Literature DB >> 30215223

Advances in Automated Urinalysis Systems, Flow Cytometry and Digitized Microscopy.

Sun Young Cho1, Mina Hur2.   

Abstract

Entities:  

Keywords:  Digitized microscopyInt; Flow cytometry; Urinalysis

Mesh:

Year:  2019        PMID: 30215223      PMCID: PMC6143476          DOI: 10.3343/alm.2019.39.1.1

Source DB:  PubMed          Journal:  Ann Lab Med        ISSN: 2234-3806            Impact factor:   3.464


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Screening of urine samples is the third most frequently performed test in clinical laboratories [1]. Urinalysis generally includes two kinds of methods: strip tests and microscopic examinations [1]. Urine microscopy, urine sediment analysis using microscope, has been used to detect various urologic diseases affecting from kidney to urinary tract [12]. However, manual microscopic examination is time consuming and needs experts for interpretation [3]. The effort of examining the particles in samples has long been a big issue in the hematologic field [2]. Wallace Coulter developed a counting method for particles in electrolyte solutions [2]. It made accurate cell counts in blood and became main equipment in laboratory hematologic analysis [2]. However, Coulter method could not be easily adapted in urinalysis until the late 1990s, because urine contains the broad spectrum of particles such as crystals, and cells that do not exist in blood [2]. Fifty years after Coulter method was introduced, laboratory instrument for identifying and enumeration urine particle was finally developed [2]. In the field of automated microscopy, the process of continuous technical development and adaptation has been achieved [3]. Consequently, flow cytometry and digitized microscopy have been introduced and established for enumerating urine particles in modern laboratories. Urinary tract infection (UIT) is the most common infections in both hospitalized and community-acquired patients [4]. Many investigators have evaluated the ability of flow cytometry to detect bacteria and WBCs in urine samples [3]. Because of the high percentage of negative urine culture results, efficient screening method with a high negative predictive value (NPV) has been required for a long time [5]. Researchers have extensively investigated to show whether laser-based flow cytometry can be useful screening tests for pyuria or bacteriuria [2]. Rosa et al. [4] reported that the new Sysmex urine analyzer, UF-5000 (Sysmex cooperation, Kobe, Japan) based on laser flow cytometry, presented high NPV up to 99.7% with conventional urine culture. If flow cytometric methods reduce the number of unnecessary urine culture tests, it can also save labor, time, and cost in laboratories [3]. On the other hand, the software image analysis of the digital microscope forms another one of the two main axes of automated urine sediment examinations. Because flow cytometric methods make a scattergram not an image, laboratorian cannot discard manual microscope to verify and differentiate problematic particles in urine [2]. In contrast, automated digital microscopy based on pattern recognition produces real images that can be reviewed by experts [23]. Compared with manual microscopy, it shows good performance and agreement to detect RBCs, WBCs, bacteria and squamous epithelial cells [2]. However, it is less reliable in detecting non-squamous epithelial cells, non-hyaline casts, unusual crystals and lipids [67]. In this issue of Ann Lab Med, Oyaert and Delanghe [3] introduced detailed reviews on recent advances in automated urinalysis systems, including application of these two practical developments. Although their performance requires further evaluation, adaptation and integration of these new technologies in urinalysis can lead to make more accurate patients results and more effectively used laboratory resources.
  7 in total

Review 1.  Advances in Urine Microscopy.

Authors:  Gavin J Becker; Giuseppe Garigali; Giovanni B Fogazzi
Journal:  Am J Kidney Dis       Date:  2016-01-22       Impact factor: 8.860

2.  Comparison of LabUMat-with-UriSed and iQ200 fully automatic urine sediment analysers with manual urine analysis.

Authors:  Okhan Kadir Akin; Muhittin A Serdar; Zeynep Cizmeci; Ozlem Genc; Suleyman Aydin
Journal:  Biotechnol Appl Biochem       Date:  2009-06       Impact factor: 2.431

3.  Urine sediment analysis: Analytical and diagnostic performance of sediMAX - a new automated microscopy image-based urine sediment analyser.

Authors:  Zahur Zaman; Giovanni Battista Fogazzi; Giuseppe Garigali; Maria Daniela Croci; Gabor Bayer; Tunde Kránicz
Journal:  Clin Chim Acta       Date:  2009-10-25       Impact factor: 3.786

Review 4.  Automated urine screening devices make urine sediment microscopy in diagnostic laboratories economically viable.

Authors:  Zahur Zaman
Journal:  Clin Chem Lab Med       Date:  2015-11       Impact factor: 3.694

5.  Evaluation of the new Sysmex UF-5000 fluorescence flow cytometry analyser for ruling out bacterial urinary tract infection and for prediction of Gram negative bacteria in urine cultures.

Authors:  Rita De Rosa; Shamanta Grosso; Giada Lorenzi; Graziano Bruschetta; Alessandro Camporese
Journal:  Clin Chim Acta       Date:  2018-05-24       Impact factor: 3.786

Review 6.  Automated Flow Cytometry: An Alternative to Urine Culture in a Routine Clinical Microbiology Laboratory?

Authors:  Patricia Mejuto; Mariam Luengo; Julio Díaz-Gigante
Journal:  Int J Microbiol       Date:  2017-09-27

Review 7.  Progress in Automated Urinalysis.

Authors:  Matthijs Oyaert; Joris Delanghe
Journal:  Ann Lab Med       Date:  2019-01       Impact factor: 3.464

  7 in total
  2 in total

1.  Urine Microscopy for Internal Medicine Residents: A Needs Assessment and Implementation of Virtual Teaching Sessions.

Authors:  Jorge Chancay; Meghana Eswarappa; Luis Sanchez Russo; Matthew A Sparks; Samira S Farouk
Journal:  Kidney360       Date:  2020-12-02

2.  Internal Quality Control Data of Urine Reagent Strip Tests and Derivation of Control Rules Based on Sigma Metrics.

Authors:  Haeil Park; Younsuk Ko
Journal:  Ann Lab Med       Date:  2021-09-01       Impact factor: 3.464

  2 in total

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