Skip to main content
Springer Nature Link
Log in

Accuracy of Microvascular Measurements Obtained From Micro-CT Images

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

Early changes in branching geometry of microvasculature and its associated impact on the perfusion distribution in diseases, especially those in which different branching generations are affected differently, require the ability to analyze intact vascular trees over a wide range of scales. Micro-CT offers an excellent framework to analyze the microvascular branching geometry. Such an analysis requires methods to be developed that can accurately characterize branching properties, such as branch diameter, length, branching angle, and branch interconnectivity of the microvasculature. The purpose of this article is to report the results of a study of two human intramyocardial coronary vascular tree casts in which the accuracy of micro-CT vascular imaging and its analysis are tested against measurements made through an optical microscope (used as the “gold-standard”). Methods related to image segmentation of the vascular lumen, vessel tree centerline extraction, individual branch segment measurement, and compensating for the non-ideal modulation transfer function of micro-CT scanners are presented. The extracted centerline accurately characterized the hierarchical structure of the vascular tree casts in terms of “parent–branch” relationships which allowed each interbranch segments’ dimensions to be compared to the optical measurement method. The comparison results show a close to ideal 1:1 relationship for both length and diameter measurements made by the two methods. Combining the results from both specimens, the standard deviation of the difference between measurement methods was 19 μm for the measurement of interbranch segment diameters (ranging from 12 to 769 μm), and 172 μm for the measurement of interbranch segment lengths (ranging from 14 to 3252 μm). These results suggest that our micro-CT image analysis method can be used to characterize a vascular tree’s hierarchical structure, and accurately measure interbranch segment lengths and diameters.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Canada)

Instant access to the full article PDF.

Institutional subscriptions

FIGURE 1
FIGURE 2
FIGURE 3
FIGURE 4
FIGURE 5
FIGURE 6
FIGURE 7
FIGURE 8
FIGURE 9
FIGURE 10
FIGURE 11
FIGURE 12

Similar content being viewed by others

References

  1. Altman, D. G., and J. M. Bland. Measurement in medicine: the analysis of method comparison studies. Statistician 32:307–313, 1983.

    Article  Google Scholar 

  2. Au, O. K.-C., C.-L. Tai, H.-K. Chu, D. Cohen-Or, and T.-Y. Lee. Skeleton extraction by mesh contraction. ACM Trans. Graph. 27:1–10, 2008.

    Article  Google Scholar 

  3. Bassingthwaighte, J. B., J. H. G. M. Van Beek, and R. B. King. Fractal branchings: the basis of myocardial flow heterogeneities. Ann. NY Acad. Sci. 591:392–401, 1990.

    Article  CAS  PubMed  Google Scholar 

  4. Cohen, L.D., and R. Kimmel. Global minimum for active contour models: a minimal path approach. Int. J. Comput. Vis. 24:57–78, 1997.

    Article  Google Scholar 

  5. Deschamps, T., and L. D. Cohen. Minimal path in 3D images and application to virtual endoscopy. In: ECCV 2000, Vol. 184, 2000, pp. 543–547.

  6. Eberly, D. and J. Lancaster. On gray scale image measurements. CVGIP: Graph. Mod. Image Proc. 53:538–549, 1991.

    Article  Google Scholar 

  7. Feldkamp, L. A., L. C. Davis, and J. W. Kress. Practical cone-beam algorithm. J. Opt. Soc. Am. A 1:612–619, 1984.

    Article  Google Scholar 

  8. Glover, G. H., and N. J. Pelc. Nonlinear partial volume artifacts in x-ray computed tomography. Med. Phys. 7:238–248, 1980.

    Article  CAS  PubMed  Google Scholar 

  9. Hassouna, M.S. and A.A. Farag. On the extraction of curve skeletons using gradient vector flow. In: 11th IEEE International Conference on Computer Vision, Vol. 2136, 2007, pp. 1–8.

  10. Herman, G. T. Image Reconstruction From Projections. NY: Academic Press, 316 pp, 1980.

    Google Scholar 

  11. Hoffman, K. R., D. P. Nazareth, L. Miskolczi, A. Gopal, Z. Wang, S. Rudin, and D. R. Bednarek. Vessel size measurements in angiograms: a comparison of techniques. Med. Phys. 29:1622–1633, 2002.

    Article  Google Scholar 

  12. Hoogeveen, R., C. Bakker, and M. Viergever. Limits to the accuracy of vessel diameter measurement in MR angiography. J. Magn. Reson. Imaging 8:1228–1235, 1998.

    Article  CAS  PubMed  Google Scholar 

  13. Jorgensen, S. M., O. Demirkaya, and E. L. Ritman. Three-dimensional imaging of vasculature and parenchyma in intact rodent organs with x-ray micro-CT. Am. J. Physiol. Heart. Circ. Physiol. 275:H1103–H1114, 1998.

    CAS  Google Scholar 

  14. Kaimovitz, B., Y. Huo, Y. Lanir, G. S. Kassab. Diameter asymmetry of porcine coronary arterial trees: structural and functional implications. Am. J. Physiol. Heart Circ. Physiol. 294:H714–H723, 2008.

    Article  CAS  PubMed  Google Scholar 

  15. Kalsho, G., and G. S. Kassab. Bifurcation asymmetry of the porcine coronary vasculature and its implications on coronary flow heterogeneity. Am. J. Physiol. 287:H2493–H2500, 2004.

    CAS  Google Scholar 

  16. Kline, T. L., Y. Dong, M. Zamir, and E. L. Ritman. Erode/dilate analysis of micro-CT images of porcine myocardial microvasculature. Proc. SPIE 7626:762620-1–762620-9, 2010.

    Google Scholar 

  17. Lam, L. and S.-W. Lee. Thinning methodologies—a comprehensive survey. IEEE Trans. Patt. Anal. Mach. Int. 14:869–885, 1992.

    Article  Google Scholar 

  18. Lee, J., P. Beighley, E. Ritman, and N. Smith. Automatic segmentation of 3D micro-CT coronary vascular images. Med. Image Anal. 11:630–647, 2007.

    Article  PubMed  Google Scholar 

  19. Lee, T.-C., and R. L. Kashyap. Building skeleton models via 3-D medial surface/axis thinning algorithms. CVGIP: Graph. Mod. Image Proc. 56:462-478, 1994.

    Article  Google Scholar 

  20. Lindquist, W. B., S.-M. Lee, D. A. Coker, K. W. Jones, and P. Spanne. Medial axis analysis of three dimensional tomographic images of drill core samples. J. Geophys. Res. 101B:8297, 1996.

    Article  Google Scholar 

  21. Lobregt, S., P. W. Veerbeek, and F. C. Groen. Three-dimensional skeletonization: principle and algorithm. IEEE Trans. Patt. An. Mach. Int. PAMI-2:75–77, 1980.

    Google Scholar 

  22. Marxen, M., J. G. Sled, L. X. Yu, C. Paget, and R. M. Henkelman. Comparing microsphere deposition and flow modeling in 3D vascular trees. Am. J. Physiol. Heart Circ. Physiol. 291:H2136–H2141, 2006.

    Article  CAS  PubMed  Google Scholar 

  23. Megalooikonomou, V., M. Barnathan, D. Kontos, P. R. Bakic, and A. D. A. Maidment. A representation and classification scheme for tree-like structures in medical images: analyzing the branching pattern of ductal trees in x-ray galactograms. IEEE Trans. Med. Imaging 28:487–493, 2009.

    Article  PubMed  Google Scholar 

  24. Nordsletten, D. A., S. Blackett, M. D. Bentley, E. L. Ritman, and N. P. Smith. Structural morphology of renal vasculature. Am. J. Physiol. Heart Circ. Physiol. 291:H296–H309, 2006.

    Article  CAS  PubMed  Google Scholar 

  25. Op Den Buijs, J., Z. Bajzer, and E. L. Ritman. Branching morphology of the rat hepatic portal vein tree: a micro-CT study. Ann. Biomed. Eng. 34:1420–1428, 2006.

    Article  Google Scholar 

  26. Osher, S., and J. Sethian. Fronts propagating with curvature speed: algorithms based on Hamilton–Jacobi formulations. J. Comput. Phys. 79:12–49, 1988.

    Article  Google Scholar 

  27. Peyré, G., and L. Cohen. Landmark-based geodesic computation for heuristically driven path planning. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, 2006, pp. 2229–2236.

  28. Popel, A. S. Network models of peripheral circulation. In: Handbook of Bioengineering, edited by R. Skalak and S. Chien. New York: McGraw-Hill Inc., 1987, pp. 20.1–20.24.

    Google Scholar 

  29. Pries, A. R., T. W. Secomb, and P. Gaehtgens. Relationship between structural and hemodynamic heterogeneity in microvascular networks. Am. J. Physiol. Heart Circ. Physiol. 270:H545–H553, 1996.

    CAS  Google Scholar 

  30. Robb, R. A., D. P. Hanson, and M. C. Stacy. ANALYZE: a comprehensive, operator-interactive software package for multidimensional medical image display and analysis. Comput. Med. Imaging Graph. 13:433–454, 1989.

    Article  CAS  PubMed  Google Scholar 

  31. Rouy, E., and A. Tourin. A viscosity solutions approach to shape-from-shading. SIAM J. Numer. Anal. 29:867–884, 1992.

    Article  Google Scholar 

  32. Sato, Y., S. Yamamoto, and S. Tamura. Accurate quantification of small-diameter tubular structures in isotropic CT volume data based on multiscale line filter responses. In: Proceedings of MICCAI’04, Vol. 3216, 2004, pp. 508–515.

  33. Schirmacher, H., M. Zockler, D. Stalling, and H.-C. Hege. Boundary surface shrinking—a continuous approach to 3D center line extraction. In: Imaging Multidimensional Digital Signal Processing, 1998, pp. 25–28.

  34. Sedgewick, R. Algorithms. Reading, MA: Addison-Wesley Publishing Company, 1988, 657 pp.

    Google Scholar 

  35. Sethian, J. Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision and Materials Science. New York, NY: Cambridge University Press, 1999, 400 pp.

    Google Scholar 

  36. Soltanian-Zadeh, H., A. Shahrokni, and R. A. Zoroofi. Voxel-coding method for quantification of vascular structure from 3D images. Proc. SPIE 4321:263–270, 2001.

    Article  Google Scholar 

  37. Spaan, J. A. E. Coronary Blood Flow. AA Dordrecht, The Netherlands: Kluwer Academic Publishers, 1991, 389 pp.

    Google Scholar 

  38. Sutera, S. P., and R. Skalak. The history of poiseuille’s law. Ann. Rev. Fluid Mech. 25:1–19, 1993.

    Article  Google Scholar 

  39. Suwa, N., and T. Takahashi. Estimation of intravascular blood pressure gradient by mathematical analysis of arterial casts. Tohoku J. Exp. Med. 79:168–198, 1963.

    Article  CAS  PubMed  Google Scholar 

  40. Telea, A., and J. J. van Wijk. An augmented fast marching method for computing skeletons and centerlines. Eurograph. Assoc. (to appear in IEEE TCVG Symposium on Visualization) 22:251–261, 2002.

    Google Scholar 

  41. Tsao, Y. F. and K. S. Fu. A parallel thinning algorithm for 3-D pictures. Comput. Graph. Imaging Process. 17:315–331, 1981.

    Article  Google Scholar 

  42. van Uitert R., and I. Bitter. Subvoxel precise skeletons of volumetric data based on fast marching methods. Med. Phys. 34:627–637, 2007.

    Article  PubMed  Google Scholar 

  43. Wischgoll, T., J. S. Choy, E. L. Ritman, and G. S. Kassab. Validation of image-based method of extraction of coronary morphometry. Ann. Biomed. Eng. 36:356–368, 2008.

    Article  PubMed  Google Scholar 

  44. Witt, S. T., C. H. Riedel, M. Goessl, M. S. Chmelik, and E. L. Ritman. Point spread function deconvolution in 3D micro-CT angiography for multiscale vascular tree separation. Proc. SPIE 5030:720–727, 2003.

    Article  Google Scholar 

  45. Yu, K.-C., E. L. Ritman, and W. E. Higgins. System for the analysis and visualization of large 3D anatomical trees. Comput. Biol. Med. 37:1802–1820, 2007.

    Article  PubMed  Google Scholar 

  46. Zamir, M. Tree structure and branching characteristics of the right coronary artery in a right-dominant human heart. Can. J. Cardiol. 12:593–599, 1996.

    CAS  PubMed  Google Scholar 

  47. Zamir, M. Mechanics of blood supply to the heart: wave reflection effects in a right coronary artery. Proc. R. Soc. Lond. B. 265:439–444, 1998.

    Article  CAS  Google Scholar 

  48. Zamir, M. The Physics of Coronary Blood Flow. New York, NY: Springer Science+Business Media Inc., 2005.

    Google Scholar 

  49. Zamir, M., and N. Brown. Arterial branching in various parts of the cardiovascular system. Am. J. Anat. 163:295–307, 1982.

    Article  CAS  PubMed  Google Scholar 

  50. Zamir, M., and H. Chee. Segment analysis of human coronary arteries. Blood Vessels 24:76–84, 1987.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Mr. Steven M. Jorgensen for scanning the specimens, Mr. Andrew J. Vercnocke for performing image reconstructions, and Ms. Delories C. Darling for her help in the preparation of this manuscript. We would also like to thank the anonymous reviewers for their helpful suggestions. This study was supported in part by NIH Grant EB000305, and The Mayo Foundation. The hand measurements and schematic diagrams, as well as the micro-CT image volumes of specimens h61 and r14 have been made available through our website (Phenoscope), http://www.mayoresearch.mayo.edu/pirl.

Author information

Authors and Affiliations

  1. Department of Physiology and Biomedical Engineering, Physiological Imaging Research Laboratory, Mayo Clinic College of Medicine, 200 First Street SW Rochester, Rochester, MN, 55905, USA

    Timothy L. Kline & Erik L. Ritman

  2. Department of Applied Mathematics, The University of Western Ontario, London, ON, N6A 5B7, Canada

    Mair Zamir

  3. Department of Medical Biophysics, The University of Western Ontario, London, ON, N6A 5B7, Canada

    Mair Zamir

Authors
  1. Timothy L. Kline
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mair Zamir
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erik L. Ritman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Erik L. Ritman.

Additional information

Associate Editor Larry V. McIntire oversaw the review of this article.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kline, T.L., Zamir, M. & Ritman, E.L. Accuracy of Microvascular Measurements Obtained From Micro-CT Images. Ann Biomed Eng 38, 2851–2864 (2010). https://doi.org/10.1007/s10439-010-0058-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-010-0058-7

Keywords

Search

Navigation