No abstract

No abstract

No abstract

The estimation of glaucoma progression is a challenging task as the rate of disease progression varies among individuals in addition to other factors such as measurement variability and the lack of standardization in defining progression. Structural tests, such as thickness measurements of the retinal nerve fiber layer or the macula with optical coherence tomography (OCT), are able to detect anatomical changes in glaucomatous eyes. Such changes may be observed before any functional damage. In this work, we built a generativedeep learning model using the conditional GAN architecture to predict glaucoma progression over time. The patient's OCT scan is predicted from three or two prior measurements. The predicted images demonstrate high similarity with the ground truth images. In addition, our results suggest that OCT scans obtained from only two prior visits may actually be sufficient to predict the next OCT scan of the patient after six months.

We herein report 2 eyes with significant loss of vision after glaucoma filtering surgery that was accompanied by progressive macular thinning detected on macular optical coherence tomography imaging. The findings provide evidence that progressive retinal ganglion cell loss is one of the causes of visual loss after uncomplicated glaucoma surgery.