Combined reflectance and Raman spectroscopy to assess degree of in vivo angiogenesis after tissue injury

Abstract

Background: Angiogenesis, the formation of blood vessels, is a critical aspect of wound healing. Disorders of wound healing are often characterized by lack of angiogenesis, a condition frequently observed in aging and diabetic patients. Current techniques for assessing blood at injury sites are limited to contrast-imaging, including angiography. However, these techniques do not directly observe oxygenation of blood and are not amenable to serial evaluation. A multimodal noninvasive reflectance and Raman spectrometer have been proposed to help clinicians as a point-of-care tool to interrogate local angiogenesis and tissue architecture, respectively. The spectrometer system is a rapid, noninvasive, and label-free technology well-suited for the clinical environment.

Materials and methods: To demonstrate feasibility, the spectrometer system was used to interrogate angiogenesis serially over 9 wk as a result of heterotopic ossification (HO) development in a validated murine model. End-stage HO was confirmed by micro-computed tomography.

Results: Our preliminary results suggest that reflectance spectroscopy can be used to delineate vessel formation and that pathologic wounds may be characterized by unique spectra. In our model, HO formed at sites 1-3, whereas sites 4 and 5 did not have radiographic evidence of HO.

Conclusions: A point-of-care system like that demonstrated here shows potential as a noninvasive tool to assess local angiogenesis and tissue architecture that may allow for timely intervention in a clinical setting.

Keywords: Angiogenesis; Light scatter; Near-infrared light; Raman spectroscopy; Reflectance spectroscopy; Tissues.

Fig. 1

Study design, including (a) measurement sites and (b) micro-computed tomography results. Note that blue indicates heterotopic ossification, corresponding to anticipated sites of HO in (a).

Fig. 2

Raman and reflectance spectroscopy were analyzed with principal components analysis. Corresponding principal components were inputs into linear mixed effects model. Results demonstrate potential for spectroscopy to characterize experimental condition (Raman: PC1, reflectance: PC2), time point of measurement (Raman: PC2-–, reflectance: PC1–3), and site of measurement (Raman: PC3, reflectance: PC1–3).