About This Webinar
Caigang Zhu reports on a point-of-care optical spectroscopy platform and novel spectroscopic data processing techniques for simultaneous precision quantification of key metabolic and vascular parameters of tissue in vivo. Both phantom and preclinical animal studies were conducted to demonstrate the capability of the optical system and data processing techniques.
Zhu briefly summarizes his group's work on point-of-care functional optical spectroscopy. He covers the following sections: 1) the rationale and a brief introduction about the design of the low-cost point-of-care spectroscopy system; 2) the optical sensing depth of the technique (
Biomed Opt Express, Vol. 11, No. 11, pp. 6311-6323); 3) the Monte Carlo inversion model for precision quantification of absorption and fluorescence (
Biomed Opt Express, Vol. 9, No. 7, pp. 3399-3412); 4) the novel ratio-metric technique for rapid spectroscopy data processing (
J Biomed Opt, Vol. 26, No. 4, p. 045001); 5) demonstration of point-of-care spectroscopy for in vivo tumor metabolism and vasculature quantification (unpublished); 6) a summary of the group's work.
***This presentation premiered during the 2021
BioPhotonics Conference. For more information on Photonics Media conferences, visit
events.photonics.com.
About the presenter:
Caigang Zhu, Ph.D., received his bachelor's degree from Huazhong University of Science and Technology in Wuhan, China, and his doctorate from Nanyang Technological University in Singapore. He was a postdoc at Duke University and is currently an assistant professor in the Department of Biomedical Engineering at the University of Kentucky. Zhu's research program at the University of Kentucky focuses on developing and applying novel point-of-care optical techniques to physiological sensing of the tissue metabolism and vascular microenvironment for the purposes of: 1) understanding the therapeutic resistance mechanism for human cancers; and 2) identifying or evaluating therapeutic targets related to the tumor metabolism and microenvironment in biological models.