Multivariate FTIR Imaging Analyses to Unveil Chemistry of Adhesive/Dentin Interfaces

Objective: Fourier transform infrared (FTIR) chemical imaging can be used to investigate molecular chemical features of the adhesive/dentin interfaces. However, the information is not straightforward, and is not easily extracted. The objective of this study was to use multivariate analysis methods, principal component analysis and fuzzy c-means clustering, to analyze spectral data in comparison with univariate analysis. Materials and Methods: The occlusal surface of 6 permanent molars was ground perpendicular to the long axis of the tooth until a flat surface composed of the caries-affected (c-a) dentin surrounded by normal dentin is exposed. Using this technique, normal and c-a dentin were acquired from the same tooth. The teeth were treated with Single Bond Plus (3M ESPE) adhesive. FTIR spectral imaging data, areas 200 x 200 μm², of the interfaces from both normal and c-a dentin specimens were acquired, analyzed and compared. Results: The univariate methods such as mapping of intensities of specific functional group do not accurately identify functional group locations and concentrations due to more or less band overlapping in adhesive and dentin. Apart from the ease with which information can be extracted, multivariate methods highlight subtle and often important changes in the spectra that are difficult to observe using univariate methods. For example, the different interfacial chemical features between normal and c-a dentin substrates are visualized; in particular, the patterns associated with water outflow from the two types of wet dentin substrates are differentiated. Conclusion: The multivariate methods give more satisfactory, interpretable results than univariate methods and are conclusive in showing that they can discriminate and classify differences between normal dentin and c-a dentin within the interfacial regions. It is demonstrated that the multivariate FTIR imaging approaches can be used in the rapid characterization of heterogeneous, complex structure. Supported by NIH K25 DE015281, R03 DE15735.