Dr. David Huang: And I also have a presentation on video tracking and how that improves OCT image. Again, this one has been in the works for several years as well and now finally it’s available. And I think it--it’s a relatively simple change that brings a very high clinical impact, and I’m glad to be able to talk to you about it
So, frame averaging has been used to improve OCT images for many years on the RTVue machine and also on a number of other OCT systems. This create images that are virtually free of speckle noise and background noise, and it looks very sharp, but this image if you blow it up and look at some fine features, like the RPE boundary, you see that the expected double line has blurred into one, and that’s because this group of B-frames [sp] or cross-sectional images was obtained without tracking. So, when the algorithm tried to line them up there’s slight misalignment and probably some out-of-plane motion that could not really be corrected using post processing techniques alone
So, what we need to do is to take out this out of frame motion, and VTRAC does that by providing real-time video tracking at 30 frames per second. That’s the speed of the video. And this give you a much sharper image, because the mis-registration due to transverse eye motion has been largely removed. When you blow up the image now you can clearly see the RPE double line and you can also see a sharper choroid/sclera boundary if you’re interested in these deep structures
So, how does this work? Well, the infrared video image that you probably thought was a little bit blurry can actually be sharpened a lot with edge enhancement software. And this has been analyzed by the computer to detect motion between frames and used for active compensation. That active compensation is applied to the OCT steering mirror to compensate for motion in real-time
And here’s some examples of the result. In this geographic atrophy case in Dry AMD you can see very sharply defined groups membrane. In another Dry AMD case this time with Drusen you can see very good definition of the inner segment/outer segment line and the RPE. So, you can see the shortening of the photo receptor outer segments over Drusens where you might expect a loss of visual function and other places where you can see that they’re preserved, indicating better preservation
In VTRAC it’s very robust. It works even with cataract and poor fixation. This eye had [unintelligible] myopic degeneration, cataract, a very small pupil, 1.5 millimeter, 20/400 acuity, so not very good fixation, and yet you can get this very long scan, 12 millimeters, by taking 75 frames. The computer only found 24 that are useable, but with that you get a very sharp image with very high signal to noise ratio, no speckle, no motion or affect
So, this is a software upgrade. Most system probably do not require any hardware. An older system may require a new video card. It’s applied to a limited selection of scans now. A cross-sectional scan pattern such as lines, cross lines, raster and grid and other patterns may be able to use this in the future. The user is able to select the number of frames to be averaged, one to 120 B-scans. And this give you good flexibility in terms of how much time you want to spend taking the image depending on the patient tolerance. Scan length can also be adjusted up to 14 millimeter
So, the conclusion is that the VTRAC, video tracking, effectively improve the quality of frame average cross-sectional images, eliminates speckle and background noise, there’s no etch blurring due to mis-registration and this improves the visualization of fine retinal features, including RPE, Bruch’s membrane, external limiting membrane and photo receptor structures. It also help you see deep structures and it’s very robust and function in adverse conditions
Thank you