Biomechanics for Breast Health
New Zealand women have a 10% lifetime risk of developing breast cancer. Women self-identified as Māori have a twofold higher risk of developing breast cancer than non-Māori. Early detection by x-ray mammography of the compressed breast offers the best chance of survival. However, small tumours are often difficult to identify because of poor image contrast and lack of reliability in reproducing the large deformations of breast tissue during compression.
The Biomechanics for Breast Imaging Group’s goal is to develop a computational framework based upon a quantitative biomechanical model of the human breast, to assist radiologists with the interpretation of x-ray mammograms and other breast imaging modalities, such as MRI and ultrasound. Reliable software tools of this kind will improve breast cancer detection.
Learn more about our approach from our research flyer or watch the video "Computer modelling and cancer outcomes" (below) which was part of the University of Auckland's Research Works Wonders series on YouTube.
You can also watch an interview with Professor Nash in which he discusses mapping medical imaging.
Modelling breast shape under gravity
We have developed computational models to track breast tissue motion due to the effects of gravity. This can simulate, for example, a patient being re-oriented from the prone position in a magnetic resonance imaging scanner to the supine position, for a subsequent biopsy or ultrasound procedure.
Modelling breast compression
We have developed techniques to simulate breast compression during x-ray mammography. Using these results, we can track and collocate suspicious features between different x-ray mammographic image views and between different breast imaging modalities, such as x-ray mammography, magnetic resonance imaging and ultrasound.
Modelling breast cancer spread
We are developing statistical models to analyse the spread of breast cancer through the lymphatic system. These models will enable clinicians to predict where a patient's primary tumor may spread, and has the potential to improve disease management.
Clinical software applications
Software applications are being developed to use our techniques in an intuitive and clinically-friendly way, with an emphasis on ensuring the software can be easily incorporated into the radiologist’s workflow. These applications will provide a visual framework for efficient breast care treatment.