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Automatic method for quantitative automatic evaluation in dynamic renal scintilography images

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Abstract

Renal insufficiency is one of the most frequent health problems in Brazil and in the world. In some cases, the renal insufficiency symptoms are not easily perceived, and the disease may evolute to a more serious stage. Nuclear medicine is a specialty for human body image acquisition based on the use of radioisotopes for the analysis of some organ functionalities. Renal scintigraphy is an image based examination used for the diagnosing of problems in renal functions. This work presents an automatic method for quantitative analysis based on renal scintigraphy. The proposed methodology is capable of segmenting regions in the image associated with kidney, background, and aorta. Based on parameters obtained from these segmented images, it is possible to compute the glomerular filtration rate, renogram and renal transit time by deconvolution. The result obtained by the methodology were compared with results of a manual analysis made by a specialist, reaching promising results to be used in a clinical use.

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Notes

  1. The images were represented in the same scale, even though they had different dimensions.

  2. Around the kidney

References

  1. Arthur D, Vassilvitskii S (2007) K-means++: the advantages of careful seeding. In: Proceedings of the eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’07, pp 1027–1035. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA. http://dl.acm.org/citation.cfm?id=1283383.1283494

    Google Scholar 

  2. Bajen MT, Puchal R, González A, GRINYO JM, Castelao A, Mora J, Martin-Comin J (1997) Mag3 renogram deconvolution in kidney transplantation: utility of the measurement of initial tracer uptake. Eur J Nucl Med 38(8):1295–1299

    Google Scholar 

  3. Benesty J, Chen J, Huang Y, Cohen I (2009) Pearson Correlation Coefficient. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 1–4. doi:10.1007/978-3-642-00296-0_5

    Google Scholar 

  4. Durand E, Blaufox MD, Britton KE, Carlsen O, Cosgriff P, Fine E, Fleming J, Nimmon C, Piepsz A, Prigent A, Samal M (2008) International scientific committee of radionuclides in nephrourology (iscorn) consensus on renal transit time measurements. Semin Nucl Med 38(1):82–102. doi:10.1053/j.semnuclmed.2007.09.009. http://www.sciencedirect.com/science/article/pii/S0001299807001158. Radionuclides in Nephrourology

    Article  Google Scholar 

  5. Gates G (1982) Glomerular filtration rate: estimation from fractional renal accumulation of 99mTc-DTPA (stannous). Am J Roentgenol 138(3):565–570

    Article  Google Scholar 

  6. Hastie T, Tibshirani R, Friedman JH (2001) The elements of statistical learning: data mining, inference, and prediction: with 200 full-color illustrations. Springer-Verlag, New York

    MATH  Google Scholar 

  7. Kalman RE (1960) A new approach to linear filtering and prediction problems. Trans ASME J Basic Eng 82(Series D):35–45

    Article  Google Scholar 

  8. Kojima A, Takaki Y, Tsuji A, Nakashima R, Kira M, Hara M, Tomiguchi S, Matsumoto M, Takahashi M (1996) Quantitative renography with the organ volume method and interporative background subtraction technique. Ann Nucl Med 10(4):401–407. doi:10.1007/BF03164801

    Article  Google Scholar 

  9. Landgren M, Sjöstrand K, Ohlsson M, Ståhl D, Overgaard N, Åström K, Sixt R, Edenbrandt L (2011) An automated system for the detection and diagnosis of kidney lesions in children from scintigraphy images. Image Analysis 489–500

  10. Lawson RS (1999) Application of mathematical methods in dynamic nuclear medicine studies. Phys Med Biol 44(4):R57

    Article  Google Scholar 

  11. Lin KJ, Huang JY, Chen YS (2011) Fully automatic region of interest selection in glomerular filtration rate estimation from 99m tc-dtpa renogram. J Digit Imaging 24(6):1010–1023

    Article  Google Scholar 

  12. Marcuzzo M, Masiero PR, Scharcanski J (2007) Quantitative parameters for the assessment of renal scintigraphic images 2007 29th Annual international conference of the IEEE engineering in medicine and biology society. doi:10.1109/IEMBS.2007.4353070, pp 3438–3441

  13. OSIRIX (2016) Osirix viewer software, http://www.osirix-viewer.com/

  14. Outcomes KDIG (2012) Kdigo 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. http://www.kdigo.org/clinical_practice_guidelines/pdf/CKD/KDIGO_2012_CKD_GL.pdf

  15. Prigent A, Cosgriff P, Gates G, Graneurs G, Fine EJ, Itoh K, Peters M, Piepsz A, Rehling M, Rutland M, Taylor A (1999) Renal nuclear medicine: including recent consensus reports 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. Semin Nucl Med 29(2):146–159. doi:10.1016/S0001-2998(99)80005-1. http://www.sciencedirect.com/science/article/pii/S0001299899800051

    Article  Google Scholar 

  16. Rijsbergen CJV (1979) Information retrieval, 2nd edn. Butterworth-Heinemann, Newton, MA, USA

    MATH  Google Scholar 

  17. Russell C, Yester M, Dubovsky E (1990) Measurement of renal parenchymal transit time of 99mtc-mag3 using factor analysis. Nuklearmedizin. Nucl Med 29(4):170

    Google Scholar 

  18. Rutland MD (1985) A comprehensive analysis of renal dtpa studies. i. theory and normal values. Nucl Med Commun 6:11–20

    Article  Google Scholar 

  19. SBN (2013) Socidade brasileira de nefrologia. http://www.sbn.org.br/

  20. Shih FY (2010) Image processing and mathematical morphology: fundamentals and applications CRC press

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

  22. Stevens LA, Coresh J, Greene T, Levey AS (2006) Assessing kidney function–measured and estimated glomerular filtration rate. N Engl J Med 354 (23):2473–2483. doi:10.1056/NEJMra054415. PMID: 16760447

    Article  Google Scholar 

  23. Taylor A Jr, Nally JV (1995) Clinical applications of renal scintigraphy. AJR Am J Roentgenol 164(1):31–41

    Article  Google Scholar 

  24. Ting KM (2010) Confusion Matrix. Springer US, Boston, MA, pp 209–209. doi:10.1007/978-0-387-30164-8_157

    Google Scholar 

  25. Valentinuzzi M, Montaldo Volachec E (1975) Discrete deconvolution. Med Biol Eng Comput 13(1):123–125

    Article  MATH  Google Scholar 

  26. Xefteris S, Tserpes K, Varvarigou T (2012) A method for improving renogram production and detection of renal pelvis using mathematical morphology on scintigraphic images. Engineering, Technology & Applied Science Research 2(4):251

    Google Scholar 

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Acknowledgements

The authors acknowledge CAPES, CNPq and FAPEMA for financial support. We thank the Clinica Nuclear Maranhao for provided image database.

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Correspondence to Steve Tsham Mpinda Ataky.

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dos Santos, W.H.S., Ataky, S.T.M., Silva, A.C. et al. Automatic method for quantitative automatic evaluation in dynamic renal scintilography images. Multimed Tools Appl 76, 19291–19315 (2017). https://doi.org/10.1007/s11042-017-4715-9

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