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

Anderlini, R.; Manieri, G.; Lucchi, C.; O, Raisi; Soliera, A.R.; Torricelli, Fábio César Miranda; Varani, Manuela; Trenti, Tommaso

doi:10.1016/j.cca.2015.10.005

Cited by 10 publications

(7 citation statements)

References 28 publications

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“…The images of small cocci detected by iQ200 are difficult for the medical technologist to classify as “bacteria.” Better classification results have been obtained for some rod forms [2124]. In addition, detection of malignant/atypical urothelial cells, which may indicate bladder carcinoma diagnosis, has been achieved using automated intelligent microscopy on iQ200 with a sensitivity of identification of 87.5% [25].…”

Section: Automated Microscopymentioning

confidence: 99%

Progress in Automated Urinalysis

2019

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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.

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Section: Automated Microscopymentioning

confidence: 99%

Progress in Automated Urinalysis

2019

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“…Hundreds of captures of a digital camera are evaluated by intelligence identification software, and each particle is classified on the basis of some characteristics such as shape, contrast and texture of the particle. Any identified particles that do not fulfill predefined characteristics, according to predetermined rules for automated classifications, are reserved in a list of unclassified cell images to be manually classified by experienced laboratory staff [5]. Previous studies have suggested that the analyzer showed similar performances and good compatibility to manual microscopy [6]; however, they are still inadequate in the determination of RBC in some pathological samples.…”

Section: Discussionmentioning

confidence: 99%

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

Xiang

Liang

Ren

2020

Journal of Laboratory Medicine

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

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“…Unfortunately, urinary cytology is performed in the pathology department and most laboratory medicine departments separate the routine urinalysis from urinary cytopathology. Some researchers have shown that atypical/malignant urothelial cells can be identified in routine urinalysis with the conventional urinary sediment examination or automated urinalysis [6,7]. Urothelial cells, either atypical or malignant, should be noted and are worth reporting in routine urinalysis specimens.…”

Section: Introductionmentioning

confidence: 99%

“…This provides important clues for a suspected diagnosis or the surveillance of urothelial carcinoma patients. Routine urinalysis can be used to identify atypical/malignant urothelial cells using automated digital or manual microscopy, but no studies have investigated the ability of the UF-5000 to detect atypical/ malignant urothelial cells [6,7]. Therefore, this study evaluated the performance of a new parameter, Atyp.C, in patients with a suspected diagnosis of urothelial carcinoma on urinary tract cytology (UTCy).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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

Cited by 10 publications

References 28 publications

Progress in Automated Urinalysis

Progress in Automated Urinalysis

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

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

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