99mTc-MAG3 diuresis renography in differentiating renal obstruction: Using statistical parameters as new quantifiable indices. (September 2019)

• Record Type: Journal Article
• Authors: Suriyanto, S.; Ng, E.Y.K.; Ng, C.E. David; Yan, Xuexian Sean; Verma, N.K.
• Is Part Of: Computers in biology and medicine. Volume 112(2019)
• Publication Date: 2019-09
• Subjects: Diuresis renography -- Radioisotope renography -- Renal obstruction -- Mean count value -- Median count value -- Compartmental analysis -- Computer-assisted diagnosis; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2019.103371
• Languages: English
• ISSNs: 0010-4825

Abstract

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. Highlights: Proposed 2 new statistical renal obstruction parameters, increased in defining and identifying the degree of obstruction. 2 novel indices are MeanCV & MedianCV to classify renal status into 3 classes: unobstructed, slightly & heavily obstructed. The indices are derived via diuretic renography & can be added to the existing CAD systems in checking kidney functionality.