Chemimage Corporation

Chemimage Technologies LLC

Cryomedical Sciences Inc.

Jeffrey Cohen

John Maier

Shona Stewart

Patrick J Treado

Ryan J Priore

Serena Augustine

Joseph E Demuth

Heather Gomer

Matthew P Nelson

Gary M Onik

Jihang Wang

Alyssa Zrimsek

Lindy A McClelland

George Reyes

J Christopher Post

Arash Samiei

John G Baust

Robert Schweitzer

Janice Panza

Heather Kirschner

Alan Wilson

Zhao H Chang

Larry Pottorff

Amy J Drauch

Aaron Smith

Systems and methods of detecting and monitoring edema in a subject are described. The systems and methods include light sources, image detectors, filters, and processors that determine whether a subject has edema and the degree of severity. In some embodiments, the processor fuses data from more than one imaging modality.

Quantification of heart failure using molecular chemical imaging

Systems and methods for the detection of calculi in the biliary system are disclosed. The systems include an illumination source, one or more filters that filter a first set of illumination photons and a second set of illumination photons, as well as associated processors and detectors. The system is also designed to generate image data sets and generated information related to the location of the calculi.

Discrimination of calculi and tissues with molecular chemical imaging

System and method for detecting and monitoring edema in a patient are described. Initially, a patient's tissue is irradiated with light by a light source. A detector collects reflected light from the patient's tissue and generates data associated with the reflected light. A processing device receives the data and reflected light and calculates an intensity of the reflected light. The processing device then determined, based upon the intensity of the reflected light, whether the patient's tissue exhibits any symptoms of edema. Additionally, the processing device can compare a current intensity of the reflected light against historic information to monitor for any changes in a patient's edema level or severity.

Systems and methods for detecting edema by fusing hyperspectral and visible image

Devices, systems, and methods for distinguishing tissue types are described herein. Such devices and systems may use dual polarization, conformal filters to acquire image data from target tissues and a processor to create an image in which the contrast between tissues has been enhanced.

System and method for intraoperative detection of cancer margins using conformal filters in a dual polarization configuration

Systems and methods for the detection of calculi in the biliary system are disclosed. The systems include an illumination source, one or more filters that filter a first set of illumination photons and a second set of illumination photons, as well as associated processors and detectors. The system is also designed to generates image data sets and generated information related to the location of the calculi.

A method for analyzing organ samples using hyperspectral imaging comprising illuminating an organ sample to generate interacted photons, collecting the interacted photons and passing the interacted photons through a tunable filter. The filtered interacted photons are detected to generate a hyperspectral image. A brightfield image is generated and associated with the hyperspectral image. Spectra from locations of interest are extracted and analyzed to assess a characteristic of the organ sample. A system may comprise an illumination source to illuminate an organ sample and generate interacted photons, a collection optics for collecting the interacted photons and a tunable filter to filter the interacted photons. A detector is configured to detect the filtered photons and generate at least one hyperspectral image. The detector may also be configured to generate at least one brightfield image representative of the organ sample.

System and method for gross anatomic pathology using hyperspectral imaging

A method for generating an image of a sample that is informative of the disease state of a cell in the sample. A sample including the cell is irradiated with monochromatic light. The Raman scattered light is assessed. A digital brightfield image of the Raman scattered light is generated and combined with the Raman scattered light emitted by the cell whereby the Raman scattered light is informative of the disease state of the cell in the sample. The method can also be used to determine the metabolic activity of the cell, the inflammatory status of the cell and/or the infected status of the cell in the sample.

Cytological analysis by raman spectroscopic imaging

System and method for determining a disease state of a sample. A sample is positioned in a field of view and a first spectroscopic data set is obtained. The positional information is stored and the sample is treated with a contrast enhancing agent. The sample is repositioned in the field of view and a digital image is obtained. The spectroscopic data is linked with the digital image and a database comprising representative spectroscopic data sets is searched to classify the disease state of the sample. The disclosure also provides for the step of obtaining a processed derivative image and searching a database comprising representative processed derivative images to classify a disease state of the sample.

System and method for classifying a disease state using representative data sets

A system and method for determining a disease state and clinical outcome of a sample. A sample is illuminated to produce Raman scattered photons, the Raman scattered photons are assessed to generate a Raman spectroscopic data set representative of the sample, wherein said Raman spectroscopic data set comprises at least one of: a Raman spectra of the sample and a spatially accurate wavelength resolved Raman image of the sample; the Raman spectroscopic data set is evaluated using a chemometric technique to classify the disease state of the sample as: acute, chronic, incipient, or none. In one embodiment, the chemontric technique is principle component analysis. In another embodiment, the sample is obtained prior to transplantation and analysis can determine the likelihood of rejection by a host.

Raman characterization of transplant tissue

System and method for differentiating tissue margins in a biological sample using pulsed laser excitation and time-gated detection. A region containing a biological tissue is irradiated with substantially monochromatic pulsed laser light to thereby produce Raman scattered photons. The Raman scattered photons are detected using time-gated detection to thereby obtain a Raman spectroscopic image from the irradiated region characteristic of either a neoplastic portion or a non-neoplastic portion of the region containing the biological tissue. A boundary between a neoplastic portion and a non-neoplastic portion is differentiated and the boundary location in the Raman spectroscopic image is displayed.

System and method of chemical imaging using pulsed laser excitation and time-gated detection to determine tissue margins during surgery

A method to diagnosis a disease state of an unknown sample. A test Raman data set for an unknown sample is generated. A reference Raman database is provided where the database contains a plurality of reference Raman data sets and a plurality of reference Raman difference data sets. The reference Raman difference data set is generated by determining a difference between a first reference Raman data set and a second reference Raman data set. A first reference Raman data set is associated with first known sample and associated with one or more of: a first known disease state and a first known clinical outcome. A second reference Raman data set is associated with a second known sample and associated with one or more of: a second known disease state and a second known clinical outcome. A diagnosis is provided of whether the unknown sample has a first disease state or a second disease state by comparing the test Raman dataset to said plurality of reference Raman difference data sets in the reference Raman database using a chemometric technique.

Raman difference spectra based disease classification

A system and method for determining at least one of: a disease state, a metabolic state, a clinical outcome, and a disease progression of a test renal or prostate sample. A test Raman data set is obtained from the sample wherein said test Raman data set may comprise at least one of a plurality of Raman spectra and a plurality of spatially accurate wavelength resolved Raman images. The test Raman data set is compared to a plurality of reference Raman data sets using a chemometric technique. For analysis of renal samples, each of these reference Raman data sets may have an associated known renal sample and an associated known metabolic state, clinical outcome, and/or disease progression. For analysis of prostate samples, each of these reference Raman data sets may have an associated known prostate sample and an associated known disease state, metabolic state, clinical outcome, and/or disease progression.

System and method for analyzing biological samples using Raman molecular imaging

A system and method to provide a diagnosis of the breast disease state of a test breast sample. A database containing a plurality of reference Raman data sets is provided where each reference Raman data set has an associated known breast sample and an associated known breast disease state. A test breast sample is irradiated with substantially monochromatic light to generate scattered photons resulting in a test Raman data set. The test Raman data set is compared to the plurality of reference Raman data sets using a chemometric technique. Based on the comparison, a diagnosis of a breast disease state of the test breast sample is provided. The breast disease state includes invasive ductal carcinoma or invasive lobular carcinoma disease state.

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Pittsburgh, PA, United States of America

Jeffrey Cohen