Olivia Ng LinkedIn
PhD Candidate, University of New South Wales, Australia.
PhD Topic:
"Clinical Predictive Tool for Arteriovenous Fistula (AVF) Failure"
Research interests: Computational Fluid Dynamics (CFD), Biomechanical Engineering, Blood Flow, Data Analysis
Email: olivia.ng@unsw.edu.au
Education/Employment
2018-present PhD Mechanical Engineering, UNSW, Sydney
2016-present Casual Academic, School of Mechanical Engineering, UNSW, Sydney
2014-2017 BEng Honours Class 1 (Mechanical Engineering), UNSW, Sydney
Publications
Journal Articles
S D. Gunasekera, O. Ng, S D. Thomas, R L. Varcoe, de Silva, Charitha and T J. Barber, “Tomographic PIV analysis of physiological flow conditions in a patient-specific arteriovenous fistula”, Experiments in Fluids 61 (12), 1-14
Conference Proceedings and Presentations
O. Ng, S. Gunasekera, S. Thomas, R. Varcoe, and T Barber, “CFD-derived resistance as a clinical indicator for problematic AVFs”, presented at 26th Congress of the European Society of Biomechanics, Milan, Italy, 2021
S D. Gunasekera, O. Ng, S D. Thomas, R L. Varcoe, de Silva, Charitha and T J. Barber, “Flow through a malapposed flexible stent within an arteriovenous fistula”, 26th Congress of the European Society of Biomechanics, Milan, Italy, 2021
O. Ng, S. Gunasekera, S. Thomas, R. Varcoe, and T Barber, “A clinical predictive tool for arteriovenous fistula (AVF) failure”, Proceedings of the 22nd Australasian Fluid Mechanics Conference AFMC2020, DOI: https://doi.org/10.14264/d3dc63e
S G. Mallinson, G D. McBain, O Ng, S D. Gunasekera and T J. Barber, “Hydraulic resistance and inertance of multi-port vessels”, Proceedings of the 22nd Australasian Fluid Mechanics Conference AFMC2020, DOI: https://doi.org/10.14264/e9afca2
S. Gunasekera, O Ng, S. Thomas, R. Varcoe, CM. De Silva, and T. Barber, “A numerical investigation of a stented arteriovenous fistula”, Proceedings of the 22nd Australasian Fluid Mechanics Conference AFMC2020, DOI: https://doi.org/10.14264/160df47
O Ng, S Gunasekera, S. Thomas, R. Varcoe, and T Barber, “Regular Non-Invasive Surveillance of Arteriovenous Fistula (AVF)”, presented at 5th Annual 3DMed Australia Conference, Melbourne, Australia, 2019
O Ng, S Gunasekera, S Thomas, R Varcoe, T Barber, “Arteriovenous Fistula (AVF) failure prediction through patient-specific (PS) modelling”, Australian Biomedical Engineering Conference 2019 (ABEC 2019): Technology & Research in Australian Medical Science. Melbourne: Engineers Australia, 2019: 3. ISBN: 9781925627435
S. Gunasekera, O Ng, S. Thomas, R. Varcoe, CM. De Silva, and T. Barber, “Flow analysis in a patient-specific arteriovenous fistula”, Australian Biomedical Engineering Conference 2019 (ABEC 2019): Technology & Research in Australian Medical Science. Melbourne: Engineers Australia, 2019: 86. ISBN: 9781925627435
Current project: AVF Failure Prediction Model
Arteriovenous fistula (AVF) is a surgically modified vascular structure, necessary for end-stage renal disease patients to undergo haemodialysis. Unfortunately, complications in these blood vessels often arise, causing inadequate blood flow in the AVF for blood filtration process to take place. Surgical intervention is needed, often urgently, to treat diseased AVF.
My research focuses on the development of a predictive tool for AVF failure, through computational and statistical modelling of real patients’ data. I work closely with vascular surgeons, clinicians and nurses to study the condition of an AVF through visualisation of 3D geometry from 2D ultrasound images, and identifying trends through available data. This work contributes to ongoing efforts in minimising emergency intervention, and improving quality of life for end-stage renal disease patients, by effectively aiding with surgical planning and outcomes.