We are delighted to announce that Professor Merryn Tawhai from the Auckland Bioengineering Institute is visiting the Insigneo Institute and will give a seminar on development of a personal digital lung to model lung structure-function over the adult lifespan on Friday 6 July 2018 at 2pm in Lecture Theatre 3, F Floor Medical School.
Professor Tawhai – Director of The Medical Technologies CoRE, Deputy Director of Auckland Bioengineering Institute and Associate Deputy Vice-Chancellor (Research) PBRE University of Auckland
Professor Merryn Tawhai graduated from the University of Auckland with a PhD in Engineering Science in 2001. At the Auckland Bioengineering Institute Merryn has established a research programme in applied computational physiology of the lung. She was the inaugural Maurice Paykel Postdoctoral Fellow and has been a recipient of RSNZ Marsden, National Institutes of Health, Health Research Council of New Zealand, and MBIE grants.
There are currently very few tools for quantitative assessment of the lung prior to surgery, radiation treatment, or other interventions. Current tools focus on image analysis, usually based on densitometry or texture analysis. No tools are currently available for patient-specific prediction of respiratory system function post-treatment. We are developing a statistical- and biophysically-based lung model to predict redistribution of air and blood flows and their impact on gas exchange and other physiological functions in response to various interventions or treatments. The digital lung spans from the nasal and oral airways to the deepest smallest parts of the lung, connects to sophisticated models of the pulmonary circulation, exchanges respiratory and other gases, and interacts with models for respiratory control. To extend this model to the adult lifespan we have incorporated data from healthy subjects aged 20-90 years to predict age-dependent lung shape and novel correlations with lung function, multi-scale imaging and model analysis of alveolar tissue mechanics, and quantitative analysis of age-related disease. Inclusion of imaging and pulmonary function data from hundreds of never-smoking healthy subjects means that the model appropriately represents structure-function relationships over the full adult lifespan. This personalisable model has the capability to link 3D imaging (MRI or PET of ventilation defects) to forced expiration (the mainstay of pulmonary function testing) as well as other laboratory tests that are more sensitive to ventilation heterogeneity. The ultimate goal is to provide a comprehensive tool that can be used to predictively test interventional approaches and therapies, both well in advance and at the bedside, to develop and optimise new and current treatments for the individual, as well as to identify and stratify patients into risk groups and groups in need of more targeted, personalised therapies.