Comparison of retinal nerve fiber layer thickness measurement bias and imprecision across three spectral-domain optical coherence tomography devices

Normative Data and Conversion Equation for Spectral-Domain Optical Coherence Tomography in an International Healthy Control Cohort

BACKGROUND

Spectral-domain (SD-) optical coherence tomography (OCT) can reliably measure axonal (peripapillary retinal nerve fiber layer [pRNFL]) and neuronal (macular ganglion cell + inner plexiform layer [GCIPL]) thinning in the retina. Measurements from 2 commonly used SD-OCT devices are often pooled together in multiple sclerosis (MS) studies and clinical trials despite software and segmentation algorithm differences; however, individual pRNFL and GCIPL thickness measurements are not interchangeable between devices. In some circumstances, such as in the absence of a consistent OCT segmentation algorithm across platforms, a conversion equation to transform measurements between devices may be useful to facilitate pooling of data. The availability of normative data for SD-OCT measurements is limited by the lack of a large representative world-wide sample across various ages and ethnicities. Larger international studies that evaluate the effects of age, sex, and race/ethnicity on SD-OCT measurements in healthy control participants are needed to provide normative values that reflect these demographic subgroups to provide comparisons to MS retinal degeneration.

METHODS

Participants were part of an 11-site collaboration within the International Multiple Sclerosis Visual System (IMSVISUAL) consortium. SD-OCT was performed by a trained technician for healthy control subjects using Spectralis or Cirrus SD-OCT devices. Peripapillary pRNFL and GCIPL thicknesses were measured on one or both devices. Automated segmentation protocols, in conjunction with manual inspection and correction of lines delineating retinal layers, were used. A conversion equation was developed using structural equation modeling, accounting for clustering, with healthy control data from one site where participants were scanned on both devices on the same day. Normative values were evaluated, with the entire cohort, for pRNFL and GCIPL thicknesses for each decade of age, by sex, and across racial groups using generalized estimating equation (GEE) models, accounting for clustering and adjusting for within-patient, intereye correlations. Change-point analyses were performed to determine at what age pRNFL and GCIPL thicknesses exhibit accelerated rates of decline.

RESULTS

The healthy control cohort (n = 546) was 54% male and had a wide distribution of ages, ranging from 18 to 87 years, with a mean (SD) age of 39.3 (14.6) years. Based on 346 control participants at a single site, the conversion equation for pRNFL was Cirrus = -5.0 + (1.0 × Spectralis global value). Based on 228 controls, the equation for GCIPL was Cirrus = -4.5 + (0.9 × Spectralis global value). Standard error was 0.02 for both equations. After the age of 40 years, there was a decline of -2.4 μm per decade in pRNFL thickness ( P < 0.001, GEE models adjusting for sex, race, and country) and -1.4 μm per decade in GCIPL thickness ( P < 0.001). There was a small difference in pRNFL thickness based on sex, with female participants having slightly higher thickness (2.6 μm, P = 0.003). There was no association between GCIPL thickness and sex. Likewise, there was no association between race/ethnicity and pRNFL or GCIPL thicknesses.

CONCLUSIONS

A conversion factor may be required when using data that are derived between different SD-OCT platforms in clinical trials and observational studies; this is particularly true for smaller cross-sectional studies or when a consistent segmentation algorithm is not available. The above conversion equations can be used when pooling data from Spectralis and Cirrus SD-OCT devices for pRNFL and GCIPL thicknesses. A faster decline in retinal thickness may occur after the age of 40 years, even in the absence of significant differences across racial groups.

A Metascore of Multiple Imaging Methods to Measure Long-Term Glaucoma Structural Progression

Purpose

To develop a structural metascore (SMS) that combines measurements from different devices and expresses them on a single scale to facilitate their long-term analysis.

Methods

Three structural measurements (Heidelberg Retina Tomograph II [HRT] rim area, HD-Cirrus optical coherence tomography [OCT] average retinal nerve fiber layer [RNFL] thickness, Spectralis OCT RNFL global thickness) were normalized on a scale of 0 to 100 and converted to a reference value. The resultant metascores were plotted against time. SMS performance was evaluated to predict future values (internal validation), and correlations between the average grades assigned by three clinicians were compared with the SMS slopes (external validation).

Results

The linear regression fit with the variance approach, and adjustment to a Spectralis equivalent was the best-performing approach; this was denominated metascore. Plots were created for 3416 eyes of 1824 patients. The average baseline age (± standard deviation) was 69.8 (±13.9), mean follow-up was 11.6 (±4.7) years, and mean number of structural scans per eye was 10.0 (±4.7). The mean numbers of scans per device were 3.8 (±2.5), 5.0 (±2.9), and 1.3 (±3.0) for HRT, Cirrus, and Spectralis, respectively. The metascore slopes' median was -0.3 (interquartile range 1.1). Correlations between the average grades assigned by the three clinicians and the metascore slopes were -0.51, -0.49, and -0.69 for the first (structural measurement printouts alone), second (metascore plots alone), and third (printouts + metascore plots) series of gradings, respectively. The average absolute predictive ability was 7.63/100 (whereas 100 = entire normalized scale).

Conclusions

We report a method that converts Cirrus global RNFL and HRT global rim area normalized measurements to Spectralis global RNFL equivalent values to facilitate long-term structural follow-up.

Translational Relevance

Because glaucoma changes usually occur slowly, patients are often examined with different instruments during their follow-up, a method that "unifies" structural measurements provided by different devices, which could assist patients' longitudinal structural follow-up.

Retinal Nerve Fiber Layer Thickness and Rim Area Profiles in Asians: Pooled Analysis from the Asian Eye Epidemiology Consortium

PURPOSE

To evaluate ethnic variations, ocular and systemic determinants of retinal nerve fibre layer (RNFL) thickness and neuroretinal rim area among Asians, using a large consortium of population-based eye studies.

DESIGN

Cross-sectional pooled-analysis.

PARTICIPANTS

22436 participants (22436 eyes) from 10 population-based studies (China, Hong Kong, India, Japan, Russia and Singapore) of the Asian Eye Epidemiology Consortium.

METHODS

Participants aged ≥40 years without glaucoma were included. All participants underwent spectral domain optical coherence tomography (OCT) imaging, systemic and ocular examinations. Data were pooled from each study. Multivariable regression analysis was performed to evaluate inter-ethnic, inter-machine variations, ocular and systemic factors associated with RNFL thickness and rim area, adjusting for age, gender, diabetes, intraocular pressure (IOP), spherical equivalent (SE), ethnicity, OCT model, and study group. When evaluating body mass index, smoking, and hypertension as exposures, these factors were additionally adjusted in the model.

MAIN OUTCOME MEASURE

Average RNFL thickness (μm) and rim area (mm²) RESULTS: Indian and Japanese eyes showed thinner RNFL, compared to other Asian ethnicities (β values ranging 7.31-12.76μm, P<0.001 for all pair-wise comparisons). Compared to measurements by Cirrus HD-OCT, RNFL was on average 7.29μm thicker when measured by Spectralis, 12.85μm thicker by Nidek, and 17.48μm thicker by Optovue (all P<0.001). Additionally, older age (per decade, β=-2.70; 95% confidence interval [CI], -2.85 to -2.55), diabetes (β=-0.72; 95%CI, -1.20 to -0.24), ), higher IOP (per mmHg, β=-0.07; 95% CI, -0.10 to -0.04), more myopic SE (per dioptre, β=-1.13; 95% CI, -1.19 to -1.07), cardiovascular disease (CVD, β=-0.94; 95% CI, -1.49 to -0.40), and hypertension (β=-0.68; 95% CI, -1.04 to -0.32), were associated with thinner RNFL (all P≤0.003). Similarly, older age (β=-0.019; 95% CI, -0.028 to -0.009), higher IOP (β=-0.010; 95% CI, -0.013 to -0.008) and more myopic SE (β=-0.025; 95% CI, -0.029 to -0.021) were associated with smaller rim area (all P<0.001).

CONCLUSIONS

In this large pooled-analysis of multiple Asian population studies, Indian and Japanese eyes were observed to have thinner RNFL profiles. In addition to previously known determinants, hypertension and CVD were associated with thinner RNFL. These findings further suggest the need of ethnic-specific normative database to improve glaucoma detection.

Focal Loss Analysis of Nerve Fiber Layer Reflectance for Glaucoma Diagnosis

Purpose

To evaluate nerve fiber layer (NFL) reflectance for glaucoma diagnosis.

Methods

Participants were imaged with 4.5 × 4.5 mm volumetric disc scans using spectral-domain optical coherence tomography. The normalized NFL reflectance map was processed by an azimuthal filter to reduce directional reflectance bias caused by variation of beam incidence angle. The peripapillary area of the map was divided into 160 superpixels. Average reflectance was the mean of superpixel reflectance. Low-reflectance superpixels were identified as those with NFL reflectance below the fifth percentile normative cutoff. Focal reflectance loss was measured by summing loss in low-reflectance superpixels.

Results

Thirty-five normal, 30 preperimetric, and 35 perimetric glaucoma participants were enrolled. Azimuthal filtering improved the repeatability of the normalized NFL reflectance, as measured by the pooled superpixel standard deviation (SD), from 0.73 to 0.57 dB (P < 0.001, paired t-test) and reduced the population SD from 2.14 to 1.78 dB (P < 0.001, t-test). Most glaucomatous reflectance maps showed characteristic patterns of contiguous wedge or diffuse defects. Focal NFL reflectance loss had significantly higher diagnostic sensitivity than the best NFL thickness parameter (from map or profile): 77% versus 55% (P < 0.001) in glaucoma eyes with the specificity fixed at 99%.

Conclusions

Azimuthal filtering reduces the variability of NFL reflectance measurements. Focal NFL reflectance loss has excellent glaucoma diagnostic accuracy compared to the standard NFL thickness parameters. The reflectance map may be useful for localizing NFL defects.

Translational Relevance

The high diagnostic accuracy of NFL reflectance may make population-based screening feasible.

Impact of optical coherence tomography scan direction on the reliability of peripapillary retinal nerve fiber layer measurements

Purpose

To evaluate the intradevice repeatability and agreement for peripapillary retinal nerve fiber layer (pRNFL) measurements in healthy eyes with two different scan directions and two different number of B scans.

Methods

pRNFL was measured with a spectral domain optical coherence tomography on 54 healthy participants. Three-dimensional optic disc scans (6 mm x 6 mm) were performed on the right eye of the participants. Two repeated scans were performed in four different settings: H1: Horizontal scan with 512 A-scans x 96 B-scans; H2: Horizontal scan with 512 A-scans x 128 B-scans; V1: Vertical scan with 512 A-scans x 96 B-scans; V2: Vertical scan with 512 A-scans x 128 B-scans. The pRNFL thickness was evaluated in twelve clock-hour sector in a circle of 3.45 mm diameter centred at the optic disc. Repeatability and agreement were assessed with within subject standard deviation (Sw) and Bland-Altman test respectively.

Results

The repeatability of pRNFL measurements varied depending on the scan direction and sectors. The repeatability for the horizontal sectors were better with H1 and H2, with sector 9 having the best Sw (< 3 μm). The repeatability for the vertical sectors were better with V1 and V2 with sector 5 and 9 having the best Sw (< 4 μm). The repeatability with vertical scan was more symmetric among the sectors than with horizontal scans. The repeatability metrics of the sectors did not vary much between H1 and H2 (difference < 2 μm) and between V1 and V2 (difference < 3.2 μm). Comparing horizontal and vertical scans, the vertical sectors had larger limits of agreement of about 45 μm.

Conclusion

The reliability of the pRNFL thickness measurements is dependent on the direction of the scan and independent on the numbers of B-scans. Vertical scans for pRNFL gives more homogeneous repeatability across the different sectors.

Remodeling of Retinal Microcirculation Is Associated With Subclinical Arterial Injury in Hypertensive Children

[Figure: see text].

Early Glaucoma Discrimination Index

PURPOSE

To develop a new structural algorithm derived from optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) thickness and asymmetry and validate it as a discriminate among normal, suspect, and early primary open-angle glaucoma (POAG).

STUDY DESIGN

A case-controlled observational clinical study.

MATERIALS AND METHODS

In total, 150 subjects (299 eyes) were selected, 61 normal, 46 suspect, and 43 early glaucoma, from Al-Azhar University Hospitals. They were in fifth decade and free from any ocular or systemic diseases affecting the retinal nerve fiber layer. They were investigated by two consecutive perimetry (1 month apart), and three scans of circumpapillary retinal nerve fiber layer (cpRNFL) by using Nidek spectral domain (SD)-OCT 3000 Lite. The cpRNFL thickness (cpRNFLT) and inter-eye asymmetry parameters were analyzed among the three groups. Then some selected parameters were selected and analyzed using a binary logistic regression analysis for developing the new algorithm. The new algorithm was tested for the best fitting, accuracy, and diagnostic ability among the three groups and was validated in the suspect group.

RESULTS

The new algorithm model [early glaucoma discrimination index (EGDI)] works well with only four variables; whole cpRNFLT, inferior quadrant cpRNFLT, inferotemporal clock hour (CH) cpRNFLT, and absolute inter-eye inferior quadrants asymmetry. The highest area under the curve (AUC) obtained from the EGDI among the three groups was 0.854. The validation analysis in the suspect group revealed a higher diagnostic ability in discrimination of early glaucoma with AUC of 0.989 (0.976-1.003).

CONCLUSION

The EGDI showed better diagnostic ability for diagnosis of glaucoma in the pre-perimetric stage. The new OCT algorithm is simple and can be run in any SD-OCT device without dependence on normative data.

HOW TO CITE THIS ARTICLE

Safwat H, Nassar E, Rashwan A. Early Glaucoma Discrimination Index. J Curr Glaucoma Pract 2020;14(1):16-24.

Comparison of a commercial spectral-domain OCT and swept-source OCT based on an angiography scan for measuring circumpapillary retinal nerve fibre layer thickness

Background/aims

To assess the agreement in measuring retinal nerve fibre layer (RNFL) thickness between spectral-domain (SD; Cirrus HD, Carl Zeiss Meditec, USA) optical coherence tomography (OCT) and swept-source (SS; Plex Elite 9000, Carl Zeiss Meditec) OCT using an OCT angiography (OCTA) scanning protocol.

Methods

57 participants (12 glaucomatous, 8 ocular hypertensive and 74 normal eyes) were scanned with two OCT instruments by a single experienced operator on the same day. Circumpapillary RNFL thicknesses were automatically segmented for SD-OCT and manually segmented for SS-OCTA scans. Agreement of global RNFL thickness, as well as average thickness in four quadrants was assessed using intraclass correlation coefficients (ICCs).

Results

There was excellent agreement in the inferior and superior quadrants and the global (all ICC >0.90), followed by good agreement in the temporal (ICC=0.79) and nasal (ICC=0.73) quadrants. The ICC values were similar in the subgroups except within the ocular hypertension group, where the nasal quadrant was less agreeable (ICC=0.31). SS-OCTA-derived RNFL thickness was on average 3 µm thicker than SD-OCT, particularly in the nasal (69.7±11.5 µm vs 66.3±9.3 µm; p<0.001) and temporal (75.6±13.7 µm vs 67.9±12.3 µm; p<0.001) quadrants.

Conclusions

RNFL measurements taken with SS-OCTA have good-to-excellent agreement with SD-OCT, which suggests that the RNFL thickness can be sufficiently extracted from wide-field OCTA scans.

Decreased Retinal Thickness in Type 1 Diabetic Children with Signs of Nonproliferative Diabetic Retinopathy

The retina functions as a neurovascular unit. How early vascular alterations affect neuronal layers remains controversial; early vascular failure could lead to edema increasing retinal thicknesses, but alternatively neuronal loss could lead to reduced retinal thickness. Objective. To evaluate retinal thickness in a cohort of pediatric patients with type 1 diabetes mellitus (PwT1DM) and to analyze differences according to the presence or absence of nonproliferative diabetic retinopathy (NPDR), poor metabolic control, and diabetes duration. Patients and Methods. We performed retinographies and optical coherence tomography (OCT) (TOPCON 3D1000®) to PwT1DM followed at our center and healthy controls. Measurements of the control group served to calculate reference values. Results. 59 PwT1DM (age 12.51 ± 2.59) and 22 healthy controls (age 10.66 ± 2.51) volunteered. Only two PwT1DM, both adolescents with poor metabolic control, presented NPRD. Both showed decreased thicknesses and retinal volumes. The odds ratio of having decreased retinal thickness when signs of NPDR were present was 11.72 (95% IC 1.16-118.28; p = 0.036). Conclusions. PwT1DM with NPDR have increased odds of decreased retinal thicknesses and volumes. Whether these changes are reversible by improving metabolic control or not remains to be elucidated.

Central Corneal Thickness Reproducibility among Ten Different Instruments

PURPOSE

To assess agreement between one ultrasonic (US) and nine optical instruments for the measurement of central corneal thickness (CCT), and to evaluate intra- and inter-operator reproducibility.

METHODS

In this observational cross-sectional study, two masked operators measured CCT thickness twice in 28 healthy eyes. We used seven spectral-domain optical coherence tomography (SD-OCT) devices, one time-domain OCT, one Scheimpflug camera, and one US-based instrument. Inter- and intra-operator reproducibility was evaluated by intraclass correlation coefficient (ICC), coefficient of variation (CV), and Bland-Altman test analysis. Instrument-to-instrument reproducibility was determined by ANOVA for repeated measurements. We also tested how the devices disagreed regarding systemic bias and random error using a structural equation model.

RESULTS

Mean CCT of all instruments ranged from 536 ± 42 μm to 577 ± 40 μm. An instrument-to-instrument correlation test showed high values among the 10 investigated devices (correlation coefficient range 0.852-0.995; p values <0.0001 in all cases). The highest correlation coefficient values were registered between 3D OCT-2000 Topcon-Spectral OCT/SLO Opko (0.995) and Cirrus HD-OCT Zeiss-RS-3000 Nidek (0.995), whereas the lowest were seen between SS-1000 CASIA and Spectral OCT/SLO Opko (0.852). ICC and CV showed excellent inter- and intra-operator reproducibility for all optic-based devices, except for the US-based device. Bland-Altman analysis demonstrated low mean biases between operators.

CONCLUSIONS

Despite highlighting good intra- and inter-operator reproducibility, we found that a scale bias between instruments might interfere with thorough CCT monitoring. We suggest that optimal monitoring is achieved with the same operator and the same device.

Thick Prelaminar Tissue Decreases Lamina Cribrosa Visibility

Purpose

Evaluation of the effect of prelaminar tissue thickness on visualization of the lamina cribrosa (LC) using optical coherence tomography (OCT).

Methods

The optic nerve head (ONH) region was scanned using OCT. The quality of visible LC microstructure was assessed subjectively using a grading system and objectively by analyzing the signal intensity of each scan's superpixel components. Manual delineations were made separately and in 3-dimensions quantifying prelaminar tissue thickness, analyzable regions of LC microstructure, and regions with a visible anterior LC (ALC) boundary. A linear mixed effect model quantified the association between tissue thickness and LC visualization.

Results

A total of 17 healthy, 27 glaucoma suspect, and 47 glaucomatous eyes were included. Scans with thicker average prelaminar tissue measurements received worse grading scores (P = 0.007), and superpixels with low signal intensity were associated significantly with regions beneath thick prelaminar tissue (P < 0.05). The average prelaminar tissue thickness in regions of scans where the LC was analyzable (214 μm) was significantly thinner than in regions where the LC was not analyzable (569 μm; P < 0.001). Healthy eyes had significantly thicker average prelaminar tissue measurements than glaucoma or glaucoma suspect eyes (both P < 0.001), and glaucoma suspect eyes had significantly thicker average prelaminar tissue measurements than glaucoma eyes (P = 0.008). Significantly more of the ALC boundary was visible in glaucoma eyes (63% of ONH) than in healthy eyes (41%; P = 0.005).

Conclusions

Thick prelaminar tissue was associated with impaired visualization of the LC. Healthy subjects generally had thicker prelaminar tissue, which potentially could create a selection bias against healthy eyes when comparing LC structures.

Automated Retinal Layer Segmentation Using Spectral Domain Optical Coherence Tomography: Evaluation of Inter-Session Repeatability and Agreement between Devices

Retinal and intra-retinal layer thicknesses are routinely generated from optical coherence tomography (OCT) images, but on-board software capabilities and image scaling assumptions are not consistent across devices. This study evaluates the device-independent Iowa Reference Algorithms (Iowa Institute for Biomedical Imaging) for automated intra-retinal layer segmentation and image scaling for three OCT systems. Healthy participants (n = 25) underwent macular volume scans using a Cirrus HD-OCT (Zeiss), 3D-OCT 1000 (Topcon), and a non-commercial long-wavelength (1040nm) OCT on two occasions. Mean thickness of 10 intra-retinal layers was measured in three ETDRS subfields (fovea, inner ring and outer ring) using the Iowa Reference Algorithms. Where available, total retinal thicknesses were measured using on-board software. Measured axial eye length (AEL)-dependent scaling was used throughout, with a comparison made to the system-specific fixed-AEL scaling. Inter-session repeatability and agreement between OCT systems and segmentation methods was assessed. Inter-session coefficient of repeatability (CoR) for the foveal subfield total retinal thickness was 3.43μm, 4.76μm, and 5.98μm for the Zeiss, Topcon, and long-wavelength images respectively. For the commercial software, CoR was 4.63μm (Zeiss) and 7.63μm (Topcon). The Iowa Reference Algorithms demonstrated higher repeatability than the on-board software and, in addition, reliably segmented all 10 intra-retinal layers. With fixed-AEL scaling, the algorithm produced significantly different thickness values for the three OCT devices (P<0.05), with these discrepancies generally characterized by an overall offset (bias) and correlations with axial eye length for the foveal subfield and outer ring (P<0.05). This correlation was reduced to an insignificant level in all cases when AEL-dependent scaling was used. Overall, the Iowa Reference Algorithms are viable for clinical and research use in healthy eyes imaged with these devices, however ocular biometry is required for accurate quantification of OCT images.

Effect of Spectral Domain Optical Coherence Tomography Image Quality on Macular Thickness Measurements and Error Rate

PURPOSE

To evaluate the effect of Topcon spectral domain optical coherence tomography (OCT) image quality on macular thickness measurements and the error rate in healthy subjects and patients with clinically significant diabetic macular edema (CSME).

METHODS

In this prospective, comparative case series, macular thickness measurements, and the rate of decentration and segmentation errors were evaluated before and after reducing the image quality factor (QF). The measurements were evaluated again after correcting the decentration and segmentation errors. To reduce the image QF below 45, tetracycline eye ointment was applied on the corneal surface.

RESULTS

Forty eyes of 40 subjects including 18 healthy eyes and 22 eyes with CSME were included. In both groups, the difference in central subfield thickness measurements before and after reducing the image QF was not statistically significant both before and after error correction (all P>0.05). The rate of decentration error was statistically similar before and after reducing image QF in normal and CSME eyes (P=0.50, P=0.69, respectively). However, the rate of segmentation error was statistically significantly higher after reducing image QF both in normal and CSME eyes (P=0.008 and P=0.004, respectively). In both groups, eyes with a segmentation error had higher image QF reduction (both P=0.01).

CONCLUSION

Reducing image quality results in a higher rate of the segmentation error in normal eyes and in eyes with CSME.

Comparison of the Abilities of SD-OCT and SS-OCT in Evaluating the Thickness of the Macular Inner Retinal Layer for Glaucoma Diagnosis

Purpose

To compare the abilities of spectral-domain optical coherence tomography (OCT) (SD-OCT; Spectralis, Heidelberg Engineering) and swept-source OCT (SS-OCT; DRI-OCT1 Atlantis system, Topcon) for analyzing the macular inner retinal layers in diagnosing glaucoma.

Methods

The study included 60 patients with primary open-angle glaucoma (POAG) and 60 healthy control subjects. Macular cube area was scanned using SD-OCT and SS-OCT on the same day to assess the thicknesses of the macular retinal nerve fiber layer (mRNFL), ganglion cell layer plus inner plexiform layer (GCIPL), and total retinal layer in nine subfields defined by the Early Treatment Diabetic Retinopathy Study (ETDRS). The abilities of the parameters to discriminate between the POAG and control groups were assessed using areas under the receiver operating characteristic curves (AUCs).

Results

Glaucoma-associated mRNFL and GCIPL thinning was more common in the outer zones than inner zones for both SD-OCT and SS-OCT. The mRNFL and GCIPL measurements showed distinct pattern differences between SD-OCT and SS-OCT in each ETDRS subfield. Although the glaucoma-diagnosis ability was comparable between SD-OCT and SS-OCT for most of the parameters, AUC was significantly larger for SD-OCT measurements of the GCIPL thickness in the outer temporal zones (p = 0.003) and of the mRNFL thickness in the outer nasal zones (p = 0.001), with the former having the largest AUC for discriminating POAG from healthy eyes (AUC = 0.894).

Conclusion

Spectralis SD-OCT and DRI SS-OCT have similar glaucoma-diagnosis abilities based on macular inner layer thickness analysis. However, Spectralis SD-OCT was potentially superior to DRI SS-OCT in detecting GCIPL thinning in the outer temporal zone, where the glaucomatous damage predominantly occurs.

Virtual Averaging Making Nonframe-Averaged Optical Coherence Tomography Images Comparable to Frame-Averaged Images

Purpose

Developing a novel image enhancement method so that nonframe-averaged optical coherence tomography (OCT) images become comparable to active eye-tracking frame-averaged OCT images.

Methods

Twenty-one eyes of 21 healthy volunteers were scanned with noneye-tracking nonframe-averaged OCT device and active eye-tracking frame-averaged OCT device. Virtual averaging was applied to nonframe-averaged images with voxel resampling and adding amplitude deviation with 15-time repetitions. Signal-to-noise (SNR), contrast-to-noise ratios (CNR), and the distance between the end of visible nasal retinal nerve fiber layer (RNFL) and the foveola were assessed to evaluate the image enhancement effect and retinal layer visibility. Retinal thicknesses before and after processing were also measured.

Results

All virtual-averaged nonframe-averaged images showed notable improvement and clear resemblance to active eye-tracking frame-averaged images. Signal-to-noise and CNR were significantly improved (SNR: 30.5 vs. 47.6 dB, CNR: 4.4 vs. 6.4 dB, original versus processed, P < 0.0001, paired t-test). The distance between the end of visible nasal RNFL and the foveola was significantly different before (681.4 vs. 446.5 μm, Cirrus versus Spectralis, P < 0.0001) but not after processing (442.9 vs. 446.5 μm, P = 0.76). Sectoral macular total retinal and circumpapillary RNFL thicknesses showed systematic differences between Cirrus and Spectralis that became not significant after processing.

Conclusion

The virtual averaging method successfully improved nontracking nonframe-averaged OCT image quality and made the images comparable to active eye-tracking frame-averaged OCT images.

Translational Relevance

Virtual averaging may enable detailed retinal structure studies on images acquired using a mixture of nonframe-averaged and frame-averaged OCT devices without concerning about systematic differences in both qualitative and quantitative aspects.

Residual and Dynamic Range of Retinal Nerve Fiber Layer Thickness in Glaucoma: Comparison of Three OCT Platforms

PURPOSE

To estimate visual field (VF) sensitivity at which retinal nerve fiber layer (RNFL) thinning reaches the measurement floor and at which RNFL stops thinning (change points), the dynamic range of RNFL thickness, and the number of steps from normal to RNFL floor among three optical coherence tomography (OCT) devices.

METHODS

Glaucomatous patients (n = 58) and healthy subjects (n = 55-60) prospectively underwent VF testing and RNFL thickness measurement with Cirrus, Spectralis, and RTVue. Change points and corresponding RNFL thicknesses were estimated with simple linear regression (SLR) and Bayesian change point (BCP) analyses. The dynamic range and number of steps to RNFL floor were determined.

RESULTS

The average VF change points and corresponding residual thickness at the time RNFL stopped thinning were -22.2 dB and 57.0 μm (Cirrus), -25.3 dB and 49.2 μm (Spectralis), and -24.6 dB and 64.7 μm (RTVue). The RNFL dynamic ranges derived from SLR values were wider on Spectralis (52.6 μm) than on Cirrus (35.4 μm) and RTVue (35.5 μm); the corresponding number of steps to reach the RNFL floor were 9.0 on Cirrus, 10.6 on Spectralis, and 8.3 on RTVue.

CONCLUSIONS

The relative VF sensitivity at which average RNFL thickness reaches the measurement floor, the residual layer thickness, and RNFL dynamic measurement range differ among the three devices. However, the number of steps from normal to the RNFL thickness floor is comparable.

A novel retinal biomarker for Parkinson's disease: Quantifying the foveal pit with optical coherence tomography

BACKGROUND

Optical coherence tomography offers a potential biomarker tool in Parkinson's disease (PD). A mathematical model quantifying symmetry, breadth, and depth of the fovea was applied.

METHODS

Nintey-six subjects (72 PD and 24 healthy controls) were included in the study. Macular scans of each eye were obtained on two different optical coherence tomography devices: Cirrus and RTVue.

RESULTS

The variables corresponding to the cardinal gradients of the fovea were the most sensitive indicators of PD for both devices. Principal component analysis distinguished 65% of PD patients from controls on Cirrus, 57% on RTVue.

CONCLUSION

Parkinson's disease shallows the superior/inferior and to a lesser degree nasal-temporal foveal slope. The symmetry, breadth, and depth model fits optical coherence tomography data derived from two different devices, and it is proposed as a diagnostic tool in PD.

Optical Coherence Tomography (OCT) Device Independent Intraretinal Layer Segmentation

PURPOSE

To develop and test an algorithm to segment intraretinal layers irrespectively of the actual Optical Coherence Tomography (OCT) device used.

METHODS

The developed algorithm is based on the graph theory optimization. The algorithm's performance was evaluated against that of three expert graders for unsigned boundary position difference and thickness measurement of a retinal layer group in 50 and 41 B-scans, respectively. Reproducibility of the algorithm was tested in 30 C-scans of 10 healthy subjects each with the Spectralis and the Stratus OCT. Comparability between different devices was evaluated in 84 C-scans (volume or radial scans) obtained from 21 healthy subjects, two scans per subject with the Spectralis OCT, and one scan per subject each with the Stratus OCT and the RTVue-100 OCT. Each C-scan was segmented and the mean thickness for each retinal layer in sections of the early treatment of diabetic retinopathy study (ETDRS) grid was measured.

RESULTS

The algorithm was able to segment up to 11 intraretinal layers. Measurements with the algorithm were within the 95% confidence interval of a single grader and the difference was smaller than the interindividual difference between the expert graders themselves. The cross-device examination of ETDRS-grid related layer thicknesses highly agreed between the three OCT devices. The algorithm correctly segmented a C-scan of a patient with X-linked retinitis pigmentosa.

CONCLUSIONS

The segmentation software provides device-independent, reliable, and reproducible analysis of intraretinal layers, similar to what is obtained from expert graders.

TRANSLATIONAL RELEVANCE

Potential application of the software includes routine clinical practice and multicenter clinical trials.

Retinal hyperaemia-related blood vessel artifacts are relevant to automated OCT layer segmentation

A frequently observed local measurement artifact with spectral domain OCT is caused by the void signal of the retinal vasculature. This study investigated the effect of suppression of blood vessel artifacts with and without retinal hyperaemia. Spectral domain OCT scans, centred on the optic nerve head, were performed in 46 healthy subjects (92 eyes). Baseline scans were made during rest, while for the follow-up scan, 23 subjects (50 %) performed strenuous physical exercise. Systemic and retinal hyperaemia were quantified. Quantification of retinal nerve fibre layer (RNFL) thickness was performed with and without suppression of retinal blood vessel artifacts. The potential systematic effect on RNFL thickness measurements was analysed using Bland-Altman plots. At baseline (no retinal hyperaemia), there was a systematic difference in RNFL thickness (3.4 μm, limits of agreement -0.9 to 7.7) with higher values if blood vessel artifacts were not suppressed. There was significant retinal hyperaemia in the exercise group (p < 0.0001). Baseline thickness increased from 93.18 to 93.83 μm (p < 0.05) in the exercise group using the algorithm with blood vessel artifact suppression, but no significant changes were observed using the algorithm without blood vessel artifact suppression. Retinal hyperaemia leads to blood vessel artifacts which are relevant to the precision of OCT layer segmentation algorithms. The two algorithms investigated in this study can not be used interchangeably. The algorithm with blood vessel artifact suppression was more sensitive in detecting small changes in RNFL thickness. This may be relevant for the use of OCT in a range of neurodegenerative diseases were only a small degree of retinal layer atrophy have been found so far.

Signal normalization reduces systematic measurement differences between spectral-domain optical coherence tomography devices

PURPOSE

To test the effect of a novel signal normalization method for reducing systematic optical coherence tomography (OCT) measurement differences among multiple spectral-domain (SD) OCT devices.

METHODS

A total of 109 eyes from 59 subjects were scanned with two SD-OCT devices (Cirrus and RTVue) at the same visit. Optical coherence tomography image data were normalized to match their signal characteristics between the devices. To compensate signal strength differences, custom high dynamic range (HDR) processing was also applied only to images with substantially lower signal strength. Global mean peripapillary retinal nerve fiber layer (RNFL) thicknesses were then measured automatically from all images using custom segmentation software and were compared to the original device outputs. Structural equation models were used to analyze the absolute RNFL thickness difference between original device outputs and our software outputs after signal normalization.

RESULTS

The device-measured RNFL thickness showed a statistically significant difference between the two devices (mean absolute difference 10.58 μm, P < 0.05), while there was no significant difference after normalization on eyes with 62.4-μm or thicker RNFL (mean absolute difference 2.95 μm, P < 0.05).

CONCLUSIONS

The signal normalization method successfully reduces the systematic difference in RNFL thickness measurements between two SD-OCT devices. Enabling direct comparison of RNFL thickness obtained from multiple devices would broaden the use of OCT technology in both clinical and research applications.

Cirrus high-definition optical coherence tomography versus spectral optical coherence tomography/scanning laser ophthalmoscopy in the diagnosis of glaucoma

PURPOSE

This study was performed to compare the positive predictive value of peripapillary retinal nerve fiber layer (RNFL) thickness measurements obtained using Cirrus high-definition optical coherence tomography (Cirrus HD-OCT; Carl Zeiss Meditec, Dublin, CA) and spectral OCT/scanning laser ophthalmoscopy (SLO) (OPKO/OTI, Miami, FL) in the diagnosis of glaucoma.

METHODS

A total of 50 eyes of 50 healthy subjects and 60 eyes of 60 subjects with glaucoma were included. All participants underwent RNFL thickness measurement using Cirrus HD-OCT and spectral OCT/SLO on the same day. Average, quadrant, clock-hour RNFL thicknesses, area under the receiver operating characteristic curve (AUC), and sensitivities at fixed specificities (80% and 95%) were calculated for comparison.

RESULTS

RNFL thickness as measured by spectral OCT/SLO was greater than that measured using Cirrus HD-OCT (p < 0.001). For both the Cirrus HD-OCT and spectral OCT/SLO, the parameter with the largest AUC was average RNFL thickness (0.954 and 0.944, respectively). The AUCs of RNFL thickness for the discrimination of glaucoma did not differ significantly between the devices (p > 0.05), with the exception of RNFL thickness in the nasal area (nasal quadrant, clock-hour sectors 3 and 4); in these areas, spectral OCL/SLO yielded greater AUCs than Cirrus HD-OCT (p < 0.05). Sensitivities varied similarly to AUCs.

CONCLUSIONS

RNFL thicknesses measures using Cirrus HD-OCT and spectral OCT/SLO were not interchangeable. The utility of RNFL thickness measurements in the diagnosis of glaucoma was similar for both the devices.

Influence of axial length on peripapillary retinal nerve fiber layer thickness in children: a study by RTVue spectral-domain optical coherence tomography

PURPOSE

To evaluate the influence of axial length on peripapillary retinal nerve fiber layer (RNFL) thickness in myopic, hyperopic and emmetropic children eyes by RTVue optical coherence tomography (OCT).

METHODS

One hundred twenty eyes of 120 children including 40 myopic, 40 emmetropic and 40 hyperopic eyes were enrolled in the study. Peripapillary RNFL thickness measurements were performed using spectral-domain RTVue OCT (Optovue, Fremont, CA). RNFL thickness parameters were obtained from all octametric sections: upper temporal (TU), superotemporal (ST), superonasal (SN), upper nasal (NU), lower nasal (NL), inferonasal (IN), inferotemporal (IT) and lower temporal (TL). Spherical equivalent refractive error was determined via cycloplegic auto-refraction (Topcon, Tokyo, Japan). The axial length was measured using IOLMaster (Carl Zeiss MEDITEC). Littmann formula was used for correction of axial length-related ocular magnification effect.

RESULTS

Peripapillary RNFL thicknesses were significantly different among the three groups in all sectors except for NU and IT sectors. RNFL thicknesses in all sectors except for TU and TL sectors had significant negative correlations with axial length. However, these differences (excluding TU and TL sectors) and correlations disappeared after correction of magnification effect.

CONCLUSION

In conclusion, axial length influences peripapillary RNFL thickness as measured by RTVue OCT. However, this appears to be due to the ocular magnification effects associated with axial length and can be corrected for with the application of the Littman formula.

Individual A-scan signal normalization between two spectral domain optical coherence tomography devices

PURPOSE

We developed a method to normalize optical coherence tomography (OCT) signal profiles from two spectral-domain (SD) OCT devices so that the comparability between devices increases.

METHODS

We scanned 21 eyes from 14 healthy and 7 glaucoma subjects with two SD-OCT devices on the same day, with equivalent cube scan patterns centered on the fovea (Cirrus HD-OCT and RTVue). Foveola positions were selected manually and used as the center for registration of the corresponding images. A-scan signals were sampled 1.8 mm from the foveola in the temporal, superior, nasal, and inferior quadrants. After oversampling and rescaling RTVue data along the Z-axis to match the corresponding Cirrus data format, speckle noise reduction and amplitude normalization were applied. For comparison between normalized A-scan profiles, mean absolute difference in amplitude in percentage was measured at each sampling point. As a reference, the mean absolute difference between two Cirrus scans on the same eye also was measured.

RESULTS

The mean residual of the A-scan profile amplitude was reduced significantly after signal normalization (12.7% vs. 6.2%, P < 0.0001, paired t-test). All four quadrants also showed statistically significant reduction (all P < 0.0001). Mean absolute difference after normalization was smaller than the one between two Cirrus scans. No performance difference was detected between health and glaucomatous eyes.

CONCLUSIONS

The reported signal normalization method successfully reduced the A-scan profile differences between two SD-OCT devices. This signal normalization processing may improve the direct comparability of OCT image analysis and measurement on various devices.

Diagnosis of glaucoma and detection of glaucoma progression using spectral domain optical coherence tomography

PURPOSE OF REVIEW

With the rapid adoption of spectral domain optical coherence tomography (SDOCT) in clinical practice and the recent advances in software technology, there is a need for a review of the literature on glaucoma detection and progression analysis algorithms designed for the commercially available instruments.

RECENT FINDINGS

Peripapillary retinal nerve fiber layer (RNFL) thickness and macular thickness, including segmental macular thickness calculation algorithms, have been demonstrated to be repeatable and reproducible, and have a high degree of diagnostic sensitivity and specificity in discriminating between healthy and glaucomatous eyes across the glaucoma continuum. Newer software capabilities such as glaucoma progression detection algorithms provide an objective analysis of longitudinally obtained structural data that enhances our ability to detect glaucomatous progression. RNFL measurements obtained with SDOCT appear more sensitive than time domain OCT (TDOCT) for glaucoma progression detection; however, agreement with the assessments of visual field progression is poor.

SUMMARY

Over the last few years, several studies have been performed to assess the diagnostic performance of SDOCT structural imaging and its validity in assessing glaucoma progression. Most evidence suggests that SDOCT performs similarly to TDOCT for glaucoma diagnosis; however, SDOCT may be superior for the detection of early stage disease. With respect to progression detection, SDOCT represents an important technological advance because of its improved resolution and repeatability. Advancements in RNFL thickness quantification, segmental macular thickness calculation and progression detection algorithms, when used correctly, may help to improve our ability to diagnose and manage glaucoma.