Abstract
Objective
The new generation high-resolution OCT (HR-OCT) offers higher axial resolution compared to standard spectral-domain OCT (SD-OCT). This study aimed to determine whether potential differences in the segmentation of retinal layers in the macula with the 2 techniques could lead to clinically meaningful differences with implications for monitoring progression when patients are switched to HR-OCT.
Design
Prospective cross-sectional study.
Subjects
This study included glaucoma patients and healthy control subjects.
Methods
Each eye underwent SD-OCT followed by HR-OCT, with both macular scan patterns acquired at the same transverse location. Automated segmentation was applied and the thickness of 6 individual retinal layers calculated for 1024 A-scans for each of 97 B-scans. Intradevice difference was also assessed with repeated scans.
Main Outcome Measures
Differences in retinal layer thickness measurements between SD-OCT and HR-OCT.
Results
A total of 68 eyes (both eyes of 17 glaucoma patients and 17 healthy control subjects) underwent imaging. Mean differences in retinal layer thickness between SD-OCT and HR-OCT ranged from –2.65 to 2.02 μm. Hyper-reflective layers were thicker with SD-OCT, while hyporeflective layers were thicker with HR-OCT, showing an alternating pattern in interdevice differences in thickness measurements. Intradevice differences in thickness measurements, evaluated in a subset of 10 eyes of 5 participants, were within ± 1 μm. Image quality was not an important predictor of the interdevice thickness differences (R2 < 0.08).
Conclusions
Interdevice differences in retinal layer thickness were small but consistent. The alternating pattern is likely due to the lower axial resolution of SD-OCT making hyper-reflective layer borders blurred and consequently thicker. For follow-up, patients can be switched to HR-OCT from SD-OCT; however, depending on the magnitude of change required for detection, the differences between the 2 techniques could potentially mask or masquerade change.
Financial Disclosure(s)
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Keywords: Retinal thickness, Optical coherence tomography (OCT), Spectral-domain OCT, High-resolution OCT
OCT enables visualization and accurate thickness measurement of retinal layers, supporting detection and monitoring of optic neuropathies and retinal diseases.1,2 Since its introduction into clinical practice, OCT has significantly advanced, providing higher axial resolution, faster image acquisition, and higher signal-to-noise ratio, thereby enhancing its clinical applicability.3
The newly developed prototype high-resolution OCT (HR-OCT) (Spectralis High-Res OCT, Heidelberg Engineering GmbH) is based on spectral-domain technology and offers superior axial resolution (<3 μm) compared with standard spectral-domain OCT (SD-OCT).4,5 This improvement allows more detailed visualization of retinal structures and vasculature. While both devices are based on SD-OCT technology, for clarity, we refer to SD-OCT and HR-OCT.
The thickness of an imaged retinal layer is determined by segmentation algorithms that rely on optical density differences between adjacent layers, which depend on axial resolution.6,7 Given the higher axial resolution of HR-OCT compared with SD-OCT, layer segmentations could vary and cause discrepancies in thickness measurements. However, the impact of the higher axial resolution of HR-OCT on retinal layer segmentation is not yet fully understood. A few studies on HR-OCT have focused on assessing the visibility of outer retinal lesions,8,9 while one study evaluated retinal layer segmentation using HR-OCT, primarily comparing its reliability and accuracy with SD-OCT.10
The study aimed to quantify retinal layer thickness differences between SD-OCT and HR-OCT in the macula and estimate the potential clinical significance of switching to the newer technology.
Methods
The present study involved participants from several observational studies conducted at the Eye Care Centre of Nova Scotia Health in Halifax, Nova Scotia, Canada. The study adhered to the tenets of the Declaration of Helsinki and was approved by the Nova Scotia Health Ethics Review Board. All participants met the eligibility criteria and provided written consent to participate in the study.
Study Participants
Participants included glaucoma patients from the Eye Care Centre at Nova Scotia Health in Halifax, Canada and healthy subjects. Individuals aged ≥18 years were invited to participate and were consecutively enrolled. Exclusion criteria included (1) eyes in either group with a refractive error exceeding ± 6.00 diopters (D) sphere or ± 3.00 D of astigmatism and (2) eyes with macular diseases that could impede retinal layer segmentation. If eligible, OCT scans were performed on both eyes of each participant and included in the analysis.
Imaging Devices
Standard SD-OCT scans were obtained with the Spectralis OCT2 (Heidelberg Engineering GmbH), while HR-OCT scans were obtained with the prototype HR-OCT device (Fig 1). Both modalities operate on the principles of spectral-domain technology; however, HR-OCT has higher axial resolution: 3 μm compared with 7 μm with SD-OCT.5,11 This improvement in HR-OCT compared with SD-OCT is achieved by increasing spectral bandwidth (137 nm vs. 50 nm), shortening the central wavelength (840–853 nm vs. 880 nm), and using a higher laser power (2.2 mW vs. 1.2 mW).4,5
Figure 1.
Horizontal macular B-scan images at the same transverse location obtained with standard spectral-domain OCT (SD-OCT) and high-resolution OCT (HR-OCT) illustrating differences in axial resolution and clarity of retinal layer visualization with HR-OCT.
OCT Imaging of the Macula
OCT volume scans, 20° × 20° centered on the fovea, were acquired. Each scan volume comprised 97 B-scans, with 1024 A-scans per B-scan, each averaged 10 times. All B-scans were manually reviewed to assess image quality. Scans judged to be of poor quality, usually those that were truncated at the edges of the B-scan, were excluded. Additionally, only scans with an image quality score >20 (on a scale from 0 [poor] to 40 [excellent]) were included in the analysis.
Pairing of SD-OCT and HR-OCT Scans
All participants underwent macular imaging with SD-OCT immediately followed with HR-OCT. The SD-OCT scan was performed first and then imported into the HR-OCT device software and set as the baseline reference image. Using the follow-up mode for image acquisition (TruTrack, Heidelberg Engineering), the HR-OCT image was then obtained in precisely the same transverse location to enable direct comparison of the 2 devices.
Automated Segmentation and Manual Correction
Automated segmentation was applied to both SD-OCT and HR-OCT scans using the device software (Heidelberg Eye Explorer, version 1.10.4.0, Spectralis SP-X1904, Heidelberg Engineering). All layers from the internal limiting membrane to the external border of the outer nuclear layer were segmented to derive the retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), inner plexiform layer, inner nuclear layer, outer plexiform layer, and outer nuclear layer. Layer segmentation in each B-scan was manually checked for accuracy by a single trained observer (SUB), and corrections were made when necessary. All B-scans were viewed with the device software, and no transformations and contrast or brightness adjustments were made. To minimize potential bias from manual intervention, manual correction was intentionally limited and applied only in cases of obvious inaccuracies where correction was deemed essential.
Layer Thickness Extraction and Processing
The thickness of each segmented layer in each A-scan was exported using the device software (Spectralis Layer Segmentation Export Special Function, Heidelberg Eye Explorer, Heidelberg Engineering). As a result, each segmentation boundary represented a vector of pixel values corresponding to the vertical positions of the boundaries.
To calculate the thickness of a specific retinal layer, the vertical distance between its upper and lower segmentation boundaries was measured (Fig S2, available at www.ophthalmologyscience.org). These values, initially expressed in pixels, were converted to micrometers with the following pixel-micrometer conversion factor according to different scaling between the devices.12 For SD-OCT, each A-scan comprised 496 pixels over a scan depth of 1.9 mm resulting in an axial resolution of 3.8 μm/pixel. For HR-OCT, the values were 992 pixels over 1.9 mm resulting in an axial resolution of 1.9 μm per pixel.13 For both SD-OCT and HR-OCT, the scan width was 5.9 mm (for 1024 pixels) resulting in a transverse resolution of 5.8 μm/pixel.
Intradevice Difference
Differences in thickness measurements between SD-OCT and HR-OCT were compared to test-retest variability by determining intradevice variability. For this purpose, 10 eyes of 5 participants, including both glaucoma patients and healthy subjects, had repeated scans with both SD-OCT (SD-OCT1 vs. SD-OCT2) and HR-OCT (HR-OCT1 vs. HR-OCT2).
Statistical Analysis
Where appropriate, data were summarized as mean (standard deviation) or median (interquartile range [IQR]). For the comparative analysis between devices, the mean thickness of each retinal layer for each participant was calculated using 1024 thickness measurements per layer.
A Bland-Altman analysis was conducted to assess whether the thickness differences between devices were dependent on the average values of the 2 devices. The 95% limits of agreement were also computed. Differences in thickness and image quality scores between the 2 devices were evaluated using paired t tests. The relationship between thickness difference and image quality was assessed using Pearson correlation coefficient, with the strength of association expressed as the coefficient of determination (R2).
All statistical analyses were conducted using SPSS Statistics (version 27 for Macintosh, IBM Corp) and MedCalc Statistical Software (version 22.014, MedCalc Software Ltd, Ostend, Belgium; https://www.medcalc.org; 2023). A P value of <0.05 was considered statistically significant.
Results
A total of 34 individuals consented to participate in the study. Three (4%) eyes were excluded: 2 due to epiretinal membrane involving the macula and 1 due to myopic degeneration causing significant segmentation errors. Consequently, 65 eyes of 34 participants were included in the final analysis: 31 eyes of 17 glaucoma patients and 34 eyes of 17 healthy subjects. The median age of the participants was 69 (IQR: 61–75) years and 18 (53%) participants were female. The median refractive error was –0.33 (IQR: –1.70 to 0.50) D. Demographic and clinical characteristics of the study participants are shown in Table 1, while details and frequency of manual corrections to layer segmentations are summarized in Table S2 (available at www.ophthalmologyscience.org).
Table 1.
Demographics and Clinical Characteristics of the Study Participants
| Glaucoma Patients (31 Eyes of 17 Patients) | Healthy Subjects (34 Eyes of 17 Subjects) | |
|---|---|---|
| Age (yr) | 74 (68–77) | 60 (42–74) |
| Sex (M/F) | 11/6 | 5/12 |
| Race | ||
| White | 15 | 16 |
| Asian | 2 | 1 |
| Refractive error (D) | –0.58 (–1.20 to 0.42) | –0.30 (–1.75 to 0.58) |
| Visual field MD (dB) | –6.49 (–10.93 to –2.68) | –1.00 (–1.80 to –0.19) |
D = diopters; F = female, M = male; MD = mean deviation.
Values are presented as median (interquartile range).
Bland-Altman plots showing the differences in retinal layer thickness measurements between SD-OCT and HR-OCT are shown in Figure 3. The mean differences ranged from –2.65 to 2.02 μm and are summarized for each layer in Table 3.
Figure 3.
Bland-Altman plots comparing retinal layer thickness measurements between SD-OCT and HR-OCT. (A–F), Differences in thickness (SD-OCT – HR-OCT) are plotted against the mean thickness for all 6 segmented layers. The bold dotted line indicates 0 difference, the solid line the mean difference, and the faint dashed lines the limits of agreement (± 1.96 SD of the mean difference in thickness). GCL = ganglion cell layer; HR-OCT = high-resolution OCT; INL = inner nuclear layer; IPL = inner plexiform layer; ONL = outer nuclear layer; OPL = outer plexiform layer; RNFL = retinal nerve fiber layer; SD = standard deviation; SD-OCT = spectral-domain OCT.
Table 3.
Differences Between SD-OCT and HR-OCT Thickness Measurements
| Layer | Mean Difference (SD-OCT – HR-OCT) (μm) | 95% Confidence Interval of the Mean (μm) | Limits of Agreement (μm) |
|---|---|---|---|
| RNFL | 2.02 | 1.64–2.40 | –6.85 to 10.90 |
| GCL | –1.10 | –1.47 to –0.62 | –11.04 to 8.84 |
| IPL | 0.43 | 0.09–0.77 | –10.02 to 10.90 |
| INL | –2.65 | –3.11 to –2.15 | –16.13 to 10.83 |
| OPL | 0.99 | 0.42–1.54 | –12.51 to 14.49 |
| ONL | –1.73 | –2.21 to –1.27 | –11.72 to 8.25 |
| ILM – ELM | –2.05 | –2.08 to –2.02 | –9.32 to 5.21 |
ELM = external limiting membrane; GCL = ganglion cell layer; HR-OCT = high-resolution OCT; ILM = inner limiting membrane; INL = inner nuclear layer; IPL = inner plexiform layer; ONL = outer nuclear layer; OPL = outer plexiform layer; RNFL = retinal nerve fiber layer; SD-OCT = spectral-domain OCT.
Positive mean differences (SD-OCT – HR-OCT) in thickness indicated that HR-OCT measurements were thinner than with SD-OCT, whereas negative values indicated the opposite. Hyper-reflective layers (i.e., RNFL, inner plexiform layer, and outer nuclear layer) appeared thicker with SD-OCT, while hyporeflective layers (i.e., GCL, inner nuclear layer, and outer nuclear layer) appeared thicker with HR-OCT, demonstrating an alternating pattern of interdevice discrepancy across retinal layers. The 95% confidence interval of the mean difference in thickness did not straddle 0 in either of the 3 hyper-reflective layers or the 3 hyporeflective layers (Table 3).
Intradevice variability was conducted in 10 eyes (1 glaucoma patient and 4 healthy control subjects). Figure 4 shows interdevice (SD-OCT – HR-OCT) and intradevice (SD-OCT1 – SD-OCT2, HR-OCT1 – HR-OCT2) comparisons. The alternating pattern of interdevice thickness differences was absent in intradevice differences. The mean intradevice differences ranged from –0.21 to 0.36 μm for SD-OCT and –0.89 to 0.98 μm for HR-OCT (Table S4, available at www.ophthalmologyscience.org).
Figure 4.
Box-and-whisker plots of differences in retinal layer thickness measurements. A, Interdevice difference (SD-OCT – HR-OCT), (B) intradevice difference (SD-OCT1 – SD-OCT2), and (C) intradevice difference (HR-OCT1 – HR-OCT2). Boxes indicate the 25th to 75th percentiles; horizontal lines indicate medians and whiskers denote the minimum and maximum values. GCL = ganglion cell layer; HR-OCT = high-resolution OCT; INL = inner nuclear layer; IPL = inner plexiform layer; ONL = outer nuclear layer; OPL = outer plexiform layer; RNFL = retinal nerve fiber layer; SD-OCT = spectral-domain OCT.
The mean (standard deviation) image quality difference between SD-OCT and HR-OCT was 0.7 dB (median: 1 dB; IQR: –2 to 3 dB), which was not statistically significant (P = 0.12; Table S5, available at www.ophthalmologyscience.org). The relationship between image quality and retinal layer thickness differences between SD-OCT and HR-OCT was weak, with all layers showing low coefficients of determination (R2 < 0.08; Fig S5, available at www.ophthalmologyscience.org). There was also no relationship between visual field mean deviation in glaucoma patients and retinal layer thickness differences (Fig S6, available at www.ophthalmologyscience.org), indicating that the systematic differences in layer thickness were not impacted by glaucoma severity.
Figure 7 shows an example comparing SD-OCT and HR-OCT. Spectral-domain OCT displayed less distinct boundaries, making hyper-reflective layers (e.g., outer nuclear layer) appear thicker and hyporeflective layers (e.g., inner nuclear layer) appear thinner.
Figure 7.
Horizontal macular B-scan images at the same transverse location obtained with standard spectral-domain OCT (SD-OCT) and high-resolution OCT (HR-OCT). The SD-OCT image shows blurrier boundaries; hence, the hyper-reflective layers appear thicker (e.g., outer plexiform layer; hollow arrowheads) and the hyporeflective layers (e.g., inner nuclear layer, solid arrowheads) appear thinner.
Discussion
In this study, SD-OCT showed thicker hyper-reflective layers and thinner adjacent hyporeflective layers compared with HR-OCT, an alternating pattern likely due to its lower axial resolution. Less well-defined layer and vascular plexus boundaries with SD-OCT can overestimate the thickness of hyper-reflective layers, while HR-OCT provides sharper delineation and relatively thinner measurements in these layers. The observed pattern is likely a compensatory effect, where reduced thickness in adjacent hyper-reflective layers results in boundaries that yield thicker measurements in neighboring hyporeflective layers.
A previous study using simulated lower-resolution OCT images showed that reduced resolution led to overestimation of the thickness of the RNFL,14 a hyper-reflective layer, consistent with our findings. Other studies have similarly demonstrated that the higher resolution of HR-OCT results in a more accurate segmentation of layer boundaries,9,15 resulting in thinner measurements of hyper-reflective layers compared with SD-OCT. For example, HR-OCT showed thinner retinal pigment epithelium measurements in neovascular age-related macular degeneration due to improved separation from adjacent layers9 and smaller lesion areas and thinner vascular plexuses in pigmented choroidal lesions.15
The improved axial resolution of HR-OCT has drawn growing interest in its potential advantages over SD-OCT or swept-source OCT. Several previous studies on HR-OCT have emphasized its enhanced visualization of microstructural retinal features, such as the retinal pigment epithelium–Bruch's membrane complex9 and photoreceptor structures;8 however, they reported only qualitative assessments. Moreover, these studies largely centered on outer retinal layers. In contrast, our study also measured thickness in inner retinal layers for the applicability of HR-OCT in diseases such as glaucoma.
As HR-OCT becomes more widely used, there are several issues to consider when transitioning patients to this modality from SD-OCT in longitudinal follow-up. During this period in routine practice, patients may have to be imaged with both SD-OCT and HR-OCT, raising concerns about consistency between these 2 modalities, especially when assessing change. A glaucoma patient previously imaged with SD-OCT may return for a follow-up with HR-OCT. In such cases, apparent thinning in a hyper-reflective layer, such as the RNFL, could represent either true disease progression or differences in segmentation due to finer boundary delineation with HR-OCT. Conversely, apparent stability in the thickness of a hyporeflective layer, such as the GCL, may mask subtle pathological changes. These interpretive challenges highlight the clinical relevance of recognizing and accounting for interdevice measurement differences.
Our study found that the mean interdevice thickness differences between SD-OCT and HR-OCT were modest (within ± 3 μm across the layers) but consistently exceeded intradevice variability (less than ± 0.5 μm for SD-OCT and ± 1 μm for HR-OCT). While these differences appear small, they may be clinically meaningful. For context, prior longitudinal studies showed RNFL and GCL thinning rates of –0.46 and –0.22 μm/year, respectively, in healthy subjects and –0.55 and –0.39 μm/year, respectively, in glaucoma patients.16 Based on these average rates, a 3-μm difference, therefore, may equate to 5 to 10 years of RNFL and GCL thinning, potentially mimicking or masking true disease progression. However, these estimates are approximations and progression rates vary considerably among individuals. In glaucoma patients with more rapid progression, a 3-μm difference could equate to a much shorter period.
Interchangeability between OCT platforms has long been debated. Previous studies demonstrated poor agreement between time-domain OCT and SD-OCT17 or between SD-OCT and swept-source OCT,18 with differences large enough to preclude reliable interdevice compatibility. In contrast, our findings suggest a more favorable scenario between SD-OCT and HR-OCT. The observed agreement, combined with the higher reproducibility of HR-OCT, as shown by von der Emde et al,10 supports its use as a reliable continuation of SD-OCT–based monitoring, particularly for trend analysis over time.
In this study, the impact of image quality on thickness measurements was minimal, with weak correlations between differences in signal strength and differences in layer thickness. This supports the notion that axial resolution, and not image quality, is an important factor influencing our findings. This aligns with previous findings demonstrating that while degradation of signal strength can affect thickness measurements, variations within acceptable image quality ranges generally produce only minor, clinically insignificant differences.19 However, because we excluded images with an image quality score of ≤20, a stronger relationship between image quality and thickness measurement may have been uncovered if we did not have an exclusion criterion based on image quality. Additionally, it should be noted that while image quality had minimal impact on the measurements made in this study, a previous report noted dependence of image quality on deeper structures such as the external limiting membrane descent when segmenting geographic atrophy.20
This study did not include peripapillary retinal layer thickness measurements, which are clinically important in glaucoma evaluation. To date, the HR-OCT software cannot perform automated segmentation in radial scans which are typically acquired for measuring retinal layer thickness. Additionally, our findings are limited to glaucoma patients, in whom disease severity did not have an impact on differences in layer thickness between the 2 devices, and healthy subjects, restricting generalizability to other retinal pathologies. Finally, while obvious segmentation errors were corrected, subtle inaccuracies, especially at poorly defined boundaries, may have remained.
Conclusions
Our study did not show full interchangeability of retinal layer thickness measurements between SD-OCT and HR-OCT. However, the consistent, resolution-related differences across layers suggest that, with clinical awareness, HR-OCT may serve as a reasonable continuation of SD-OCT–based imaging. We propose that SD-OCT and HR-OCT are conditionally compatible for follow-up, provided segmentation-related thickness differences are appropriately considered.
Manuscript no. XOPS-D-25-01065.
Footnotes
Supplemental material available atwww.ophthalmologyscience.org.
Disclosure(s):
All authors have completed and submitted the ICMJE disclosures form.
The authors made the following disclosures:
B.C.C.: All support for the present manuscript – Heidelberg Engineering: Dalhousie University/Nova Scotia Health.
HUMAN SUBJECTS: Human subjects were included in this study. The study adhered to the tenets of the Declaration of Helsinki and was approved by the Nova Scotia Health Ethics Review Board. All participants met the eligibility criteria and provided written consent to participate in the study.
No animal subjects were included in this study.
Author Contributions:
Conception and design: Baek, Sharpe, Chauhan.
Analysis and interpretation: Baek, Chauhan.
Data collection: Baek, Sharpe, Shuba, Nicolela, Chauhan.
Obtained funding: Chauhan.
Overall responsibility: Chauhan.
Analysis and interpretation: Baek, Chauhan.
Supplementary Data
References
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