Validation of a simple histological-histochemical cartilage scoring system Academic Article uri icon


MeSH Major

  • Cartilage, Articular
  • Histocytochemistry
  • Periosteum
  • Research Design


  • In this study, we assessed the validity of a subjective histological-histochemical scoring system as compared to an automated histomorphometry program for analyzing cartilage repair tissue. In the first part of the study, we assessed the ability of the human eye to estimate the percent cartilage in a histological section. Twenty-nine rabbit periosteal explants that had been cultured in agarose transforming growth factor-beta (TGF-beta) were selected so that the percentage of cartilage in the specimens was distributed equally from 0% to 100%. Color photomicrographs were evaluated by 5 expert observers who gave a visual estimate of the percent cartilage. There was a strong correlation between the estimated and actual percent cartilage (R(2) = 0.92, p < 0.0001) and among the observers (I.C.C. = 0.89). On average, the estimated percent cartilage was within ten percent of the actual percent measured. In the second part, we compared the data derived using a simple cartilage score with those obtained by automated image analysis. The histological slides from 159 explants cultured under various experimental conditions (14 treatment groups) in two different experiments were analyzed. The cartilage content was estimated visually and a score from 0 to 3 was assigned. A previously validated, computerized image analysis system was used to measure the actual percent cartilage. Statistical analyses revealed a good linear regression (R(2) = 0.84, p = 0.0001), and even better polynomial correlation between the actual measurement and the score (R(2) = 0.88, p = 0.0001). These data demonstrate the validity of a simple histological-histochemical subjective scoring system. A computerized automated program such as the one employed in this study is preferable due to its many advantages. However, a subjective scoring system may be appropriate to use when the funding and expertise required for a computerized image analysis program are not available.

publication date

  • July 5, 2001



  • Academic Article



  • eng

Digital Object Identifier (DOI)

  • 10.1089/10763270152044170

PubMed ID

  • 11429151

Additional Document Info

start page

  • 313

end page

  • 20


  • 7


  • 3