Detecting breast cancer early is a matter of life or death. Making detection easier and more accessible is the mission of University of Manitoba student Gabrielle Fontaine.
The 24-year-old graduate student in physics is building a portable breast cancer-detection device that could be used in places where current technology isn’t available.
"There are a few things that I'm taking into consideration when I'm trying to make this device portable. The first is to minimize the size, the cost and the complexity, that way it can easily be transported to remote or low-income areas," she said.
"The second is to use artificial intelligence to enable the response to the presence or absence of a tumour in real time. Essentially, if the device does tell the patient there is a breast abnormality, then the patient can go to a hospital to take further scans, or further tests to see exactly what is wrong."
Fontaine is Anishinaabe and her family is from Sagkeeng First Nation. She’s always loved science and originally wanted to go into medicine. As she studied, she fell in love with physics, and naturally fell into the medical physics field. Her early research focused on radiation therapy for lung cancer patients, and more recently, her work has been in the field of medical imaging and particularly microwave sensing.
Fontaine said she is excited about the use of microwave sensors to detect breast cancer.
Current methods, including X-ray mammography and MRIs, can be unsafe in large doses, uncomfortable, and they use large expensive equipment. A smaller, safer breast cancer device that uses microwave sensing would allow people to test themselves. Greater accessibility could reduce mortality rates.
"If you look at the incidence and the mortality rates around the globe, you can see that a lot of low- and middle-income countries have lower incident rates, but their mortality rates are disproportionately higher," she said. "Lack of early detection contributes to these disproportionately high mortality rates."
Fontaine is part of the physics department’s equity, diversity and inclusion alliance committee, which hopes to entice more Indigenous students into the field. She said she hasn’t seen much Indigenous student representation in physics but the reasons for that are nuanced. Part of the work the committee does is support projects that encourage students and educators to incorporate traditional knowledge into their work.
"I think that's very important for a lot of Indigenous peoples, is to be able to still hold and keep your own traditional knowledge, while incorporating that into the type of technology and in science that we're learning nowadays in the university," she said.
Part of that support comes from the U of M’s upcoming Wawatay project, which the committee helped develop. The project seeks to mentor Indigenous students who have an "emerging" interest in science, program lead Dennis Ballard said.
"The concept is that we’ll work with Indigenous people to identify projects or research topics that they wish to have that'll benefit the Indigenous community. Hopefully, in the near future, they’ll identify students in their communities with an interest in science and we’ll take them on as a Wawatay student," he said.
At the U of M, five per cent of faculty of science students identified as Indigenous in 2019.
The project, which will start taking on students in 2022, will connect Indigenous communities with U of M researchers, and a mutual sharing of ideas of both mainstream scientific methods and Indigenous methods will take place, Ballard said.
"It'll be their community, so they'll maintain their cultural ties and connections," he said. "They'll learn more about themselves as a people through learning about the Indigenous science available to them in their own communities, or through other Indigenous communities."
Applications for the program are set to open in late fall. The project is accepting donations on the U of M website.
In the meantime, Fontaine plans to start her PhD next year. Her timeline to complete the device is limited by the number of students working on it, which is based on funding. She hopes for "reliable results" from the artificial intelligence and machine learning needed to detect tumours by the end of her PhD thesis. From there, she hopes to optimize the process and then look at clinical trials, which would test the machine using human breast tissue.
"It depends on what else is going on with research around the world, because if another group already comes up with some sort of prototype, then the steps for mine would just be to improve theirs and help along with theirs," she said.
Malak Abas is a reporter for the Winnipeg Free Press.