Enhancing Diagnostic Precision in Fuchs Dystrophy: Comparative Evaluation of REVO HR and FC130 OCT Systems

Abstract

Purpose

To compare the diagnostic performance of two anterior segment optical coherence tomography devices, REVO FC130 and REVO HR, in patients with Fuchs endothelial corneal dystrophy (FECD).

Methods

This prospective cross-sectional study included 33 patients with FECD. Each patient was imaged with both devices. Eleven corneal features were graded independently by two evaluators. A third grader resolved disagreements. Agreement between graders and between devices was quantified by calculating the proportion of concordant assessments, including agreement for both detected and non-detected features, with corresponding 95% confidence intervals.

Results

REVO HR provided better visualization of key corneal structures, including Descemet's membrane, Bowman's layer, and hyperreflective basal changes. Hyperreflective basal features were detected 11 times more often with REVO HR. Bowman's layer was identified 2.06 times more frequently with REVO HR compared to REVO FC130. Interoperator agreement was high for REVO HR (PropOverall ≥ 0.97 in 10 of 11 features). FC130 showed lower and more variable agreement, especially in low-contrast regions. Interdevice comparisons indicated systematic differences in detection capability.

Conclusions

REVO HR showed higher sensitivity and reproducibility in detecting corneal microstructural changes in FECD. Improved image resolution allows better identification of subtle abnormalities, which may support more accurate disease staging and better timing of surgical intervention. For follow-up, the same OCT device should be used consistently.

Translational Relevance

This study demonstrates that improved OCT resolution enhances detection of corneal microstructural abnormalities in Fuchs endothelial corneal dystrophy, improving diagnostic precision, disease staging, and clinical decision-making in routine clinical practice.

Introduction

Optical coherence tomography (OCT) has become an essential noninvasive tool for assessing corneal morphology, providing high-resolution cross-sectional imaging of individual corneal layers. Technological advancements in OCT, especially the transition from time-domain to spectral-domain and swept-source systems, have significantly improved axial and lateral resolution over the years.^1,2 As a result, the detection of subtle pathological changes, including those seen in corneal dystrophies, has improved.

Fuchs endothelial corneal dystrophy (FECD) is a progressive, bilateral disorder characterized by endothelial cell loss, guttae formation, and progressive stromal and epithelial edema, which ultimately leads to visual impairment.^3,4 On OCT imaging, these pathological changes may manifest as thickening and irregularity of Descemet's membrane, hyperreflective guttae, increased stromal reflectivity due to edema, and epithelial irregularities. Accurate visualization of these microstructural alterations is essential for the diagnosis, staging, and monitoring of FECD.^5,6

Early detection of corneal edema is particularly important in patients being considered for Descemet membrane endothelial keratoplasty, because timely surgical intervention may prevent irreversible structural damage and improve visual outcomes.⁷ OCT is also valuable in the postoperative setting for detecting graft detachment or dehiscence following Descemet membrane endothelial keratoplasty and Descemet stripping automated endothelial keratoplasty, enabling prompt management and monitoring of graft adherence and corneal recovery.⁸ Furthermore, anterior segment OCT (AS-OCT) can quantify stromal reflectivity changes, allowing sensitive differentiation between edematous and non-edematous tissue.⁹

Currently available OCT systems differ in resolution, scanning protocols, and image-processing algorithms, all of which may influence diagnostic accuracy. In clinical practice, subtle findings—such as disruptions of Bowman's layer, irregularities of Descemet's membrane, or thin hyperreflective deposits—can be difficult to identify, especially in early disease stages. Previous studies have emphasized the importance of in vivo assessment of Descemet's membrane to better understand the pathogenesis and progression of FECD.¹⁰ However, earlier imaging technologies were limited by insufficient resolution.¹¹ Therefore comparative evaluation of modern OCT platforms is necessary to establish diagnostic standards, optimize image interpretation, and improve clinical outcomes in corneal dystrophies such as FECD.

The present study compares two OCT devices—REVO FC130 and REVO HR (Optopol Technology, Zawiercie, Poland)—with respect to their ability to visualize key corneal structures and pathological features in patients with FECD. By analyzing device performance and grading reproducibility, this study aims to provide clinically relevant evidence regarding the diagnostic utility of high-resolution OCT in corneal disease.

Material and Methods

Study Procedures

This prospective, cross-sectional observational study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethics Committee of the Silesian Medical University (approval number KNW/0022/KB1/128/18/19). Written informed consent was obtained from all participants prior to any study procedures.

All patients were imaged with both OCT devices—REVO FC130 and REVO HR (Optopol Technology, Zawiercie, Poland)—during the same visit. Imaging was performed consecutively, one device immediately after the other, to minimize potential variability related to time-dependent corneal changes.

Scans were acquired using SOCT software (version 20.0.1). Before image acquisition, patients were instructed to blink and then keep the examined eye open during scanning. Two high-resolution 9-mm line scans, each consisting of 100 repeated B-scans, were obtained 90 degrees apart and centered on the corneal apex, with a focus setting of −1.0 D.

Basic Statistics

The study population included 33 patients (22 women and 11 men) diagnosed with FECD. The mean age was 69.3 ± 12.12 years (range, 41–92 years).

Each eye was evaluated for the visibility of the following corneal structures and/or pathological features: epithelium, additional epithelial layer, basal layer, Bowman's layer (three-line pattern), Descemet's membrane, additional Descemet's membrane layer, longitudinal stromal fibers, endothelium, guttae, hyperreflective layer above the basal epithelium, and oblique stromal fibers.

All scans were independently assessed by two graders. Each feature was graded as “yes” (visible) or “no” (not visible). In cases of disagreement, a third grader adjudicated the final result.

For clarity, several OCT-derived structural descriptors used in the grading process were defined as follows. “Bowman's layer (three-line pattern)” refers to the appearance of three closely spaced reflective interfaces corresponding to the epithelial–Bowman's interface and Bowman's layer reflectivity that may be resolved on high-resolution OCT imaging. The term “hyperreflective layer above the basal epithelium” denotes a thin reflective band located immediately anterior to the basal epithelial layer. “Additional epithelial layer” refers to the intermediate epithelial layer located between the superficial epithelial cells and basal epithelial cells. Visualization of these microstructural features depends on the axial resolution and contrast characteristics of the OCT system.^6,10

Statistical Analyses

Descriptive statistics and agreement analyses were performed using R software (version 4.2.1; RStudio version 2024.12.0). Inter-grader and inter-device agreement was quantified by calculating the proportion of concordant evaluations, including overall agreement, as well as agreement for positive and negative findings, with corresponding 95% confidence intervals (CIs).

Results

Agreement Between Operators

To establish agreement between operators for the included region or pathology, comparison between raters was performed, and the overall percentage of agreement, average positive agreement, and average negative agreement were calculated. Parameters were defined as follows: overall percentage of agreementt (PropOverall):

$$\begin{array}{c}\hfill \mathrm{PropOverall}=\frac{\left(a+d\right)}{\left(a+b+c+d\right)}\end{array}$$

Average positive agreement (PropPos): number of positive matches as a proportion of the average of the number of positive results by X, Y.

$$\begin{array}{c}\hfill \mathrm{PropPos}=\frac{2*a}{\left(2*a+b+c\right)}\end{array}$$

Average negative agreement (PropNeg): number of negative matches as a proportion of the average of the number of negative results by X, Y.

$$\begin{array}{c}\hfill \mathrm{PropNeg}=\frac{2*d}{\left(2*d+b+c\right)}\end{array}$$

Confidence intervals for parameters were computed using the Bayesian interval with the default Dirichlet prior for PropPos and PropNeg and Beta (1,1) prior for overall agreement (Table 1). The Egon-Pearson corrected χ² test for independence was also used.

Table 1.

Bayesian Interval With the Default Dirichlet for PropPos, PropNeg, and Beta (1,1)

Rater 1	Rater 2 (+)	Rater 2 (−)	Total
(+)	a	b	a + b
(−)	c	d	c + d
Total	a + c	b + d	n

Comparison Between Devices

To compare the two diagnostic devices (FC 130 and HR) also the total percentage of agreement (PropOverall), as well as the average positive (PropPos) and average negative agreement (PropNeg) for binary outcomes were reported.

Adding Third Rater

Additionally, a third rater's (AW) gradation was included in case of operators 1 (DS) and 2's (PP) disagreement. In the three raters' analysis, we assumed that the third rater would agree in cases when raters 1 and 2 agreed. Pairwise analyses were also conducted for 1&3 and 2&3 raters.

Results

Table 2 summarizes the assessments made by all three Graders. For each, the number of cases in which the visibility of structure (region) or pathology was identified (as well as the percentage of all analyzed patients) was calculated individually. Grader 1 and Grader 2 each evaluated 33 patients. Grader 3 assessed only the disputed cases (i.e., when the evaluations of Grader 1 and Grader 2 differed).

Table 2.

Summary of the Assessment Made by the Three Graders

	REVO FC130			REVO HR
Region Or Pathology Recognition	First Grader	Second Grader	Third Grader*	First Grader	Second Grader	Third Grader*
Epithelium
Yes	31 (93.94%)	31 (93.94%)	0 (0%)	33 (100%)	33 (100%)	—
No	2 (6.06%)	2 (6.06%)	2(100%)	0 (0%)	0 (0%)	—
Additional epithelium layer
Yes	33 (100%)	32 (96.97%)	0 (0%)	33 (100%)	33 (100%)	—
No	0 (0%)	1 (3.03%)	1 (100%)	0 (0%)	0 (0%)	—
Hyperreflective layer above the basal epithelium
Yes	2 (6.06%)	1 (3.03%)	0 (0%)	11 (33.33%)	11 (33.33%)	—
No	31 (93.94%)	32 (96.97%)	1 (100%)	22 (66.67%)	22 (66.67%)	—
Basal epithelial layer
Yes	25 (75.76%)	25 (75.76%)	—	33 (100%)	33 (100%)	—
No	8 (24.24%)	8 (24.24%)	—	0 (0%)	0 (0%)	—
Bowman's layer (three-line pattern)
Yes	16 (48.48%)	17 (51.52%)	3 (42.85%)	33 (100%)	33 (100%)	—
No	17 (51.52%)	16 (48.48%)	4 (57.15%)	0 (0%)	0 (0%)	—
Oblique stromal fibers
Yes	32 (96.97%)	32 (96.97%)	—	33 (100%)	33 (100%)	—
No	1 (3.03%)	1 (3.03%)	—	0 (0%)	0 (0%)	—
Longitudinal stromal fibers
Yes	33 (100%)	33 (100%)	—	33 (100%)	33 (100%)	—
No	0 (0%)	0 (0%)	—	0 (0%)	0 (0%)	—
Descemet's membrane
Yes	24 (72.73%)	25 (75.76%)	1 (20.0%)	32 (96.97%)	32 (96.97%)	—
No	9 (27.27%)	8 (24.24%)	4 (80.0%)	1 (3.03%)	1 (3.03%)	—
Endothelium
Yes	30 (90.91%)	24 (72.73%)	1 (16.67%)	33 (100%)	33 (100%)	—
No	3 (9.09%)	9 (27.27%)	5 (83.33%)	0 (0%)	0 (0%)	—
Guttae
Yes	28 (84.85%)	28 (84.85%)	—	33 (100%)	33 (100%)	—
No	5 (15.15%)	5 (15.15%)	—	0 (0%)	0 (0%)	—
Additional Descemet's membrane layer
Yes	25 (75.76%)	25 (75.76%)	—	31 (93.94%)	30 (90.91%)	1 (100%)
No	8 (24.24%)	8 (24.24%)	—	2 (6.06%)	3 (9.09%)	0 (0%)

^*The third Grader assessed the exams only when there was no agreement between the first and second graders.

Table 3 ³ summarizes the final assessment of the visibility of regions and/or pathologies (rates for Grader 3) with the assumption that the assessment of Grader 3 is equal to evaluations made by Grader 1 and Grader 2 when they were consistent, and the assessment of Grader 3 in disputed cases. Additionally, the rate ratio of region or pathology recognition REVO HR/REVO FC 130 was calculated for each region and/or pathology.

Table 3.

The Final Assessment of the Visibility of Region or Pathologies

Structure/Pathology Recognition	REVO FC130	REVO HR	Rate Ratio—REVO HR/REVO FC130
Epithelium			1.10
Yes	30 (90.91%)	33 (100%)
No	3 (9.09%)	0 (0%)
Additional epithelium layer			1.03
Yes	32 (96.97%)	33 (100%)
No	1 (3.03%)	0 (0%)
Hyperreflective layer above the basal epithelium			11.00
Yes	1 (3.03%)	11 (33.33%)
No	32 (96.97%)	22 (66.67%)
Basal epithelial layer			1.32
Yes	25 (75.76%)	33 (100%)
No	8 (24.24%)	0 (0%)
Bowman's layer (three-line pattern)			2.06
Yes	16 (48.48%)	33 (100%)
No	17 (51.52%)	0 (0%)
Oblique stromal fibers*			1.03
Yes	32 (96.97%)	33 (100%)
No	1 (3.03%)	0 (0%)
Longitudinal stromal fibers			1
Yes	33 (100%)	33 (100%)
No	0 (0%)	0 (0%)
Descemet's membrane			1.39
Yes	23 (69.70%)	32 (96.97%)
No	10 (30.30%)	1 (3.03%)
Endothelium			1.32
Yes	25 (75.76%)	33 (100%)
No	8 (24.24%)	0 (0%)
Guttae			1.18
Yes	28 (84.85%)	33 (100%)
No	5 (15.15%)	0 (0%)
Additional Descemet's membrane layer			1.24
Yes	25 (75.76%)	31 (93.94%)
No	8 (24.24%)	2 (6.06%)

^*All ratings by first and second graders were consistent, so the assumed ratings by third grader were considered coherent.

Based on the rate ratio (HR/FC130), we can conclude that the largest disparity in detection frequency in the visualization of a region and/or pathology between the two devices is observed for the hyperreflective layer above the basal epithelium region. The HR device detects this area 11 times more frequently than the FC130 device In the case of Bowman's layer, the presence of all three distinguishable lines was observed 2.06 times more frequently with the HR device compared to the FC130 (Figs. 1, 2³⁴⁵⁶⁷⁸). Greater visibility on the HR device was also noted for the remaining examined regions, except for the longitudinal stromal fibers. For these regions, the rate ratio HR/FC130 values remained at a similar level (1.03–1.39). In the case of the longitudinal stromal fibers, no difference in the frequency of lesion detection was observed between the HR and FC130 devices.

Figure 1.

Image acquired with REVO HR clearly delineates the three distinguishable lines of Bowman's layer, demonstrating high axial resolution and structural clarity.

Figure 2.

Image acquired with REVO FC130 from the same patient shows limited distinguishability of Bowman's layer, reflecting reduced imaging sensitivity and resolution.

Figure 3.

The device overall agreement for pooled data (first and second grader) is shown below.

Figure 4.

1–3 operator agreement.

Figure 5.

2–3 operator agreement.

Figure 6.

Operator negative agreement.

Figure 7.

Device overall agreement.

Figure 8.

Agreement between devices.

Operator and Agreement Analysis

Agreement between graders was calculated for 11 regions or pathological features for each device (REVO HR and FC130), as well as between devices. For REVO HR, nearly perfect inter-grader agreement was observed for most regions (PropOverall = 1.000 in 10 of 11 regions). Only the additional Descemet's membrane layer showed slightly lower agreement (PropOverall = 0.970). Agreement for FC130 was more variable but remained generally good (range of PropOverall: 0.788–1.000). The lowest agreement values for FC130 were observed for Bowman's layer (three-line pattern; 0.788), endothelium (0.818), and Descemet's membrane (0.849). Perfect agreement (PropOverall = 1.000) was achieved for basal epithelial layer, oblique stromal fibers, longitudinal stromal fibers, guttae, and the additional Descemet's membrane layer.

Overall, inter-grader agreement was high, supporting the use of pooled evaluations as the primary measure for inter-device comparison. Although intraclass correlation coefficients based on a linear mixed model were considered as a secondary reliability measure, intraclass correlation coefficients have known limitations for binary outcomes with sparse events; therefore these results were interpreted with caution.

Inter-device agreement analysis showed high pooled overall agreement for the epithelium (0.94; CI, 0.85–0.98), additional epithelial layer (0.98; CI, 0.92–1.00), oblique stromal fibers (0.97; CI, 0.90–0.99), and longitudinal stromal fibers (1.00; CI, 0.95–1.00) (Fig. 3). Moderate agreement between devices was observed for the additional Descemet's membrane layer (0.83; CI, 0.73–0.90), endothelium (0.82; CI, 0.71–0.89), guttae (0.85; CI, 0.74–0.92), and Descemet's membrane (0.77; CI, 0.66–0.86). Lower agreement was found for Bowman's layer (three-line pattern; 0.50; CI, 0.38–0.62), the hyperreflective layer above the basal epithelium (0.65; CI, 0.53–0.76), and the basal epithelial layer r (0.76; CI, 0.64–0.84).

The pooled overall agreement values for the basal epithelial layer and the hyperreflective layer above the basal epithelium—both of which demonstrated almost perfect inter-grader agreement—suggest systematic differences between the two devices. Similarly, pooled agreement values for Bowman's layer, Descemet's membrane, and the endothelium indicate inter-device disagreement. However, for these structures, part of the variability may be attributable to lower inter-grader agreement observed with the FC130 device.

To further clarify whether disagreement was device-related rather than grader-dependent, a third grader was included in cases of discrepancy between the first and second graders. When the first two graders agreed, the third grader's evaluation was assumed to be concordant. In cases of disagreement, the third grader provided an independent adjudication.

Agreement analyses were then performed for all grader pairs, as well as for the pooled group of three graders. These analyses were conducted separately for each device and for inter-device comparisons.

Considerable disagreement was observed when all three raters were analyzed together. The highest level of agreement was noted between graders 2 and 3, suggesting improved consistency after adjudication (Fig. 4). Inter-grader agreement for the Grader 1–3 and Grader 2, 3 pairs is presented in Figures 4 and 5, respectively, whereas operator negative agreement is presented in Figure 6.

Comparison of the pooled three-grader analysis with pairwise analyses revealed some variability in device-level overall agreement. In general, pooled overall agreement values based on three graders were similar to or slightly lower than those obtained from the two-grader pooled analysis. The pooled three-grader analysis continued to demonstrate high inter-device agreement for the epithelium (pooled overall = 0.93; CI, 0.86–0.96), additional epithelial layer (0.98; CI, 0.93–0.99), oblique stromal fibers (0.97; CI, 0.91–0.99), and longitudinal stromal fibers (1.00; CI, 0.96–1.00). Moderate agreement between devices was observed for the additional Descemet's membrane layer (0.83; CI, 0.74–0.89), endothelium (0.80; CI, 0.71–0.87), and guttae (0.85; CI, 0.76–0.91).

Lower inter-device agreement persisted for Bowman's layer (three-line pattern; 0.50; CI: 0.40–0.59), the hyperreflective layer above the basal epithelium (0.65; CI: 0.55–0.73), the basal epithelial layer (0.76; CI: 0.66–0.84), and Descemet's membrane (0.76; CI: 0.66–0.83). The overall inter-device agreement based on pooled three-grader data, as well as inter-grader agreement by region and grader pair, is presented below (Figs. 7, 8).

Although inter-grader agreement for the FC130 improved for Bowman's layer, Descemet's membrane, and the endothelium—particularly for the grader pair 2–3, where agreement exceeded 0.90—inter-device agreement for these same structures did not improve in the corresponding pairwise analysis. For the endothelium, inter-device agreement even decreased substantially. These findings support the conclusion that the observed lack of agreement between devices for Bowman's layer, Descemet's membrane, and the endothelium is primarily attributable to intrinsic differences in device performance rather than grader variability. Systematic inter-device differences were also confirmed for the hyperreflective layer above the basal epithelium and the basal epithelial layer.^12–16

Discussion

This study aimed to determine whether the manufacturer's reported improvement in axial resolution with the REVO HR translates into measurably superior visualization of corneal microstructures in FECD compared with the REVO FC130. Within-manufacturer device comparisons are well established in ophthalmic imaging research, as newer models frequently incorporate substantial differences in optical components, scan protocols, and image-processing algorithms that may significantly influence diagnostic performance.^1–3 Such comparative evaluations are essential for evidence-based clinical decision-making, allowing clinicians to determine whether hardware upgrades provide meaningful diagnostic benefits that justify their implementation. This approach follows prior studies comparing successive generations of OCT technology, where devices sharing the same platform demonstrated clinically relevant performance differences attributable to specific technical refinements.^3,4

AS-OCT has become an important tool for evaluating structural corneal changes in FECD, enabling objective and reproducible assessment of corneal layers and early detection of edema.^8,17–20 Prior imaging studies have compared different OCT technologies and corneal imaging modalities in the evaluation of FECD. For example, comparisons between time-domain and swept-source OCT have demonstrated improved visualization of anterior segment structures with newer OCT platforms,¹ while studies comparing swept-source OCT with Scheimpflug tomography have shown that imaging parameters such as corneal thickness and tomographic indices can aid in detecting corneal edema and predicting disease progression.^17,23 On OCT imaging, guttae and FECD-related abnormalities typically appear as irregularities and increased reflectivity at the posterior corneal interface, often accompanied by thickening of Descemet's membrane and increased stromal reflectivity associated with corneal edema.^5,10,18,19 In addition, emerging quantitative and artificial intelligence–based approaches have been developed to analyze anterior segment OCT images, including automated detection of corneal guttae and objective assessment of FECD severity, which may further improve diagnostic accuracy and disease monitoring.²¹

Our findings demonstrate that REVO HR provides enhanced visualization of fine corneal structures compared with FC130. The improved performance is attributable to its higher axial resolution (approximately 3 µm in tissue compared with 5–6 µm for FC130), which facilitates clearer delineation of thin and weakly reflective structures. Although both systems are classified as high-resolution OCT devices, this difference proved clinically meaningful, particularly for delicate anatomical features. The difference in axial resolution is particularly relevant for Descemet's membrane, which typically measures approximately 8–12 µm in normal corneas and may thicken in FECD.¹⁹ When axial resolution approaches the order of magnitude of the structure being imaged, partial volume effects and interface blurring can reduce layer discrimination. A resolution of ∼3 µm enables clearer separation of thin reflective boundaries within or adjacent to Descemet's membrane, whereas 5–6 µm resolution may lead to merging of closely spaced interfaces, thereby limiting precise structural delineation. In addition to axial resolution, several technical specifications of the OCT systems may contribute to the differences in visualization observed in this study. The REVO HR system provides an axial resolution of approximately 3 µm in tissue, whereas the REVO FC130 offers an axial resolution of approximately 5–6 µm. Both devices operate using a swept-source OCT platform with a central wavelength of approximately 1300 nm, which enables deeper penetration and improved imaging of anterior segment structures. The systems also differ in scanning density and signal acquisition parameters, including A-scan rate and averaging protocols. The REVO HR incorporates optimized signal averaging and higher effective sampling density, which improve the signal-to-noise ratio and enhance the contrast of weakly reflective interfaces. In contrast, the lower axial resolution and broader point-spread function of the FC130 may reduce the ability to distinguish thin corneal layers or closely spaced reflective interfaces. Additionally, lateral resolution and scan sampling strategies influence the delineation of fine stromal patterns and epithelial interfaces. These technical differences collectively contribute to the improved visualization of subtle corneal microstructures observed with the REVO HR in this study.

The largest disparity in detection frequency was observed for the hyperreflective layer above the basal epithelial layer. This difference likely reflects optical and algorithmic distinctions between the devices. REVO HR uses denser A-scan sampling and improved signal processing, enhancing contrast at interfaces with subtle refractive index changes. In contrast, the lower resolution and broader point-spread function of FC130 reduce its ability to separate thin reflective layers from background scatter. These factors plausibly explain the markedly higher detection rate of this feature with REVO HR. Previous studies have reported increased anterior corneal reflectivity and densitometric changes in FECD, particularly in association with early edema and altered stromal backscatter.^9,18,19 These findings suggest that subtle optical changes may occur in the anterior cornea; however, they have not been defined as a specific structural layer.

Therefore the higher detection rate observed with REVO HR may reflect either enhanced visualization of subtle anterior corneal changes or a resolution-dependent phenomenon related to improved axial resolution and signal processing. Similarly, details within Bowman's layer were identified twice as frequently with REVO HR. With the exception of longitudinal stromal fibers, which were equally detected by both systems, REVO HR consistently demonstrated superior detection rates. Although rate ratios for most features ranged from 1.03 to 1.39, indicating modest differences, the consistency of these findings across multiple regions supports a systematic performance advantage.

REVO HR also demonstrated superior reproducibility, achieving near-perfect inter-grader agreement (PropOverall = 1.000) in 10 of 11 evaluated regions. In contrast, FC130 showed more variable inter-grader agreement, particularly for structures requiring higher resolution, such as Bowman's layer, the endothelium, and Descemet's membrane. These findings suggest that imaging limitations rather than grader variability contributed to reduced consistency.

The inclusion of a third grader confirmed that the observed discrepancies were not attributable to subjective interpretation but reflected systematic differences in imaging performance. Importantly, pooled agreement analyses demonstrated persistent inter-device disagreement for several key structures. In this context, “systematic disagreement” indicates that the two OCT systems are not interchangeable for certain diagnostic features. Switching between devices may therefore lead to inconsistencies in disease assessment and follow-up.

In contrast, structures such as the epithelium and stromal fiber patterns demonstrated high inter-device and inter-grader agreement, suggesting that these features are less dependent on ultra-high resolution and are more robust across imaging platforms.

Given its reliability and reproducibility, AS-OCT—alongside Scheimpflug-based tomography—has become an important modality for objective grading of FECD severity, providing a more standardized alternative to slit-lamp–based assessment.^22–24 Our findings reinforce the importance of device consistency in longitudinal monitoring.

The present study has several limitations. First, no external reference standard—such as in vivo confocal microscopy, specular microscopy, pachymetry, or histopathological correlation—was available. Therefore, although REVO HR demonstrated increased visibility of several microstructural features, it cannot be definitively determined whether all additionally detected findings represent true pathological alterations or resolution-dependent imaging effects.

Second, the relatively small sample size (n = 33) may limit the generalizability of the results and reduce statistical power for detecting subtle inter-device differences. Larger studies incorporating multimodal imaging and longitudinal follow-up are needed to confirm the biological relevance and clinical implications of these observations.

Finally, this study included only patients with FECD. As a result, the observed inter-device differences may not be directly generalizable to other corneal pathologies. Further investigations across a broader spectrum of corneal disorders are required to determine whether similar performance differences are present in other clinical contexts.

Conclusions

The REVO HR demonstrated superior sensitivity and reliability in the detailed assessment of corneal microstructures, making it a more effective imaging tool for diagnosing and monitoring FECD. Its enhanced resolution and higher inter-operator agreement allowed for improved visualization of diagnostically significant features such as Bowman's layer, Descemet's membrane, and epithelial basal regions, which are critical for early disease detection. The findings of this study support the REVO HR as the preferred OCT device in clinical settings where precision and consistency are essential. Moreover, the observed systematic differences between the REVO HR and FC130 underscore the importance of using the same imaging platform consistently in clinical follow-up and longitudinal studies, as switching between devices may compromise diagnostic accuracy and interfere with disease monitoring and treatment evaluation.