Raman imaging for quantification of the volume fraction of biodegradable polymers in histological preparations.

Abstract

Postretrieval analysis of biodegradable polymeric constructs for degradation rates requires correct identification of the degradable polymer, de novo tissue and the confounding presence of a secondary polymer used for embedding. Similarities between the structures of many tissue engineering polymers may make them difficult to distinguish from the polymer used to embed explants prior to histological sectioning. In this study, we assessed the feasibility of a chemical imaging method, Raman microscopy, to discriminate between more than one polymer species. From the perspective of spectroscopy, this is not a straightforward process because of the emergence of multiple peaks, ubiquity of embedding medium, and presence of observations sourcing from points sampled at the interface of two phases. A multivariate K-means data clustering method was used to discriminate between different polymeric components. The method was able to classify 95% of the observations to the correct category. The remaining data displayed multiple memberships because of (1) the laser spot coinciding with the interfaces of more than one phase or (2) infiltration of histological embedding polymer. Combined with multivariate analysis methods, this technique may prove useful in the future for tissue engineering and biomaterials analysis of degradation rates of, and tissue ingrowth into, polymer scaffolds.