Review of corneal endothelial specular microscopy for FDA clinical trials of refractive procedures, surgical devices, and new intraocular drugs and solutions

Abstract

Specular microscopy can provide a noninvasive morphologic analysis of the corneal endothelial cell layer from subjects enrolled in clinical trials. The analysis provides a measure of the endothelial cell physiologic reserve from aging, ocular surgical procedures, pharmaceutical exposure, and general health of the corneal endothelium. The purpose of this review is to discuss normal and stressed endothelial cell morphology, the techniques for determining the morphology parameters, and clinical trial applications.

Figure 1

The size and shape of the reflected image of the light source is modified by the reflecting surface. A flat surface reflects the image undistorted. The curved surface will bend the image into a minimized image.

Figure 2

The endothelial cell area is a compromise between the width of the light beam and the thickness of the cornea . As the narrow slit light beam show in Figure A is broadened the light reflex can be seen from the rectangular epithelial and endothelial surfaces. As the slit width is increased further the epithelial surface reflex will encroach upon the endothelial reflex as shown in Figure B.

Figure 3

The endothelial cell layer image is increasingly degraded by light being scattered in the stroma. The endothelial cell micrograph insert demonstrated the contrast and light intensity gradient across the cell pattern.

Figure 4

The progressive development of corneal endothelial polymegethism has been hypothesized by Bergmanson

Figure 5

A non-contact photographic macro-camera was used to document age verses endothelial cell density in the Caucasian race. A linear regression line through 17 to 83 years of age resulted in a 0.22% cell loss per year.

Figure 6

The cell density for Asian subject is greater at all age ranges than the Caucasion race. The data points (diamonds) are from a Japanese patient group (linear line, Y=4109-124X) and the data (triangles) are from an Caucasian American patient group (linear line, Y=3254-121X).

Figure 7

Mean endothelial cell density values for ICCE patients (Inable eta 1985 32) are plotted in Graph A to demonstrate regional endothelial cell changes after superior incision ICCE. In Graph B, ECCE patient data from Schultz et al shows regional endothelial cell changes after ECCE with IOL implantation with 1% sodium hyaluronate (Healon). Regrouped data from Hoffer on regional endothelial cell changes after ECCE and phacoemulsification cataract extraction is plotted in Graph C.

Figure 8

There are four techniques to analyze the endothelial cell images; (A) compare relative cell size to standards, (B) count cells within a predetermined fixed frame with the frame size significantly affecting accuracy, (C) an algorithm using inputted cell corners, and (D) an algorithm using inputted cell centers.

Figure 9

A perfect hexagon pattern can be imported into the Konan KSS300 software for analysis. Figure A is a 1600 density (hexagon per mm²). Figure B is a 2500 density (hexagon per mm²).

Figure 10

A perfect drawing of a patient's endothelial cell pattern can be imported into the Konan KSS300 software for analysis. Figure A is a pattern of 1470 cells per mm². Figure B is a pattern of 2625 cells per mm².

Figure 11

The center to center analysis method requires more cells identified and dotted than in the final cell area analysis. In order to define the area of a 6-sided cell, the six adjacent cells must also be located. Thus, to define the area of the 6-sided cell requires placing dots in 7 cells. To define the area of 100 cells, dots must be placed in the center of 150 cells. The relationship is linear (Y=0.808X-17) and can not exceed 200 cells dotted because of a maximum data entry in the analysis software.

Figure 12

The same center to center data set presented in Figure 11 is re-plotted as the per cent of cells doted relative to the number of cell areas defined. If 50 cells are dotted then cell area will be defined for 45% of the dotted cells. This relationship plateaus at approximately 70%.

Figure 13

The effect of endothelial cell coefficient of variation relative to the number of cells counted per field is demonstrated in Figures A to D. Figures A and B are from a corneal with CV=25. Based on Graph A, a minimum of 75 cells per field should be counted to best represent cell density. In Figure B illustrates the large variation in estimating the coefficient of variation when counting <25 cells per field. Figures C and D were generated from a corneal with a coefficient of variation of 45. As the coefficient of variation increases the estimate for the endothelial cell density has a large increase in variation.

Figure 14

Non-contact specular micrographs of patient eyes (n=197) with various endothelial cell image qualities. The linear regression line fit to the good quality images (n=122) is Y=0.468X-4.2. The two endothelial cell images demonstrate good and poor image quality.

Figure 15

The endothelial cell image is from a Fucks dystrophy cornea. Even though the endothelial cell image is of excellent quality, cell density can only be determined from a few contiguous cells.

Figure 16

The specular micrographs illustrate corneal endothelial cell clustering.

Figure 17

Practice images for the Konan KSS-300 software.

Figure 18

A selection of endothelial micrograph illustrates different qualities of cell imaging; good, fair, poor, and impossible to analyze.