Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/113627
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Type: Journal article
Title: Evaluation of an image analysis device (APAS) for screening urine cultures
Author: Glasson, J.
Hill, R.
Summerford, M.
Giglio, S.
Citation: Journal of Clinical Microbiology, 2016; 54(2):300-304
Publisher: American Society for Microbiology
Issue Date: 2016
ISSN: 0095-1137
1098-660X
Editor: Onderdonk, A.
Statement of
Responsibility: 
John Glasson, Rhys Hill, Michael Summerford, Steven Giglio
Abstract: While advancements have been made in some areas of pathology with diagnostic materials being screened using image analysis technologies, the reporting of cultures from agar plates remains a manual process. We compared the results for 2,163 urine cultures read by a reference panel of microbiologists, by the routine laboratory process, and by an automated plate reading system, APAS (LBT Innovations Ltd., South Australia). APAS detected colonies with a sensitivity of 99.1% and a specificity of 99.3% on blood agar, while on MacConkey agar, the colony detection sensitivity was 99.4% with a specificity of 99.3%. The device's ability to enumerate growth had an accuracy of 89.2%, and the morphological identification of colonies showed a high level of performance for the colony types typical of Escherichia coli and other enteric bacilli. On blood agar, lactose-fermenting colonies were morphologically identified with a sensitivity of 98.9%, while on MacConkey agar they were identified with a sensitivity of 99.2%. In this first clinical evaluation, APAS demonstrated high performance in the detection, enumeration, and colony classification of isolates compared with that for conventional plate-reading methods. The device found all cases reported by the laboratory and detected the most commonly encountered organisms found in urinary tract infections.
Keywords: Bacteriological techniques
Rights: Copyright © 2016 Glasson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.
DOI: 10.1128/JCM.02365-15
Published version: http://dx.doi.org/10.1128/jcm.02365-15
Appears in Collections:Aurora harvest 8
Computer Science publications

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