A new imaging technique developed by a University of Pittsburgh researcher and colleagues could significantly advance how eye health and disease are assessed, according to the results of a study published this week in theProceedings of the National Academy of Sciences. The method is the first to be able to make out individual cells at the back of the eye that are implicated in vision loss in diseases like glaucoma. The research team hopes the new technique will prevent vision loss by enabling earlier diagnosis and treatment of these diseases.
Ethan A. Rossi, Ph.D., assistant professor of ophthalmology at the Pitt’s School of Medicine, developed the new method to non-invasively image the human retina, a layer of cells at the back of the eye that are essential for vision. The study was conducted by Rossi at the University of Rochester prior to his appointment at Pitt and led by David Williams, Ph.D., Dean for Research of Arts, Sciences, and Engineering and the William G. Allyn Chair for Medical Optics at the University of Rochester.
There has been a longstanding interest in imaging RGCs because their death causes vision loss in glaucoma, the second leading cause of acquired blindness worldwide. Despite great efforts, no one has successfully captured images of individual human RGCs, in part because they are nearly perfectly transparent.
“This technique offers the opportunity to evaluate many retinal features that have previously remained inaccessible to imaging in the living eye,” said Rossi. “Not only RGCs, but potentially other nearly transparent cell classes as well.”
Instead of imaging RGCs directly, glaucoma is currently diagnosed by assessing the thickness of the nerve fibers projecting from the RGCs to the brain. However, by the time a change is typically detected in the retinal nerve fiber thickness, a patient may have lost tens of thousands of RGCs or more.
“In principle, this new approach might eventually allow us to detect the loss of single ganglion cells,” said Williams. “The sooner we can catch the loss, the better our chances of halting disease and preventing vision loss.”
Rossi and his colleagues were able to see RGCs by modifying an existing technology – confocal adaptive optics scanning light ophthalmoscopy (AOSLO). They collected multiple images, varying the size and location of the detector they used to gather light scattered out of the retina for each image, and then combined those images. The technique, called multi-offset detection, was performed at the University of Rochester Medical Center in animals as well as volunteers with normal vision and patients with age-related macular degeneration.
Not only did this technique allow the group to visualize individual RGCs, but structures within the cells, like nuclei, could also be distinguished in animals. If Rossi can achieve that level of resolution in humans, he hopes to be able to assess glaucoma before the retinal nerve fiber thins – and even before any RGCs die – by detecting size and structure changes in RGC cell bodies.
While RGCs were the main focus of Rossi’s investigations, they are just one type of cell that can be imaged using this new technique. In age-related macular degeneration, cone photoreceptors that detect color and are important for central vision are the first to die. AOSLO has been used to image cones before, but these cells were difficult to see in areas near Drusen, fatty deposits that are the most common early sign of the disease. Using their multi-offset technique in age-related macular degeneration patients, Rossi was able to assess the health of cones near Drusen and in areas where the retina had been damaged.
Rossi and his colleagues warn that their study included a small number of volunteers and an even smaller number of age-related macular degeneration patients. More studies will be needed to improve the robustness of the technique before it can be widely used in the clinic. Rossi is now setting up his own laboratory at the University of Pittsburgh and plans to continue working with Williams’ group in studying this technique and its ability to detect changes in retinal cells over the course of retinal diseases.