4 March 2016 Raman spectroscopy and the spectral correlation index for predicting wound healing outcome: towards in vivo application
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Abstract
Combat wounds are sometimes confounded by healing complications that are not as prevalent in civilian wounds due to their high energy etiology. One complication of wound healing is dehiscence, where a surgically closed wound reopens after closure. This complication can have serious consequences for the patient, but knowledge about the molecular composition of the wound bed beyond what is readily visible may help clinicians mitigate these complications. It is necessary to develop techniques that can be used in vivo to assess and predict wound healing pointof- care so that care-takers can decide the best way to make informed clinical decisions regarding their patient’s healing. Raman spectroscopy is a perfect candidate for predicting wound healing due to its ability to provide a detailed molecular fingerprint of the wound bed noninvasively. Here, we study the spectral correlation index, a measure of orthogonality, with ten reference tissue components to stratify wounds based on how they heal. We analyze these indexes over time to show the modulation of these tissue components over the wound healing process. Results show that qualitative observation of the spectra cannot reveal major differences between the dehisced and normal healing wounds, but the spectral correlation index can. Analysis of the spectral correlations across the wound healing process demonstrates the changes throughout the wound healing process, showing that early differences in tissue components may portend wound healing. Furthermore, Raman spectroscopy coupled with the spectral correlation index presents as a possible point-of-care tool for enabling discrimination of wounds with impaired healing.
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Adam G. Berger, Nicole J. Crane, Eric A. Elster, "Raman spectroscopy and the spectral correlation index for predicting wound healing outcome: towards in vivo application", Proc. SPIE 9715, Optical Diagnostics and Sensing XVI: Toward Point-of-Care Diagnostics, 97150C (4 March 2016); doi: 10.1117/12.2212833; https://doi.org/10.1117/12.2212833
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