99m Tc-MAG 3 diuresis renography in differentiating renal obstruction: Using statistical parameters as new quantifiable indices

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. 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. 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 MeanCV and the MedianCV . The cutoff points of MeanCV 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 MedianCV in separating unobstructed and obstructed classes as well as slightly and heavily obstructed classes were 0.35 and 0.69, respectively. Notably, MeanCV and MedianCV were not significantly influenced by either age or gender. The MeanCV and the MedianCV 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.