Neural network-enabled multiparametric impedance signal templating for high throughput single-cell deformability cytometry under viscoelastic extensional flows
AssigneeUniversity of Virginia Licensing & Ventures Group
InventorsNathan Swami, Abdullah-Bin Siddique, Mohammad Javad Azizi Jarmoshti
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Abstract
An exemplary microfluidic high-throughput cytometry system and method that employ AI/ML-based analysis and impedance-based measurements of heterogeneous population of cells and biological particles in viscoelastic flow within hyperbolic extensional channels of a microfluidic device to provide estimation of progressive modulation of cell deformation under shear and compression forces through varying the channel geometry, flow rate and/or media viscosity to assess subpopulations of cells and biological particles.
Claims31
A system comprising:
- a microfluidic device comprising:
- a microfluidic channel defining a flow path and configured to receive a sample comprising a heterogeneous population of biological particles, wherein the microfluidic channel includes a contoured constriction region larger than particle size that is configured to induce viscoelastic extensional flow for deformation and relaxation of the biological particles flowing therethrough, and
- an impedance sensing unit comprising one or more sets of electrodes disposed along the flow path of the microfluidic channel, wherein the one or more sets of electrodes is configured to interrogate single-particle impedance characteristics corresponding to a biophysical features of the biological particle, including their size, velocity, shape anisotropy and dielectric properties along the flow path of the microfluidic channel to provide impedance signal data;
- and
- a processor, and memory operatively coupled to the processor and having instructions stored thereon, wherein execution of the instructions by the processor causes the processor to:
- obtain the impedance signal data acquired from the impedance sensing unit;
- and
- classify the biological particles into cell or particle subpopulations via a trained machine learning (ML) model, wherein the trained ML model is trained using a training data set comprising a sequence of images, or associated data, of a set of biological particles flowing in viscoelastic extensional flow along a flow path of a microfluidic channel through a contoured constriction region and corresponding impedance signal data.
A method of characterizing and/or manipulating biological particles, the method comprising:
- receiving a sample comprising a heterogeneous population of biological particles in a microfluidic device,
- flowing the biological particles through a microfluidic channel of the microfluidic device having a contoured constriction region larger than particle size to cause viscoelastic extensional flow for deformation and relaxation of the biological particle,
- measuring impedance signal data of the biological particle at one or more locations along the microfluidic channel;
- classifying the biological particles into cell or particle subpopulations via a trained machine learning (ML) model, wherein the trained ML model is trained using a training data set comprising a sequence of images, or associated data, of a set of biological particles flowing in viscoelastic extensional flow along a flow path of the microfluidic channel through the contoured constriction region and corresponding impedance signal data.
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A microfluidic device comprising:
- a microfluidic channel defining a flow path and configured to receive a sample comprising a heterogeneous population of biological particles, wherein the microfluidic channel includes a contoured constriction region larger than particle size that is configured to induce viscoelastic extensional flow for deformation and relaxation of the biological particles flowing therethrough, and
- an impedance sensing unit comprising one or more sets of electrodes disposed along the flow path of the microfluidic channel, wherein the one or more sets of electrodes is configured to interrogate impedance characteristics corresponding to a biophysical features of the biological particle along the flow path of the microfluidic channel to provide impedance signal data on particle size, velocity, shape and dielectric properties;
- wherein the microfluidic channel comprises a compliant material operatively coupled to an external actuator, wherein the microfluidic channel is configured to deform in response to a force generated by the external actuator.
Dependencies are inferred from the claim text.