Predicting changes in glomerular filtration rate in patients with kidney cancer using a mathematical model

Authors

  • S.M. Pasichnyk Danylo Halytsky Lviv National Medical University
  • M.S. Pasichnyk Danylo Halytsky Lviv National Medical University
  • A.E. Lychkovsky Danylo Halytsky Lviv National Medical University
  • E.O. Stakhovsky National Cancer Institute, Kyiv
  • A.I. Gozhenko Ukrainian Research Institute of Transport Medicine
  • S.V. Shatnyi National University of Water and Environmental Engineering
  • M.A. Pasichnyk Danylo Halytsky Lviv National Medical University

DOI:

https://doi.org/10.32471/exp-oncology.2312-8852.vol-43-no-2.16214

Keywords:

chronic renal failure, nephrometry, organ-sparing surgery

Abstract

Summary. Chronic renal failure is one of the most challenging complications after the completed surgical treatment for renal cell cancer. In 2016, a grading system of tumorous renal involvement was developed, referred to as NCIU nephrometry. However, the systematic parameter to reflect the functional status of the functional renal parenchyma is defined by tumor volume only, with no regard for spatial disposition of the segment(s) where the tumor is located. Our research team decided to improve the NCIU nephrometry system by developing and testing a modified formula for calculation of creatinine clearance, which makes allowance for spatial disposition of tumor within the kidney. We performed numerical computations and analysis of changes in functional status of renal parenchyma depending on coordinate-based spatial location of the tumor in order to augment the existing NCIU nephrometry scale; Matlab, a specialized software package was used as a principal instrument to calculate the number of nephrons and functional renal parenchyma depending on the coordinate-based position of the mass center of the tumor and tumor volume. This model was shown to create a feasible opportunity to increase the percentage of organ-sparing procedures for renal cell cancer and to reduce the incidence/progression of chronic renal failure in these patients.

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Published

26.05.2023

How to Cite

Pasichnyk, S., Pasichnyk, M., Lychkovsky, A., Stakhovsky, E., Gozhenko, A., Shatnyi, S., & Pasichnyk, M. (2023). Predicting changes in glomerular filtration rate in patients with kidney cancer using a mathematical model. Experimental Oncology, 43(2), 185–188. https://doi.org/10.32471/exp-oncology.2312-8852.vol-43-no-2.16214

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