The 3rd International Conference on Biomedical Engineering and Biotechnology (iCBEB2014)
The Exhibition on Biotechnology and Equipment
September 25-28, 2014, Beijing, China
Keynote Speaker--Ng Yin Kwee

Dr. Ng Yin Kwee

Division of Thermal and Fluids Engineering, School of Mechanical & Aerospace  Engineering, College of Engineering, Nanyang Technological University, SG.


Quantitative Means for Differentiating Kidney Obstruction by modelling Renography Data and derivation of Novel Renal Index of Urine Flow rate

The kidney has a main role in the blood filtration process to get rid of waste materials and maintain homeostatic functions, such as regulation of electrolytes, maintenance of acid-base balance and regulation of blood pressure. Renography is a kidney imaging technique used to detect renal health status. However for the purpose of diagnosis renal obstruction, there is still no precise technique and standard protocol accepted and applied in the clinical setting. This research example was carried out to search for a non-invasive method in the assessment of renal obstruction and to come out with a benchmark for clinical evaluation of the severity of obstructed kidney. In order to achieve this objective, the model that represented the behaviour of tracer from the input into kidney through filtration process to the flow out from the renal pelvis was developed using two compartmental modelling. Then, the model was compared to clinical data from renography and it had been verified in this work that the mathematical model was accurate in predicting the relative severity of obstructed kidney. Lastly, using Support Vector Machine (SVM) classifier as a quantitative means for differentiating kidney obstructions was proposed based on the simulation results of the samples that had been compared with clinical interpretation of renograms by a certified nuclear medicine doctor. The SVM predictions had been shown accurate in diagnostic of the functionality of kidney. The SVM classifier gave precise identification whether the kidney is normal, slightly obstructed or heavily obstructed. This new method could be used to determine the condition of patient’s kidneys analytically through non-invasive technique as compared to the usual invasive technique and current inaccurate subjective practice in visual interpretation of renography. The categorization for the severity level of kidney with larger number of patients will be useful for further treatment planning to determine the best solution for each clinical condition. In order to make this technique to be more convenient to be used by doctors, in-house developed specified software (instead of MATLAB) that can run the whole analysis and calculation can also be developed.

Contact Person: Ms. Li Ling
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