Clinical evaluation of the APAS® Independence: Automated imaging and interpretation of urine cultures using artificial intelligence with composite reference standard discrepant resolution

Brenton, Lisa; Waters, Mary Jo; Stanford, Tyman; Giglio, Steven

doi:10.1016/j.mimet.2020.106047

Cited by 9 publications

(7 citation statements)

References 22 publications

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“…There are several publications on the high accuracy of automated plate reading of urine cultures by the APAS system ( 12 – 14 ). In addition to our study, one other evaluation assessing a similar MRSA analysis module was reported by Aurbach et al ( 15 ).…”

Section: Discussionmentioning

confidence: 99%

Comparison of an Automated Plate Assessment System (APAS Independence) and Artificial Intelligence (AI) to Manual Plate Reading of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus CHROMagar Surveillance Cultures

et al. 2021

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Background: The Automated Plate Assessment System (APAS Independence) [Clever Culture System, Bäch, Switzerland] is an automated imaging station linked with interpretive software that detects target colonies of interest on chromogenic media and sorts samples as negative or presumptive positive. We evaluated the accuracy of the APAS to triage methicillin-resistant Staphylococcus aureus (MRSA) and S. aureus ) cultures using chromogenic media compared to human interpretation. Methods: Patient samples collected from the nares on Eswabs were plated to BD BBL™ CHROMagar™ MRSA II and BD BBL CHROMagar Staph aureus and allowed to incubate for 20-24 h at 37°C in non-CO2. Mauve colonies are suggestive of S. aureus and were confirmed with latex agglutination. Following incubation, samples were first interrogated by APAS before being read by a trained technologist blinded to the APAS interpretation. The triaging by both APAS and the technologists were compared for accuracy. Any discordant results required further analysis by a third reader. Results: Over a five-month period, 5,913 CHROMagar MRSA cultures were evaluated. Of those, 236 were read as concordantly positive, 5,525 were read as concordantly negative, and 152 required discordant analysis. Positive and negative percent agreements (PPA, NPA) were 100% and 97.3%, respectively. The APAS detected 5 positive cultures that were missed by manual reading, and determined to be true positives. In a separate analysis, 744 CHROMagar Staph aureus plates were read in parallel. Of these, 133 were concordantly positive, 585 were concordantly negative, and 26 required discordant analysis. PPA and NPA were 95.7% and 96.7%, respectively. Conclusion: This study confirmed the high sensitivity of digital image analysis by the APAS Independence such that negative cultures can be reliably reported without technologist intervention (NPV 100% for CHROMagar MRSA and 99.0% for CHROMagar Staph aureus). Triaging using the APAS Independence may provide great efficiencies in a laboratory with high throughput of MRSA and S. aureus surveillance cultures.

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Section: Discussionmentioning

confidence: 99%

Comparison of an Automated Plate Assessment System (APAS Independence) and Artificial Intelligence (AI) to Manual Plate Reading of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus CHROMagar Surveillance Cultures

et al. 2021

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“…With the APAS system, laboratories can expedite the overall diagnostic process by reducing plate sorting times (processing up to 200 plates per hour) and allowing technicians to prioritize the analysis of positive cultures rather than evaluating the plates for all the negative cultures ( 4 ). The system functions by relying upon artificial intelligence to interpret growth patterns on urine plates and determine whether that growth may be clinically significant ( 12 – 14 ).…”

Section: Introductionmentioning

confidence: 99%

“…Conventional microbiology laboratories are highly reliant upon manual labor and the interpretative assessments of laboratory technicians ( 12 ). Unfortunately, many laboratories are experiencing labor shortages of trained and skilled staff, with an average vacancy rate of 7.2% among all laboratory departments and a vacancy rate of 7.26% across the western United States ( 15 ).…”

Section: Introductionmentioning

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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“…Non-consensus results between microbiologists have also been reported by Glasson et al (2016) who found that agreement between microbiologists for colony morphology is 97.5% when reading MacConkey agar but only 87.5% when reading blood agar. Similarly, Brenton et al (2020) identified that microbiologists agree 88.6% of the time when enumerating bi-plate growths. Who would have thought microbiologists can’t agree?…”

mentioning

confidence: 99%

“…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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Clinical evaluation of the APAS® Independence: Automated imaging and interpretation of urine cultures using artificial intelligence with composite reference standard discrepant resolution

Cited by 9 publications

References 22 publications

Comparison of an Automated Plate Assessment System (APAS Independence) and Artificial Intelligence (AI) to Manual Plate Reading of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus CHROMagar Surveillance Cultures

Comparison of an Automated Plate Assessment System (APAS Independence) and Artificial Intelligence (AI) to Manual Plate Reading of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus CHROMagar Surveillance Cultures

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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