Automated urinalysis with expert review for incidental identification of atypical urothelial cells: An anticipated bladder carcinoma diagnosis

Advances and Progress in Automated Urine Analyzers

The clinical analysis of urine has classically focused on conventional chemical-based urinalysis and urine microscopy. Contemporary advances in both analysis subsets have started to employ new technologies such as automated image analysis, flow cytometry, and mass spectrometry. In addition to new detection technologies, current analyzers have incorporated more advanced imaging, automated sample handing, and machine learning analyses into their workflow. The most advanced semiautomated analyzers can be interfaced with hospital medical record systems, and in the point-of-care setting, smartphones can be used for image analysis. This review will discuss current technological advancements in the field of urinalysis and urine microscopy.

Comparison of the clinical performance of the Atyp.C parameter of the UF-5000 fully automated urine particle analyzer with that of microscopic urine sediment analysis

a Objectives

Urinalysis is one of the most common laboratory screening tests to detect problems in the renal and urinary system; however, they cannot detect atypical cells (Atyp.Cs). The Sysmex UF-5000, a fully automated urine particle analyzer, can detect Atyp.Cs via its Atyp.C parameter. This study aimed to compare the clinical value of the Atyp.C parameter with that of urine sediment microscopy.

b Method

A total of 471 leftover urine samples were submitted to the Department of Clinical Laboratory at the University of Tokyo Hospital for urinalysis by manual sediment microscopy examination and UF-5000 Atyp.C analysis.

c Result

Of 471 submitted samples, 117 were positive for Atyp.Cs by urine sediment and 354 samples were negative. The histological subtypes of the Atyp.Cs included 105 cases of suspected urothelial carcinoma cells, 10 suspected squamous carcinoma cells, and 2 of suspected adenocarcinoma cells. The Atyp.C values for the Atyp.C-positive and -negative groups were 2.64 ± 0.69 and 0.38 ± 0.16, respectively. The optimal Atyp.C cutoff value determined by the receiver operating characteristic curve analysis was 0.4/μL. The area under the curve was 0.856, with a sensitivity of 79.5% and specificity of 85.1%. Atyp.C values of the UF-5000 showed high predictive performance for Atyp.C-positive specimens identified by urine sediment microscopy.

d Conclusions

This study shows that a combination of UF-5000 analysis and microscopic examination of urine sediment improves Atyp.C detection in urine sediment analysis. These results suggest that Atyp.C measured by UF-5000 could be a useful screening parameter in routine testing of urine samples.

Improving clinical performance of urine sediment analysis by implementation of intelligent verification criteria

OBJECTIVES

Urinary test strip and sediment analysis integrated with intelligent verification criteria can help to select samples that need manual review. This study aimed to evaluate the improvement in the diagnostic performance of combined urinary test strip and urinary sediment analysis using intelligent verification criteria on the latest generation automated test strip and urinary fluoresce flow cytometry (UFFC) analysers.

METHODS

Urine test strip and sediment analysis were performed using the Sysmex UC-3500 and UF-5000 (Kobe, Japan) on 828 urinary samples at the clinical laboratory of the Ghent University Hospital. The results were compared to manual microscopy using phase-contrast microscopy as a reference. After the application of the intelligent verification criteria, we determined whether the diagnostic performance of urine sediment analysis could be improved.

RESULTS

Application of intelligent verification criteria resulted in an increase in specificity from 88.5 to 96.8% and from 88.2 to 94.9% for red blood cells and white blood cells, respectively. Implementing review rules for renal tubular epithelial cells and pathological casts increased the specificity from 66.7 to 74.2% and from 96.2 to 100.0%, respectively; and improved the diagnostic performance of urinary crystals and atypical cells.

CONCLUSIONS

The implementation of review rules improved the diagnostic performance of UFFC, thereby increasing the reliability and quality of urine sediment results.

Atypical cells parameter in Sysmex UN automated urine analyzer: feedback from the field

BACKGROUND

"Atypical cells" parameter in automated urinalysis has recently been introduced. An instrument capable of measuring quantitative and qualitative features of nuclear and cytoplasmic properties of a cell has the potential to detect cellular atypia. Instruments using flow cytometry have been detecting atypical cells in blood for a long time; yet instruments using the same methodology very lately developed this parameter in urinalysis.

MATERIALS AND METHODS

Samples with an atypical cells value higher than 1 atypical cell/µL were included in the study. Besides automated urinalysis, every sample was reflexed to modular unit for digital imaging. The remainder of each sample was stained with Sternheimer dye and examined manually under a light microscope.

RESULTS

50 samples with higher than1 atypical cell/µL result were included in the study. Patients were composed of 43 females (86 %) and 7 males (14 %). The mean age was 47.12 ± 19.45 years. The median atypical cells value was 1.8/µL (95 % range 1.5-2.4/µL). Manual microscopic evaluation of the 50 samples showed atypical cells in 1 sample. The patient had papillary lesions on cystoscopy and pathology report informed a high grade urothelial carcinoma. Other 49 samples were negative for atypical cells in manual microscopy. They were crowded samples with leucocytes and squamous epithelial cells.

CONCLUSIONS

The positive case provided evidence for Sysmex UN's capability to detect atypical cells in urine. The negative cases presented clues that probable vulvovaginal contamination and crowded specimens could be deceptive for Sysmex UN in this particular parameter.

Investigation of Atyp.C using UF-5000 flow cytometer in patients with a suspected diagnosis of urothelial carcinoma: a single-center study

BACKGROUND

This study evaluated the predictive power of Atyp.C (a parameter of UF-5000 flow cytometer) for patients with a suspected diagnosis of urothelial carcinoma.

METHODS

We analyzed 163 urine specimens from 128 patients with suspected urothelial carcinoma using a fully automated fluorescence flow cytometry analyzer (UF-5000) and evaluated its performance on identifying atypical/malignant urothelial cells. From January 1, 2019 to April 4, 2019, all consecutive specimens for urinary cytopathology were enrolled.

RESULTS

Of the specimens with urinary cytopathology, 67 specimens (41.1%) revealed abnormal findings in cytology analysis. Among them, 20 specimens (12.3%) were diagnosed as atypical urothelial cells, 26 specimens (16.0%) as suspicious for malignancy (S-malignancy), and 21 specimens (12.9%) as confirmed malignancy. The UF-5000 findings were positive in 59 specimens (36.2%); therefore, the agreement with cytopathology was 73.0%. Using follow-up histologic diagnosis of urothelial carcinoma with or without urinary tract cytology (UTCy) as a reference standard (suspicious and confirmed malignancy were the positive criteria for UTCy), the sensitivity was 59.0%, specificity was 82.1%, positive predictive value was 75.0%, negative predictive value was 68.8%, and the agreement was 71.1%.

CONCLUSIONS

It is worth knowing and reporting that the Atyp.C assay may be used as an accessory test for patients with suspected urothelial carcinoma, based on its ability to identify high-risk patients who might need closer follow-up or additional medical treatment.

Double false-negative traps in urine routine test: a case report

Background

Urinalysis is one of the most commonly performed tests in clinical practice and supplies important information for a series of clinical conditions, including renal and urinary tract diseases. The clinical laboratory often completes urinalysis through the combined use of urinary dry-chemistry and formed-element analyzers. Urine red blood cell (RBC) morphology test is often used to discriminate the source of hematuria by manual microscopy.

Case presentation

In this case report, we describe a 39-year-old woman with chronic glomerulonephritis (CGN) who underwent both urine routine test and RBC morphology test. Her RBC count was in the normal range and the occult blood test was negative in routine test, while the RBC morphology test indicated the presence of non-homogeneous hematuria.

Conclusions

Therefore, we analyzed the causes of false-negative result on the urine chemical analyzer and the automatic microscope system, respectively.

Diagnostic significance of dual immunocytochemical staining of p53/cytokeratin20 on liquid-based urine cytology to detect urothelial carcinoma

Background:

Urine cytology is a noninvasive and inexpensive method; however, it is limited in low sensitivity for detecting and monitoring urothelial carcinoma (UC). To overcome limitation of cytology, several tests using urine samples have been attempted that immunocytochemical staining is an inexpensive and easy to perform ancillary technique. Dual immunocytochemical staining for p53 and cytokeratin 20 (CK20) is assessed in liquid-based urine cytology slides.

Materials and Methods:

Liquid-based urine cytology samples collected between 2008 and 2013 and matched follow-up biopsy samples of high-grade UC (HGUC) (n = 44) and low-grade UC (LGUC) (n = 14) were analyzed.

Results:

Urine cytology showing atypical cells was subjected to dual-color immunostaining for p53 and CK20. The sensitivity of urine cytology combined with p53 and CK20 immunostaining was 77.3% in HGUC and 52.9% in LGUC. Of 20 cases diagnosed with atypia by urine cytology, 13 (65%) were positive for p53 or CK20. Dual immunocytochemical staining for p53/CK20 improved the diagnostic accuracy of urine cytology.

Conclusions:

The present results indicate that cytomorphology combined with p53/CK20 immunostaining is useful for the detection of HGUC and LGUC.

Progress in Automated Urinalysis

New technological advances have paved the way for significant progress in automated urinalysis. Quantitative reading of urinary test strips using reflectometry has become possible, while complementary metal oxide semiconductor (CMOS) technology has enhanced analytical sensitivity and shown promise in microalbuminuria testing. Microscopy-based urine particle analysis has greatly progressed over the past decades, enabling high throughput in clinical laboratories. Urinary flow cytometry is an alternative for automated microscopy, and more thorough analysis of flow cytometric data has enabled rapid differentiation of urinary microorganisms. Integration of dilution parameters (e.g., creatinine, specific gravity, and conductivity) in urine test strip readers and urine particle flow cytometers enables correction for urinary dilution, which improves result interpretation. Automated urinalysis can be used for urinary tract screening and for diagnosing and monitoring a broad variety of nephrological and urological conditions; newer applications show promising results for early detection of urothelial cancer. Concomitantly, the introduction of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has enabled fast identification of urinary pathogens. Automation and workflow simplification have led to mechanical integration of test strip readers and particle analysis in urinalysis. As the information obtained by urinalysis is complex, the introduction of expert systems may further reduce analytical errors and improve the quality of sediment and test strip analysis. With the introduction of laboratory-on-a-chip approaches and the use of microfluidics, new affordable applications for quantitative urinalysis and readout on cell phones may become available. In this review, we present the main recent developments in automated urinalysis and future perspectives.