Optimization of Data Collection for Visible–Near-Infrared Fiber Optic Spectroscopy of Osteochondral Tissues in Hydrated Environments

Abstract

Arthroscopic procedures rely on qualitative methods for cartilage assessment, such as tissue visualization and mechanical probing. Visible–near-infrared (Vis-NIR) spectroscopy offers the potential to include compositional tissue characterization which could improve surgical guidance. The primary objective of this study was to assess the feasibility of using a fiber optic Vis-NIR probe in environments typically experienced during arthroscopy. Given the geometric constraints of articulating joints, a probe was fabricated with a 90-degree bend at the tip to enable movement and access to tissues. Absorbances from arthroscopic irrigation fluid (saline) are prominent in the NIR spectral region and thus need to be minimized during spectral collection. The current study aims to identify spectral data where the probe was not in contact with the tissues and/or where environmental saline contributed to the spectra. Porcine patella tissues were used to model how spectra collection in various conditions (probe offset from tissue and presence of fluid) impact spectra. Spectra were collected from cartilage, bone, and osteochondral tissues (n = 6 each) in experimental configurations with and without tissue contact and/or saline. Additionally, arthroscopic spectra collection in an equine stifle joint was investigated. Spectra collected while the fiber optic probe was in contact with the tissues resulted in minimal impact of environmental saline. Principal component analysis of spectra resulted in the separation of groups based on experimental configuration, demonstrating the potential for the development of more advanced machine learning algorithms focused on exclusion of spectra without appropriate tissue contact and with saline interference.

Graphical abstract

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