Objective Analyses of Tessellated Fundi and Significant Correlation between Degree of Tessellation and Choroidal Thickness in Healthy Eyes

Abstract

A tessellated fundus is a common characteristic of myopic eyes and is an important clinical marker for the development of retinochoroidal changes. However, the exact cause and significance of tessellated fundi have not been definitively determined. We determined the degree of tessellation in fundi objectively in normal, non-pathological myopic eyes, and correlated the degree of tessellation and the choroidal thickness (CT) and axial length (AL). This was a prospective observational cross sectional study. The eyes were classified subjectively into three groups based on the degree of tessellation observed ophthalmoscopically. Digital color fundus photographs were assessed for the degree of tessellation by ImageJ, an image processing program. Three tessellated fundus indices (TFIs) were calculated and were compared to the three subjectively-determined groups. The subfoveal and nasal CTs were measured in the optical coherence tomographic images. The correlations between the TFIs and the CT were calculated. Additionally, the correlation between the TFIs and the AL was calculated. One hundred right eyes of 100 healthy volunteers (mean age 25.8±3.9 years) were studied. Ophthalmoscopically, 57 eyes were placed in the non-tessellated group, 27 eyes into the weakly tessellated group, and 16 eyes into the strongly tessellated group. There was a significant correlation between the subjective classifications and the TFI values (P<0.05, Kruskal-Wallis test). All of the TFIs were significantly associated with the subfoveal and nasal CT (R = −0.20 to −0.24, P<0.05). The TFIs were not significantly correlated with the ALs. In conclusion, the significant correlation between the subjective and objective classifications of the degree of tessellation indicates that TFIs can be used to classify the degree of tessellation. The results indicate that the differences in the CT account for the degree of tessellation.

Peripapillary Nerve Fiber Elevation in Young Healthy Eyes

“…Indeed, the nonfoveal retina and choroid are both thinner, and the degree of thinning is proportional to the elongation of the axial length. 28,29 This would indicate that the retina and choroid are unusually stretched in these eyes. However, there must be some variations in this structure and forming process.…”

Quantitative comparison of disc rim color in optic nerve atrophy of compressive optic neuropathy and glaucomatous optic neuropathy

“…Fundus color can be calculated from a digital image using indices based on relative RGB pixel numbers because the number of RGB pixels in an image determines coloration [21]. For example, R/(R + G + B) has been used to quantify the degree of sunset glow fundus, the color of a myopic fundus, and the degree of tessellation in a myopic fundus [15,16,18]. R-G has been used to semi-quantify hemoglobin levels in the vessels of the optic nerve head [17].…”

“…To quantify the color of the ONH, we used calculation algorithms described in detail in previous reports [15][16][17][18]. Three disc color indices for quantifying ONH redness, DCI1, DCI2, and DCI3, were calculated using mean red intensity (R), mean green intensity (G), and mean blue intensity (B) as follows:…”

“…This technique was successfully used to assess the sunset glow fundus of Vogt-Koyanagi-Harada disease, characteristic changes in myopic fundi, and hemoglobin levels in the optic nerve head [15][16][17][18]. In the current study, we employed an objective and quantitative method to estimate optic disc pallor and evaluate optic disc color tone in eyes with CON and GON exhibiting varying extents of optic nerve damage.…”

A Comparative Study of Severity and Duration of Diabetic Retinopathy in Type 2 Diabetes in Tessellated and Non-Tessellated Fundus

“…Special features of tessellated fundus include RPE atrophy, choroidal segmentation and large surface area of retinal thinning. 3 Risk factors for type 2 diabetes include ethnicity, age, lack of physical activity, increased dietary cholesterol intake, obesity with Body Mass Index more than 30 kg/sq. m, family history, drugs causing diabetes, insulin resistance and smoking.…”