Scientists Develop MRI Tool That Makes Cancer Cell Detection A Lot Easier

A team of researchers at the University of Waterloo has developed a new magnetic resonance imaging (MRI) tool. What makes it stand out is that under its sensors the cancerous tissue glows in medical images. This tool could help doctors detect and track the progression of cancer more accurately over time.

The innovation will create images in which cancerous tissue appears to light up as compared to healthy tissue, making it easier for doctors to notice them. Notably, this MRI tool was developed as a part of a study, which was published in the journal ‘Scientific Reports’, reported Science Daily.

Compared to standard MRI techniques, synthetic correlated diffusion imaging is better at delineating significant cancerous tissue, making it a potentially powerful tool for doctors and radiologists.

Canada Research Chair in Artificial Intelligence and Medical Imaging and a professor of systems design engineering at Waterloo, Alexander Wong stated that their studies show this new technology has promising potential to improve cancer screening, prognosis, and treatment planning.

The new technology, which is called synthetic correlated diffusion imaging, highlights the differences by capturing, synthesizing and mixing MRI signals at different gradient pulse strengths and timings. It is the largest study of its kind in which the researchers collaborated with medical experts at the Lunenfeld-Tanenbaum Research Institute, along with several Toronto hospitals and the Ontario Institute for Cancer Research to apply the technology to a cohort of around 200 patients with prostate cancer.

Wong said that prostate cancer is the second most common cancer in men worldwide and also the most frequently diagnosed cancer among men in more developed countries. Hence, they targeted it first in their research. The scientist added that the team also received very promising results for breast cancer screening, detection, and treatment planning. “This could be a game-changer for many kinds of cancer imaging and clinical decision support,” he said.

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