New screening diagnostic techniques in urinalysis

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.

Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis

Currently available urinalysis methods are often applied for screening and monitoring of several pathologies. However, traditionally analyzed biomarkers in urinalysis still lack sensitivity and specificity to accurately diagnose some diseases. Several studies have proposed the use of electronic noses (eNoses) for the analysis of volatile organic compounds in urine samples that may, directly or indirectly, correlate with certain pathologies. Hence, the aim of this study was to perform a systematic review and meta-analysis of studies concerning the use of portable electronic noses for diagnosis or monitoring of pathologies through analysis of urine samples. A systematic review of the literature was held according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Twenty-four articles met the inclusion criteria and were included in the analysis. The results of the revised studies showed that there are various volatile organic compound profiles, identified through eNose analysis, that may be applied for diagnosis or monitoring of several diseases, such as diabetes, urinary tract infection, inflammatory bowel disease, and kidney disease. A meta-analysis was conducted taking into consideration the data of 10 of the initial 24 articles. The pooled sensitivity, specificity, and diagnostic odds ratio were 84% (95% CI, 0.72-0.92), 85% (95% CI, 0.75-0.91), and 24.17 (95% CI: 7.85-74.41), respectively. The area under the receiver operating characteristic curve was 0.897. These results suggest that eNose technology has adequate diagnostic accuracy for several pathologies and could be a promising screening tool for clinical settings. However, more studies are needed to reduce heterogeneity between results.

A review on B/A measurement methods with a clinical perspective

The nonlinear parameter of ultrasound B/A has shown to be a useful diagnostic parameter, reflecting medium content, structure, and temperature. Despite its recognized values, B/A is not yet used as a diagnostic tool in the clinic due to the limitations of current measurement and imaging techniques. This review presents an extensive and comprehensive overview of the techniques developed for B/A measurement of liquid and liquid-like media (e.g., tissue), identifying the methods that are most promising from a clinical perspective. This work summarizes the progress made in the field and the typical challenges on the way to B/A estimation. Limitations and problems with the current techniques are identified, suggesting directions that may lead to further improvement. Since the basic theory of the physics behind the measurement strategies is presented, it is also suited for a reader who is new to nonlinear ultrasound.

Using elastic scattering to determination of diseases via urine samples

<abstract> <p>In diagnosing the urinary tract and related diseases, the problem of light scattering from human urine was examined on the basis of classical electromagnetic theory. Numerical calculations were made for the designed cylindrical model with the help of optical parameters in the literature obtained from the laboratory test results of urine samples. In the designed model, the changes of the scattered intensity of the light from the urine solution according to the size parameter of the particles and the angular distribution of the system (including forward, side and back scattering) in the equatorial plane were obtained, in both transverse electric (TE) and transverse magnetic (TM) of the polarization states of the light. It was observed that the molecular density changes caused by the materials in the urine sample changed primarily the optical parameters and indirectly the intensity distribution of the scattered light. Thus, with the contribution of standard data provided as a result of light scatter calculations from urine samples taken from people with normal and different diseases, it will be easier to diagnose diseases that will be encountered later.</p> </abstract>

Current state of the morphological assessment of urinary erythrocytes in The Netherlands: a nation-wide questionnaire

Background The morphological assessment of urinary erythrocytes (uRBC) is a convenient screening tool for the differentiation of nephrological (dysmorphic) and urological (isomorphic) causes of hematuria. Considering the morphological heterogeneity, this analysis is often perceived as difficult. There is no clear (inter)national consensus and there is a lack of external quality assessment programs. To gain insight into the heterogeneity within and between laboratories, we scrutinized the current state of this analysis in Dutch medical laboratories. Methods The laboratories, affiliated with the Dutch Foundation for Quality Assessment in Medical Laboratories, were invited to participate in a web-based survey, consisting of two questionnaires. The first one provided information about the institution and laboratory organization, and the second explored the variability in the morphological analysis of uRBC on the basis of categorization of 160 uRBC images. Statistical analysis was premised on binomial significance testing and principal component analysis. Results Nearly one third of the Dutch medical laboratories (65/191) with 167 staff members participated in the survey. Most of these laboratories (83%) were an integral part of secondary care. The statistical analysis of the evaluations of the participants in comparison to the consensus (three experts from two different medical laboratories) suggested a great degree of heterogeneity in the agreement. Nearly half of the participants consciously disagreed with the consensus, whereas one fifth demonstrated a random relationship with it. Conclusions In Dutch medical laboratories, results from morphological analysis of uRBC are heterogeneous, which point out the necessity for standardization and harmonization.

Lensfree Diffraction Reconstruction Approach Enables Early Detection of Cancer In Vitro Based on Molecular Diagnosis

Before there are any megascopic cancer clinical symptoms, molecular diagnosis is the main method for detecting cancer-associated gene and tumor marker. The existing detection facilities are all expensive, complicated to operate, and time-consuming, thereby making them difficult to popularize and benefit humans. In this study, we proposed a high-throughput and cost-effective approach, which enables accurate detection of extremely rare cancer cells based on molecular diagnosis of target tumor marker and a lensfree diffraction imaging platform. This approach achieves high-speed and high-quality reconstruction of huge images, which well solves the problem that precise recognition is almost impossible utilizing raw image because of significant pattern magnification and serious overlaps. Furthermore, the cells which are labeled with immune microbeads can be screened using the determined covered pixel sets, which are extracted in different focus reconstruction planes. The recognition strategy is implemented based on set intersection. With this method, the target cancer cells can be rapidly and accurately screened in a large number of benign cell samples. Besides, the detection equipment is cost-effective and easy to operate and popularize. It is expected to be widely used as a diagnostic tool for early detection of cancer.

The Use of Motion Analysis as Particle Biomarkers in Lensless Optofluidic Projection Imaging for Point of Care Urine Analysis

Urine testing is an essential clinical diagnostic tool. The presence of urine sediments, typically analyzed through microscopic urinalysis or cell culture, can be indicative of many diseases, including bacterial, parasitic, and yeast infections, as well as more serious conditions like bladder cancer. Current urine analysis diagnostic methods are usually centralized and limited by high cost, inconvenience, and poor sensitivity. Here, we developed a lensless projection imaging optofluidic platform with motion-based particle analysis to rapidly detect urinary constituents without the need for concentration or amplification through culture. A removable microfluidics channel ensures that urine samples do not cross contaminate and the lens-free projection video is captured and processed by a low-cost integrated microcomputer. A motion tracking and analysis algorithm is developed to identify and track moving objects in the flow. Their motion characteristics are used as biomarkers to detect different urine species in near real-time. The results show that this technology is capable of detection of red and white blood cells, Trichomonas vaginalis, crystals, casts, yeast and bacteria. This cost-effective device has the potential to be implemented for timely, point-of-care detection of a wide range of disorders in hospitals, clinics, long-term care homes, and in resource-limited regions.

Urine Sediment Recognition Method Based on Multi-View Deep Residual Learning in Microscopic Image

Urine sediment recognition is attracting growing interest in the field of computer vision. A multi-view urine cell recognition method based on multi-view deep residual learning is proposed to solve some existing problems, such as multi-view cell gray change and cell information loss in the natural state. Firstly, the convolutional network is designed to extract the urine sediment features from different perspectives based on the residual network, and the depth-wise separable convolution is introduced to reduce the network parameters. Secondly, Squeeze-and-Excitation block is embedded to learn feature weights, using feature re-calibration to improve network representation, and the robustness of the network is enhanced by adding spatial pyramid pooling. Finally, for further optimizing the recognition results, the Adam with weight decay optimization method is used to accelerate the convergence of the network model. Experiments on self-built urine microscopic image data-set show that our proposed method has state-of-the-art classification accuracy and reduces network computing time.

Diagnosis of Urinary Tract Infections by Urine Flow Cytometry: Adjusted Cut-Off Values in Different Clinical Presentations

Background

Bacterium and leucocyte counts in urine can be measured by urine flow cytometry (UFC). They are used to predict significant bacterial growth in urine culture and to diagnose infections of the urinary tract. However, little information is available on appropriate UFC cut-off values for bacterium and leucocyte counts in specific clinical presentations.

Objective

To develop, validate, and evaluate adapted cut-off values that result in a high negative predictive value for significant bacterial growth in urine culture in common clinical presentation subgroups.

Methods

This is a single center, retrospective, observational study with data from patients of the emergency department of Bern University Hospital, Switzerland, with suspected infections of the urinary tract. The patients presented with different symptoms, and urine culture and urine flow cytometry were performed. For different clinical presentations, the patients were grouped by (i) age (>65 years), (ii) sex, (iii) clinical symptoms (e.g., fever or dysuria), and (iv) comorbidities such as diabetes and immunosuppression. For each group, cut-off values were developed, validated, and analyzed using different strategies, i.e., linear discriminant analysis (LDA) and Youden's index, and were compared with known cut-offs and cut-offs optimized for sensitivity.

Results

613 patients were included in the study. Significant bacterial growth in urine culture depended on clinical presentation and ranged from 32.3% in male patients to 61.5% in patients with urinary frequency. In all clinical presentations, the predictive accuracy of UFC leucocyte and UFC bacterium counts was good for significant bacterial growth in urine culture (AUC ≥ 0.88). The adapted LDA₉₅ equations did not exhibit consistently high sensitivity. However, the in-house cut-offs (test positive if UFC leucocytes > 17/μL or UFC bacteria > 125/μL) were highly sensitive (>90%). In female, younger, and dysuric patients, even higher cut-offs for UFC leucocytes (169/μL, 169/μL, and 205/μL) exhibited high sensitivity. Specificity was insufficient (<0.9) for all tested cut-offs.

Conclusions

For various clinical presentations, significant bacterial growth in urine culture can be excluded if flow cytometry measurements give a bacterial count of ≤125/μL or a leucocyte count of ≤17/μL. In female patients, dysuric patients, and patients younger than ≤65 years, the leucocyte cut-off can be increased to 170/μL.

Proteinuria and the Clinical Course of Dobrava-Belgrade Hantavirus Infection

Purpose

Human infection with Dobrava-Belgrade virus (DOBV) in Northern Germany causes a mild form of hantavirus disease predominantly characterized by acute kidney injury due to interstitial nephritis. We evaluated the largest number of DOBV-infected patients so far regarding clinical course, proteinuria, and prognostic markers.

Patients and Methods

Patients with DOBV-associated hantavirus disease admitted to the Renal Division of the University of Lübeck (Germany) between 1997 and 2012 were included in this study. Symptoms, clinical course, laboratory parameters, and urinary protein analysis were investigated at admission (baseline, t₀), 3–5 days (t_3–5), 10–17 days (t_10–17), and after 1 year of follow-up (t₃₆₅).

Results

Of the 34 patients (male/female ratio: 23/11; age: 41 ± 14 years) included in the study, 4 underwent hemodialysis (HD). Glomerular filtration rate was 17 ± 14 mL/min at t₀ and increased to 27 ± 26 mL/min (t_3–5), 57 ± 20 mL/min (t_10–17), and 84 ± 16 mL/min (t₃₆₅). Albuminuria and tubular proteinuria (α₁- and β₂-microglobulin) decreased during follow-up; the urinary α₁-microglobulin concentration in patients who required HD was significantly higher than that in patients not requiring HD (t₀: 186 ± 51 vs. 45 ± 26 mg/g creatinine; t_3–5: 87 ± 14 vs. 32 ± 16 mg/g creatinine; t_10–17: 63 ± 18 vs. 28 ± 12 mg/g creatinine; p < 0.001).

Conclusions

DOBV infection of inpatients in Northern Germany is associated with severe kidney injury that recovers within a few weeks and normalizes within 1 year. Tubular proteinuria is associated with the severity of kidney injury and the necessity of renal replacement therapy in these DOBV-infected patients.

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

BACKGROUND

The most common diagnostic technique for the detection of malignant/atypical urothelial cells (m/AUC) is urinary cytology (Ucytol). Urinary sediment (Used) examination, often prescribed for asymptomatic, healthy subjects, can incidentally identify suspicious/AUC (s/AUC) in routine daily practice.

METHODS

Unstained, unfixed and uncentrifuged urine samples were analyzed with an automated intelligent microscopy (AIM) system. From January 2010, any incidental identification of s/AUC through expert revision of unclassified cell images was reported, according to internal protocols, as an additional note on the patients' laboratory report. Patients' symptomatology or previous history was unknown to the pathologist. All referrals from January 2010 to December 2014, with the s/AUC note, were reviewed and cross-referenced with Ucytol and histology data from a central database.

RESULTS

Of the 162 patients identified with s/AUC (0.1/1000 samples), 84% (n=136) performed further Ucytol and/or histological examinations. The sensitivity of the identification of non-transitory AUC at Used was 87.5%. Positive histological examinations were 91.2% classified as high-grade urothelial carcinoma.

CONCLUSIONS

Routine Used examination, with an AIM and expert revision, can identify the presence of AUC in a clinical laboratory setting, and for some subjects, may anticipate bladder carcinoma diagnosis.

Detection of significant bacteriuria by use of the iQ200 automated urine microscope

In the microbiology laboratory, there is an augmented need for rapid screening methods for the detection of bacteria in urine samples, since about two-thirds of these samples will not yield any bacteria or will yield insignificant growth when cultured. Thus, a reliable screening method can free up laboratory resources and can speed up the reporting of a negative urine result. In this study, we have evaluated the detection of leukocytes, bacteria, and a new sediment indicator, the "all small particles" (ASP), by an automated instrument, the iQ200 urine analyzer, to detect negative urine samples that can be excluded from culture. A coupled automated strip reader (iChem Velocity), enabling the detection of nitrite and leukocyte esterase, was tested in parallel. In total, 963 urine samples were processed through both conventional urine culture and the iQ200/iChem Velocity workstation. Using the data, a multivariate regression model was established, and the predicted specificity and the possible reduction in urine cultures were calculated for the indicators and their respective combinations (leukocytes plus bacteria plus ASP and leukocyte esterase plus nitrite). Among all options, diagnostic performance was best using the whole microscopic content of the sample (leukocytes plus bacteria plus ASP). By using a cutoff value of ≥ 10(4) CFU/ml for defining a positive culture, a given sensitivity of 95% resulted in a specificity of 61% and a reduction in urine cultures of 35%. By considering the indicators alone, specificity and the culture savings were both much less satisfactory. The regression model was also used to determine possible cutoff values for running the instrument as part of daily routine. By using a graphical representation of all combinations possible, we derived cutoff values for leukocyte, bacterial, and ASP count, which should enable the iQ200 microscope to screen out approximately one-third of the urine samples, significantly reducing the workload in the microbiology laboratory.

Pursuing type 1 diabetes mellitus and related complications through urinary proteomics

Diabetes mellitus is a chronic metabolic disease with multiple complications, and its successful management requires early diagnosis, to allow timely interventions. Here, we have comprehensively analyzed the proteome changes in urine of type 1 diabetic subjects with and without complications such as retinopathy and nephropathy. gel electrophoresis combined to liquid chromatography-tandem mass spectrometry (GeLC-MS/MS) analysis of midstream urine highlighted the mechanisms involved in disease pathogenesis as, for instance wound healing and blood coagulation in all diabetics or altered ganglioside metabolism in retinopathy, and also some urinary proteins with potential diagnosis value. From these, gelsolin and antithrombin-III appear as promising diagnosis markers for type 1 diabetes mellitus (T1DM), whereas ephrin type-B receptor 4 and vitamin K-dependent protein Z seem to be promising markers for advanced T1DM disease state presenting retinopathy and nephropathy (T1DM-R + N). Data also suggest urinary ganglioside GM2 activator and beta-hexosaminidase subunit beta as potential urinary markers of retinopathy in diabetics. Taken together, the present exploratory urinary proteomic analysis might be seen as an important starting point for studies targeting specific urinary proteins aimed at the implementation of new biomarkers for the early detection of T1DM-related microvascular complications.

Preanalytical requirements of urinalysis

Urine may be a waste product, but it contains an enormous amount of information. Well-standardized procedures for collection, transport, sample preparation and analysis should become the basis of an effective diagnostic strategy for urinalysis. As reproducibility of urinalysis has been greatly improved due to recent technological progress, preanalytical requirements of urinalysis have gained importance and have become stricter. Since the patients themselves often sample urine specimens, urinalysis is very susceptible to preanalytical issues. Various sampling methods and inappropriate specimen transport can cause important preanalytical errors. The use of preservatives may be helpful for particular analytes. Unfortunately, a universal preservative that allows a complete urinalysis does not (yet) exist. The preanalytical aspects are also of major importance for newer applications (e.g. metabolomics). The present review deals with the current preanalytical problems and requirements for the most common urinary analytes.

A sensitive quantitative test strip based point-of-care albuminuria screening assay

BACKGROUND

Chronic kidney disease is a major health problem and the global guidelines require screening of albuminuria. Therefore, affordable and sensitive albuminuria screening tests are needed. We explored the potential of urine strips, generally reported in the ordinal scale, measured on an automatic strip reader for reporting quantitative and sensitive albumin results.

METHODS

We compared reflectance data of Combur-Test® strips obtained from the Cobas U411 reader (Roche) with albuminuria data from a nephelometer BNII (Siemens) and with protein concentrations from the pyrogallol red method (Modular P, Roche) for 389/328 non-pathologic and pathologic urine samples, respectively.

RESULTS

Imprecision of the reflectance signal of the Cobas U411 was measured with commercial control material (Bio-Rad). Inter-run coefficients of variations (CVs) for reflectance for levels 1 and 2 were 1.7%/4.9%, respectively, and intra-run CVs were 1.8%/4.2%, respectively. Good agreement was obtained between the albumin concentration of the BNII and the protein strip reflectance data (n=389): Y (10,000/protein reflectance, 1/%)=160+0.132·X (albuminuria BNII, mg/L)-0.0000111·X2 (albuminuria BNII, mg/L); r2=0.921. Lower agreement was found between the protein assay (n=328) and the reflectance (r2=0.831). A calibration curve was made between 11.5 mg/L and 121.5 mg/L. The limit of blank (LOB) was 44.7 mg/L.

CONCLUSIONS

The present study demonstrates that reflectance data generated by a test strip reader allows for quantitative analysis of albumin. Although the lower limit of the microalbumin range (30 mg/L) cannot be achieved with the dye-binding method, the results are satisfactory for screening purposes.

A simple and smart telemedicine device for developing regions: a pocket-sized colorimetric reader

We have proposed a novel mobile healthcare platform, combining a pocket-sized colorimetric reader (13.5 × 6.5 × 2.5 cm(3)) and commercially available 10-parameter urinalysis paper strips (glucose, protein, glucose, bilirubin, urobilinogen, ketones, nitrite, pH, specific gravity, erythrocytes, and leukocytes), capable of sending data with a smart phone. The reader includes a novel colorimetric multi-detection module, which consists of three-chromatic light-emitting diodes, silicon photodiodes and a novel poly(methylmethacrylate) (PMMA) optical splitter. We employed data reading methods using conversions of the signal data (red, blue, and green) to the hue (H) color map or the Y model data, and used a curve-fitting method for the quantification. The reader is battery-powered, inexpensive, light-weight, and very speedy in analysis. And, it was applied to detection of a thousand of human urine samples and demonstrated reliable quantification of urinary glucose and protein. The features can be used by unskilled people on-site to transfer the analyzed data to experts off-site.

The pre-analytical challenges of routine urinalysis

An effective diagnostic strategy for urinalysis should be based on standard procedures for collection, transport, sample preparation and analysis. In view of a better reproducibility of the analyses, the pre-analytical requirements become stricter. Various sample methods can cause significant pre-analytical errors. It is a challenge for the laboratory to control the steps in the pre-analytical phase that contribute to pre-analytical variability. To reduce the variability, it is necessary to look at the pre-analytical process as a complete entity, from test ordering to the moment of specimen processing. Clinical laboratories are responsible for the clinical and financial outcome of this phase. In a culture of increasing productivity, lower costs and improving quality, the challenge is to use several tools designed to standardize and optimize urinalysis. Despite advances in the performance of analytic systems, the pre-analytical phase of modern urinalyses has not been studied very thoroughly. This review of the literature lights on different problems in current pre-analytical requirements for particle and test strip analysis of urine samples.