Ohio State Innovation Foundation

Heather C Allen

Edward W Martin

Charles L Hitchcock

James Coe

Thomas J Magliery

Brandon J Sullivan

Nicholas E Long

E David Alten

Juan Velez

Disclosed are systems and methods utilizing an infrared probe and discriminating software to rapidly discriminate abnormal tissue processes from normal tissue during surgery, physical examination of in-situ lesions, and in the assessment of biopsy and resected tissue specimens. Examples demonstrate discrimination of cancerous from noncancerous tissues. The discriminating software, i.e. the metrics, algorithms, calibrant spectra, and decision equations, allows tissue to be identified as abnormal or normal using a minimum of infrared (IR) wavelengths in order to be measured rapidly. The probe records IR metrics approximately 1000 times faster than current commercial instruments, i.e. on a timescale fast enough for clinical use. The probe uses a tunable mid-infrared laser with a small set of selected wavelengths that are optimized for detecting the chemical and molecular signatures of tissue specific lesions to include, but not limited to, cancer, preneoplasia, intracellular accumulations (e.g. steatosis), inflammation, and wound healing.

Discrimination of tissues using a fast infrared probe

A hand-held sized imaging instrument identifies molecules with high selectivity and in complex mixtures. The instrument uses inelastic scattering and scattering intensities from with machine learning algorithms based on convolutional neural networks (CNN's) to identify the presence of a specified chemical or combination of chemicals. A laser is housed within the instrument to initiate a material response of a sample using laser light of a specified wavelength. The instrument uses an image sensor to capture visible images with inelastic scattering information. The CNN is able to classify the image to determine whether the specified chemical or combination of chemicals is present in the sample. The instrument is inexpensive, portable, easy to use by anyone (nonchemist, nonprofessional), and safe (laser is completely housed). The instrument can be used efficiently and easily for quality control, security, and other applications to reliably detect the presence of specified substances.

Material identification through image capture of Raman scattering

System and method for the discrimination of tissues using a fast infrared cancer probe

Systems and methods utilize an infrared probe and discriminating software to rapidly discriminate normal tissue processes from normal tissue during surgery, physical examination of in-situ lesions, and in the assessment of biopsy and resected tissue specimens. Examples demonstrate discrimination of cancerous from noncancerous tissues. The discriminating software, i.e. the metrics, algorithms, calibrant spectra, and decision equations, allows tissue to be identified as abnormal or normal using a minimum of infrared (IR) wavelengths in order to be measured rapidly. The probe records IR metrics approximately 1000 times faster than current commercial instruments, i.e. on a timescale fast enough for clinical use. The probe uses a tunable mid-infrared laser with a small set of selected wavelengths that are optimized for detecting the chemical and molecular signatures of tissue specific lesions to include, but not limited to, cancer, preneoplasia, intracellular accumulations (e.g. steatosis), inflammation, and wound healing.

Disclosed herein are methods and compositions related to single chain antibody fragments which specifically bind sialyl-Tn epitope of tumor-associated glycoprotein 72 (TAG-72).

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Columbus, OH, United States of America

Heather C Allen