Spatial Frequency Domain Imaging (SFDI) is a model-based, wide-field, non-contact method for measuring the absorption, scattering, and fluorescence properties of biological tissue. Optical properties are determined in each pixel simultaneously, by measuring the attenuation (or fluorescence) of sinusoidal patterns of light projected onto the sample at varying spatial frequencies and phases. Images are demodulated by processing 3 phase-shifted views of the sample. The mean interrogation depth at a given wavelength is controlled by the spatial frequency of projection, and frequency-dependent differences in path length are used to calculate tissue optical properties using computational models. Because 3 specific phases are required for each projected frequency, care must be taken to perfectly sequence all projections and camera triggers. While each of these processes is fairly rapid, together they can slow the acquisition to a fraction of the camera frame rate. In order to overcome this limitation and facilitate real-time SFDI, we will develop new methods using """"""""frequency synthesis"""""""" - multiple frequencies synthesized into customized projection patterns. These patterns will be optimized for speed and frequency-dependent information content in order to facilitate rapid and accurate optical property measurements, probe buried objects, and perform tomography. When properly selected, frequency synthesized projections can potentially decrease the minimum acquisition time to the frame rate of the camera, allowing real-time SFDI and SFD tomography. The ability to project custom patterns not only allows us to generate multi-frequency components, it also adds the ability to change their orientation. This allows us to explore a new mode of contrast based on probing tissue structures that are aligned with the direction of the projected pattern. This is due to the fact that many tissue types, including bone, muscle, skin, and white matter in the brain, have orientated internal structures such that the degree of optical scattering depends on the direction of light propagation. The scattering direction of these oriented tissues is determined by their microscopic structure and obeys a diffusion equation. We will derive accurate solutions to the anisotropic diffusion equation in the spatial frequency domain. In an ordered medium, the attenuation of sinusoidal patterns depends on the relative orientation of the spatial frequency pattern and scatterer direction. Thus, by projecting multiple spatial frequencies in different directions and measuring the attenuation, we will be able to image the spatially varying scattering orientation over a large field of view. We expect that the combination of spatial frequency synthesis and orientation control will lead to new methods for quantitative, real-time imaging and tomography in thick tissues, as well as the characterization of exciting new contrast mechanisms based on an optical diffusion tensor.

Public Health Relevance

These studies will allow us to acquire sufficient data to develop and validate a new optical technology for real-time, quantitative imaging and depth sectioning of tissues based on relatively simple, cost-effective imaging cameras and patterned light projection techniques. The technology has potential to replace conventional camera-based imaging methods by allowing quantitative viewing of functional tissue attributes beneath the surface, where disease typically begins. Our approach is expected to lead to new, bedside medical imaging methods for detecting disease, monitoring therapy response, and guiding surgical procedures.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21EB014440-02
Application #
8494045
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Conroy, Richard
Project Start
2012-07-01
Project End
2014-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
2
Fiscal Year
2013
Total Cost
$169,266
Indirect Cost
$51,391
Name
University of California Irvine
Department
Type
Organized Research Units
DUNS #
046705849
City
Irvine
State
CA
Country
United States
Zip Code
92697
Ghijsen, Michael; Lentsch, Griffin R; Gioux, Sylvain et al. (2018) Quantitative real-time optical imaging of the tissue metabolic rate of oxygen consumption. J Biomed Opt 23:1-12
Ghijsen, Michael; Choi, Bernard; Durkin, Anthony J et al. (2016) Real-time simultaneous single snapshot of optical properties and blood flow using coherent spatial frequency domain imaging (cSFDI). Biomed Opt Express 7:870-82
Nadeau, Kyle P; Rice, Tyler B; Durkin, Anthony J et al. (2015) Multifrequency synthesis and extraction using square wave projection patterns for quantitative tissue imaging. J Biomed Opt 20:116005
Saager, Rolf B; Balu, Mihaela; Crosignani, Viera et al. (2015) In vivo measurements of cutaneous melanin across spatial scales: using multiphoton microscopy and spatial frequency domain spectroscopy. J Biomed Opt 20:066005
Konecky, Soren D; Wilson, Robert H; Hagen, Nathan et al. (2015) Hyperspectral optical tomography of intrinsic signals in the rat cortex. Neurophotonics 2:045003
Lin, Alexander J; Ponticorvo, Adrien; Durkin, Anthony J et al. (2015) Differential pathlength factor informs evoked stimulus response in a mouse model of Alzheimer's disease. Neurophotonics 2:045001
Wilson, Robert H; Nadeau, Kyle P; Jaworski, Frank B et al. (2015) Review of short-wave infrared spectroscopy and imaging methods for biological tissue characterization. J Biomed Opt 20:030901
Nadeau, Kyle P; Durkin, Anthony J; Tromberg, Bruce J (2014) Advanced demodulation technique for the extraction of tissue optical properties and structural orientation contrast in the spatial frequency domain. J Biomed Opt 19:056013
Wilson, Robert H; Nadeau, Kyle P; Jaworski, Frank B et al. (2014) Quantitative short-wave infrared multispectral imaging of in vivo tissue optical properties. J Biomed Opt 19:086011
Lin, Alexander J; Liu, Gangjun; Castello, Nicholas A et al. (2014) Optical imaging in an Alzheimer's mouse model reveals amyloid-?-dependent vascular impairment. Neurophotonics 1:011005

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