%0 Journal Article %A Fowler, Philip W. %A Gibertoni Cruz, Ana LuĂ­za %A Hoosdally, Sarah J. %A Jarrett, Lisa %A Borroni, Emanuele %A Chiacchiaretta, Matteo %A Rathod, Priti %A Lehmann, Sarah %A Molodtsov, Nikolay %A Walker, Timothy M. %A Robinson, Esther %A Hoffmann, Harald %A Peto, Timothy E. A. %A Cirillo, Daniela Maria %A Smith, Grace E. %A Crook, Derrick W. %T Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis %D 2018 %J Microbiology, %V 164 %N 12 %P 1522-1530 %@ 1465-2080 %R https://doi.org/10.1099/mic.0.000733 %K image processing %K microtitre plates %K tuberculosis %K drug susceptibility testing %K antibiotic resistance %K Mycobacterium tuberculosis %I Microbiology Society, %X M. tuberculosis grows slowly and is challenging to work with experimentally compared with many other bacteria. Although microtitre plates have the potential to enable high-throughput phenotypic testing of M. tuberculosis, they can be difficult to read and interpret. Here we present a software package, the Automated Mycobacterial Growth Detection Algorithm (AMyGDA), that measures how much M. tuberculosis is growing in each well of a 96-well microtitre plate. The plate used here has serial dilutions of 14 anti-tuberculosis drugs, thereby permitting the MICs to be elucidated. The three participating laboratories each inoculated 38 96-well plates with 15 known M. tuberculosis strains (including the standard H37Rv reference strain) and, after 2 weeks' incubation, measured the MICs for all 14 drugs on each plate and took a photograph. By analysing the images, we demonstrate that AMyGDA is reproducible, and that the MICs measured are comparable to those measured by a laboratory scientist. The AMyGDA software will be used by the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) to measure the drug susceptibility profile of a large number (>30000) of samples of M. tuberculosis from patients over the next few years. %U https://www.microbiologyresearch.org/content/journal/micro/10.1099/mic.0.000733