Quantitative principal component model for skin chromophore mapping using multi-spectral images and spatial priors

Kainerstorfer, Jana M.; Riley, Jason D.; Ehler, Martin; Najafizadeh, Laleh; Amyot, Franck; Hassan, Moinuddin; Pursley, Randall; Demos, Stavros G.; Chernomordik, Victor; Pircher, Michael; Smith, Paul D.; Hitzenberger, Christoph K.; Gandjbakhche, Amir H.

doi:10.1364/boe.2.001040

Quantitative principal component model for skin chromophore mapping using multi-spectral images and spatial priors

Journal Article · Sat Jan 01 00:00:00 EST 2011 · Biomedical Optics Express

DOI:https://doi.org/10.1364/boe.2.001040· OSTI ID:1627118

Kainerstorfer, Jana M. ^[1]; Riley, Jason D. ^[2]; Ehler, Martin ^[2]; Najafizadeh, Laleh ^[3]; Amyot, Franck ^[2]; Hassan, Moinuddin ^[2]; Pursley, Randall ^[2]; Demos, Stavros G. ^[4]; Chernomordik, Victor ^[2]; Pircher, Michael ^[5]; Smith, Paul D. ^[2]; Hitzenberger, Christoph K. ^[5]; Gandjbakhche, Amir H. ^[2]

National Institutes of Health (NIH), Bethesda, MD (United States); Medical University of Vienna (Austria); DOE/OSTI
National Institutes of Health (NIH), Bethesda, MD (United States)
National Institutes of Health (NIH), Bethesda, MD (United States); Henry M. Jackson Foundation, Rockville, MD (United States)
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Medical University of Vienna (Austria)

We describe a novel reconstruction algorithm based on Principal Component Analysis (PCA) applied to multi-spectral imaging data. Using numerical phantoms, based on a two layered skin model developed previously, we found analytical expressions, which convert qualitative PCA results into quantitative blood volume and oxygenation values, assuming the epidermal thickness to be known. We also evaluate the limits of accuracy of this method when the value of the epidermal thickness is not known. We show that blood volume can reliably be extracted (less than 6% error) even if the assumed thickness deviates 0.04mm from the actual value, whereas the error in blood oxygenation can be as large as 25% for the same deviation in thickness. This PCA based reconstruction was found to extract blood volume and blood oxygenation with less than 8% error, if the underlying structure is known. We then apply the method to in vivo multi-spectral images from a healthy volunteer’s lower forearm, complemented by images of the same area using Optical Coherence Tomography (OCT) for measuring the epidermal thickness. Reconstruction of the imaging results using a two layered analytical skin model was compared to PCA based reconstruction results. A point wise correlation was found, showing the proof of principle of using PCA based reconstruction for blood volume and oxygenation extraction.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1627118

Journal Information:: Biomedical Optics Express, Journal Name: Biomedical Optics Express Journal Issue: 5 Vol. 2; ISSN 2156-7085

Publisher:: Optical Society of America (OSA)Copyright Statement

Country of Publication:: United States

Language:: English

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