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Open AccessArticle

Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care

1
Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
2
Pat Walker Health Center, University of Arkansas, Fayetteville, AR 72701, USA
*
Author to whom correspondence should be addressed.
Diagnostics 2019, 9(3), 122; https://doi.org/10.3390/diagnostics9030122
Received: 29 August 2019 / Revised: 11 September 2019 / Accepted: 16 September 2019 / Published: 18 September 2019
(This article belongs to the Section Point-of-Care Diagnostics and Devices)
A urinary tract infection (UTI) can be diagnosed via urinalysis, consisting of a dipstick test and manual microscopic examination. Point-of-care (POC) image-based systems have been designed to automate the microscopic examination for low-volume laboratories or low-resource clinics. In this pilot study, acridine orange (AO) was evaluated as a fluorescence-based contrast agent to aid in detecting and enumerating urine sediment specific for diagnosing a UTI. Acridine orange staining of epithelial cells, leukocytes, and bacteria provided sufficient contrast to successfully implement image segmentation techniques, which enabled the extraction of classifiable morphologic features. Surface area bounded by each cell border was used to differentiate the sediment; epithelial cells were larger than 500μm2, bacteria were less than 30μm2, and leukocytes in between. This image-based semi-automated technique using AO resulted in similar cell counts to the clinical results, which demonstrates the feasibility of AO as an aid for POC urinalysis systems. View Full-Text
Keywords: urinalysis; urinary tract infection; acridine orange; fluorescence; point-of-care; cell classification urinalysis; urinary tract infection; acridine orange; fluorescence; point-of-care; cell classification
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MDPI and ACS Style

Powless, A.J.; Prieto, S.P.; Gramling, M.R.; Conley, R.J.; Holley, G.G.; Muldoon, T.J. Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care. Diagnostics 2019, 9, 122.

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