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Optically Barcoding Cells and Tissues Through Infrared Spectroscopic Imaging

Rohit Bhargava, Director of the Cancer Center at Illinois and Grainger, Distinguished Chair in Engineering at the University of Illinois Urbana-Champaign

Presented in Goergen 101 and on Zoom

Abstract

The spatial organization and chemical composition of biomedical tissues or materials determines its properties. In tissues, recognition of functional cell types, presence of disease and characterization of disease progression is typically conducted by examining morphology via optical microscopy with stains or dyes providing contrast. Infrared (IR) spectroscopic imaging can record both morphology and chemical content, such that the native composition of cell types or physiology directly provides contrast. Artificial intelligence (AI) algorithms can then be used to parse this contrast in terms of chemical databases and physical parameters of the microscope. We first present the underlying principles of image formation in the mid-IR from physical (image formation), chemical (spectral content) and information (confidence limits) science perspectives. We show that confidence in the spatial and spectral quality of the data are related; together, they provide a foundation for AI workflows and limits on performance. We detail a new IR laser scanning microscope that is designed with optimal physical sampling and exceptional signal to noise ratio to provide consistent enough data for clinical decision-making. We show that a combination of fast, reliable IR imaging and AI can provide improved recognition and better disease diagnoses compared to the current state of the art. We show examples of application in automated pathology for a variety of organs, real time surgical decision making, prediction of disease progression, and deepfake pathology. Turning to more fundamental developments that seek to illustrate human biology, we describe nanoscale IR imaging that builds on these concepts with a novel instrument design to explore the limits of performance of IR imaging. Nanoscale pixels, with database-powered biological information extraction and whole cell modeling, together point to a future role for optics in quantitative cell biology.

Biography

Rohit Bhargava is the Director of the Cancer Center at Illinois and Grainger Distinguished Chair in Engineering at the University of Illinois Urbana-Champaign. Rohit has made scientific contributions to develop the field of chemical imaging and its applications to histopathology. He has developed new instrument designs, modes of data acquisition, theory and modeling for infrared (IR) spectroscopic imaging. He developed the use of modern IR imaging for pathology and continues to provide significant studies that move this technology to widespread adoption. Using AI workflows, his group has provided optical imaging tools for both for clinical translation as well as for cell biology. Rohit has also served to connect the research community in new and exciting ways. He was the first external hire in the UIUC Bioengineering department, part of the founding group of the engineering-based Carle Illinois College of Medicine and founded the Cancer Center at Illinois - a novel cancer research center at the convergence of engineering and oncology. He is a leading proponent of the emerging field of Cancer Engineering. He also serves as the Associate Director for the NSF Science and Technology Center on Quantitative Cell Biology and Director of an NIH T32 training grant on the tissue microenvironment. His work is supported by the NIH (NIBIB, NIGMS, and NCI), NSF, Chan-Zuckerburg Biohub, ARPA-H, and Mayo Clinic. He is a fellow of Optica and won its 2021 Lippincott Award, among other honors.