Aller au contenu principal
Accès ouvert déclaré 2026 article

P-1996. Performance Evaluation of an Artificial-Intelligence-Driven Single-Cell Imaging Platform for Rapid Phenotypic Antimicrobial Susceptibility Testing

1Citations signalées — pas une note de qualité
2Institutions déclarées
1Pays d’affiliation déclarés

Résumé fourni par la source

Abstract Background Conventional microbiological methods require several days from specimen receipt to organism identification and antimicrobial susceptibility testing (AST), delaying appropriate therapy. We evaluated an early prototype of the PhAST assay, a novel artificial-intelligence (AI)-driven single-cell imaging platform for rapid phenotypic AST. Methods The prototype PhAST assay was developed to provide bacterial identification at the group level defined by the Clinical and Laboratory Standards Institute, and phenotypic AST results were obtained in ninety minutes, directly from a positive blood culture. Susceptibility was determined by AI-based quantitative analysis of single-cell phenotypes from images and videos of antibiotic-exposed and untreated cells (Figure 1). The assay was performed on positive blood culture broth samples flagged by a routine blood culture system obtained from the clinical laboratory. Only samples containing Gram-negative bacteria were tested. We also measured the time to result (TTR) of the assay. Broth microdilution (BMD) was performed in triplicate as the reference method. Results from the commercial automated AST system (VITEK2) were also assessed against BMD. Results A total of 122 Enterobacterales, including 69 (56.6%) Escherichia coli, 37 (30.3%) Klebsiella pneumoniae, and 6 (4.9%) Enterobacter cloacae complex, were identified. Resistance to third-generation cephalosporins was observed in 54 (44.3%) of the isolates, based on BMD results. The prototype PhAST assay showed a mean (± standard deviation) TTR of 117 (± 3) minutes. The assay achieved favorable results, with a categorical agreement (CA) of 95.1%, and very major error (VME), major error (ME), and minor error (mE) rates of 0.2%, 1.1%, and 3.6%, respectively (Table 1). The commercial AST system exhibited CA, ME, and mE rates of 93.9%, 0.4%, and 3.9%, respectively, with a slightly high VME rate of 1.9%. Conclusion The prototype PhAST assay provided acceptable performance for Enterobacterales within two hours of blood culture positivity. This rapid phenotypic AST assay has significant potential to support timely clinical decision-making. Further expansion to additional organisms and antibiotics could enhance its clinical utility. Disclosures Jeong Su Park, M.D. / Ph.D., PhAST Corp.: Advisor/Consultant|PhAST Corp.: Grant/Research Support Kyoung-Ho Song, MD, PhD, PhAST Corp.: Advisor/Consultant|PhAST Corp.: Grant/Research Support

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
P-1996. Performance Evaluation of an Artificial-Intelligence-Driven Single-Cell Imaging Platform for Rapid Phenotypic Antimicrobial Susceptibility Testing
Date Crossref
01/01/2026
Éditeur
Oxford University Press (OUP)
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Sujets associés

Bacterial Identification and Susceptibility TestingCell Image Analysis TechniquesBiosensors and Analytical Detection

BNTIC News n’est pas le producteur de ces données. Recherche à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, ROR et la Banque mondiale, sans clé ; OpenAlex reste optionnel. Aucun service payant requis, aucune donnée externe enregistrée en base. Sources et limites.