Assoc. Professor in MAE; Snr. Hall Fellow. Ng obtained a B.Eng (CL I) from Uni. of Newcastle upon Tyne; Ph.D at Cambridge Univ. with a Cambridge Commonwealth Scholarship; PG Diploma in Teaching Higher Edu., NIE-NTU. He is an invited keynotes speaker for more than 15 international scientific confs./workshops. He is active in offering consulting services & a fellow of SAF-NTU Academy. 15 of his thermal imaging papers have been adopted as references in Singapore Standard (SS 582: 2013) and ISO/IEC 80601-2-59: 2008. He is also presently serving as panel member for the Biomedical Standards Committee, Singapore.

Speech Title: Enhanced Statistical Parameters for Renograms as New Quantitative Indices in Differentiating Renal Obstruction

Abstract: Renography is a renal imaging technique that utilizes radioisotopes and is commonly used for evaluating renal functions. Here, we studied 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. Both MeanCV and MedianCV data derived from renograms with duration of 25 min could successfully separate the diagnosis into unobstructed and obstructed classes. Using compartmental modeling based on the derivation of fluid flow rate equation of kidney [1], we enhanced both the parameters by extending the duration of renograms. As a result, the extended MeanCV and MedianCV were better separated into 3 distinct classes – i) unobstructed, ii) slightly obstructed and iii) heavily obstructed. Based on machine learning classifier results, the enhanced MeanCV derived from renogram with duration of 50 min had an overall accuracy of 92.42% and the enhanced MedianCV derived from renogram with duration of 60 min had an overall accuracy of 93.18%.

In brief, this talk demonstrates more objective methods in the assessment of renal obstruction through quantification of renogram (via bio-fluids & bio-statistical analysis) and to develop robust systematic methods for clinical evaluation of renogram. Both the new parameters could be derived easily and applied to diagnose renal obstruction with a high level of accuracy. They can potentially be added to existing computer-aided diagnosis system of renography as parameters in evaluating the functionality of kidney. We therefore propose the extended MeanCV and MedianCV generated from renograms as new quantitative indices in differentiating renal obstruction.

Ref: [1] Suriyanto, Ng, E.Y.K., Say, X J., Ng, C.E.D., Yan, X.S. & Kumar, S.D. Quantitative means for differentiating renal obstruction by analysing renography by compartmental modelling of renal fluid flow rate. Nucl. Med. Commun. 37, 904-910 (2016).
[2] Suriyanto; Ng, E. Y-K; C.E.D Ng; S.X. Yan; N.K. Verma, "Using statistical parameters derived from renograms as new quantitative indices in differentiating renal obstruction", Nucl. Med. Commun., 2018