A method for digital renal scintigram analysis based on brightness and geometric features
A.V. Gaidel, A.G. Khramov, A.V. Kapishnikov, A.V. Kolsanov, Yu.S. Pyshkina

 

Samara National Research University, Samara, Russia,
Image Processing Systems Institute of the RAS–Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia,
Samara State Medical University, Samara, Russia

Full text of article: Russian language.

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Abstract:
We proposed a method of automated scintigram image processing enabling an objective evaluation of the renal parenchyma condition to be made based on scintigram brightness and geometric characteristics with threshold processing. We studied the method using a set of real radionuclide images of a renal transplant. The results of clinical studies confirm the effectiveness of the developed method. We obtained objective numerical values associated with thresholding the image from 40% to 80%, based on which one can form an independent assessment of the presence or absence of focal lesions in the renal parenchyma.

Keywords:
image processing, pattern recognition, scintigraphy, kidney disease, transplantation.

Citation:
Gaidel AV, Khramov AG, Kapishnikov AV, Kolsanov AV, Pyshkina YuS. A method for digital renal scintigram analysis based on brightness and geometric features. Computer Optics 2017; 41(1): 103-109. DOI: 10.18287/2412-6179-2017-41-1-103-109.

References:

  1. Ribeiro MP, Sandes-Freitas TV, Sato KH, Ribeiro Junior MA, Silva-Junior HT, Medina-Pestana JO. Effect of induction therapy in kidney transplantation in sensitive patients: analysis of risks and benefits. J Bras Nefrol 2016; 38(1): 82-89. DOI: 10.5935/0101-2800.20160013.
  2. Ayaz S, Gencoglu EA, Moray G, Gozukara MY, Haberal M. Evaluation of the effects of recipient/donor gender on early/late postoperative renal graft functions by renal scintigraphy. Exp Clin Transplant 2014; 12(6): 510-514. DOI: 10.6002/ect.2013.0275.
  3. Kapishnikov AV, Kolsanov AV, Pyshkina JuS. Radionuclide imaging in the evaluation of the functional state of the transplanted kidney in the post-transplant period [In Russian]. Annals of the Russian academy of medical sciences 2014; 11-12: 89-96.
  4. Kapishnikov AV, Kolsanov AV, Pyshkina YuS. Dynamic renal scintigraphy potential to diagnose renal posttransplant complications in kidney recipients [In Russian]. Russian journal of transplantology and artificial organs 2014; 16(2): 39-45. DOI: 10.15825/1995-1191-2014-2-39-45.
  5. Glumov NI, Kapishnikov AV. Computer processing of scintigraphic lung images [In Russian]. Computer Optics 2003; 25: 158-164.
  6. Dupont PJ, Psimenou E, Lord R, Buscombe JR, Hilson AJ, Sweny P. Late recurrent urinary tract infections may produce renal allograft scarring even in the absence of symptoms or vesicoureteric reflux. Transplantation 2007; 84(3): 351-355. DOI: 10.1097/01.tp.0000275377.09660.fa.
  7. Coulthard MG, Keir MJ. Reflux nephropathy in kidney transplants, demonstrated by dimercaptosuccinic acid scanning. Transplantation 2006; 82(2): 205-210.
  8. Lishmanov YuB, Chernov VI. Radionuclide diagnostics for practitioners [In Russian]. Tomsk: “STT” Publisher; 2004.
  9. Neubauer N, Johnson L, Lemmers M, Petri B, Stevens JS. MAG3 renal transplant tomography SPECT with a non-SPECT agent. Clin Nucl Med 1996; 21(1): 11-14.
  10. Hutchinson C, Beckett M, Kiratli P, Gordon I, Trompeter RS, Rees L. The significance of a defect on DMSA scan in children with renal transplants. Pediatr Transplant 2003; 7(6): 441-445.
  11. Budihna NV, Milcinski M, Kajtna-Koselj M, Malovrh M. Relevance of Tc-99m DMSA scintig-raphy in renal transplant parenchymal imaging. Clin Nucl Med 1994; 19(9): 782-784.
  12. Antonov OV, Kitaeva JuJu, Antonova IV, Komarova AA, Philippov GP. Nosologic components of chronic kidney disease: terminology, epidemiological features and their unit weight in the urinary pathology structure (literature review). Part 1 [In Russian]. Annals of Surgut State University. Medicine 2013; 2(16): 4-8.
  13. Cairns HS, Spencer S, Hilson AJ, Rudge CJ, Neild GH. 99mTc-DMSA imaging with tomography in renal transplant recipients with asdnormal lower urinary tracts. Nephrol Dial Transplant 1994; 9(8): 1157-61. DOI: 10.1093/ndt/9.8.1157.
  14. Grabe M, Bartoletti R, Bjerklund-Johansen TE, Çek HM, Pickard RS, Tenke P, Wagenlehner F, Wullt B. Urinary tract infections in renal insufficiency, transplant recipients, diabetes mellitus and immunosuppression. Guideline of the European Association of Urology [In Russian]. Effective Pharmacotherapy 2015; 6: 4-14.
  15. Gaidel AV. Matched polynomial features for the analysis of grayscale biomedical images. Computer Optics 2016; 40(2): 232-239. DOI: 10.18287/2412-6179-2016-40-2-232-239.
  16. Kotina ED, Ovsyannikov DA, Ploskikh VA, Babin AV, Tuzi­kova OF. Data processing in radionuclide diagnostics [In Russian]. Ulyanovsk Medico-biological Journal 2014; 1: 174-175.
  17. Gaidel AV, Larionova SN, Khramov AG. Research of textural features for the diagnostics of nephrological diseases using ultrasound images [In Russian]. Vestnik of the Samara State Aerospace University 2014; 1(43): 229-237.
  18. Soifer VA, ed, Gashnikov MV, Glumov NI, Ilyasova NYu, Myasnikov VV, Popov SB, Sergeev VV, Khramov AG, Chernov AV, Chernov VM, Chicheva MA, Fursov VA. Methods for computer image processing [In Russian]. Moscow: “Fizmatlit”; 2003. ISBN: 5-9221-0270-2.
  19. Kobzar AI. Applied mathematical statistics. For engineers and scientists [In Russian]. Moscow: “Fizmatlit”; 2006. ISBN: 978-5-9221-1375-5.
  20. Weisberg S. Applied Linear Regression. New York: Wiley; 2013.
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