To evaluate the performance of 3-dimensional (3D) endothelium/Descemet membrane complex thickness (En/DMT) maps vs total corneal thickness (TCT) maps in the diagnosis of active corneal graft rejection.
Eighty-one eyes (32 clear grafts and 17 with active rejection, along with 32 age-matched control eyes) were imaged using high-definition optical coherence tomography (HD-OCT), and a custom-built segmentation algorithm was used to generate 3D color-coded maps of TCT and En/DMT of the central 6-mm cornea. Regional En/DMT and TCT were analyzed and compared between the studied groups. Receiver operating characteristic curves were used to determine the accuracy of En/DMT and TCT maps in differentiating between studied groups. Main outcome measures were regional En/DMT and TCT.
Both regional TCT and En/DMT were significantly greater in actively rejecting grafts compared to both healthy corneas and clear grafts ( P < .001). Using 3D thickness maps, central, paracentral, and peripheral En/DMT achieved 100% sensitivity and 100% specificity in diagnosing actively rejecting grafts (optimal cut-off value [OCV] of 19 μm, 24 μm, and 26 μm, respectively), vs only 82% sensitivity and 96% specificity for central TCT, OCV of 587 μm. Moreover, central, paracentral, and peripheral En/DMT correlated significantly with graft rejection severity (r = 0.972, r = 0.729, and r = 0.823, respectively; P < .001).
3D En/DMT maps can diagnose active corneal graft rejection with excellent accuracy, sensitivity, and specificity. Future longitudinal studies are required to evaluate the predictive and prognostic role of 3D En/DMT maps in corneal graft rejection.
Corneal transplantation is the most common type of organ transplantation, with approximately 185,000 corneas transplanted annually in a survey of 116 countries, and 1 in 70 of the needs are covered worldwide. Corneal graft rejection is the leading cause of graft failure in the late postoperative period, , and up to 68% of penetrating keratoplasties are affected by at least 1 episode of rejection. In full-thickness corneal transplants, graft failure rate secondary to a rejection ranges from 5% in low-risk grafts after 5 years to 35% in high-risk grafts at 3 years. These failures impose a heavy burden on the health care system and on patients’ quality of life. Hence, early detection of graft rejection is crucial to enhance corneal graft survival and maintain patients’ productivity.
Clinicians rely on slit-lamp findings of conjunctival injection, corneal edema, epithelial and endothelial rejection lines, subepithelial infiltrates, anterior chamber cells and flare, and Descemet folds to diagnose graft rejection, , but these findings are only clinically apparent after irreversible loss of endothelial cells, which are critical for maintenance of corneal transparency, has already happened. Pachymetry, in vivo confocal microscopy, specular microscopy, and anterior segment optical coherence tomography (OCT) have been investigated to help diagnose a rejection earlier than clinical diagnosis. , However, these methods analyzed the changes only in the central area of the corneal graft and could thus miss an early rejection in the peripheral parts of the corneal graft. In our previous work, we disclosed that manual measurement of central endothelial/Descemet membrane complex thickness (En/DMT) is a novel quantitative index that correlates accurately with the severity of rejection in both ex vivo and in vivo studies. Also, we have shown that central En/DMT has better diagnostic performance than endothelial cell density and central corneal thickness in characterizing the immunologic status of corneal grafts. , However, these measurements were 2-dimensional (2D) and thus more susceptible to missing minor changes in the optical scan.
In this study, we compared the performance of 3-dimensional (3D) En/DMT maps vs total corneal thickness (TCT) maps in the diagnosis of active corneal graft rejection. A custom-built segmentation algorithm was used to generate 3D color-coded En/DMT maps from the captured high-definition (HD) OCT images of the central 6-mm cornea. Compared with manual segmentation, this algorithm has been validated to be capable of segmenting all corneal layers of healthy eyes with similar accuracy, albeit with significantly better repeatability as well as significantly less running time per image. It uses automated segmentation algorithms to generate 3D thickness maps of corneal layers. This quasi-histologic visualization can enhance evaluation and diagnosis of various corneal pathologies such as keratoconus, Fuchs endothelial corneal dystrophy, , and corneal graft rejection. , Additionally, we analyzed central, paracentral, and peripheral En/DMT parameters that we found highly sensitive and specific in diagnosing active corneal graft rejection. We also present data demonstrating that regional En/DMT is a much better indicator than central corneal thickness in assessing the immunologic status of the corneal graft.
This study was approved by the University of Miami Institutional Review Board. All participants provided written informed consent before enrollment. The study design followed the tenets of the Declaration of Helsinki for biomedical research.
Forty-nine eyes of 49 patients and 32 eyes of 32 normal controls were prospectively and consecutively recruited from December 2016 to January 2019 at Bascom Palmer Eye Institute, University of Miami (Miami, Florida, USA). Inclusion criteria for participation included uneventful penetrating keratoplasty (PK) or Descemet stripping automated endothelial keratoplasty (DSAEK) surgery performed greater than 1 month prior. Exclusion criteria included corneal grafts with microbial infection or past history of a rejection episode. For the unoperated control eyes, a best-corrected visual acuity (BCVA) better than 20/25 on the Snellen scale and no corneal abnormalities as detected by slit-lamp examination were required to be included in the study. Individuals with recent contact lens use, ocular diseases, previous ocular surgery, and systemic diseases with ocular involvement were excluded. Slit-lamp examination was performed on each eye by a masked cornea specialist (either M.A. or S.Y.) in order to assign the examined cornea into either a clear graft or actively rejecting category. Active endothelial graft rejection was diagnosed by detecting new keratic precipitates (KPs) or a Khodadoust line in the presence of anterior chamber cells and new persistent corneal graft edema on 2 consecutive visits in a graft that was previously clear. , Clinical grading of corneal graft rejection based on the ejection severity was not attempted.
Image Acquisition and Analysis
Each participant received anterior segment HD-OCT (Envisu R2210; Bioptigen, Buffalo Grove, Illinois, USA) with 6-mm radial cuts centered on the corneal vertex. This device uses a super-luminescent diode light source with a central wavelength of 840 nm, and it has an axial resolution of 3 μm and a scanning speed of 32,000 A-scans per second with 36 frames per scan. Each participant was asked to look at a central fixation target and the presence of a visible specular reflection in all images confirmed optimal centration. In decentered grafts and post-PK eyes with high irregular astigmatism, the patient was asked to look at an optimized fixation target to maintain the geometric centration of the scan upon the graft. Custom-built segmentation software was used to segment the corneal epithelium, Descemet membrane, and endothelium automatically, with manual editing if needed ( Figure 1 ). Manual editing was executed by 2 masked operators when the automatic segmentation failed to delineate the irregularities on the endothelial layer in the rejecting corneal grafts. The segmentation software used the Random Sample Consensus method with a polynomial model to estimate the corneal layer boundaries from potential points obtained from thresholding the OCT image. Then, the estimates are refined by searching locally in the original image for the best points. The segmentation method is robust to the specular reflection, as each boundary is fitted to a polynomial model that depends on all points and is not much affected by the specular reflection, as shown in Figure 1 . Then, the segmentation of different frames of the scan is mapped into 3D and interpolated using bi-cubic interpolation to obtain the corneal surfaces. After that, 3D ray tracing is applied iteratively at each interpolated surface to correct for the refraction in the OCT imaging light by applying the vector form of Snell’s law at the refractive interface between each 2 successive layers ( Figure 2 A). Finally, the inter-surface distances are measured as the shortest axial distance between each consecutive surface to generate the thickness maps. We used the refractive index of 1.376 for the corneal layers. Thickness maps were regionally divided into a central 2-mm circle, surrounded by 2-mm-wide paracentral and 2-mm-wide peripheral concentric rings ( Figure 2 B). The average central, paracentral, and peripheral thickness parameters were calculated and used for further analysis. Validation studies of our automated image processing techniques were published in our previous work and the results were comparable to those of the manual operators.
We used 3 diagnostic indices to describe the regional microstructural characteristics of the endothelial/Descemet membrane (En/DM) complex: central, paracentral, and peripheral En/DMT. We previously reported the 2 interfaces of the En/DM complex as the 2 most posterior hyperreflective bands of the cornea on HD-OCT images. ,
Statistical analyses were performed using SPSS software version 22.0 (SPSS, Chicago, Illinois, USA) to calculate descriptive statistics for all eyes. The obtained TCT measurements were verified to have a normal distribution by assessment of histograms and a Shapiro-Wilk test of normality, while En/DMT was not. Therefore, mean ± standard deviation (SD) was used to characterize the distribution of the corneal thickness values, while the median values were used to characterize both En/DMT. In addition, 1-way analysis of variance (ANOVA) with post hoc comparisons was performed to account for the differences in central, paracentral, and peripheral corneal thickness, while a Kruskal-Wallis test with pairwise comparisons was used for regional En/DMT. Additionally, factorial ANOVA was performed to verify if the changes in the corneal thickness and En/DMT depend on the type of graft (PK vs DSAEK). The sensitivity and specificity of regional En/DMT and regional TCT in differentiating between studied groups were determined by generating receiver operating characteristic curves. In order to determine if central, paracentral, and peripheral En/DMT would be descriptive of graft rejection severity, coefficient of correlation (r-value) of those indices and rejection severity based on central TCT was computed. , Two-sided P values less than .05 were considered to be statistically significant. Moreover, intraclass correlation coefficients (ICC) were used to assess the inter-operator reliability of the manual measurements in the selected eyes. The ICC is defined as the ratio of the between-subjects variance to the sum of the pooled within-subjects variance and the between-subjects variance. The ICC interpretation that was used considered the reliability of the values as poor for values less than 0.2, fair for values from 0.21 to 0.40, moderate for values from 0.41 to 0.60, good for values from 0.61 to 0.80, and excellent for values higher than 0.80.
Our study included 49 eyes of 49 patients; the breakdown included 32 clear grafts (21 PK and 11 DSAEK), 17 actively rejecting grafts (13 PK and 4 DSAEK), and 32 eyes of 32 age- and sex-matched healthy controls. Table 1 summarizes the different characteristics of all groups. The type of graft (PK vs DSAEK) had no statistically significant effect on the changes in the mean regional corneal thickness and En/DMT values between the studied groups ( Figure 3 ).
|Actively Rejecting Grafts
|Number of eyes
|P = .06 b
|46 ± 18
|56 ± 18
|59 ± 22
|P = .06 b
|Postoperative time (months)
|8 ± 5
|10 ± 4
|P = .11 b
|Central corneal thickness (μm)
|516 ± 28
|518 ± 39
|697 ± 119
|P < .001 b
|Paracentral corneal thickness (μm)
|527 ± 27
|552 ± 41
|766 ± 149
|P < .001 b
|Peripheral corneal thickness (μm)
|543 ± 29
|569 ± 37
|744 ± 119
|P < .001 b
|Central DMT (μm) a
|P < .001 c
|Paracentral DMT (μm) a
|P < .001 c
|Peripheral DMT (μm) a
|P < .001 c