Project Lead(s): Stephen Pistorius
Breast cancer kills approximately 500,000 women every year, with almost 58% of these deaths in developing countries.
The current gold standard for breast cancer detection is based on fragile, x-ray-based imaging systems that require highly trained personnel to carry out the procedure and to interpret the results.
The main goal of this project was to use quantum physics and cell phone technology to develop a portable breast cancer detection system prototype that could be used in remote communities by people with minimal or no technical training.
The team designed and assembled the enclosure and mechanical components of the portable breast cancer detection system.
This system is designed to illuminate the breast using microwave signals, with a power of less than half of what a cellphone emits, and to collect the reflections from internal breast tissue.
Recorded data are then processed using novel algorithms to determine if there is a tumor present.
The system enclosure is designed to be able to fit in a large briefcase, in order to be easy to transport to remote communities.
A motion mechanism for a microwave antenna was integrated into the enclosure, to allow a microwave antenna and sensors to record the breast reflections from several angles.
System controls were integrated into a tablet computer and a set of instruction animations (which are also displayed on the tablet screen) guide the user through the scanning procedure.
The team successfully developed a prototype of a portable breast cancer detection system that could be used in remote communities by people with minimal or no technical training.
Usability tests on 135 women in Nigeria and South Africa were encouraging, as 91% of participants believed that they could operate the system by themselves, 90% found the instructions easy to follow and 90% said they would use the system if they had access to it.
Next steps for the project are to optimize and evaluate the algorithms that will be used to detect abnormalities in the breast, using datasets recorded by the system.
The team has received additional funding from CancerCare Manitoba to scale the project and the team plans to apply for Phase II Transition To Scale funding.