Multiscale three-dimensional modeling of ultrasound cancer imaging

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The continuing improvement of ultrasound imaging technology creates opportunities for ultrasound to fill new roles in medical imaging.  Substantial health care benefits can result from new uses of ultrasound, because ultrasound provides advantages in cost, accessibility, and patient safety and comfort compared to other imaging technologies.  Our research team is creating a comprehensive computer simulation resource for use in developing methods to improve the cancer imaging capabilities of ultrasound.  The simulations will use a Southwestern Ontario high-performance computing facility, SHARCNET.  Software will be designed and tested for three-dimensional modeling of the gross and microscopic anatomy of tumours and surrounding tissues and accurate, efficient simulation of the physics of ultrasound image formation.  The tissue and tumour models will be designed for research on two topics where ultrasound technology is rapidly advancing: breast cancer detection and high-resolution imaging of small animals used in cancer research.  The breast cancer simulations will investigate methods to improve the ability of ultrasound to screen for small tumours.  This capability would be especially valuable for patients younger than 40 years, because young women who develop breast cancer generally have the most aggressive tumours and mammography often produces unsatisfactory images of young patients.  The small animal imaging simulations will be used to define more reliable methods to evaluate new cancer therapies in the laboratory.  Small animal imaging has the potential to accelerate and reduce the costs of cancer drug development by ensuring that only the most promising drugs are selected for clinical trials in human patients.  In both of these areas, existing computer and experimental models for ultrasound imaging rely on idealizations of the physical properties of tissue that are avoided in the computational methods established by our research team.  We expect that the proposed simulation platform will provide a valuable tool for addressing these and other challenging issues in cancer imaging.