• DocumentCode
    760935
  • Title

    Robust quantification of in vitro angiogenesis through image analysis

  • Author

    Niemistö, Antti ; Dunmire, Valerie ; Yli-Harja, Olli ; Zhang, Wei ; Shmulevich, Ilya

  • Author_Institution
    Dept. of Pathology, Univ. of Texas M. D. Anderson Cancer Center, Houston, TX, USA
  • Volume
    24
  • Issue
    4
  • fYear
    2005
  • fDate
    4/1/2005 12:00:00 AM
  • Firstpage
    549
  • Lastpage
    553
  • Abstract
    An automated image analysis method for quantification of in vitro angiogenesis is presented. The method is designed for in vitro angiogenesis assays that are based on co-culturing endothelial cells with fibroblasts. Such assays are used in many current studies in which anti-angiogenic agents for the treatment of cancer are being sought. This search requires accurate quantification of the stimulatory and inhibitory effects of the different agents. The quantification method gives lengths and sizes of the tubule complexes as well as the numbers of junctions in each of them. The method is tested with a set of test images obtained with a commercially available in vitro angiogenesis assay. The results correctly indicate the inhibitory effect of suramin and the stimulatory effect of vascular endothelial growth factor. Moreover, the image analysis method is shown to be robust against variations in illumination. We have implemented a software package that utilizes the methods. The software as well as a set of test images are available at http://www.cs.tut.fi/sgn/csb/angioquant/.
  • Keywords
    blood vessels; cellular biophysics; medical image processing; automated image analysis; endothelial cells; fibroblasts; in vitro angiogenesis; inhibitory effects; software package; stimulatory effects; suramin; vascular endothelial growth factor; Cancer; Fibroblasts; Image analysis; In vitro; In vivo; Length measurement; Pathology; Robustness; Signal processing; Testing; Angiogenesis; image analysis; quantification; segmentation; Algorithms; Animals; Artificial Intelligence; Cells, Cultured; Coculture Techniques; Endothelial Cells; Fibroblasts; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Neovascularization, Physiologic; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; Suramin; Tissue Engineering; Vascular Endothelial Growth Factor A;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2004.837339
  • Filename
    1413502