Quantitative means for differentiating renal obstruction by analysing renography by compartmental modelling of renal fluid flow rate.
OBJECTIVE
The aim of this study was to investigate the accuracy of using a newly developed index, the ratio of urine outflow to renal pelvis volume U/V2 (1/s), in evaluating renal obstruction and determining the severity of obstruction.


METHODS
A total of 42 patients' renograms (80 kidneys) were studied. Compartmental modelling was used to model the behaviour of tracers flowing through the kidney. The derived model led to the formation of the normalized urine flow rate U/V2. An analysis was carried to test the accuracy of the developed index by comparing the developed model and the clinical evaluation of renograms. The Support Vector Machine algorithm was implemented to predict the renal obstruction status.


RESULTS
From the comparison performed between the index and the clinical evaluation from certified experts, it was shown that a higher value of index U/V2 indicated a normal kidney, whereas a lower value indicated an obstructed kidney. The classifier developed could provide a 100% accurate diagnosis of differentiated unobstructed kidneys (42/42) and obstructed kidney (18/18). For further classification of obstructed kidneys, the system grouped the samples into slightly obstructed cases with an accuracy of 100% (9/9) and heavily obstructed cases with an accuracy of 89% (8/9).


CONCLUSIONS
The use of the single parameter U/V2 could produce the diagnosis of renal obstruction with a high level of accuracy. This method has the potential to be used as a benchmark to distinguish the severity level of the renal obstruction.
aNanyang Institute of Technology in Health and Medicine, Interdisciplinary Graduate School bLee Kong Chian School of Medicine cSchool of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University dDepartment of Nuclear Medicine and PET, Singapore General Hospital eDuke-NUS Medical School, Singapore, Singapore.
Suriyanto
Eddie Y K
EY
Ng
Xian Jue
XJ
Say
C E David
CE
Ng
Xuexian Sean
XS
Yan
S Dinesh
SD
Kumar
D000465:Algorithms; D006801:Humans; D057446:Hydrodynamics; D007674:Kidney Diseases / Q000000981:diagnostic imaging* / Q000503:physiopathology; D008954:Models, Biological; D011866:Radioisotope Renography / Q000379:methods*; D060388:Support Vector Machine; D014517:Ureteral Obstruction / Q000000981:diagnostic imaging / Q000503:physiopathology