Annals of Biomedical Engineering

, Volume 27, Issue 5, pp 656–662

Method for Quantitative Analysis of Glycosaminoglycan Distribution in Cultured Natural and Engineered Cartilage

  • Ivan Martin
  • Bojana Obradovic
  • Lisa E. Freed
  • Gordana Vunjak-Novakovic
Article

DOI: 10.1114/1.205

Cite this article as:
Martin, I., Obradovic, B., Freed, L.E. et al. Annals of Biomedical Engineering (1999) 27: 656. doi:10.1114/1.205

Abstract

Cartilage tissue engineering can provide a valuable tool for controlled studies of tissue development. As an example, analysis of the spatial distribution of glycosaminoglycans (GAG) in sections of cartilaginous tissues engineered under different culture conditions could be used to correlate the effects of environmental factors with the structure of the regenerated tissue. In this paper we describe a computer-based technique for quantitative analysis of safranin-O stained histological sections, using low magnification light microscopy images. We identified a parameter to quantify the intensity of red color in the sections, which in turn was proportional to the biochemically determined wet weight fraction of GAG in corresponding tissue samples, and to describe the spatial distribution of GAG as a function of depth from the section edge. A broken line regression model was then used to determine the thickness of an external region, with lower GAG fractions, and the spatial rate of change in GAG content. The method was applied to the quantitatation of GAG distribution in samples of natural and engineered cartilage, cultured for 6 weeks in three different vessels: static flasks, mixed flasks, and rotating bioreactors. © 1999 Biomedical Engineering Society.

PAC99: 8780Rb, 8715Mi, 8763Lk

Image analysis Tissue engineering Bioreactor Safranin O 

Copyright information

© Biomedical Engineering Society 1999

Authors and Affiliations

  • Ivan Martin
    • 1
  • Bojana Obradovic
    • 1
  • Lisa E. Freed
    • 1
  • Gordana Vunjak-Novakovic
    • 1
  1. 1.Division of Health Sciences and TechnologyMassachusetts Institute of TechnologyCambridge