Optical Coherence Tomography Angiography

In a series of images taken at a sufficient interval, a moving object will appear at different positions on the successive images. When these images are compared pixel by pixel, nonmoving regions will show no change, while moving objects will produce areas that show high variance. If the color black is assigned to areas of low variance (ie, areas that do not move), and the color white is assigned to areas with high variance, then the resulting image will highlight movement; this is called motion contrast. The retina has no moving parts, except for the flow of blood. If the images are high resolution, successive retinal images can show the movement of blood through the retina. Images taken with OCT are not only high resolution but also depth-resolved. Therefore, data obtained from tissue can be compared with successive data. The result is a 3-dimensional visualization of movement within the retina, corresponding to blood flow in its various layers.

Unlike fluorescein angiography, which can only visualize the superficial capillary plexus, optical coherence tomography angiography (OCTA) can image all capillary layers, including the superficial plexus, the radial peripapillary capillary network, and the deep vascular plexus. This provides huge opportunities to advance our understanding of retinal diseases. En face OCT is another way to visualize flow information. En face imaging of flow in the retina is a useful technique because the resulting image of the retina is arranged in layers, as is its blood supply. In this method, a slab of the flow information corresponding to the expected position of a layer of vessels is selected. Next, the brightest pixel in each column of voxels is selected and displayed, which is called a maximal intensity projection. This projection creates a flat image from the data, which exists in 3 dimensions.

OCTA can visualize the retinal vasculature at a higher resolution than any other current imaging modality (Fig 2-4). However, OCTA is prone to artifacts; understanding how these artifacts are created is key to understanding and interpreting the images produced. Motion results in bright areas in the image, but this motion does not necessarily come from blood flow. For example, if the patient’s eye moves during the examination, portions of the resulting image will contain motion artifacts. Multiple automatic scans with eye tracking and software repair can suppress most motion artifacts. Another type of defect, called a projection artifact, is created when light passes through a blood vessel and strikes a deeper reflective structure; over time, the light that reflects from that structure will change, mimicking the overlying blood vessel. The image created will have what appears to be 2 levels of the same vessel: the first at its actual location and the second at the level of the reflecting structure. Several mathematical approaches can remove projection artifacts. A third potential issue in OCTA is the appearance of dark areas on the image. Dark areas visualized in the fundus can be the result of a lack of blood flow, or at least blood flow too slow to be detected in successive scans at the interval time used. However, frequently it is too difficult to ascertain whether there is a true lack of flow, so the dark areas on the images are called signal voids.

Finally, segmentation works well on normal retinas, but the more diseased a retina is, the less accurate the segmentation becomes. If the layer has not been segmented properly, it becomes much more difficult to visualize the flow in any given layer. This difficulty has led to the creation of alternate methods of showing flow data, such as volume rendering (Fig 2-5).

Excerpted from BCSC 2020-2021 series: Section 10 - Glaucoma. For more information and to purchase the entire series, please visit https://www.aao.org/bcsc.