Method for single cell antimicrobial susceptibility testing in a sub-doubling time

A system for antibacterial susceptibility testing of a single-cell sample, comprising:

• a sample holder;
• an image sensor positioned to obtain one or more images of a sample held in the sample holder;
• a processor in electronic communication with the image sensor, wherein the processor is configured to:
• receive from the image sensor a series of images of a sample over time after exposure to an antimicrobial agent;
• extract, for each image of the series of images, values of each feature in a set of morphological features of the sample, wherein the set of morphological features comprises one or more of area, aspect ratio, length, circularity, perimeter, angularity, curvature, ferret, pole, roundness, sinuosity, width, trajectory, and z-score;
• calculate a rate of change for each feature of the set of morphological features during the imaging period;
• and
• determine an inhibition status of the sample using a machine-learning classifier applied to input data comprising the rate of change for each feature of the set of morphological features.

A non-transitory computer-readable medium having stored thereon a computer program for instructing a computer, the computer program comprising:

• receive from an image sensor a series of images of a sample over time after exposure to an antimicrobial agent;
• extract, for each image of the series of images, values of each feature in a set of morphological features of the sample, wherein the set of morphological features comprises one or more of area, aspect ratio, length, circularity, perimeter, angularity, curvature, ferret, pole, roundness, sinuosity, width, trajectory, and z-score;
• calculate a rate of change for each feature of the set of morphological features during the imaging period;
• and
• determine an inhibition status of the sample using a machine-learning classifier applied to input data comprising the rate of change for each feature of the set of morphological features.