Antimicrobial susceptibility testing with large-volume light scattering imaging and deep learning video microscopy

• Main Authors: Yu, Hui, Tao, Nongjian, Wang, Shaopeng
• Format: Patent
• Language: English
• Published: 05.12.2023
• Subjects: BEER; BIOCHEMISTRY; CALCULATING; CHEMISTRY; COMPOSITIONS OR TEST PAPERS THEREFOR; COMPUTING; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES; COUNTING; ENZYMOLOGY; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES; MEASURING; MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS; METALLURGY; MICROBIOLOGY; MUTATION OR GENETIC ENGINEERING; PHYSICS; PROCESSES OF PREPARING SUCH COMPOSITIONS; SPIRITS; TESTING; VINEGAR; WINE

A method for deep learning video microscopy-based antimicrobial susceptibility testing of a bacterial strain in a sample by acquiring image sequences of individual bacterial cells of the bacterial strain in a subject sample before, during, and after exposure to each antibiotic at different concentrations. The image sequences are compressed into static images while preserving essential phenotypic features. Data representing the static images is input into a pre-trained deep learning (DL) model which generates output data; and antimicrobial susceptibility for the bacterial strain is determined from the output data.