Quantitative assessment of human donor corneal endothelium with Gabor domain optical coherence microscopy

Abstract. We report on a pathway for Gabor domain optical coherence microscopy (GD-OCM)-based metrology to assess the donor’s corneal endothelial layers ex vivo. Six corneas from the Lions Eye Bank at Albany and Rochester were imaged with GD-OCM. The raw 3-D images of the curved corneas were flattened using custom software to enhance the 2-D visualization of endothelial cells (ECs); then the ECs within a circle of 500-μm-diameter were analyzed using a custom corner method and a cell counting plugin in ImageJ. The EC number, EC area, endothelial cell density (ECD), and polymegethism (CV) were quantified in five different locations for each cornea. The robustness of the method (defined as the repeatability of measurement together with interoperator variability) was evaluated by independently repeating the entire ECD measurement procedure six times by three different examiners. The results from the six corneas show that the current modality reproduces the ECDs with a standard deviation of 2.3% of the mean ECD in every location, whereas the mean ECD across five locations varies by 5.1%. The resolution and imaging area provided through the use of GD-OCM may help to ultimately better assess the quality of donor corneas in transplantation.


Introduction
The corneal endothelium is the innermost layer of the cornea, which serves as a leaky barrier to aqueous humor flow that supplies the stroma with necessary nutrients. Corneal transparency is maintained by healthy endothelial cells (ECs) that contain fluid pumps that control the level of stromal hydration. 1 A malfunction in the deturgescence state of the cornea can lead to corneal edema and eventually to blindness. From penetrating keratoplasty, first developed in 1905, to endothelial keratoplasty, 2,3 corneal transplantation remains the main method of treatment for endothelial dysfunction and failure. 4 Endothelial cell density (ECD) is a key determinant in tissue selection/placement and graft survival.
Noncontact specular microscopy (SM) is a standard imaging apparatus used in eye banks to assess the donor corneal endothelium. Although the imaging modality is user-friendly, costeffective, and fast, most SMs have a small field of view 5 (e.g., Konan EB-10 of 200 μm × 280 μm), 6 which introduces sampling error in ECD evaluation. 7 Furthermore, given the curvature of the cornea, SM images often provide a partial view of ECs, which further limits the area of interest for EC analysis 5 and a mixture of proximate layers near the endothelium. The latter issue has been mitigated using the confocal principle, found in various in vivo confocal microscopy (IVCM) such as tandem scanning confocal microscopy, 8,9 slit scanning confocal microscopy, 10,11 and laser scanning confocal microscopy. 12 More thorough explanations of the utilized techniques and the limitations of various IVCMs for imaging the cornea were reviewed in previous articles, 13,14 and IVCMs showed an ECD analysis comparable to SM. 15,16 Optical coherence tomography (OCT) has been actively adopted in various ophthalmic applications 17 to visualize cross-sectional views of the sample and is used at eye banks for corneal pachymetry. 18 For the histological study of a cornea (e.g., endothelial cells), an embodiment of OCT with a high numerical aperture (NA) microscope objective called optical coherence microscopy (OCM) 19 is gaining attention from researchers for its improved spatial resolution relative to that of IVCM. OCM has steadily evolved into two platforms, depending on the type of illumination and operating principles: full-field OCM (FF-OCM) [20][21][22] and Fourier-domain OCM (FD-OCM). 23-28 FF-OCM is a time-domain OCT, which provides direct access to en face images of the tissue. The volumetric image is obtained by scanning in depth and stacking all en face images from different depths. Cross-sectional images can be extracted from the volumetric image. On the other hand, FD-OCM is a spectral-domain OCT with high-spatial resolution comparable to that of confocal microscopy, which gives direct access to cross-sectional images. En face images can be extracted by restacking the volumetric image. Because of their high-spatial resolution typically obtained with an increase in NA, OCM methods have limited imaging depth that is set by the depth of focus (DOF) of the microscope objective. The DOF is estimated at tens of micrometers (i.e., 40 to 80 μm depending on the criterion for contrast considered); the curvature of the cornea creates a depth which the ECs lie within 30 μm. So, in principle, if focused carefully, one could image all ECs across the curved cornea within two zones of the Gabor domain optical coherence microscopy (GD-OCM) using the strictest criterion for DOF. Two or three zones allow the zones to be separated by less than ∼1∕2 of the DOF of GD-OCM for achieving the highest quality in-focus imaging throughout the endothelium. All imaging was conducted with at least two and up to three zones around the ECs locations for the full 1 × 1 mm 2 field of view of the GD-OCM.
GD-OCM, 29 which is a variation of FD-OCM, was introduced to overcome the DOF limitation. The microscope objective in GD-OCM is custom designed and integrates a liquid lens to effectively extend the depth of imaging beyond the instantaneous DOF of the microscope by scanning the focus of light through depth with an invariant lateral resolution 30,31 and acquiring and fusing multiple DOF-limited volumes at different depths for creating an image with high contrast across the extended depth. Fusion of multiple imaging volumes at different depths 32 and high-speed parallel processing 33 provides a 3-D volumetric GD-OCM image with an uncompromised resolution. GD-OCM has successfully revealed the morphologies of human corneas 34-36 with a 2-μm isotropic resolution over a millimeter range imaging depth.
In this pilot study, a pathway to assess corneal endothelial cells from ex vivo donor corneas using GD-OCM was demonstrated on six corneas. To assess the variability in ECD across the location of the cornea, the endothelial layer was evaluated at five locations, namely, nasal, temporal, central, superior, and inferior with respect to the apex of the mounted cornea. Four statistical metrics of the corneal endothelium-ECN, ECA, ECD, and CV-were quantified at the five locations. From the image acquisition to cell analysis, the entire process was repeated six times at each location to evaluate the variability in the estimation of ECD.

Protocol and Sample Preparation
The donor corneas were received from Lions Eye Bank at Albany and Rochester, New York. Corneas were preserved upon recovery in Optisol-GS medium (Bausch and Lomb, Rochester) inside a storage container for corneas and were delivered to the University of Rochester inside a polystyrene box filled with packs of ice. The donor age ranged from 32 to 66 years. Time from death to tissue preservation was about 5 to 22 h. Donor tissue details are summarized in Table 1. Prior to imaging, corneas were stored at room temperature for 1 h to improve the image quality. 37 As a reference, a conventional noncontact specular microscope, Kerato Analyzer (EKA-98, Konan Medical Inc., Japan) was first employed to image the central location of the corneal endothelium through the storage container. A USAF calibration target (R1L1S1P, THORLABS) was used to convert the number of pixels into the physical dimension of endothelial cells area. Corneas were then removed from the storage container and mounted onto a corneal artificial chamber (Moria, Inc., France) equipped with a microfluidic system that was used to control the physiological pressure inside the anterior chamber. The latter was perfused using Optisol to avoid air bubbles inside the anterior chamber.

Imaging with GD-OCM
The light source of GD-OCM had a central wavelength of 840 nm and a bandwidth of 100 nm. The FWHM of the axial PSF in air was ∼4 μm up to 1.2-mm-depth, equivalent to 2.8 μm in the cornea. At least 2.2-μm lateral separation could be resolved. 36 The NA of the GD-OCM microscope objective was 0.2 and the theoretical DOF (for λ ¼ 840 nm) was ∼40 μm. The MTF-driven experimental DOF assuming 20% contrast at 177 lp∕mm was 80 μm in air. 31 The assembly was secured on the deck of a tip, tilt and rotation stage (TTR001, THORLABS) mounted on two horizontal Xand Y-linear stages (DTS25, THORLABS) and a vertical Z-linear stage (MVN80, Newport) as shown in Fig. 1(a). The positioning of the sample relative to the GD-OCM probe was monitored using 2-D scanning in X and Y directions. The air gap of ∼100 μm between the GD-OCM probe's window and the cornea was filled with Optisol for index matching, thus reducing high-reflection imaging artifacts resulting from the corneal anterior surface. For imaging the four near-peripheral endothelial layer (superior, inferior, nasal, and temporal) locations, the cornea platform was tilted by 5 deg (up, down, left, and right, respectively) using the tip, tilt and rotation stage as shown in Fig. 1(b). In all cases, the centering of the cornea on the probe was performed using the 2-D scanning in X and Y directions.
The effective number of focal planes allocated for imaging the curved endothelial layer was two to three depending on the cornea, accounting for the corneal curvature. For estimating the robustness of ECD measurement, each time the cornea platform was realigned mostly along the vertical direction, the GD-OCM images were acquired. Using the GD-OCM 4D™ software (LighTopTech Corp., Rochester, New York), a set of liquid lens voltages corresponding to two or three focal planes around the endothelial layer were configured to partition the effective imaging volume as shown in Fig. 2. The imaging procedure from the sample positioning to the reconfiguration of focal planes was repeated six times at each location by three examiners. We obtained thirty images per cornea (six images per location × five-central, superior, inferior, nasal, and temporal-locations) and a total of one hundred eighty volumetric images for six corneas to analyze.

Flattening the GD-OCM Image
The three-dimensional visualization of the endothelial layer was a curved surface. To easily assess the endothelial cells on the curved surface, the raw GD-OCM images of the endothelial layer were projected onto a single plane using a custom MATLAB ® code described in Fig. 3. The imaging flattening code runs on every B-scan image and first finds the depth coordinate of the endothelial layer using the peak intensity of the layer at each A-scan. Using the consecutive coordinates for one B-scan, the endothelium layer is curve-fitted by polynomials as a trial. Then any possible erroneous depth coordinate is automatically found based on the smoothness of the layer and is excluded in the secondary curve-fitting step. After curvefitting, every A-scan is shifted using the second coordinate to create an image of a flat endothelium layer. This process is simultaneously applied to all B-scans of the volumetric image using the parallel computing toolbox in MATLAB ® . The resulting volumetric image is then restacked to extract the wide en face view of the endothelial cells layer [ Fig. 4(c)].

Counting the Endothelial Cells
The 2-D images of the flattened endothelial layers from all corneas were circularly cropped around the central region for the cell analysis as shown in Fig. 5(a). The diameter of the analysis  Journal of Biomedical Optics 085001-3 August 2019 • Vol. 24 (8) area, where the cell borders were reasonably visible, ranged from 500 to 700 μm depending on the location on the cornea. The smaller diameter of 500 μm was then chosen for the analysis of all of the corneas to compare the results [ Fig. 5(b)]. Thirty en face images of the flattened endothelial layers per cornea (total of 180 images for 6 corneas) were distributed to three blinded examiners. Every corner of the endothelial cells was manually identified by the examiners; then a custom MATLAB ® algorithm was used to delineate the cell borders with a rule of connecting each corner to three other adjacent corners, as shown in Fig. 5(c). The corner algorithm often misinterpreted the cell borders in a way that caused the border to cross the center of a cell. This occurred both at all outer cells near the window of analysis and at some inner cells of irregular hexagonality. Three blinded examiners edited the borders using Adobe Illustrator® and generated an image of the cell borders, as shown in Fig. 5(d), after comparing the cropped image of the endothelial layer with the cell borders found with the custom MATLAB ® algorithm. For the three examiners, it took about one hour from cropping the image to creating the refined cell borders per image. Finally, the images of the cell borders were analyzed using the "Analyze Particles. . . " plugin in Fiji 38 (an advanced version of ImageJ). Every single counted cell was labeled with the cell index and the pixelated area was obtained, coupled to the corresponding cell index as shown in Fig. 5(e).

Results
The cell counting procedure was applied to all the processed images of the endothelial layers as shown in Fig. 6. For the n'th sample of the counted cells as shown in Fig. 5(e), ECN n , ECA n , ECD n , and CV n were first evaluated using Eq. (1)-(4), respectively. Then ECN, ECA, ECD, and CV were calculated with six samples as mean AE SD, respectively. The variability in the ECD measurements with six samples was quantified as a ratio of the standard deviation to the mean of the ECD in percent as shown in Eq. (5). The statistics of the donor endothelial cells are summarized in Table 2 and Fig. 7. Variabilityð%Þ ¼ SD of ECD n s mean of ECD n s × 100: For the purpose of validation, six SM images in total were taken near the central location of corneas 5 and 6 (not exactly at the same location as where the GD-OCM image was taken) then an image with the best quality of contrast was used per cornea to analyze the endothelial cells. The identical procedures of the cell count and parameterization were applied to the SM images.   Journal of Biomedical Optics 085001-4 August 2019 • Vol. 24 (8) respectively, for cornea 6. For cornea 6, the ECD SM fell within the range of the average ECD GD-OCM of all areas. However, for cornea 5, the ECD SM showed a smaller value than the average ECD GD-OCM of all areas by ∼100 cells∕mm 2 . The results from six corneas showed that (1) the interoperator variability in the estimation of the ECD via our current modality was <2.3% for each location and <5.3% for all locations and (2) the ECD value varied with the location of the assessment, which points to the need for evaluating ECD at multiple locations. 40

Discussion
We presented a pathway to measure the clinical parameters of cornea endothelial cells, i.e., ECN, ECA, ECD, and CV, with GD-OCM. This metrology showed promise in the assessment with the capability of counting more than 400 cells from a curved cornea (but, depending on the image quality, the number of counted cells can be lower). It is worth noting that the standard deviation for the ECD measurement is small and <2.3% of the mean ECD value at each location. Furthermore, 3-D visualization of corneal structures with cellular resolution and wide field of view (1 × 1 × 1 mm 3 ) allows for integrative study of corneal structure across the layers. However, the current metrology has four technical limitations for its practical use in eye banks. First, the current flattening algorithm projects the curved endothelial cells to a plane; therefore, the cellular area measured is smaller than its actual area at the curve. This feature will locally result in increased ECD value depending on the curvature. The future flattening algorithm must account for the curvature dependence in the measurement of the cellular area. Second, a donor cornea had to be mounted onto a corneal artificial chamber for the GD-OCM imaging. GD-OCM is a noninvasive imaging technology but the manner of imaging required a mounted cornea. This limitation originated from the short working distance of the GD-OCM probe, which hindered the ability to image a donor cornea through its cornea storage  Note: N, nasal; T, temporal; C, center; S, superior; and I, inferior with respect to the apex of the mounted cornea. ECDs of corneas 1, 2, and 3 were measured as higher than typical ECDs measured with SM. 39 We present the likely cause for this discrepancy in the discussion.
Journal of Biomedical Optics 085001-6 August 2019 • Vol. 24 (8) container. However, this inability has been recently surmounted using the GD-OCM probe with a working distance of 15 mm, 35 developed by LighTopTech Co., Rochester, New York. Third, the area of the cellular analysis did not cover the entire field of view of 1 × 1 mm 2 provided by the GD-OCM. This third issue arose from a lower scattering signal at the periphery of the imaging field of view even though the imaging conditions were optimized using multiple focuses across the curved layer. The low scattering signal from the inclined surface is the common phenomena for all intensity-based imaging techniques like SM and IVCM, but the issue might not have been resolved with the interference imaging technique that has an advantage of weak signal detection, herein, GD-OCM. In general, the scattering intensity highly depends on the incident angle of light. If the incident angles at the periphery could be reduced without flattening a donor cornea by force, e.g., adjusting the chief ray angles at the corneal surface via the nontelecentric illumination, 41 this issue could be mitigated. Finally, the cell counting method took about 1 h for one en-face image regardless of the examiner. We attribute this issue to the image quality that influences the correct identification of a single endothelial cell.
A robust cell counting algorithm that is less sensitive to image quality is needed to speed up this modality.