All About Eyes: Detecting Eye Disease

All About Eyes: Detecting Eye Disease

All About Eyes: Detecting Eye Disease

 Eye Disease
Eye Disease
  Some other research that we’re doing now at the Beetham Eye Institute involves really exciting and cutting-edge imaging technology to look at the retina in ways that we never could before and there are a few different ways in which we’re doing this. we’re looking at ultra wide-field images. Photographs of the retina that take a much broader area of the retina than we’ve ever done before. to give you some sense a perspective think back in the late 1960s when people were for starting to talk about how to classify diabetic retinopathy the ability to take retinal photographs out to the periphery of the retina and to then montage to put together those photographs took about twelve hours and now with a single image we can get about 82 percent of the retina in an image that takes less than a quarter of a second toacquire. So it’s a huge advance and doctor PauloSilva and doctor Lloyd Aiello and myself and others from our group have started to look at changes on UltraWide Field images to see . now that we can look further out to the edge of the retina than we’ve done before does this change the ways in which we can predict the progression of diabetic eye complications does it help us understand better who might worsen in their eye disease then we could before and there some very interesting data in the studies that Dr. Silva has spearheaded suggesting that perhaps we can actually use the presence of diabetic lesions or diabetic changes in the retinal periphery to help us better predict who’s going to have worsening eye disease over time? In addition to that my particular group has looked at studies using cross-sectional imaging of the retina to look at the neural retina to see if we can better predict not just to worsen diabetic retinopathy but particularly who’s going to have better or worse vision over time and this is crucially important because right now we don’t have good ways of predicting which patients with diabetes which eyes patiently with diabetes will gain vision over time or lose vision over time. As we give them the current treatment we have available and as we evaluate new treatments and our group at the Joslin has actually recently just published a paper suggesting that perhaps a specific feature of the retina that we can now evaluate on a technology called optical coherence tomography imaging this is a technique that uses the reflection of the light from the retina to look at individual retinal layers and we’ve shown that the disorganization of the inner layers of the retina actually is very closely associated with rates vision loss and gain over time. And this is a new biomarker that we’ll be evaluated in further studies I think last imaging technology that we’ve been evaluating and using to evaluate the eyes of patients with diabetes is a technology called adaptive optics scanning laser ophthalmoscopy and this is a technique that was proposed in astronomy actually first to correct for wavefront aberrations of light coming through to get sharper and better images and using the AOSLO technology we can image a section retina and get the resolution down to about the two-micron level just to give you some perspective on that the size love the retinal blood vessels the largest rental blood vessels in the eye is about 125 microns in diameter and the diameter of the red blood cells that travel through those blood vessels is about 6 to 8 microns in diameter Soto get the resolution down to 2 microns means that we can see the individual red blood cells that flow through the retinal vessels and capillaries and we can even image structures that are smaller than that diameter including the central photoreceptors or light-sensing cells in the eye so this gives us the ability to look for the first time in human eyes in a dynamic fashion at blood flow through the retinal vessels and through changes in those vessels as they occur because of diabetes and so we’re very interested again in using this technology to see if we explore new and predictive markers outcomes in patients with diabetes