Efficient automated semi-quantitative urine culture analysis via BD Urine Culture App

Uwamino, Yoshifumi; Nagata, Morio; Aoki, Wataru; Kato, Atsushi; Daigo, Miho; Ishihara, Osamu; Igari, Hirotaka; Inose, Rika; Hasegawa, Naoki; Murata, Mitsuru

doi:10.1016/j.diagmicrobio.2021.115567

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…Total lab automation, combined with automated analysis of the plates using digital imaging and artificial intelligence software, has spread in clinical microbiology laboratories in recent years ( 10 , 11 ). Solutions such as PhenoMATRIX, WASPLab Image Analysis Software, or the BD Urine Culture App have mainly been developed for automated colony count and color analysis on chromogenic agar plates for urine samples, but also for the screening of MDR bacteria ( 1 , 8 , 12 , 13 ). Global agreements with standard detection techniques are above 90% ( 1 , 12 , 13 ).…”

Section: Discussionmentioning

confidence: 99%

“…Solutions such as PhenoMATRIX, WASPLab Image Analysis Software, or the BD Urine Culture App have mainly been developed for automated colony count and color analysis on chromogenic agar plates for urine samples, but also for the screening of MDR bacteria ( 1 , 8 , 12 , 13 ). Global agreements with standard detection techniques are above 90% ( 1 , 12 , 13 ). A 100% sensitivity comes at the price of a lower specificity (around 80–90%), and these solutions have been demonstrated to reduce the turnaround times for negative results ( 8 , 14 ).…”

Section: Discussionmentioning

confidence: 99%

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Rapid and automated screening of carbapenemase- and ESBL-producing Gram-negative bacteria from rectal swabs using chromogenic agar media and the ScanStation device

Peyroux,

Almahmoudh,

Prebe-Coquerel

et al. 2023

Microbiol Spectr

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The ScanSation 100 device (Interscience, France) is an incubator allowing real-time detection of bacterial colony growth by frequently imaging agar plates over time, counting CFU, and detecting colony color. This study evaluated its performance for the early detection of carbapenemase-producing bacteria (CPB) and extended-spectrum β-Lactamase-producing bacteria (ESBL-PB) from rectal swabs inoculated on CHROMagar mSuperCARBA and ESBL media, respectively. Rectal screening ESwabs collected from patients admitted to Grenoble University Hospital between January and June 2021 were analyzed. After inoculation, chromogenic media were incubated for 24 h in the automaton, with image acquisition every 30 min. ScanStation results were compared to visual observations of the plates after 24 h of incubation. In total, 501 rectal swabs were tested. ScanStation showed 100% positive percent agreement (PPA) for the detection of CPB and ESBL-PB, whereas the PPA of color categorization ranged between 45% and 100%. Negative percent agreement (NPA) ranged between 70% and 98%. Negative predictive values (NPVs) were 100% for both bacterial groups, whereas positive predictive values (PPVs) were 70.3% for CPB and 81.0% for ESBL-PB. Importantly, real-time screening allowed detection of the first suspected colony within 10–14 h of growth, on average, whereas visual observation is usually only performed once a day after 18–24 h of incubation. Our study demonstrates the potential use of early images to accelerate the detection of CPB and ESBL-PB and implement effective and timely infection control measures. IMPORTANCE The ScanStation 100 device is an incubator able to follow the real-time growth of bacterial colonies on agar plates through digital imaging, allowing users to sort plates according to the presence or absence of colonies, and to distinguish their color using four numeric color filters. Real-time screening shows that first colony detection is possible much earlier (after 10–14 h of growth, on average), whereas visual observation is usually performed only once a day after 18–24 h of incubation. The ScanStation device, combined with chromogenic agar media, is an efficient automated screening method to accelerate the detection of Gram-negative multidrug-resistant bacteria in laboratories that do not have access to larger laboratory automation systems. Our study shows that setting the image acquisition to one or two early images may allow for the detection of positive samples that were inoculated in the morning, by the end of the working day.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Rapid and automated screening of carbapenemase- and ESBL-producing Gram-negative bacteria from rectal swabs using chromogenic agar media and the ScanStation device

Peyroux,

Almahmoudh,

Prebe-Coquerel

et al. 2023

Microbiol Spectr

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“…The Copan WASP instrument was utilized in this study as part of both the SOC and the APAS workflows ( 10 ). The use of digital images for interpretation of urine plates has been demonstrated using Copan WASPLab segregation software ( 20 ) and BD Kiestra ( 21 ). However, these current platforms do require the user to inspect and verify the segregated results.…”

Section: Discussionmentioning

confidence: 99%

Comparison of the APAS Independence Automated Plate Reader System with the Manual Standard of Care for Processing Urine Culture Specimens

et al. 2022

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“…It is also somewhat risky to expect algorithms to “learn” as they go and adapt sample by sample in an uncontrolled manner. Certainly, the fixed algorithm approach has generated enough evidence to demonstrate that the use of these technologies is low risk to patients, demonstrated by high sensitivities/positive percent agreements (PPA) and high negative predictive values ( Faron et al, 2016 ; Brenton et al, 2020 ; Uwamino et al, 2022 ). It may also be a stretch to think that AI will reliably identify organisms in a reproducible manner, without any additional confirmatory work (unless indicated by media manufacturers).…”

mentioning

confidence: 99%

Microbiology 2.0–A “behind the scenes” consideration for artificial intelligence applications for interpretive culture plate reading in routine diagnostic laboratories

DeYoung¹,

Morales²,

Giglio³

2022

Front. Microbiol.

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Laboratory automation with Artificial Intelligence (AI) features have now emerged into routine diagnostic clinical use to interpret growth on agar plates. Applications are currently limited to urine samples and infection control screens, yet some of the details around the development of algorithms remain entrenched with AI development specialists and are not well understood by laboratorians. The generation of algorithms is not a trivial task and is a highly structured process, with several considerations needed to develop the appropriate data for specific intended uses. Understanding these considerations highlights the limitations of any algorithm created and informs better design practices so that algorithm objectives can be thoroughly tested prior to routine use.

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Efficient automated semi-quantitative urine culture analysis via BD Urine Culture App

Cited by 7 publications

References 8 publications

Rapid and automated screening of carbapenemase- and ESBL-producing Gram-negative bacteria from rectal swabs using chromogenic agar media and the ScanStation device

Rapid and automated screening of carbapenemase- and ESBL-producing Gram-negative bacteria from rectal swabs using chromogenic agar media and the ScanStation device

Comparison of the APAS Independence Automated Plate Reader System with the Manual Standard of Care for Processing Urine Culture Specimens

Microbiology 2.0–A “behind the scenes” consideration for artificial intelligence applications for interpretive culture plate reading in routine diagnostic laboratories

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