Clin. Lab. 2014;60:693-697 Copyright SHORT COMMUNICATION Urinalysis: Comparison between Microscopic Analysis and a New Automated Microscopy Image-Based Urine Sediment Instrument PAULA V. BOTTINI, MAYARA H. M. MARTINEZ, CÉLIA R. GARLIPP Division of Clinical Pathology, University of Campinas/UNICAMP, Campinas, SP, Brazil SUMMARY Background: Urinalysis is a high demand procedure, with a large amount of manual labor and poorly standardized. Recently a new walk-away automated urine analyzer has been introduced. The aim of this study was to evaluate the performance of UriSed as an alternative to the microscopic analysis of urine samples. Methods: Four hundred mid-stream urine samples from patients with several clinical conditions were analyzed by bright field microscopy and by UriSed. The validation protocol included studies of precision, carryover, and comparison with the gold standard microscopy. Results: Our data showed that UriSed is a precise method. Repeatability and reproducibility ranged from 8 to 15%. Carryover was negligible. All the elements showed good agreement between both methods, with an extremely high correlation between the erythrocyte and leukocyte counts (r > 0.95) Conclusions: UriSed is a precise and accurate alternative to microscopy that allows a better workflow and may significantly improve turnaround time. (Clin. Lab. 2014;60:693-697. DOI: 10.7754/Clin.Lab.2013.130725) KEY WORDS urinalysis, microscopic examination, automated sediment analysis INTRODUCTION Urinalysis is a high demand procedure which includes physical, chemical, and microscopic examinations. Although the analysis of urine sediment provides essential information on the functional state of the kidneys, it is a labor intensive and time consuming procedure. Besides that, it is poorly standardized and features a wide interobserver variability as several factors may contribute to the inaccuracy of this method (e.g., centrifugation, differences in interpretation of cellular elements, cylinders, etc.) [1,2]. Automation seems to be the answer to this issue [3]. In an attempt to automate the microscopic analysis of urine, some urine analysis systems have been developed beginning in the late 80s. The great advantage of automated analysis over microscopic procedure is that the former reduces the inter-observer variability and increases the accuracy and the productivity. While microscopic analysis usually takes several minutes to be performed automation can release a result in about one minute [4]. A few years ago, a new walk-away automated urine sediment analyzer based on the KOVA method with on-screen review of the images was introduced. This analyzer is basically the automation of the traditional manual microscopy [5]. The aim of this study was to evaluate the performance of this image based automated sediment analyzer (UriSed, also called sedimax in some countries) as an alternative to the microscopic analysis of urine samples. MATERIALS AND METHODS We analyzed 400 mid-stream urine samples from patients (262 women and 138 men) with several clinical conditions. Their ages varied from 2 to 91 years (median = 41 years). All samples were analyzed by bright field microscopy Short Communication accepted July 24, 2013 Clin. Lab. 4/2014 693
P. V. BOTTINI et al. Table 1. Precision of UriSed. Intra-assay precision Inter-assay precision LEVEL 1 LEVEL 2 LEVEL 1 LEVEL 2 element/hpf mean ± SD CV mean ± SD CV mean ± SD CV mean ± SD CV RBC 25.7 ± 2.0 8% 83.6 ± 7.2 9% 25.5 ± 2.0 8% 95.8 ± 7.7 8% WBC 11.7 ± 1.2 10% 64.7 ± 6.9 11% 16.1 ± 2.4 15% 79. 9 ± 10.6 13% RBC - red blood cell, WBC - white blood cell hpf - high power field, SD - standard deviation, CV - coefficient of variation. Table 2. Diagnostic performance of UriSed. RBC WBC Hyaline Casts Path Casts Crystals Bacteria Sensitivity (%) 75 72. 52 54 100.0 69.4 Specificity (%) 99 98 69 82 100.0 85.0 Positive Predictive value (%) 94 94 17 27 100.0 68.8 Negative Predictive value (%) 96 92 92 94 100.0 86.2 Agreement (%) 95.0 91 67 79 100.0 80.1 2 269.812 242.585 7.195 26.686 397.000 120.247 p < 0.001 < 0.001 < 0.05 < 0.001 < 0.001 < 0.001 RBC - red blood cell, WBC - white blood cell, Path - pathological. using the KOVA method with the results expressed in terms of quantitative elements (erythrocytes-rbc and leukocytes-wbc; arithmetic mean of 10 fields of 400x) and qualitative elements (casts, crystals, and bacteria, considering all fields), and by a fully automated sediment analyzer (UriSed - 77 Elektronika Kft, Budapest, Hungary). UriSed is based on microscopic examination of urine samples (KOVA method). The analyzer homogenizes, aspires, and transfers the sample to a special disposable cuvette. The cuvette is centrifuged and placed in microscopy position and whole-field images are obtained and evaluated by an auto image evaluation module (AIEM). Results were expressed as particle concentration/hpf (high power field). These high definition images are displayed on-screen and can be stored for further review and for educational purposes [5]. All 15 images of each sample were reviewed by an experienced analyst and manually edited, if necessary. The validation protocol was based on local regulation, on CLSI documents EP05-A2 [6] and EP15-A2 [7], and on ICSH guideline [8] and included studies of precision (repeatability/reproducibility) and carryover. Repeatability (intra assay precision) was obtained from the analysis of 20 replicates of two urine samples with different particle numbers. The inter assay precision (reproducibility) was performed by analyzing two levels of control samples (Liquichek Urinalysis Control - Biorad) on 20 consecutive days. Carryover effect was assessed by testing a high-level urine sample consecutively in triplicate (H1, H2 and H3) followed by a low-level sample (L1, L2 and L3). Carryover was calculated using the following formula: carryover (%) = [(L1 - L3)/(H1 - L3)] x 100. Accuracy of the automated method was evaluated by comparison with microscopic analysis. Simple linear regression (least square method) was used to evaluate the correlation between quantitative analysis (RBC and WBC) by both methods. The Chi-squared statistical method was used to determine the agreement between microscopic analysis and UriSed. RBC and WBC counts > 5/hpf were classified as abnormal. Qualitative elements were compared according to the detection of them by each method. RESULTS Intra assay precision (repeatability) and inter assay precision (reproducibility) ranged from 8 to 15%, depending on the considered parameter (Table 1). As expected, there was no carryover since UriSed uses single-use cuvette for each sample. The results of high to low carryover returned negative values: -3.2% (RBC), -1.8% (WBC) and -1.2% (bacteria). There was a good correlation between the erythrocyte 694 Clin. Lab. 4/2014
URINALYSIS: MICROSCOPIC AND AUTOMATED ANALYSIS Figure 1. Distribution of RBC and WBC counts. and leukocyte counts by both methods (r > 0.95). Figure 1 shows the distribution of RBC and WBC counts by manual and automated analysis. All the elements showed good agreement between microscopic analysis and UriSed, as seen in Table 2. The analyzer easily detected the most common crystals seen in urine samples. The major causes of misclassification are the presence of squamous epithelial cells, mucus or amorphous crystals, emphasizing the importance of a recently collected mid-stream urine sample. DISCUSSION There is no doubt that microscopy is an important part of urinalysis and may provide useful information. As it is a labor intensive and time consuming procedure many efforts have been made to develop a better, cost-effective strategy without loss in the diagnostic yield. The first attempt in reducing the number of urine microscopy analyses was based on urine dipsticks. This procedure led to conflicting results as studies showed that a significant percentage of urine samples with normal chemistry results on the dipsticks had abnormal findings on microscopic analysis of sediment [9-11]. Studies have demonstrated significant inter-observer variation in the identification and interpretation of urine structures [1,12,13]. Automated urine microscopy is able to classify, quantify, and report urine particles and it seems to be an efficient alternative to reduce the manual workload and improve inter-observer reliability. Microscopic examination of urine sediment involves classification and quantification of particles present in this fluid and automated devices were developed to facilitate and standardize this procedure. This goal can be achieved through three systems with different methodologies. One of them (Sysmex UF-100/UF-1000i) is based on the use of fluorescence flow cytometry to classify the elements present in urine. Results are displayed as scattergrams and numerical values are reported [2]. Samples whose results have been flagged need to be reviewed by microscopy. Another analytical system is based on flow cell digital imaging with automatic particle recognition software (Iris iq 200) to identify and classify isolated images based on the texture, contrast, size, and shape of each element. The images are displayed to the analyst, allowing edition and reclassification, if necessary [14]. These images are considerably different from those observed in microscopy requiring substantial training before using the equipment [15]. The third analyzer (UriSed) is based on microscopic urine sediment analysis with digital images and automatic recognition of particles. UriSed corresponds to the automation of manual microscopy. Due to its characteristics, UriSed eliminates the need of microscopic Clin. Lab. 4/2014 695
P. V. BOTTINI et al. review of most of the samples. Images are very similar to those observed by microscopy and can be easily reviewed by the analyst. It is noteworthy that automated urinalysis, enables better workflow and may significantly improve turnaround time, since its processing time is much faster than the manual method (80-100 samples/hour versus around 10 samples hour/technologist, respectively). Our data showed that UriSed is a precise method. Interand intra-assay precision ranged from 8% to 15%. This rate is much lower than that observed in manual microscopy where several studies showed a variation of more than 50% depending on the particle counts [14-16]. Carryover was negligible, as described by Zaman et al. [17]. All the elements showed good agreement between microscopic and automated analysis. Our data were in accordance with those obtained by Akin et al. [14] and Zaman et al. [17]. Other authors, using automated urine analyzers based on flow cytometry (UF-100/UF-1000i) or digital image with particle recognition (iq 200) also observed good correlation with the gold standard microscopy [16,18,19]. Akin et al. compared the analytical performance of UriSed with another automated analyzer (iq 200) and observed a significant correlation between them [14]. Appropriate preanalytical procedures are the basic condition for obtaining an adequate sample that allows reliable results and a proper clinical interpretation. As stated before, one of the major causes of misclassification was the presence of contaminating elements such as squamous epithelial cells and mucus. Collecting a midstream sample is the most relevant step to prevent contamination. A recent multicenter study conducted by Manoni et al. [20] clearly confirmed mid-stream urine as the most suitable sample for routine urinalysis. In summary, UriSed is a precise and accurate alternative to the gold standard microscopy. The implementation of this automated routine allows a better workflow and may significantly improve turnaround time. Besides that, it has the potential to eliminate the need of a microscopic review of most of the samples as UriSed permits an on-screen review of the images. It is noteworthy that the use of a system that photographs and stores high-definition images provides an invaluable training tool for technologists and medical students. Acknowledgement: We thank José Ricardo Lauand, Luciane Franco-Fernandes, and Solange Gomes Lara Cioffi for helping us during the validation process. Declaration of Interest: The authors declare that there are no conflicts of interest. References: 1. Winkel P, Statland BE, Jorgenson J. Urine microscopy: an ill-defined method examined by a multifactorial technique. Clin Chem 1974;20:436-9. 2. Delanghe JR, Kouri TT, Huber AR, et al. The role of automated urine particle flow cytometry in clinical practice Clinica Chimica Acta 2000;301:1-18. 3. Langlois MR, Delanghe JR, Steyaert SR, Everaert KC, De Buyzere ML. Automated flow cytometry compared with an automated dipstick reader for urinalysis. Clinical Chemistry 1999;45: 1 118-22. 4. Block DR, Lieske JC. Automated urinalysis in the clinical lab. Medical Laboratory Observer 2012;44(10):8-10. 5. Barta Z, Kránicz Tünde, Bayer G. UriSed technology - A standardised automatic method of urine sediment analysis. European Infectious Disease 2011;5(2):139-42. 6. Clinical and Laboratory Standards Institute. Evaluation of precision performance of quantitative measurement methods. CLSI document EP05-A2. Wayne, PA, USA: CLSI; 2004. 7. Clinical and Laboratory Standards Institute. User verification of performance for precision and trueness; approved guideline - second edition. CLSI document EP15-A2. Wayne, PA, USA: CLSI; 2005. 8. International Council for Standardization in Haematology. Guidelines for the evaluation of blood cell analysers including those used for differential leucocyte and reticulocyte counting and cell marker applications. Clin Lab Haemat 1994;16:157-74. 9. Szwed JJ, Schaust C. The Importance of microscopic examination of the urinary sediment. American Journal of Medical Technology 1982;48(2):141-3. 10. Shaw ST Jr, Poon SY, Wong ET. Routine urinalysis : is the dipstick enough? JAMA 1985;253:1596-600. 11. Resnick M. Comment on simplifying urinalysis. Clin Chem 1985;31:450-1. 12. Wald R, Bell CM, Nisenbaum Ret al. Interobserver reliability of urine sediment interpretation. Clin J Am Soc Nephrol 2009;4: 567-71. 13. Tsai JJ, Yeun JY, Kumar VA, Don BR. Comparison and interpretation of urinalysis performed by a nephrologist versus a hospitalbased clinical laboratory. American Journal of Kidney Diseases 2005;46(5):820-9. 14. Akin OK, Serdat MA, Cizmeci Z, et al. Comparison of LabUMatwith-UriSed and iq 200 fully automatic urine sediment analysers with manual urine analysis. Biotechnol Appl Biochem 2009:53:139-44. 15. Block DR, Lieske JC. Automated urinalysis in the clinical lab. MLO Med Lab Obs 2012;44(10):8-10,12;quiz 14. 16. Mayo S, Acevedo D, Quiñones-Torrelo C, Canós I, Sancho M. Clinical laboratory automated urinalysis: comparison among automated microscopy, flow cytometry, two test strips analyzers, and manual microscopic examination of the urine sediments. J Clin Lab Anal 2008;22(4):262-70. 17. Zaman Z, Fogazzi GB; Garigali G et al. Urine sediment analysis: Analytical and diagnostic performance of sedimax - A new automated microscopy image-based urine sediment analyser. Clinica Chimica Acta 2010;411:147-54. 696 Clin. Lab. 4/2014
URINALYSIS: MICROSCOPIC AND AUTOMATED ANALYSIS 18. Jiang T, Chen P, Ouyang J, Zhang S, Cai D. Urine particles analysis: performance evaluation of Sysmex UF-1000i and comparison among urine flow cytometer, dipstick, and visual microscopic examination. Scand J Clin Lab Invest 2011;71(1):30-7. 19. Manoni F, Tinello A, Fornasiero L, et al. Urine particle evaluation: a comparison between the UF-1000i and quantitative microscopy. Clin Chem Lab Med 2010;48(8):1107-11. 20. Manoni F, Gessoni G, Alessio MG, et al. Mid-stream vs. firstvoided urine collection by using automated analyzers for particle examination in healthy subjects: an Italian multicenter study. Clin Chem Lab Med 2011;50(4):679-84. Correspondence: Paula V. Bottini MD, PhD Divisão de Patologia Clínica/HC - UNICAMP Rua Vital Brasil 251- Cidade Universitária Zeferino Vaz CEP: 13083-888, Campinas, S.P., Brasil Tel.: + 55 19 3521-7539 Fax: + 55 19 3521-7510 Email: paula@hc.unicamp Clin. Lab. 4/2014 697