Abstract
Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the acquisition, storage and evaluation of images with dedicated hardware and software.
Major advantages of quantitative image analysis over traditional techniques include sophisticated calibration systems, interaction, speed, and control of inter- and intraobserver variation. This results in a well controlled environment, which is essential for quality control and reproducibility, and helps to optimize sensitivity and specificity. To achieve this, an optimal quantitative image analysis system combines solid software engineering with easy interactivity with the operator. Moreover, the system also needs to be as transparent as possible in generating the data because a “black box design” will deliver uncontrollable results.
In addition to these more general aspects, specifically for the analysis of synovial tissue the necessity of interactivity is highlighted by the added value of identification and quantification of information as present in areas such as the intimal lining layer, blood vessels, and lymphocyte aggregates.
Speed is another important aspect of digital cytometry. Currently, rapidly increasing numbers of samples, together with accumulation of a variety of markers and detection techniques has made the use of traditional analysis techniques such as manual quantification and semi-quantitative analysis unpractical. It can be anticipated that the development of even more powerful computer systems with sophisticated software will further facilitate reliable analysis at high speed.
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References
Goodman, A. H. (1986) CCD line-scan image sensor for the measurement of red cell velocity in microvessels. J. Biomed. Eng. 8, 329–333.
Kraan, M. C., Reece, R. J., Smeets, T. J., Veale, D. J., Emery, P., and Tak, P. P. (2002) Comparison of synovial tissues from the knee joints and the small joints of rheumatoid arthritis patients: Implications for pathogenesis and evaluation of treatment. Arthritis Rheum. 46, 2034–2038.
Dolhain, R. J., Tak, P. P., Dijkmans, B. A., et al. (1998) Methotrexate reduces inflammatory cell numbers, expression of monokines and of adhesion molecules in synovial tissue of patients with rheumatoid arthritis. Br. J. Rheumatol. 37, 502–508.
Tak, P. P., van der Lubbe, P. A., Cauli, A., et al. (1995) Reduction of synovial inflammation after anti-CD4 monoclonal antibody treatment in early rheumatoid arthritis. Arthritis Rheum. 38, 1457–1465.
Kraan, M. C., Patel, D. D., Haringman, J. J., et al. (2001) The development of clinical signs of rheumatoid synovial inflammation is associated with increased synthesis of the chemokine CXCL8 (interleukin-8). Arthritis Res. 3, 65–71.
Boyle, D. L., Rosengren, S., Bugbee, W., Kavanaugh, A., and Firestein, G. S. (2003) Quantitative biomarker analysis of synovial gene expression by real-time PCR. Arthritis Res. Ther. 5, R352–R360.
Dolhain, R. J. E. M., Haar ter, N. T., Kuiper de, et al. (1998) Distribution of T cells and signs of T cell activation in the rheumatoid joint: implications for semiquantitative comparative histology. Br. J. Rheumatol. 37, 324–330.
Rooney, M., Condell, D., Quinlan, W., et al. (1988) Analysis of the histologic variation of synovitis in rheumatoid arthritis. Arthritis Rheum. 31, 956–963.
Kraan, M. C., Versendaal, H., Jonker, M., et al. (1998) Asymptomatic synovitis precedes clinical manifest arthritis. Arthritis Rheum. 41, 1481–1488.
Kraan, M. C., Smith, M. D., Weedon, H., Ahern, M. J., Breedveld, F. C., and Tak, P. P. (2001) Measurement of cytokine and adhesion molecule expression in synovial tissue by digital image analysis. Annals Rheum. Dis. 60, 296–298.
Kroustrup, J. P. and Gundersen, H. J. (1983) Sampling problems in a heterogeneous organ: quantitation of relative and total volume of pancreatic islets by light microscopy. J. Microsc. 132, 43–55.
Gundersen, H. J. and Osterby, R. (1981) Optimizing sampling efficiency of stereological studies in biology: or ‘do more less well!’. J. Microsc. 121, 65–73.
Bresnihan, B., Tak, P. P., Emery, P., Klareskog, L., and Breedveld, F. (2000) Synovial biopsy in arthritis research: five years of concerted European collaboration. Ann. Rheum. Dis. 59, 506–511.
Bresnihan, B. and Tak, P. P. (1999) Synovial tissue analysis in rheumatoid arthritis. Best Pract. Res. Clin. Rheumatol. 13, 645–659.
Tak, P. P. and Bresnihan, B. (2000) The pathogenesis and prevention of joint damage in rheumatoid arthritis. Advances from synovial biopsy and tissue analysis. Arthritis Rheum. 43, 2619–2633.
Sundarrajan, M., Boyle, D. L., Chabaud-Riou, M., Hammaker, D., and Firestein, G. S. (2003) Expression of the MAPK kinases MKK-4 and MKK-7 in rheumatoid arthritis and their role as key regulators of JNK. Arthritis Rheum. 48, 2450–2460.
Wunder, A., Muller-Ladner, U., Stelzer, E. H., et al. (2003) Albumin-based drug delivery as novel therapeutic approach for rheumatoid arthritis. J. Immunol. 170, 4793–4801.
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© 2007 Humana Press Inc., Totowa, NJ
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van der Hall, P.O., Kraan, M.C., Tak, P.P. (2007). Quantitative Image Analysis of Synovial Tissue. In: Cope, A.P. (eds) Arthritis Research. Methods in Molecular Medicine, vol 135. Humana Press. https://doi.org/10.1007/978-1-59745-401-8_8
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DOI: https://doi.org/10.1007/978-1-59745-401-8_8
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