99mTc-MAG3 diuresis renography in differentiating renal obstruction: Using statistical parameters as new quantifiable indices

S. Suriyanto, E. Y.K. Ng*, C. E.David Ng, Xuexian Sean Yan, N. K. Verma

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Objective: The aim of this study was to research, develop and assess the feasibility of using basic statistical parameters derived from renogram, “mean count value (MeanCV) and “median count value (MedianCV)”, as novel indices in the diagnosis of renal obstruction through diuresis renography. Subjects and Methods: First, we re-digitalized and normalized 132 renograms from 74 patients in order to derive the MeanCV and MedianCV. To improve the performance of the parameters, we extrapolated renograms by a two-compartmental modeling. After that, the cutoff points for diagnosis using each modified parameter were set and the sensitivity and specificity were calculated in order to determine the best variants of MeanCV and MedianCV that could differentiate renal obstruction status into 3 distinct classes – i) unobstructed, ii) slightly obstructed, and iii) heavily obstructed. Results: The modified MeanCV and MedianCV derived from extended renograms predicted the severity of the renal obstruction. The most appropriate variants of MeanCV and MedianCV were found to be the MeanCV50 and the MedianCV60. The cutoff points of MeanCV50 in separating unobstructed and obstructed classes as well as slightly and heavily obstructed classes were 0.50 and 0.72, respectively. The cutoff points of MedianCV60 in separating unobstructed and obstructed classes as well as slightly and heavily obstructed classes were 0.35 and 0.69, respectively. Notably, MeanCV50 and MedianCV60 were not significantly influenced by either age or gender. Conclusions: The MeanCV50 and the MedianCV60 derived from a renogram could be incorporated with other quantifiable parameters to form a system that could provide a highly accurate diagnosis of renal obstructions.

Original languageEnglish
Article number103371
JournalComputers in Biology and Medicine
Volume112
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd

ASJC Scopus Subject Areas

  • Computer Science Applications
  • Health Informatics

Keywords

  • Compartmental analysis
  • Computer-assisted diagnosis
  • Diuresis renography
  • Mean count value
  • Median count value
  • Radioisotope renography
  • Renal obstruction

Fingerprint

Dive into the research topics of '99mTc-MAG3 diuresis renography in differentiating renal obstruction: Using statistical parameters as new quantifiable indices'. Together they form a unique fingerprint.

Cite this