Methods of optical spectroscopy and imaging are being developed for biomedical applications in non- or minimally invasive tissue diagnostics, including sensing molecular concentrations of delivered pharmaceutical or contrast agents, probing tissue physiologic status, and detecting early stages of disease in vivo. In tissue optics, one of the challenges is to obtain quantitative information despite the detected signal variability introduced by tissue morphology and optical absorption and scattering. The overall goal of this application is to develop, validate, and disseminate computational codes to numerically simulate photon migration characteristics useful for quantitative tissue spectroscopy and imaging. We will develop and employ innovative computational codes designed to model steady-state and time-resolved excitation and fluorescent light propagation in complex tissues approximately 102 -104 times faster than current methods. The computational resources developed here will be broadly applicable to problems in pre-clinical and clinical biomedical optical spectroscopy and imaging, including minimally-invasive applications requiring light delivery and collection via fiber-optic probe configurations. A multidisciplinary team of researchers with expertise in biomedical optics and clinical endoscopy has been assembled to ensure that these goals are achieved.
The specific aims of this R01 grant proposal are: (1) To develop and numerically test novel computational codes for steady-state and time-resolved photon migration in tissues with complex morphologies and source-detector geometries; (2) To experimentally validate the computational codes developed in Aim #1; (3) To efficiently disseminate the computational codes developed in Aim #1 and validated in Aim #2 to the scientific community via download links and platform-independent user-interactive interfaces on the Pi's web-site. The innovative computational codes developed and validated here will be broadly applicable to a variety of problems in quantitative tissue optical spectroscopy and imaging. Rapid electronic dissemination via the internet will facilitate the generalized use of these digital tools, which will serve as a resource for a broad cross-section of researchers investigating problems in tissue optics. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA114542-02
Application #
7078589
Study Section
Special Emphasis Panel (ZRG1-SBIB-Q (50))
Program Officer
Baker, Houston
Project Start
2005-06-14
Project End
2009-05-31
Budget Start
2006-06-01
Budget End
2007-05-31
Support Year
2
Fiscal Year
2006
Total Cost
$211,792
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Wilson, Robert H; Chandra, Malavika; Scheiman, James M et al. (2017) Tissue Classification Using Optical Spectroscopy Accurately Differentiates Cancer and Chronic Pancreatitis. Pancreas 46:244-251
Chang, Ching-Wei; Mycek, Mary-Ann (2012) Total variation versus wavelet-based methods for image denoising in fluorescence lifetime imaging microscopy. J Biophotonics 5:449-57
Keller, Matthew D; Vargis, Elizabeth; de Matos Granja, Nara et al. (2011) Development of a spatially offset Raman spectroscopy probe for breast tumor surgical margin evaluation. J Biomed Opt 16:077006
Wilson, R H; Mycek, M-A (2011) Models of light propagation in human tissue applied to cancer diagnostics. Technol Cancer Res Treat 10:121-34
Chang, Ching-Wei; Mycek, Mary-Ann (2010) Precise fluorophore lifetime mapping in live-cell, multi-photon excitation microscopy. Opt Express 18:8688-96
Chang, Ching-Wei; Mycek, Mary-Ann (2010) Enhancing precision in time-domain fluorescence lifetime imaging. J Biomed Opt 15:056013
Chandra, Malavika; Scheiman, James; Simeone, Diane et al. (2010) Spectral areas and ratios classifier algorithm for pancreatic tissue classification using optical spectroscopy. J Biomed Opt 15:010514
Wilson, Robert H; Chandra, Malavika; Chen, Leng-Chun et al. (2010) Photon-tissue interaction model enables quantitative optical analysis of human pancreatic tissues. Opt Express 18:21612-21
Keller, Matthew D; Wilson, Robert H; Mycek, Mary-Ann et al. (2010) Monte Carlo model of spatially offset Raman spectroscopy for breast tumor margin analysis. Appl Spectrosc 64:607-14
Raghavan, Mekhala; Sahar, Nadder D; Wilson, Robert H et al. (2010) Quantitative polarized Raman spectroscopy in highly turbid bone tissue. J Biomed Opt 15:037001

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