Automatic Methodology for Applying Quantitative Methods in Dynamic Renal Scintigraphy Images

• Wallas H. S. Santos UFMA
• Bruno M. C. Leite Clínica Nuclear Maranhão
• Aristófanes C. Silva UFMA
• Thiago P. Freire UFMA
• Anselmo C. Paiva UFMA

Abstract

In dynamic renal scintigraphy or renography images, quantitative methods are applied to study the function of the kidneys. In this examination processing, the specialist has to define in the image the regions of interest (ROI). This is usually done manually or semi-automatically. This article proposes an automatic method for ROI segmentation of renography examination produced by radiotracer 99m-TC-DTPA. The tests were compared with traditional methods results. For ROIs pixels the rates of true positive, false positive and false negative were 95.33%, 10.37% and 4.67% respectively. Also we evaluate the estimation of the glomerular filtration within this automatically segmented ROI. We achieved rate estimation of the correlation coefficient of 0.95 and root mean square error of 3.88.

References

Gates, G. (1982). Glomerular filtration rate: estimation from fractional renal accumulation of 99mtc-dtpa (stannous). American Journal of Roentgenology, 138(3):565–570.

Lin, K.-J., Huang, J.-Y., and Chen, Y.-S. (2011). Fully automatic region of interest selection in glomerular filtration rate estimation from 99m tc-dtpa renogram. Journal of Digital Imaging, 24(6):1010–1023.

Ma, X., Wan, W., and Yao, J. (2008). Texture image segmentation on improved watershed and multiway spectral clustering. In Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on, pages 1693–1697. IEEE.

Malladi, R. and Sethian, J. A. (1995). Image processing via level set curvature flow. proceedings of the National Academy of sciences, 92(15):7046–7050.

Powsner, R. A., Powsner, E. R., and Powsner, E. R. (2006). Essential nuclear medicine physics. Blackwell Pub.

Prigent, A., Cosgriff, P., Gates, G. F., Graneurs, G., Fine, E. J., Itoh, K., Peters, M., Piepsz, A., Rehling, M., Rutland, M., et al. (1999). Consensus report on quality control of quantitative measurements of renal function obtained from the renogram: International consensus committee from the scientific committee of radionuclides in nephrourology. In Seminars in nuclear medicine, volume 29, pages 146–159. Elsevier.

Ståhl, D., Åström, K., Overgaard, N., Landgren, M., Sjöstrand, K., and Edenbrandt, L. (2011). Automatic compartment modelling and segmentation for dynamical renal scintigraphies. Image Analysis, pages 557–568.

Von Luxburg, U. (2007). A tutorial on spectral clustering. Statistics and computing, 17(4):395–416.

Yan, D., Huang, L., and Jordan, M. I. (2009). Fast approximate spectral clustering. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 907–916. ACM.