Cytoveris, Inc.

The Chinese University of Hong Kong

Rishikesh Pandey

Alan D Kersey

David Fournier

Gary Root

Renjie Zhou

Xin Shu

A method and system for determining the presence or absence of cancerous cells within subject tissue. The method includes: providing a material that includes a peptide component configurable in a non-binding form when disposed in a neutral pH environment, and in a binding form when disposed in an acidic pH environment, wherein the peptide component is configured to produce a first Raman spectrum when subjected to one or more predetermined wavelengths of light; administering the material to a subject tissue; interrogating the subject tissue with light; sensing the subject tissue for light emitted from the subject tissue, and producing signals representative of the sensed emitted light; analyzing the signals to determine a presence or absence of the first Raman spectrum; and determining the presence or absence of cancerous cells based on the presence or absence of the first Raman spectrum within the sensed light emitted from the subject tissue.

Method and system for detecting cancerous tissue and tumor margin using raman spectroscopy

The subject invention pertains to methods and systems for classifying leukocytes using artificial intelligence called AIRFIHA (artificial-intelligence enabled reagent-free imaging hematology analyzer) that can accurately classify subpopulations of leukocytes in a label-free manner. AIRFIHA can not only subtype lymphocytes into B and T cell but is capable of sorting different types of T cells subtypes. AIRFIHA is realized through training a two-step neural network using label-free images of separated leukocytes acquired from a custom-built quantitative phase microscope. Owing to its easy operation, low cost, and strong discerning capability of complex leukocyte subpopulations, AIRFIHA is clinically translatable and can also be deployed in resource-limited settings.

Artificial intelligence enabled reagent-free imaging hematology analyzer

A system and method for mapping a tissue sample is provided. The system includes a light source, a scanner, a digital mirror device (DMD), a light detector, and an analyzer. The DMD has an array of micromirrors. The analyzer controls the light source, controls the scanner, controls the DMD to have on-state micromirrors aligned with a light beam, and other micromirrors in an off-state. The on-state micromirrors direct the light beam to a tissue sample. The analyzer assigns one or more location codes to the on-state micromirrors, controls the light detector to receive Raman light emitted from the tissue sample, correlates the location codes of the on-state micromirrors with light detector signals representative of the Raman emitted light, and produces a spatial map of the Raman emitted light.

Digital mirror device based code-division multiplexed Raman optical mapping system for wide field imaging

A method and system for identifying tissue types is provided that utilizes Raman scattered light in the high wavenumber region (HWN) of Raman spectrum. The method includes: a) interrogating a tissue specimen with at least one wavelength of light, the wavelength of light operable to produce Raman scattered light in a HWN region of Raman spectrum from the tissue specimen; b) producing signal data representative of the Raman scattering, the signal data relating signal intensity as a function of wavenumber within the HWN region; c) fitting a curve to a portion of the signal data attributable to a HWN peak within the signal data, for a plurality of different HWN peaks; d) determining a plurality of characteristics of each fitted curve; and e) determining a tissue type using the determined characteristics and stored collective data representative of fitted peaks in the HWN region of a plurality of different tissue types.

Method and system for identifying tissue type based on peak-fitted parameters in high-wavenumber Raman spectrum

A method and system for classifying a tissue specimen is provided. The method includes: a) interrogating a tissue specimen with a first interrogation light; b) detecting first light from the tissue specimen resulting from the interrogation, wherein the first light includes a first scattered light component and a first fluorescence light component, and producing first signals; c) interrogating the tissue specimen with a second interrogation light at a second excitation wavelength, wherein the first and second excitation wavelengths are within about 2 nm of each other; d) detecting second light from the tissue specimen resulting from the interrogation, wherein the second light includes a second scattered light component and a second fluorescence light component, and producing second signals; e) determining a difference between the first and second lights; f) determining a fluorescence spectrum produced by the interrogation of the tissue specimen; and g) classifying the tissue specimen.

System and method for classification of tissue based on Raman and fluorescence in high-wavenumber Raman spectrum

A system for processing Raman scattering light from a sample is provided. The system includes a source, a digital mirror device (DMD), a detector, and an analyzer. The DMD is configured to reflect Raman scattering light and includes micromirrors selectively controllable between ON and OFF states. The detector is configured to detect Raman scattering light and to produce signals representative of the Raman scattering light. The analyzer is in communication with the light source, the DMD, the detector, and a memory storing instructions, which instructions when executed cause the processor to: a) control the light source to produce a beam of light for interrogating the sample; b) control the DMD to place in an ON or OFF state based on one or more known spectral shapes stored in the memory; and c) process the Raman scattering light reflected by the micromirrors in the ON state.

Raman spectroscopy-based optical matched filter system and method for using the same

A system and method for assaying high and low abundant biomolecules within a biological fluid sample is provided. The method includes: a) placing a biological fluid sample in contact with a first nanostructure surface; b) interrogating the sample with a light source, the sample in contact with the first nanostructure surface, the interrogation using a SERS technique; c) detecting an enhanced Raman scattering from at least one high abundant biomolecule type and producing first signals representative thereof; d) placing the sample in contact with a second nanostructure surface having a targeting agent that targets a low abundant biomolecule; e) interrogating the sample with the light source using the SERS technique; f) detecting the enhanced Raman scattering from the low abundant biomolecules and producing second signals representative thereof; and g) assaying the biological fluid sample using the first signals and the second signals.

Raman spectroscopy based assay for both low and high abundant biomolecules in a biological fluid sample

A method and system for identifying a Raman spectrum component of an observed spectrum is provided. The observed spectrum is produced by interrogating a material such as a tissue sample with light at the one or more predetermined wavelengths, and the observed spectrum includes a background fluorescence component representative of fluorescent emissions resulting from the light interrogation and a Raman spectrum component representative of a Raman scattering resulting from the light interrogation. The method includes a) creating a reconstructed fluorescence spectrum representative of the background fluorescence component of the observed spectrum using one or more empirically determined fluorescent spectral profiles; and b) identifying the Raman spectrum of the observed spectrum using the reconstructed fluorescence spectrum.

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Unionville, CT, United States of America

Rishikesh Pandey