Method and system for characterizing cell motion
Inventors
Maddah, Seyyedeh Mahnaz • Loewke, Kevin
Assignees
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Publication Number
US-9355459-B2
Publication Date
2016-05-31
Expiration Date
Abstract
A method and system for characterizing cell motion comprising: receiving image data corresponding to a set of images of a cell culture captured at a set of time points; segmenting, from at least one image of the set of images, a cell subpopulation from the cell culture; determining a resting signal for the cell subpopulation; determining a single-peak motion signal based upon the set of images, the set of time points, and the resting signal; detrending the single-peak motion signal of the cell subpopulation based upon the resting signal; determining values of a set of motion features of the cell subpopulation, thereby characterizing cell motion; and clustering the cell subpopulation with at least one other cell subpopulation based upon at least one of the single-peak motion signal and a value of the set of motion features.
Core Innovation
The invention characterizes cell motion from time-lapse image data of a cardiomyocyte culture or a cell culture captured at set time points. The method receives the image data and performs a time-domain-based determination of a multi-peak motion signal for a cell subpopulation across a subset of the images, then compares the multi-peak motion signal to a threshold condition to determine a resting signal associated with a reference image.
Based on the comparison and selection of resting-state images having high similarity to an immediately adjacent image, the invention determines a resting signal and derives a single-peak motion signal using the image dataset, the set of time points, and the reference image. The determination of motion signals supports generating values of motion features, including beating features for cardiomyocyte subpopulations such as beating duration, beating frequency, and beating irregularity.
In further aspects, the invention segments cell subpopulations and determines how subpopulations relate to one another by clustering based on single-peak motion signals and/or motion-feature values. The approach can segment subpopulation motion regions, represent regions with descriptor vectors derived from motion signals, and perform hierarchical clustering based on pairwise distances. The invention can also characterize responses of the cardiomyocyte culture to a drug dosage chemical factor by comparing beating features under conditions with and without the chemical factor.
Claims Coverage
The document includes three independent claims. They cover a cardiomyocyte subpopulation method that derives multi-peak and single-peak motion signals and beating features, a more general cell-motion method that includes subpopulation clustering, and a system that performs the same motion characterization and transmits motion features for user monitoring.
Time-domain multi-peak motion signal and resting signal using threshold condition
A method receiving image data of a cardiomyocyte culture captured at set time points; performing a time-domain-based determination of a multi-peak motion signal for a cardiomyocyte subpopulation across a subset of the images; generating a comparison between values of the multi-peak motion signal and a threshold condition; determining a resting signal with an associated reference image based upon the comparison across a subset of the images, including identifying a subset of resting-state images with high similarity to an immediately adjacent image.
Single-peak motion signal and beating features for cardiomyocyte subpopulation
A method determining a single-peak motion signal based upon the set of images, the set of time points, and the reference image; and determining values of a set of beating features of the cardiomyocyte subpopulation based upon at least one of the multi-peak motion signal and the single-peak motion signal, wherein the set of beating features includes at least one of beating duration, beating frequency, and beating irregularity, thereby characterizing cell motion.
Resting signal based on multi-peak motion signal and clustering of cell subpopulations
A method receiving image data of a cell culture captured at set time points; segmenting, from at least one image, a cell subpopulation; determining a resting signal with an associated reference image based upon a time domain-based determination of a multi-peak motion signal across a subset of the images; determining a single-peak motion signal based upon the image dataset, the set of time points, and the reference image; determining values of a set of motion features based upon at least one of the multi-peak motion signal and the single-peak motion signal, thereby characterizing cell motion; and after segmenting, clustering the cell subpopulation with at least one other cell subpopulation based upon at least one of the single-peak motion signal and a value of the set of motion features.
System with imaging module, processing subsystem, and transmission of motion features
A system for characterizing cell motion of a cell culture and facilitating cell culture monitoring by a user, comprising an imaging module generating an image dataset corresponding to images captured at set time points; a processing subsystem including a first module receiving the image dataset, a second module segmenting a cell subpopulation from at least one image, a third module determining a resting signal with an associated reference image based upon a comparison of values of the multi-peak motion signal and the threshold condition across a subset of the image dataset, a fourth module determining a single-peak motion signal based upon the image dataset, the set of time points, and the reference image, and a fifth module determining values of a set of motion features to characterize cell motion; and a transmission module transmitting values of the set of motion features to a device of the user.
Across the independent claims, the core claim coverage is directed to deriving resting signals and reference images from multi-peak motion signals via a threshold comparison, deriving a single-peak motion signal using the reference image, and computing motion features including beating features for cardiomyocyte subpopulations. The claims also cover clustering cell subpopulations based on single-peak motion signals and/or motion-feature values, and system-level monitoring through transmission of computed motion-feature values to a user device.
Stated Advantages
Characterizing cell motion by determining beating features including beating duration, beating frequency, and beating irregularity.
Facilitating cell culture monitoring by transmitting values of the set of motion features to a device of the user.
Documented Applications
Characterizing a cardiomyocyte culture by computing beating features from time-lapse image data.
Clustering subpopulations within a cell culture based on motion signals and/or motion-feature values.
Characterizing responses of a cardiomyocyte culture to a drug dosage chemical factor by comparing beat duration, beating frequency, and/or beating irregularity under conditions with and without the chemical factor.
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