Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care
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 stu...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-09-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/9/3/122 |
| _version_ | 1811183807939739648 |
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| author | Amy J. Powless Sandra P. Prieto Madison R. Gramling Roxanna J. Conley Gregory G. Holley Timothy J. Muldoon |
| author_facet | Amy J. Powless Sandra P. Prieto Madison R. Gramling Roxanna J. Conley Gregory G. Holley Timothy J. Muldoon |
| author_sort | Amy J. Powless |
| collection | DOAJ |
| description | 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 500μm<sup>2</sup>, bacteria were less than 30μm<sup>2</sup>, 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. |
| first_indexed | 2024-04-11T13:02:51Z |
| format | Article |
| id | doaj.art-8b370a40c5d74ca6a247b93d665cc2ee |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-04-11T13:02:51Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-8b370a40c5d74ca6a247b93d665cc2ee2022-12-22T04:22:52ZengMDPI AGDiagnostics2075-44182019-09-019312210.3390/diagnostics9030122diagnostics9030122Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-CareAmy J. Powless0Sandra P. Prieto1Madison R. Gramling2Roxanna J. Conley3Gregory G. Holley4Timothy J. Muldoon5Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USADepartment of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USAPat Walker Health Center, University of Arkansas, Fayetteville, AR 72701, USAPat Walker Health Center, University of Arkansas, Fayetteville, AR 72701, USAPat Walker Health Center, University of Arkansas, Fayetteville, AR 72701, USADepartment of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USAA 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 500μm<sup>2</sup>, bacteria were less than 30μm<sup>2</sup>, 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.https://www.mdpi.com/2075-4418/9/3/122urinalysisurinary tract infectionacridine orangefluorescencepoint-of-carecell classification |
| spellingShingle | Amy J. Powless Sandra P. Prieto Madison R. Gramling Roxanna J. Conley Gregory G. Holley Timothy J. Muldoon Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care Diagnostics urinalysis urinary tract infection acridine orange fluorescence point-of-care cell classification |
| title | Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care |
| title_full | Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care |
| title_fullStr | Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care |
| title_full_unstemmed | Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care |
| title_short | Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care |
| title_sort | evaluation of acridine orange staining for a semi automated urinalysis microscopic examination at the point of care |
| topic | urinalysis urinary tract infection acridine orange fluorescence point-of-care cell classification |
| url | https://www.mdpi.com/2075-4418/9/3/122 |
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