Applying Full Spectrum Analysis to a Raman Spectroscopic Assessment of Fracture Toughness of Human Cortical Bone

Abstract

A decline in the inherent quality of bone tissue is a

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Equal contributors

contributor to the age-related increase in fracture risk. Although this is well-known, the important biochemical factors of bone quality have yet to be identified using Raman spectroscopy (RS), a nondestructive, inelastic light-scattering technique. To identify potential RS predictors of fracture risk, we applied principal component analysis (PCA) to 558 Raman spectra (370–1720 cm^–1) of human cortical bone acquired from 62 female and male donors (nine spectra each) spanning adulthood (age range = 21–101 years). Spectra were analyzed prior to R-curve, nonlinear fracture mechanics that delineate crack initiation (K_init) from crack growth toughness (K_grow). The traditional ν₁phosphate peak per amide I peak (mineral-to-matrix ratio) weakly correlated with K_init (r = 0.341, p = 0.0067) and overall crack growth toughness (J-int: r = 0.331, p = 0.0086). Sub-peak ratios of the amide I band that are related to the secondary structure of type 1 collagen did not correlate with the fracture toughness properties. In the full spectrum analysis, one principal component (PC5) correlated with all of the mechanical properties (K_init: r = − 0.467, K_grow: r = − 0.375, and J-int: r = − 0.428; p < 0.0067). More importantly, when known predictors of fracture toughness, namely age and/or volumetric bone mineral density (vBMD), were included in general linear models as covariates, several PCs helped explain 45.0% (PC5) to 48.5% (PC7), 31.4% (PC6), and 25.8% (PC7) of the variance in K_init, K_grow, and J-int, respectively. Deriving spectral features from full spectrum analysis may improve the ability of RS, a clinically viable technology, to assess fracture risk.