined at cellular level, and the resulting diagnostic approach is presented in a highly "algorithmic" way. Nevertheless, there is no commercially available morphological diagnostic aid, and very few predictive devices are still undergoing clinical validation. The analysis of different systems using artificial intelligence in urinary cytology rises clear prospects for mutual contributions.

Evaluating Urine Cytology Slide Digitization Efficiency: A Comparative Study Using an Artificial Intelligence-Based Heuristic Scanning Simulation and Multiple Z-Plane Scanning

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.

Deep-learning-assisted snapshot optical tomography for microscopic volume prediction: a simulation study

In this simulation study, we demonstrate fast-yet-accurate volume measurement of microscopic objects by combining snapshot optical tomography and deep learning. Snapshot optical tomography simultaneously collects a multitude of projection images and thus can perform 3D imaging in a single snapshot. However, as with other wide-field microscopy techniques, it suffers from the missing-cone problem, which can seriously degrade the quality of 3D reconstruction. We use deep learning to generate a volume prediction from 2D projection images bypassing the 3D reconstruction.

Atypical urothelial cells classified according to the Paris System for Reporting Urinary Cytology: A 2-year experience with histological correlation from a Finnish tertiary care center-low rate and high risk of malignancy

BACKGROUND

The Paris System for Reporting Urinary Cytology (TPS) was issued to shift the focus of urine cytology to high-grade lesions to increase the diagnostic accuracy of urine cytology. The aim of this study was to evaluate the power of TPS in the atypical urothelial cells (AUC) category with histological correlation and follow-up.

METHODS

The data cohort consisted of 3741 voided urine samples collected during a 2-year period between January 2017 and December 2018. All samples were prospectively classified using TPS. This study focuses on the subset of 205 samples (5.5%) classified as AUC. All cytological and histological follow-up data were analyzed until 2019, and the time between each sampling was documented.

RESULTS

Of the 205 AUC cases, cytohistological correlation was possible in 97 (47.3%) cases. Of these, 36 (12.7%) were benign in histology, 27 (13.2%) were low-grade urothelial carcinomas, and 34 (16.6%) were high-grade urothelial carcinomas. Overall, the risk of malignancy was 29.8% for all cases in the AUC category, and 62.9% in the histologically confirmed cases. The risk of high-grade malignancy was 16.6% in all the AUC category samples and 35.1% in the histological follow-up group.

CONCLUSIONS

The performance of 5.5% AUC cases is considered good and within the limits proposed by TPS. TPS is widely accepted by cytotechnologists, cytopathologists, and clinicians; it improves communication and patient management.

Perceptions of Paris: an international survey in preparation for The Paris System for Reporting Urinary Cytology 2.0 (TPS 2.0)

INTRODUCTION

An international panel of experts in the field of urinary cytopathology conducted a survey, supported by the American Society of Cytopathology, to seek opinions, gather evidence, and identify practice patterns regarding urinary cytology before and after the introduction of The Paris System for Reporting Urinary Cytopathology (TPS). Results from this survey were utilized in the development of the second edition of TPS (TPS-2.0).

MATERIALS AND METHODS

The study group, originally formed during the 2013 International Congress of Cytology, reconvened at the 2019 annual meeting of the American Society of Cytopathology. To prepare for the second edition of TPS, the group generated a survey that included 43 questions related to the taxonomy and practice of urinary cytology.

RESULTS

A total of 523 participant responses were collected, and 451 from 54 countries passed a qualifying screen. Three hundred ninety-four participants provided information about their work settings. Eighty-two percent (218/266) of responding participants use TPS. One hundred sixty-eight people who responded on their urinary cytology atypia rates reported an average decrease from 21.6% to 16%. Over three fourths of participants felt that the same criteria should be used for upper and lower tract interpretations and for instrumented and voided samples. There were varied opinions on addressing atypical squamous cells and suggestions for an expanded discussion of the issue to be included in TPS 2.0.

CONCLUSIONS

Results of the survey demonstrate strong support for TPS and show a decreased self-reported atypia rate in the laboratories using TPS. The majority of participants related that the criteria put forth for the reporting categories were user-friendly and applied with relative ease. The comment section of the survey included suggestions from the participants for further improvement of TPS. Results of this survey have been useful in fine-tuning and advancing TPS. They were considered along with recent literature to generate the second edition of TPS.

Collagen Obtained from Leather Production Waste Provides Suitable Gels for Biomedical Applications

Collagen and its derivates are typically obtained by extracting them from fresh animal tissues. Lately, however, there has been an increased interest in obtaining collagen from other sources, such as waste material, because of the growing trend to replace synthetic materials with sustainable, natural counterparts in various industries, as well as to ensure a rational waste revalorization. In this paper, collagen was obtained from non-tanned waste of leather production, taken at different stages of the production process: limed pelt, delimed pelt, and fleshings. A stepwise extraction through acid hydrolysis in 0.5 M acetic acid and subsequent precipitation with NaCl lead to collagen-containing protein extracts. The highest collagen yield was achieved in extracts based on delimed pelt (2.3% m/m after a first extraction round, and an additional 1.4% m/m after the second round). Hyp/Hyl molar ratios of 10.91 in these extracts suggest the presence of type I collagen. Moreover, gels based on these collagen extracts promote adhesion and spreading of HEK293 cells, with cells grown on collagen from delimed pelt showing a larger nuclear and cell expansion than cells grown on traditional bovine tendon atelocollagen. This suggests that these collagen gels are promising natural biomedical carriers and could be used in a wide range of medical and cosmetic applications.

Large-scale longitudinal comparison of urine cytological classification systems reveals potential early adoption of The Paris System criteria

INTRODUCTION

Urine cytology is used to screen for urothelial carcinoma in patients with hematuria or risk factors (eg, smoking, industrial dye exposure) and is an essential clinical triage and longitudinal monitoring tool for patients with known bladder cancer. However, urine cytology is semisubjective and thus susceptible to issues including specimen quality, interobserver variability, and "hedging" towards equivocal ("atypical") diagnoses. These factors limit the predictive value of urine cytology and increase reliance on invasive procedures (cystoscopy). The Paris System for Reporting Urine Cytology (TPS) was formulated to provide more quantitative/reproducible endpoints with well-defined criteria for urothelial atypia. TPS is often compared to other assessment techniques to justify its adoption. TPS results in decreased use of the atypical category and better reproducibility. Previous reports comparing diagnoses pre- and post-TPS have not considered temporal differences between diagnoses made under prior systems and TPS. By aggregating across time, studies may underestimate the magnitude of differences between assessment methods.

MATERIALS AND METHODS

We conducted a large-scale longitudinal reassessment of urine cytology using TPS criteria from specimens collected from 2008 to 2018, prior to the mid-2018 adoption of TPS at an academic medical center.

RESULTS

Findings indicate that differences in atypical assignment were largest at the start of the period and these differences progressively decreased towards insignificance just prior to TPS implementation.

CONCLUSIONS

This finding suggests that cytopathologists had begun to utilize the quantitative TPS criteria prior to official adoption, which may more broadly inform adoption strategies, communication, and understanding for evolving classification systems in cytology.

Evaluation of an artificial intelligence algorithm for assisting the Paris System in reporting urinary cytology: A pilot study

BACKGROUND

The Paris System for Reporting Urinary Cytology (TPS) has been shown to improve bladder cancer diagnosis. Advances in artificial intelligence (AI) may assist and improve the clinical workflow by applying TPS in routine diagnostic services.

METHODS

A deep-learning-based algorithm was developed to identify urothelial cancer candidate cells using whole-slide images (WSIs). In the testing cohort, 131 urine cytology slides were retrospectively retrieved and analyzed using this AI algorithm. The authors compared the performance of one cytopathologist and two cytotechnologists using AI-assisted digital urine cytology. Then, the AI-assisted WSIs were evaluated in the clinical workflow. The cytopathologist first made a diagnosis by reviewing the AI-inferred WSIs and quantitative data (nuclear-to-cytoplasmic ratio and nuclear size) for each sample. After a washout period, the same cytopathologist made a diagnosis for the same samples using direct microscopy. All diagnosis results were compared with the expert panel consensus.

RESULTS

The AI-assisted diagnosis by the two cytotechnologists and the one cytopathologist demonstrated performance results that were comparable to the expert panel consensus (sensitivity, 79.5% and 82.1% vs. 92.3%, respectively; specificity, 100% and 98.9% vs. 100%, respectively). Furthermore, the performance of the AI-assisted WSIs compared with the microscopic diagnosis by the cytopathologist demonstrated superior sensitivity (92.3% vs. 87.2%) and negative predictive value (96.8% vs. 94.8%). In addition, the AI-assisted reporting demonstrated near perfect agreement with the expert panel consensus (κ = 0.944) and the microscopic diagnosis (κ = 0.862).

CONCLUSIONS

The AI algorithm developed by the authors effectively assisted TPS-based reporting by providing AI-inferred WSIs and quantitative data.

Cyto-histo correlation and false-negative urine: Before and after the Paris system for reporting urinary cytology

BACKGROUND

The impact of implementing the Paris system (TPS) on the rate of discrepant cases in the negative for high-grade urothelial carcinoma (NHGUC) category that had a subsequent diagnosis of high-grade urothelial carcinoma (HGUC) on histology is not well studied.

METHODS

We adopted TPS in May 2019. We searched discrepant cases with negative urine cytology 2017-2019 in our cyto-histo correlation database. The urine cytology and follow-up biopsy/resection were reviewed by a cytopathologist who also did Genitourinary (GU) Pathology subspecialty sign-out. Voided urine and instrumented urine were included in this study.

RESULTS

There were total of 70 discrepant cases with negative cytology interpretation but HGUC on the subsequent biopsy or resected specimen. Following the TPS criteria, the rate of discrepant negative cytology cases increased from 6 cases between January 2017 and May 2019 to 64 cases after May 2019 when we adopted TPS. There were 2 discrepant negative cases in 2017, 3 cases in 2018, and 65 cases in 2019. Out of 65 cases in 2019, 64 cases were identified after May 2019. Additional 55 urine cytology slides were reviewed according to the TPS criteria, of which, the diagnoses remained unchanged in 45 (82%) cases and 10 (19%) cases were reassigned to either atypical or suspicious categories. The discrepancy was noted more on the instrumented urine and the upper tract urine. However, the false-negative rate rose faster in voided urine and lower tract urine. The risk of HGUC with the category of NHGUC was 0.03% in 2017, 0.05% in 2018, and 1.06% in 2019 at our institution. The increase in false-negative rate could not be attributed to a single cytopathologist.

CONCLUSION

After adopting TPS for reporting urine cytology, there was an increase in HGUC from negative urine cytology which was subsequently confirmed on histology as cases of HGUC. The quality control of negative urines could be important monitoring the process when implementing TPS.

We'll always have Paris The Paris System for Reporting Urinary Cytology 2022

Following the amazing acceptance of The Paris System for Reporting Urinary Cytology (TPS), the second edition (TPS 2.0) was inevitable. Based on new studies since the publication of the first edition, diagnostic criteria are refined, and pitfalls discussed. In addition to reinforcing the mandate that the focus of diagnostic urinary cytology is the detection of high-grade urothelial carcinoma, other issues are addressed. Low-grade lesions are included in the category of negative for high-grade urothelial cancer. The rationale for that decision is strongly supported by evidence from the authors' experiences as well as the recent literature. A new chapter on urine cytology of the upper tract, a rarely addressed topic, explores the challenges involved. Furthermore, the issue of cellular degeneration is discussed in the criteria of all diagnostic categories. Most importantly, data defining the risk of high-grade malignancy (ROHM) for each diagnostic category informs clinical management. The 65 authors are recognized authorities from 33 countries, attesting to the global impact of TPS 2.0.

Indeterminate atypia in urinary tract cytology: Does it really matter?

The study of atypia in urinary cytology has been ongoing for decades but most studies have focused primarily on test performance in patients with concurrent biopsies and/or limited follow-up periods. While these data are useful, many studies fail to consider patient factors that may alter the pretest probability, which can subsequently affect test performance. An isolated diagnosis of malignancy in urinary cytology usually has a high positive predictive value and allows a urologist to conduct a rigorous workup of the patient to establish a tissue diagnosis. However, it is less certain how an atypical diagnosis impacts patient care, given that many patients have a history of bladder cancer and are already under surveillance with cystoscopy at regular screening intervals. Furthermore, a discrete negative urine cytology is unlikely to allow a patient to forego a cystoscopy procedure due to limitations in the sensitivity of urine cytology. Over the last several years, the introduction of The Paris System for Reporting Urinary Cytology (TPS) has improved the predictive value of atypical diagnoses, but additional studies are needed to evaluate the performance of these diagnoses in specific clinical situations. Such data could better inform urologists on how to manage patients with atypical diagnoses. This review discussed the diagnosis of atypia in urinary cytology and the impact of such a diagnosis in various clinical contexts.

Comparison of Diagnostic Performances of Urine Cytology Before and After the Use of The Paris System Criteria: An Institutional Experience from Turkey

Background:

Urine cytology remains to be the test of choice in the detection of high-grade urothelial carcinomas (HGUC) due to its favorable sensitivity. However, a significant rate of cases is reported under atypical/indeterminate categories, which result in a decrease in its specificity. Providing standardized cytologic criteria, one of the aims of The Paris System (TPS) is to reduce the use of indeterminate diagnoses and provide a higher predictive value in these categories.

Aims:

We compared the diagnostic performances of TPS and our original reporting system, and also investigated the interobserver reproducibility of the cytologic criteria used.

Materials and Methods:

A total of 386 urine samples were reviewed retrospectively. Original cytologic diagnoses have been made using similar cytologic features proposed by TPS. All slides were recategorized after the use of the cytologic criteria as described by TPS guideline.

Results:

After TPS, specificity of the test increased from 39.6% to 63.5, sensitivity decreased from 92.5% to 88.8%, and diagnostic accuracy increased from 63.6% to 75%. The use of negative category increased threefold. Frequencies of indeterminate categories of atypical urothelial cells (AUC) and suspicious for HGUC (SHGUC) decreased by 36% and 56.5%, respectively. A subsequent detection of HGUC after AUC and SHGUC categories increased by 38% and 64%, respectively. Interobserver agreement for TPS categorization was 39%.

Conclusions:

TPS improved diagnostic accuracy of urine cytology by reducing the use of indeterminate categories, and resulted in increase in their predictive value for subsequent diagnosis of HGUC. However, reproducibility of diagnostic categories seemed to be imperfect.

Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness

Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitating the metastatic cascade. Metastatic lesions often exhibit a similar epithelial-like state to that of the primary tumour, in particular, by forming carcinoma cell clusters via E-cadherin-mediated junctional complexes. However, the factors enabling mesenchymal-like micrometastatic cells to resume growth and reacquire an epithelial phenotype in the target organ microenvironment remain elusive. In this study, we developed a workflow using image-based cell profiling and machine learning to examine morphological, contextual and molecular states of individual breast carcinoma cells (MDA-MB-231). MDA-MB-231 heterogeneous response to the host organ microenvironment was modelled by substrates with controllable stiffness varying from 0.2kPa (soft tissues) to 64kPa (bone tissues). We identified 3 distinct morphological cell types (morphs) varying from compact round-shaped to flattened irregular-shaped cells with lamellipodia, predominantly populating 2-kPa and >16kPa substrates, respectively. These observations were accompanied by significant changes in E-cadherin and vimentin expression. Furthermore, we demonstrate that the bone-mimicking substrate (64kPa) induced multicellular cluster formation accompanied by E-cadherin cell surface localisation. MDA-MB-231 cells responded to different substrate stiffness by morphological adaptation, changes in proliferation rate and cytoskeleton markers, and cluster formation on bone-mimicking substrate. Our results suggest that the stiffest microenvironment can induce MET.

An image-based flow cytometric approach to the assessment of the nucleus-to-cytoplasm ratio

The nucleus-to-cytoplasm ratio (N:C) can be used as one metric in histology for grading certain types of tumor malignancy. Current N:C assessment techniques are time-consuming and low throughput. Thus, in high-throughput clinical contexts, there is a need for a technique that can assess cell malignancy rapidly. In this study, we assess the N:C ratio of four different malignant cell lines (OCI-AML-5-blood cancer, CAKI-2-kidney cancer, HT-29-colon cancer, SK-BR-3-breast cancer) and a non-malignant cell line (MCF-10A -breast epithelium) using an imaging flow cytometer (IFC). Cells were stained with the DRAQ-5 nuclear dye to stain the cell nucleus. An Amnis ImageStreamX® IFC acquired brightfield/fluorescence images of cells and their nuclei, respectively. Masking and gating techniques were used to obtain the cell and nucleus diameters for 5284 OCI-AML-5 cells, 1096 CAKI-2 cells, 6302 HT-29 cells, 3159 SK-BR-3 cells, and 1109 MCF-10A cells. The N:C ratio was calculated as the ratio of the nucleus diameter to the total cell diameter. The average cell and nucleus diameters from IFC were 12.3 ± 1.2 μm and 9.0 ± 1.1 μm for OCI-AML5 cells, 24.5 ± 2.6 μm and 15.6 ± 2.1 μm for CAKI-2 cells, 16.2 ± 1.8 μm and 11.2 ± 1.3 μm for HT-29 cells, 18.0 ± 3.7 μm and 12.5 ± 2.1 μm for SK-BR-3 cells, and 19.4 ± 2.2 μm and 10.1 ± 1.8 μm for MCF-10A cells. Here we show a general N:C ratio of ~0.6-0.7 across varying malignant cell lines and a N:C ratio of ~0.5 for a non-malignant cell line. This study demonstrates the use of IFC to assess the N:C ratio of cancerous and non-cancerous cells, and the promise of its use in clinically relevant high-throughput detection scenarios to supplement current workflows used for cancer cell grading.

Urine cell image recognition using a deep-learning model for an automated slide evaluation system

OBJECTIVES

To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant).

PATIENTS AND METHODS

We collected 195 urine cytology slides from consecutive patients with a histologically confirmed diagnosis of urothelial cancer (between January 2016 and December 2017). Two certified cytotechnologists independently evaluated and labelled each slide; 4637 cell images with concordant diagnoses were selected, including 3128 benign cells (negative), 398 atypical cells, and 1111 cells that were malignant or suspicious for malignancy (positive). This pathologically confirmed labelled dataset was used to represent the ground truth for AI training/validation/testing. Customized CutMix (CircleCut) and Refined Data Augmentation were used for image processing. The model architecture included EfficientNet B6 and Arcface. We used 80% of the data for training and validation (4:1 ratio) and 20% for testing. Model performance was evaluated with fivefold cross-validation. A receiver-operating characteristic (ROC) analysis was used to evaluate the binary classification model. Bayesian posterior probabilities for the AI performance measure (Y) and cytotechnologist performance measure (X) were compared.

RESULTS

The area under the ROC curve was 0.99 (95% confidence interval [CI] 0.98-0.99), the highest accuracy was 95% (95% CI 94-97), sensitivity was 97% (95% CI 95-99), and specificity was 95% (95% CI 93-97). The accuracy of AI surpassed the highest level of cytotechnologists for the binary classification [Pr(Y > X) = 0.95]. AI achieved >90% accuracy for all cell subtypes. In the subgroup analysis based on the clinicopathological characteristics of patients who provided the test cells, the accuracy of AI ranged between 89% and 97%.

CONCLUSION

Our novel AI classification system for urine cytology successfully classified all cell subtypes with an accuracy of higher than 90%, and achieved diagnostic accuracy of malignancy superior to the highest level achieved by cytotechnologists.

Quantitative cytomorphological comparison of SurePath and ThinPrep liquid-based cytology using high-grade urothelial carcinoma cells

OBJECTIVE

In The Paris System for Reporting Urinary Cytology (TPS), the important cytomorphological features for diagnosing high-grade urothelial carcinoma (HGUC) are a nuclear-to-cytoplasmic (N:C) ratio exceeding 0.7, hyperchromasia, coarse chromatin, and irregular nuclear borders. However, quantitative cytomorphological assessments of HGUC cells using SurePath slides are rare. Therefore, we evaluated HGUC cells on SurePath slides quantitatively using a digital image analysis system and compared these data with ThinPrep data.

METHODS

The same urine samples were divided into two aliquots and used to prepare SurePath and ThinPrep slides. We used ImageJ to measure the N:C ratio, hyperchromasia, and irregular nuclear borders for HGUC cells on SurePath and ThinPrep slides.

RESULTS

The total number of analysed HGUC cells on SurePath slides was 981, versus 889 on ThinPrep slides. Hyperchromasia and irregular nuclear borders were significantly more severe on SurePath than on ThinPrep slides. Conversely, the N:C ratio did not differ between the methods. Additionally, HGUC cells with N:C ratios exceeding 0.7 were present on almost all slides for both methods.

CONCLUSIONS

Our data indicated the reasonableness of using the N:C ratio as the major criterion for TPS on both SurePath and ThinPrep slides, and an N:C ratio cut-off of 0.7 as suitable for identifying HGUC cells. However, the severity of hyperchromasia and irregular nuclear borders differed between the processing methods.

The predictive value of positive and suspicious urine cytology: Are they different?

BACKGROUND

Urine cytology evaluation is an effective test in the detection of high-grade urothelial carcinoma (HGUC). While the guideline distinguishes the 2 categories: "positive for HGUC" (PHGUC) and "suspicious for HGUC" (SHGUC), the association between these categories with their subsequent follow-up biopsies remains unclear. This study aims to determine and compare the positive predictive value (PPV) of the specimens in PHGUC and SHGUC categories with their respective histologic diagnoses.

METHODS

During the period of 03/01/2008 to 07/31/2018, urine cytology cases diagnosed as PHGUC and SHGUC with subsequent bladder biopsy within 12 months were retrieved. All cases were correlated with first biopsy obtained during 12 months of cytology specimen. Biopsy result with HGUC, carcinoma in situ, or non-urothelial carcinoma diagnoses were considered as concordance.

RESULTS

378 cases (229 SHGUC and 149 PHGUC) were identified from 263 patients. For the 229 SHGUC cases, the PPV was 72% (n = 166) and for the 149 PHGUC cases, the PPV was 85% (n = 127). While both categories have high PPV, they are statistically significant (p < 0.0001). Additionally, 33 cases were found to have low-grade urothelial carcinoma (LGUC), constituting a portion of discordant results.

CONCLUSION

PHGUC and SHGUC categories are both associated with a high risk of malignancy, however, there is a statistically significant difference between them in our study, supporting the PSRUC guidelines of two separate categories. In instances when urine cytology is discordant with biopsy results, further investigation and clinical follow up is warranted. LGUC appears to remain a common pitfall especially in the suspicious category.

Interobserver reproducibility of The Paris System of Reporting Urine Cytology on cytocentrifuged samples

BACKGROUND

The Paris System of Reporting Urine Cytology aims to screen samples for HGUC and to provide a universally acceptable reporting format for urine cytology specimens. However, studies detailing the reproducibility of this system, especially on cyto-centrifuge preparations, are lacking.

METHODS

149 voided urine samples received in Department of Pathology were reviewed independently by five cytopathologists. To estimate the overall agreement, Gwet's AC and AC1statistics between each pair of raters were used. To measure the random error component, polychoric correlations were used. To assess the systematic error, Friedman test was used.

RESULTS

There was moderately good inter-rater agreement between the raters. Gwets AC2 ranged between 0.67 and 0.89 for the classification of the cases once the sample was found adequate for assessment, while the Gwet's AC1 ranged between 0.61 and 0.94 in assessing for adequacy. There were significant systematic differences between raters in their thresholds for the different categories as well as in differentiating between an adequate and inadequate sample (P value by Friedman test <.001). The association between pathologists was moderately high (polychoric correlations ranging from 0.67 to 0.93). In the majority (108 of 149, 72.5%) of the cases, the range of differences between raters were of one category or less, suggesting satisfactory agreement, but having large disagreements in minority.

CONCLUSION

The interobserver reproducibility for the Paris System is moderately good, and is suitable for adoption. It is limited by the lack of agreement as to what constitutes an adequate specimen and differing threshold for categorizing the lesions in differing groups.

Methylation study of the Paris system for reporting urinary (TPS) categories

AIMS

Bladder EpiCheck is one of several urinary tests studied to identify bladder tumours and analyses 15 methylation biomarkers determining bladder cancer presence on the basis of methylation profile.

METHODS

374 patients diagnosed with high-grade non-muscle invasive bladder cancer were treated and followed for 1 year with voided urine cytology and white-light cystoscopy and biopsies according to European Association of Urology Guidelines. 268 cases were diagnosed with high-grade papillary carcinoma, while 106 cases were carcinoma in situ. Bladder EpiCheck test was performed together with cytology in all cases.

RESULTS

Comparing cytological categories of negative for high-grade urothelial carcinoma (NHGUC) and atypical urothelial cells (AUCs), we found that an EpiScore <60 correlates with NHGUC (p=0.0003, Fisher's exact test), while comparing AUC and suspicious for high-grade urothelial carcinoma (SHGUC) or SHGUC and high-grade urothelial carcinoma (HGUC) categories, an EpiScore ≥60 correlates with SHGUC and HGUC, respectively (p=0.0031 and p=0.0027, Fisher's exact test). In each TPS category, we found that sensitivity, specificity, Positive Predicitve Value (PPV) and Negative Predictive Value (NPV) of the Bladder EpiCheck test in HGUC category were higher than those observed in SHGUC group (sensitivity=98%, specificity=100%, NPV=85.7%, PPV=100% vs sensitivity=86.6%, specificity=52.3%, NPV=84.6%, PPV=56.5%).

CONCLUSIONS

Analysing methylation study results, we demonstrated that different TPS cytological categories also carry a distinct molecular signature. Moreover, our results confirm that cytological categories SHGUC and HGUC are different entities also from a molecular point of view and should continue to represent distinct groups in TPS.

L-Glucose: Another Path to Cancer Cells

Cancerous tumors comprise cells showing metabolic heterogeneity. Among numerous efforts to understand this property, little attention has been paid to the possibility that cancer cells take up and utilize otherwise unusable substrates as fuel. Here we discuss this issue by focusing on l-glucose, the mirror image isomer of naturally occurring d-glucose; l-glucose is an unmetabolizable sugar except in some bacteria. By combining relatively small fluorophores with l-glucose, we generated fluorescence-emitting l-glucose tracers (fLGs). To our surprise, 2-NBDLG, one of these fLGs, which we thought to be merely a control substrate for the fluorescent d-glucose tracer 2-NBDG, was specifically taken up into tumor cell aggregates (spheroids) that exhibited nuclear heterogeneity, a major cytological feature of malignancy in cancer diagnosis. Changes in mitochondrial activity were also associated with the spheroids taking up fLG. To better understand these phenomena, we review here the Warburg effect as well as key studies regarding glucose uptake. We also discuss tumor heterogeneity involving aberrant uptake of glucose and mitochondrial changes based on the data obtained by fLG. We then consider the use of fLGs as novel markers for visualization and characterization of malignant tumor cells.

Diagnostic Agreement for High-Grade Urothelial Cell Carcinoma in Atypical Urine Cytology: A Nationwide Survey Reveals a Tendency for Overestimation in Specimens with an N/C Ratio Approaching 0.5

In the Paris System (TPS), standardized cytomorphological criteria and diagnostic categories were proposed for reporting urine cytology. To evaluate the diagnostic agreement and interobserver concordance for assessing TPS criteria, the Taiwan Society of Clinical Cytology organized an online survey with 10 atypical urine cytology cases. A total of 137 participants completed the survey. The mean agreement of diagnosis was 51.2%, ranging from 34.3% to 83.2% for each case. For 60% (6/10) of cases, the agreement was <50%. The interobserver concordance of diagnosis and cytological criteria assessment showed poor agreement. The nuclear-to-cytoplasmic (N/C) ratio had the highest kappa value of 0.386, indicating a significantly higher interobserver concordance and reproducibility than the other three TPS criteria. The correct rate of assessing the N/C ratio increased as the N/C ratio increased (correlation coefficient: 0.891, p < 0.01). Three cases with an N/C ratio near 0.5 were overestimated. Poor interobserver concordance of diagnosis and TPS criteria was revealed. Compared with other cytological features, the N/C ratio assessment was quantitative and more reproducible, but a tendency to overestimate cells was noted when the N/C ratio was approximately 0.5. Continuing education programs should emphasize the accurate assessment of N/C ratio to improve the application of TPS.

Impact of the Paris system for reporting urine cytopathology on predictive values of the equivocal diagnostic categories and interobserver agreement

Background:

The Paris System (TPS) acknowledges the need for more standardized terminology for reporting urine cytopathology results and minimizing the use of equivocal terms. We apply TPS diagnostic terminologies to assess interobserver agreement, compare TPS with the traditional method (TM) of reporting urine cytopathology, and evaluate the rate and positive predictive value (PPV) of each TPS diagnostic category. A survey is conducted at the end of the study.

Materials and Methods:

One hundred urine samples were reviewed independently by six cytopathologists. The diagnosis was rendered according to TPS categories: negative for high-grade urothelial carcinoma (NHGUC), atypical urothelial cells (AUC), low-grade urothelial neoplasm (LGUN), suspicious for high-grade urothelial carcinoma (SHGUC), and high-grade urothelial carcinoma (HGUC). The agreement was assessed using kappa. Disagreements were classified as high and low impacts. Statistical analysis was performed.

Results:

Perfect consensus agreement was 31%, with an overall kappa of 0.362. Kappa by diagnostic category was 0.483, 0.178, 0.258, and 0.520 for NHGUC, AUC, SHGUC, and HGUC, respectively. Both TM and TPS showed 100% specificity and PPV. TPS showed 43% sensitivity (38% by TM) and 70% accuracy (66% by TM). Disagreements with high clinical impact were 27%. Of the 100 cases, 52 were concurrent biopsy-proven HGUC. The detection rate of biopsy-proven HGUC was 43% by TPS (57% by TM). The rate of NHGUC was 54% by TPS versus 26% by TM. AUC rate was 23% by TPS (44% by TM). The PPV of the AUC category by TPS was 61% versus 43% by TM. The survey showed 33% overall satisfaction.

Conclusions:

TPS shows adequate precision for NHGUC and HGUC, with low interobserver agreement for other categories. TPS significantly increased the clinical significance of AUC category. Refinement and widespread application of TPS diagnostic criteria may further improve interobserver agreement and the detection rate of HGUC.

Determination of cell nucleus-to-cytoplasmic ratio using imaging flow cytometry and a combined ultrasound and photoacoustic technique: a comparison study

While the nucleus-to-cytoplasmic (N:C) ratio has traditionally been used for assessing cell malignancy, most N:C measurement techniques are time-consuming and performed on thin histological sections, which prohibit assessment of three-dimensional cell structure. A combined ultrahigh frequency ultrasound (US) and photoacoustic (PA) technique was used to assess the size and N:C ratio of cultured cancer cells in three dimensions (3D). The diameters of the cells and their stained nuclei were obtained by fitting the power spectrum of backscattered US pulses and emitted PA waves, respectively, to well-established theoretical models. For comparison, an imaging flow cytometer (IFC) was also used to determine the two-dimensional cell and nucleus sizes from large cell populations using brightfield and fluorescence images, respectively. An N:C ratio was calculated for each cell using the quotient of the measured nucleus diameter and the total cell diameter. The mean N:C ratios calculated using the sound-based approach were 0.68, 0.66, and 0.54 for MCF-7, PC-3, and MDA-MB-231 cells, respectively, and were in good agreement with the corresponding values of 0.68, 0.67, and 0.68 obtained using the IFC. The combined US and PA technique, which assesses cellular N:C ratio in 3D, has potential applications in the detection of circulating tumor cells in liquid biopsies.

Performance of an artificial intelligence algorithm for reporting urine cytopathology

BACKGROUND

Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite The Paris System for Reporting Urinary Cytology, there still is poor interobserver agreement with urine cytology and many cases in which a definitive diagnosis cannot be made. In the current study, the authors have reported on the development of an image algorithm that applies computational methods to digitized liquid-based urine cytology slides.

METHODS

A total of 2405 archival ThinPrep glass slides, including voided and instrumented urine cytology cases, were digitized. A deep learning computational pipeline with multiple tiers of convolutional neural network models was developed for processing whole slide images (WSIs) and predicting diagnoses. The algorithm was validated using a separate test data set comprised of consecutive cases encountered in routine clinical practice.

RESULTS

There were 1.9 million urothelial cells analyzed. An average of 5400 urothelial cells were identified in each WSI. The algorithm achieved an area under the curve of 0.88 (95% CI, 0.83-0.93). Using the optimal operating point, the algorithm's sensitivity was 79.5% (95% CI, 64.7%-90.2%) and the specificity was 84.5% (95% CI, 81.6%-87.1%) for high-grade urothelial carcinoma.

CONCLUSIONS

The authors successfully developed a computational algorithm capable of accurately analyzing WSIs of urine cytology cases. Compared with prior studies, this effort used a much larger data set, exploited whole slide-level and not just cell-level features, and used a cell gallery to display the algorithm's output for easy end-user review. This algorithm provides computer-assisted interpretation of urine cytology cases, akin to the machine learning technology currently used for automated Papanicolaou test screening.

Unsupervised organization of cervical cells using bright-field and single-shot digital holographic microscopy

We report results on unsupervised organization of cervical cells using microscopy of Pap-smear samples in brightfield (3-channel color) as well as high-resolution quantitative phase imaging modalities. A number of morphological parameters are measured for each of the 1450 cell nuclei (from 10 woman subjects) imaged in this study. The principal component analysis (PCA) methodology applied to this data shows that the cell image clustering performance improves significantly when brightfield as well as phase information is utilized for PCA as compared to when brightfield-only information is used. The results point to the feasibility of an image-based tool that will be able to mark suspicious cells for further examination by the pathologist. More importantly, our results suggest that the information in quantitative phase images of cells that is typically not used in clinical practice is valuable for automated cell classification applications in general.

Artificial intelligence in cytopathology: a review of the literature and overview of commercial landscape

Artificial intelligence (AI) has made impressive strides recently in interpreting complex images, thanks to improvements in deep learning techniques and increasing computational power. Researchers have started applying these advanced techniques to pathology images, although most efforts have been focused on histopathology. Cytopathology, however, remains the original field of pathology for which AI models for clinical use were successfully commercialized, to assist with automating Papanicolaou test screening. Recent AI efforts have focused on whole slide images of both gynecologic and non-gynecologic cytopathology. This review summarizes the literature and commercial landscape of AI as applied to cytopathology.

Variability among observers utilizing the CellSolutions BestCyte Cell Sorter imaging system for the assessment of urinary tract cytology specimens

INTRODUCTION

Image analysis systems are not currently commonly used for evaluating urinary cytology specimens. We evaluated whether the BestCyte Cell Sorter (CellSolutions, Greensboro, NC) imaging system can reliably identify atypical cells in urinary cytology specimens.

METHODS

Fifty-three consecutive urine cytology specimens underwent 2 preparations: one slide using SurePath (SP; BD Diagnostics, Sparks, MD)^™ for routine clinical evaluation, and a second slide using the CellSolutions F50 system for analysis by the BestCyte Cell Sorter (BCCS) scanning system. Eight observers reviewed atypical cells flagged by BCCS and assigned a BCCS diagnosis to each of the 53 specimens. The observers also blindly reviewed the SP preparation (when available) and assigned an SP diagnosis. The SP diagnoses given by one "expert" observer was considered as a reference diagnosis.

RESULTS

There was fair-to-moderate agreement among observers for identifying any atypia and high-grade atypia (Fleiss kappa: 0.417 and 0.338, respectively) using BCCS. Review of SP preparations had slightly better agreement (Fleiss kappa: 0.558 and 0.564, respectively). Intraobserver agreement between the two methods varied greatly between individuals (Cohen's kappa range: 0.260 to 0.647). When a consensus diagnosis could be reached among the observers for cases with surgical follow-up, the consensus diagnosis was concordant in 11 of 12 instances, with one instance being a one-step discrepancy.

CONCLUSIONS

Specimen review by BCCS resulted in slightly greater interobserver variability than review of routine SP preparations. This may have been due to variations in observer experience and comfort with the use of a digital imaging system, which is further suggested by the wide range of intraobserver agreement among individuals.

Utility of The Paris System for Reporting Urinary Cytology in upper urinary tract specimens

INTRODUCTION

Diagnosing upper urinary tract (UUT) lesions using cytology has been historically difficult because of a lack of standardized terminology, cytomorphologic criteria, and the presence of instrumentation artifact. The goal of The Paris System for Reporting Urinary Cytology (TPSRUC) was to provide standardized terminology and cytomorphologic criteria. The aim of this study was to evaluate the utility of TPSRUC in UUT cytology specimens at our institution.

MATERIALS AND METHODS

Single ThinPrep archival slides from 30 UUT cytology cases with corresponding histological follow-up were reviewed using TPSRUC. Those results were compared with the original cytology diagnoses.

RESULTS

The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for high-grade urothelial carcinoma (HGUC) using TPSRUC were 71%, 100%, 100%, and 71%.

CONCLUSIONS

The TPSRUC was reliable at identifying HGUC. These data showed that this system had a lower sensitivity (71% versus 100%) and NPV (71% versus 100%) for UUT specimens compared with original cytology diagnoses. TPSRUC had a sensitivity and specificity that were comparable to reported overall sensitivity and specificity of UUT cytology for detection of HGUC. A major cause of discrepancy with TPSRUC was the classification of urine samples (n = 8) from histologically proven HGUC cases as only atypical (n = 6) or negative (n = 2), mainly owing to nuclear hypochromasia rather than hyperchromasia. Thus, hyperchromasia, a criteria used in TPSRUC, may not be as relevant in UUT specimens.

Histopathological Image QTL Discovery of Immune Infiltration Variants

Genotype-to-phenotype association studies typically use macroscopic physiological measurements or molecular readouts as quantitative traits. There are comparatively few suitable quantitative traits available between cell and tissue length scales, a limitation that hinders our ability to identify variants affecting phenotype at many clinically informative levels. Here we show that quantitative image features, automatically extracted from histopathological imaging data, can be used for image quantitative trait loci (iQTLs) mapping and variant discovery. Using thyroid pathology images, clinical metadata, and genomics data from the Genotype-Tissue Expression (GTEx) project, we establish and validate a quantitative imaging biomarker for immune cell infiltration. A total of 100,215 variants were selected for iQTL profiling and tested for genotype-phenotype associations with our quantitative imaging biomarker. Significant associations were found in HDAC9 and TXNDC5. We validated the TXNDC5 association using GTEx cis-expression QTL data and an independent hypothyroidism dataset from the Electronic Medical Records and Genomics network.

The Paris System for Reporting Urinary Cytology: early review of the literature reveals successes and rare shortcomings

The Paris System for Reporting Urinary Cytology (TPS) provides recommendations for the diagnosis of urinary tract cytology (UTC) specimens and has found acceptance on an international level. Since the official release of TPS in 2016, numerous research studies have been published analyzing its impact. This review summarizes the studies published since the release of TPS, highlighting areas in which TPS has performed well and other areas in which TPS may need improvement.

On reprogramming of tumor cells metabolism: detection of glycogen in the cell lines of hepatocellular origin with various degrees of dedifferentiation

The reprogramming of cancer cells includes shifts in glucose and glycogen metabolism. The aim of our work was to check the ability of forming glycogen grains in hepatocellular tumor cell lines of various dedifferentiation levels. We studied the monolayer culture established in vitro after explanting cells from rat ascites Zajdela hepatoma strain C (ZH-C) as a "parental" line and its five daughter clonal sublines: the holoclonal sublines 3H, 5F, 6H and the meroclonal ones 1E, 9C, which possess, respectively, the properties of cancer stem-like cells (CSLCs) and cancer progenitor-like cells (CPLCs). Besides, we studied four permanent cell lines of a rat hepatoma HTC, two murine hepatomas BWTG3 and MH-22a, and human hepatoblastoma HepG2. We used normal rat hepatocytes as positive control cells that form glycogen. We estimated relative cell dedifferentiation levels of the studied lines via analysis of cell morphology, morphometry and motility character on stained cell preparations and lifetime video files. Glycogen in the cells was detected using a Schiff type Au-SO2 reagent. All studied hepatocellular tumor lines were not of equal dedifferentiation level as manifested by different nucleus-to-cytoplasm ratio, by epithelium-like or fibroblast-like morphology, by tight or loosen intercellular contacts, by cell migration of collective or individual types. Glycogen fluorescence of uneven intensity was observed in all normal rat hepatocytes, but only in some cell groups or in single cells of hepatocellular tumor lines. The large or small fluorescent grains were found not only in relatively less dedifferentiated parental ZH-C line, BWTG3 and HepG2 lines, but also in moderately dedifferentiated 1E and HTC lines and even in severely dedifferentiated 3H, 5F and 6H sublines, as well as in the islets of the rat ascites hepatoma induced in vivo by the injection of 3H cells (the tumor-initiating cells). On the other hand, MH-22 and 9C lines, being relatively less and moderately dedifferentiated, showed no glycogen fluorescence. Thus, in 10 tumor cell lines of hepatocellular origin, an ability to reserve glycogen manifested no obvious dependency on their dedifferentiation level. Glycogen grains were detected in some cells even of the severely dedifferentiated lines: in single CSLCs of holoclonal ZH sublines grown in vitro and in a majority of tumor-initiating cells derived from ascites hepatoma in vivo. We suggest that dynamic changes in glycogen formation in CSLCs and tumor-initiating cells might be of importance for their dedifferentiation, self-renewal in vitro, survival and metastasis in vivo. The role of glycogen in maintaining viability and metastasis of tumor cells is to be further studied.

Interobserver reproducibility of The Paris System for Reporting Urinary Cytology

BACKGROUND

The Paris System for Reporting Urinary Cytology represents a significant improvement in classification of urinary specimens. The system acknowledges the difficulty in cytologically diagnosing low-grade urothelial carcinomas and has developed categories to deal with this issue. The system uses six categories: unsatisfactory, negative for high-grade urothelial carcinoma (NHGUC), atypical urothelial cells, suspicious for high-grade urothelial carcinoma, high-grade urothelial carcinoma, other malignancies and a seventh subcategory (low-grade urothelial neoplasm).

METHODS

Three hundred and fifty-seven urine specimens were independently reviewed by four cytopathologists unaware of the previous diagnoses. Each cytopathologist rendered a diagnosis according to the Paris System categories. Agreement was assessed using absolute agreement and weighted chance-corrected agreement (kappa). Disagreements were classified as low impact and high impact based on the potential impact of a misclassification on clinical management.

RESULTS

The average absolute agreement was 65% with an average expected agreement of 44%. The average chance-corrected agreement (kappa) was 0.32. Nine hundred and ninety-nine of 1902 comparisons between rater pairs were in agreement, but 12% of comparisons differed by two or more categories for the category NHGUC. Approximately 15% of the disagreements were classified as high clinical impact.

CONCLUSIONS

Our findings indicated that the scheme recommended by the Paris System shows adequate precision for the category NHGUC, but the other categories demonstrated unacceptable interobserver variability. This low level of diagnostic precision may negatively impact the applicability of the Paris System for widespread clinical application.