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 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 (Kinit) from crack growth toughness (Kgrow). The traditional ν1phosphate peak per amide I peak (mineral-to-matrix ratio) weakly correlated with Kinit (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 (Kinit: r = − 0.467, Kgrow: 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 Kinit, Kgrow, 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.