Raman Spectroscopy Enables Noninvasive Biochemical Characterization and Identification of the Stage of Healing of a Wound

• Published in: Analytical chemistry (Washington) 2014-04, Vol.86 (8), p.3764-3772
• Main Authors: Jain, Rishabh, Calderon, Diego, Kierski, Patricia R, Schurr, Michael J, Czuprynski, Charles J, Murphy, Christopher J, McAnulty, Jonathan F, Abbott, Nicholas L
• Format: Article
• Language: English
• Subjects: Animals; Assessments; Biochemistry; Biopsy; Factor Analysis, Statistical; Granulation Tissue - chemistry; Healing; Inflammation - metabolism; Least-Squares Analysis; Mice; Mice, Inbred BALB C; Multivariate Analysis; Phases; Raman spectroscopy; Rodents; Skin - chemistry; Spectra; Spectrum analysis; Spectrum Analysis, Raman - methods; Wound healing; Wound Healing - physiology; Wounds and Injuries - classification; Wounds and Injuries - pathology
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/ac500513t

Accurate and rapid assessment of the healing status of a wound in a simple and noninvasive manner would enable clinicians to diagnose wounds in real time and promptly adjust treatments to hasten the resolution of nonhealing wounds. Histologic and biochemical characterization of biopsied wound tissue, which is currently the only reliable method for wound assessment, is invasive, complex to interpret, and slow. Here we demonstrate the use of Raman microspectroscopy coupled with multivariate spectral analysis as a simple, noninvasive method to biochemically characterize healing wounds in mice and to accurately identify different phases of healing of wounds at different time-points. Raman spectra were collected from “splinted” full thickness dermal wounds in mice at 4 time-points (0, 1, 5, and 7 days) corresponding to different phases of wound healing, as verified by histopathology. Spectra were deconvolved using multivariate factor analysis (MFA) into 3 “factor score spectra” (that act as spectral signatures for different stages of healing) that were successfully correlated with spectra of prominent pure wound bed constituents (i.e., collagen, lipids, fibrin, fibronectin, etc.) using non-negative least squares (NNLS) fitting. We show that the factor loadings (weights) of spectra that belonged to wounds at different time-points provide a quantitative measure of wound healing progress in terms of key parameters such as inflammation and granulation. Wounds at similar stages of healing were characterized by clusters of loading values and slowly healing wounds among them were successfully identified as “outliers”. Overall, our results demonstrate that Raman spectroscopy can be used as a noninvasive technique to provide insight into the status of normally healing and slow-to-heal wounds and that it may find use as a complementary tool for real-time, in situ biochemical characterization in wound healing studies and clinical diagnosis.