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Background: To evaluate the efficacy of corneal tattooing in a large case series. Methods: The medical charts of 62 eyes of 62 patients who underwent corneal tattooing between March 2016 and August 2017 were retrospectively reviewed. The causes of opacity and various methods of corneal tattooing applied were analyzed. Results: Among our 62 patients, 38 were male and 24 female. Average age was 48.47±15.30 (range, 12-74)years old. The mean follow-up period was 23.19 ±2.34 (range, 19-27) months. The most common causes of corneal opacity were ocular trauma (33 eyes, 53.2%), prior retinal surgery (9 eyes, 14.5%), congenital etiologies (8 eyes, 12.9%) and measles (5 eyes, 8.0%). The most common associated ocular findings were strabismus (23eyes, 37.0%), phthisis bulbi (17 eyes, 27.4%) and band keratopathy (13 eyes, 20.9%). Cosmetic outcomes improved without serious complications in all cases. Conclusions: Corneal tattooing is a viable option with an expanding set of indications, such as discolored corneal tattoos, white pupil due to inoperable cataract with clear cornea, and dense corneal opacities in blind eyes. Elective corneal tattooing seems to be a viable and convenient method to improve cosmesis with minimal complications and high patient satisfaction.

The aim of this study was to assess the feasibility of using a commercially available high-resolution adaptive optics (AO) camera to image the cone mosaic in Japanese macaques (Macaca fuscata) with dominantly inherited drusen. The macaques examined develop drusen closely resembling those seen in humans with age-related macular degeneration (AMD). For each animal, we acquired and processed images from the AO camera, montaged the results into a composite image, applied custom cone-counting software to detect individual cone photoreceptors, and created a cone density map of the macular region. We conclude that flood-illuminated AO provides a promising method of visualizing the cone mosaic in nonhuman primates. Future studies will quantify the longitudinal change in the cone mosaic and its relationship to the severity of drusen in these animals.

Adaptive optics (AO) has been increasingly used to study retinal disease.1–26 Until recently, the application of AO technology in ophthalmic imaging has been restricted to custom-built systems that require extensive technical infrastructure, which limits their use in a typical clinical setting. Now with commercially available AO imaging systems, such as the flood-illuminated rtx1 from Imagine Eyes (Orsay, France), the Compact AO retinal imager from Physical Sciences, Inc. (Andover, MA, USA), and an AO scanning laser ophthalmoscope from Canon, Inc. (Tokyo, Japan), AO-aided imaging is becoming a more clinically viable tool for assessing retinal disease.27–30 We used the rtx1 flood-illuminated AO camera from Imagine Eyes to develop a protocol for imaging and sampling cone density from a large macular area in healthy subjects. Previous studies have used the rtx1 to examine retinal diseases,12,21,22,31–36 study the healthy eye,37–40 and optimize AO imaging parameters.41,42 However, the practicality and limitations of using the rtx1 and other commercial systems have not been well established. Most studies have sampled density in small, manually selected areas of high image quality, even though a major advantage of flood-illuminated AO imaging is to allow for large areas of the retina to be imaged quickly. The density analysis methods typically used are also prohibitively labor intensive when analyzing large datasets with extensive retinal areas. Therefore, the clinical and research utility of adaptive optics remains limited by a lack of automated cone sampling and density representation methods. Additionally, although some studies have explored the effect of different-sized sampling windows on measurements of cone density,43 it is still unclear how to best represent or sample cone density most accurately and consistently. We describe our process for image acquisition, processing, and cone density analysis using the rtx1. We evaluated three methods of automatically sampling cone density, assessed the repeatability of our measurements, and compared our cone density values to histological studies,44,45 adding our data to previous studies that have used AO imaging systems to characterize the normal photoreceptor mosaic.37,38,46–52