INNOVATION July-August 2018

One of the significant advantages of Dr. Sarunic's retinal scanner is its compact size. His scanner design uses adaptive optics but without a wavefront sensor, allowing for a final product that could fit into almost any clinical environment. P hoto : M ike C rane

the scanner to become a high-value product, like an x-ray, which wouldn’t be high-value if clinicians didn’t know what a hairline fracture looks like in an x-ray image.” Whether or not the scanner will make its way into the neighbourhood optometrist office is debatable, but it may well become a staple for vision specialists. “What Marinko

example, and then can tailor treatment to the severity of the disease. The third big step is that after a few weeks the ophthalmologist can do another scan and can find out if the treatment worked or not, did the patient get better or worse.” A few years ago, though, the retinal images the team was producing were still not as precise as clinicians would like or as the Sarunic believed they could be. So Jian travelled down to the University of California, Davis, for 10 months to learn about adaptive optics. By reducing the blurring and distortion that happens when light refracts inside the eye, high-resolution adaptive optics combined with OCT proved to be the next leap forward. “It’s advancing the state of the art,” says Beg. “For the first time in history, we are getting these exquisite images of the eye, down to individual photoreceptors and rods and cones and blood vessels and cells. It’s of fundamental importance to better diagnose eye diseases.” And that importance is being recognized. In March 2018, Sarunic and his team received a $300,000 Ignite Award from the BC Innovation Council, intended specifically to help them get the scanner to the clinical commercial market. “It’s already in pre-clinical use by vision scientists at McGill University working on developing medications to treat eye diseases,” says Jian. “Making it commercially available to eye clinics is our next step.” There are a few challenges, however, in addition to the usual regulatory hurdles, to cross first. “We are confident in our proof of concept,” says Sarunic, “so we are now at the stage where we’re concentrating on hardware refinements—getting it to run a little faster, a little smoother, etc. The second part of refinement is a validation study. This will look at detailed data sets to identify regions of interest in the retinal images, and confirm that they correlate with the diagnoses made by clinicians. This is required for

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