Characterizing human subchondral bone properties using near-infrared (NIR) spectroscopy

Sci Rep. 2018 Jun 27;8(1):9733. doi: 10.1038/s41598-018-27786-3.

Abstract

Degenerative joint conditions are often characterized by changes in articular cartilage and subchondral bone properties. These changes are often associated with subchondral plate thickness and trabecular bone morphology. Thus, evaluating subchondral bone integrity could provide essential insights for diagnosis of joint pathologies. This study investigates the potential of optical spectroscopy for characterizing human subchondral bone properties. Osteochondral samples (n = 50) were extracted from human cadaver knees (n = 13) at four anatomical locations and subjected to NIR spectroscopy. The samples were then imaged using micro-computed tomography to determine subchondral bone morphometric properties, including: plate thickness (Sb.Th), trabecular thickness (Tb.Th), volume fraction (BV/TV), and structure model index (SMI). The relationship between the subchondral bone properties and spectral data in the 1st (650-950 nm), 2nd (1100-1350 nm) and 3rd (1600-1870 nm) optical windows were investigated using partial least squares (PLS) regression multivariate technique. Significant correlations (p < 0.0001) and relatively low prediction errors were obtained between spectral data in the 1st optical window and Sb.Th (R2 = 92.3%, error = 7.1%), Tb.Th (R2 = 88.4%, error = 6.7%), BV/TV (R2 = 83%, error = 9.8%) and SMI (R2 = 79.7%, error = 10.8%). Thus, NIR spectroscopy in the 1st tissue optical window is capable of characterizing and estimating subchondral bone properties, and can potentially be adapted during arthroscopy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Cadaver
  • Cartilage, Articular / diagnostic imaging*
  • Female
  • Humans
  • Least-Squares Analysis
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Regression Analysis
  • Spectroscopy, Near-Infrared / methods*