Quantifying 3D breast shape and stiffness using surface imaging

Breast cancer affects 1 in 9 NZ women. Early detection is key to improving the likelihood of survival. The ABI’s Biomechanics for Breast Imaging group is developing biomechanical models of the breast to assist clinicians with addressing challenges in detecting and treating breast cancer. This novel workflow automatically builds computational models of the breast from clinical magnetic resonance images (MRI) acquired in the prone position, and uses these models to predict where tumours would move to in the supine position, in which treatment procedures are performed.


The existing workflow requires diagnostic prone MRI images to be acquired for building the biomechanical models. However, these images are only acquired in 10 % of women undergoing breast cancer screening due to the low specificity of this imaging modality. MR imaging is very expensive and time consuming to acquire making their acquisition for generating computational models of the breast, infeasible. This prevents the application of our workflow for the majority of women with breast cancer. The existing workflow also does not include subject specific estimates of breast tissues stiffness that are required for obtaining accurate predictions of breast tissue motion.


This project will focus on developing a framework that uses only measurements from the surface of the breast for: 1) automatically constructing 3D breast biomechanical models; and 2) identifying personalised estimates of breast tissue stiffness. Multiple gravity loaded positions will be investigated for improving reconstruction of subsurface tissues and their stiffnesses using world leading stereo imaging algorithms developed at ABI. Computational model-based design of experiments approaches developed at ABI will be used to determine the optimal orientation(s) to measure the surface of the breast to maximise the accuracy to which the breast shape and stiffness can be reconstructed. The framework will be validated by performing MR and surface imaging on a cohort of volunteers with the help of our clinical collaborators at Auckland City Hospital and our research collaborators at Breast Research Australia,


The development and implementation of this framework will not only make our computational modelling workflow applicable to all women with breast cancer, but also enable the models to be applied in a number of additional applications from helping co-localise breast tumors in x-ray mammograms (the primary imaging modality for breast cancer screening) to improving bra designs.


Candidates must hold a BE in Biomedical Engineering, Bioengineering, Computer Science, or a related field involving computational mechanics. Prior experience in computational modelling, solid mechanics, and code development is preferred.