Visualisation and modelling of renal capillaries from confocal images

Article

Abstract

A computer aided design was developed to support three-dimensional visualisation and modelling of vascular networks. Volume data comprised a series of images obtained using a Zeiss confocal laser scanning microscope. The profiles of vessels were automatically segmented using two-dimensional morphological filters. Segmented contours of the vessels were used to form a spatial model of the network. The centre points of segmented contours were used to derive a three-dimensional graph representing the vascular network. The proposed method was applied to renal capillary networks of normal rats, and showed well the lobular structure of glomeruli. The average length of renal capillary networks was 6.09 mm. Three-dimensional models based on confocal data require much less effort than reconstructions based on serial sections, and can be adapted for any vascular patterns.

Keywords

Renal glomerulus Capillary networks Image analysis Confocal microscopy Three-dimensional modelling Graph theory Reconstruction 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. AVS, Inc. (1992): ‘AVS users guide’. Waltham, MassachusettsGoogle Scholar
  2. Boyer, C. C. (1956): ‘The vascular pattern of the renal glomerulus as revealed by plastic reconstruction from serial sections’,Anat. Rec.,125, pp. 433–441CrossRefGoogle Scholar
  3. Culling, C. F. A., andVassar, P. S. (1985): ‘Fluorescence PAS’,in Cullings, C. F. A., Allison, R. T., andBarr, W. T. (Eds.): ‘Cellular pathology technique’, 4th Ed., (Butterworth & Co, London), pp. 230–231.Google Scholar
  4. Deen, W. M., Bridges, C. R., Brenner, B. M., andMyers, B. D. (1985): ‘Heteroporous model of glomerular size selectivity. Application to normal and nephrotic humans’,Am. J. Physiol.,249, pp. F374–389Google Scholar
  5. Deen, W. M., Robertson, C. R., andBrenner, B. M. (1972): ‘A model of glomerular ultrafiltration in the rat’,Am. J. Physiol.,223, pp. 1178–1183Google Scholar
  6. Hibbard, L. S., Grothe, R. A. Jr., Arnicar-Sulze, T. L., Dovey-Hartman, B. J., andPage, R. B. (1993): ‘Computed three-dimensional reconstruction of median-eminence capillary modules: image alignment and correlation’,J. Microsc.,171, pp. 39–56Google Scholar
  7. Interrante, V., Oliver, W., Pier, S., andFuchs, H. (1994): ‘Display methods for gray-scale, voxel-based data sets’,in ‘Three-dimensional confocal microscopy: volume investigation of biological specimens’, edited byStevens, J. K., Mills, L. R. andTrogadis, J. E., San Diego, Academic Press, 1994, pp. 131–167Google Scholar
  8. Kaczmarek, E. (1996a): ‘Quantification of three-dimensional vascular patterns in renal glomeruli’, Proc. 9 ICS Copenhagen, 1995,Acta Stereol.,15/2, pp. 103–200Google Scholar
  9. Kaczmarek, E. (1996b): ‘Visualizing of kidney capillaries with three-dimensional tree structures’, Proceedings of 12 Spring Conference on Computer Graphics. Bratislava-Budmerice June 5–7, 1996 (Comenius University, Bratislava) pp. 77–86. Electronic book:http://www.cg.tuwien.ac.at/~wp/SCCG96-proceedings/ Google Scholar
  10. Kaczmarek, E., andBecker, R. L. (1997): ‘Three-dimensional modeling of renal glomerular capillary networks’,Anal. Quant. Cytol. Histol.,19, pp. 93–101Google Scholar
  11. Margadant, F., Leemann, T., andNiederer, P. (1996): ‘A precise light attenuation correction for confocal scanning microscopy with O(n4/3) computing time O(n) memory requirements for n voxels’,J. Microsc.,182, pp. 121–132CrossRefGoogle Scholar
  12. Papenfus, H. D., andGross, J. F. (1978): ‘Analytic study of the influence of capillary pressure drop and permeability on glomerular ultrafiltration’,Microvasc. Res.,16, pp. 59–72CrossRefGoogle Scholar
  13. Preston, K. (1991): ‘Residue-producing Ξ filters and their applications in medical image analysis’, Proc. SPIE/SPSE Conference on Electronic Imaging Science and Technology,1450, pp. 59–70Google Scholar
  14. Preston, K., Joe, B., Siderits, R., andWelling, J. (1995): ‘Three-dimensional reconstruction of the human renal glomerulus’,J. Microsc.,177, pp. 7–17Google Scholar
  15. Remuzzi, A., Brenner, B. M., Pata, V., Tebaldi, G., Mariano, R., Belloro, A., andRemuzzi, G. (1992): ‘Three-dimensional reconstructed glomerular capillary network: blood flow distribution and local filtration’,Am. J. Physiol.,263, pp. F562-F572Google Scholar
  16. Remuzzi, A., andEne-Iordache, B. (1995): ‘Capillary network structure does not affect theoretical analysis of glomerular size selectivity’,Am J. Physiol.,268, pp. F972-F979Google Scholar
  17. Shea, S. (1979): ‘Glomerular hemodynamics and vascular structure. The pattern and dimensions of a aingle rat glomerular capillary network reconstructed from ultrathin sections’,Microvasc. Res.,18, pp. 129–143CrossRefGoogle Scholar
  18. Shea, S. M., andRaskova, J. (1984): ‘Glomerular hemodynamics and vascular structure in uremia: a network analysis of glomerular path lengths and maximal blood transit times computed for a microvascular model reconstructed from subserial ultrathin sections’,Microvasc. Res.,28, pp. 37–50CrossRefGoogle Scholar
  19. Shimizu, H., Shinohara, N., andYokohama, T. (1988): ‘Topological analysis of the three-dimensional structure of the human renal glomerulus using a computer aided reconstruction system’,Microvasc. Res.,36, pp. 130–139CrossRefGoogle Scholar
  20. Stoyan, D., Kendall, W. S., andMecke, J. (1987): ‘Stochastic geometry and its applications’ (Akademie Vlg., Berlin)MATHGoogle Scholar

Copyright information

© IFMBE 1999

Authors and Affiliations

  1. 1.Department of Medical Informatics and StatisticsUniversity of Medical SciencesPoznanPoland

Personalised recommendations