Ivania Pereira

Central retinal thickness measured with HD-OCT shows a weak correlation with visual acuity in eyes with CSME

Aims To investigate the correlation between increased retinal thickness (RT) measured with spectral domain high-definition optical coherence tomography (OCT) (Cirrus HD-OCT (Carl Zeiss Meditec, Dublin, California, USA)) and best-corrected visual acuity (BCVA) in eyes with clinically significant macular oedema (CSME) and type 2 diabetes. Methods Seventy eyes with CSME were included in this observational study. Sixty-two eyes were considered for analysis and were classified as having/not having retinal thickening in the central fovea (central 500-μm-diameter circle) by Cirrus HD-OCT. RT measurements were computed and correlated with BCVA. For comparison purposes, the Stratus OCT (Carl Zeiss Meditec, Dublin, California, USA) central point thickness was also obtained in these eyes. Results In the 19 eyes with CMSE identified by Cirrus HD-OCT without increased RT in the central fovea (500-μm-diameter circle), no correlation was found between RT and BCVA (R=0.062; 95% CI −0.404 to 0.502). In the 43 eyes where the Cirrus HD-OCT identified an increased RT in the central fovea (central 500-μm-diameter circle), only a moderate correlation between RT and BCVA was found (R=−0.459; 95% CI −0.667 to −0.184). Conclusion Correlations between RT and BCVA in CSME are only present when the central 500-μm-diameter circle is involved. However, even in this circumstance, a correlation was found in only 48.8% of the cases. RT cannot, therefore, be used as a surrogate outcome for visual acuity changes.

Correlation between retinal vessel density profile and circumpapillary RNFL thickness measured with Fourier-domain optical coherence tomography.

Aim To assess circumpapillary retinal vessel density (RVD) profiles and correlate them with retinal nerve fibre layer (RNFL) thickness measured by Fourier domain optical coherence tomography (FD-OCT). Methods RNFL thickness of 106 healthy volunteers was measured using Cirrus FD-OCT. A proprietary software was developed in MATLAB to assess the thickness and position of circumpapillary retinal vessels using the scanning laser ophthalmoscopy fundus image, centred on the optic disc. The individual retinal vessel positions and thickness values were integrated in a 256-sector RVD profile, and intrasubject and intersubject correlations were calculated. Results The mean value±SD for intrasubject correlation between RVD and RNFL was 0.5349±0.1639, with 101 of 106 subjects presenting significant correlation (p<0.05). 181 (out of 256) sectors presented a significant correlation between RVD and RNFL, with a mean value±SD of 0.2600±0.1140 (p<0.05). Conclusions Using our model of the circumpapillary retinal vessel distribution, 70% of the RNFL thickness is influenced by RVD. On average, 7% of the interindividual variance of the RNFL thickness may be explained by RVD. A normative database that takes into account the circumpapillary blood vessels might slightly improve the diagnostic power of RNFL measurement.

Influence of disc-fovea angle and retinal blood vessels on interindividual variability of circumpapillary retinal nerve fibre layer.

Background To assess whether intersubject variability of circumpapillary retinal nerve fibre layer (RNFL) thickness in healthy subjects acquired with spectral domain optical coherence tomography (SD-OCT) can be reduced by considering the disc-fovea angle (DFA), either alone or together with a compensation based on retinal blood vessel distribution (RVD). Methods 106 healthy volunteers underwent SD-OCT examination centred on the optic disc (OD) and on the macula. OD contours and foveal positions were automatically calculated. RVD at 3.4 mm diameter circle was manually assessed. We made two approaches to reduce interindividual variability in RNFL values using compensation processes; RVD compensation: RNFL thickness values were compensated according to RVD variation (RNFLRVD) and DFA compensation: we shifted the RNFL thickness measurements according to the DFA (RNFLDFA). Coefficient of variance (CoV) was calculated in 12 clock hour sectors for original RNFL (RNFLo), RNFLDFA, RNFLRVD and RNFL with both compensation methods (RNFLDFA-RVD). Results Compared with the mean CoV of RNFLO, mean CoV of RNFLDFA, RNFLRVD and RNFLDFA-RVD was changed by −0.71% (p>0.05), −9.51% (p<0.001) and −7.55% (p=0.001), respectively. When compared with RNFLDFA, RNFL DFA-RVD significantly reduced the mean CoV by −6.69% (p=0.001), while compared with RNFLRVD, RNFL DFA-RVD did not significantly increase the mean CoV (+2.20%), (p>0.05). Conclusions Although reaching an improvement in some sectors, rotation of RNFL measurements according to the DFA on average does not reduce intersubject variability of RNFL. However, adjusting for RVD reduced the variance significantly. The results reinforce our work in assessing RVD as an important anatomical factor responsible for intersubject variability in RNFL measurements.

Compensation for retinal vessel density reduces the variation of circumpapillary RNFL in healthy subjects.

This work intends to assess circumpapillary retinal vessel density (RVD) at a 3.46 mm diameter circle and correlate it with circumpapillary retinal nerve fiber layer (RNFL) thickness measured with Fourier-Domain Optical Coherence Tomography. Furthermore, it aims to evaluate the reduction of intersubject variability of RNFL when considering RVD as a source of information for RNFL distribution. For that, 106 healthy subjects underwent circumpapillary RNFL measurement. Using the scanning laser ophthalmoscope fundus image, thickness and position of retinal vessels were assessed and integrated in a 256-sector RVD profile. The relationship between local RVD value and local RNFL thickness was modeled by linear regression. RNFL was then compensated for RVD variation by regression formulas. A strong statistically significant intrasubject correlation was found for all subjects between RVD and RNFL profiles (mean R = 0.769). In the intersubject regression analysis, 247 of 256 RNFL sectors showed a statistically significant positive correlation with RVD (mean R = 0.423). RVD compensation of RNFL resulted in a relative reduction of up to 20% of the intersubject variance. In conclusion, RVD in a 3.46mm circle has a clinically relevant influence on the RNFL distribution. RVD may be used to develop more individualized normative values for RNFL measurement, which might improve early diagnosis of glaucoma.

Retinal Blood Vessel Distribution Correlates With the Peripapillary Retinal Nerve Fiber Layer Thickness Profile as Measured With GDx VCC and ECC.

Purpose:Aim of the present study was to evaluate whether there is a correlation between retinal blood vessel density (RVD) and the peripapillary retinal nerve fiber layer (RNFL) thickness profile. Methods:RNFL thickness of 106 healthy subjects was measured using scanning laser polarimetry, GDx variable corneal compensation (VCC), and GDx enhanced corneal compensation (ECC). A proprietary software was developed in MATLAB to measure the peripapillary retinal vessels using scanning laser ophthalmoscopy fundus images, centered on the optic disc measured by Cirrus spectral domain optical coherence tomography. The individual retinal vessel positions and thickness values were integrated in a 64-sector RVD profile and intrasubject and intersubject correlations were calculated. Results:The mean R value±SD for intrasubject correlation between RVD and RNFL thickness measured with GDx VCC and GDx ECC was 0.714±0.157 and 0.629±0.140, with 105 of 106 subjects presenting significant correlations. In the intersubject linear regression analysis for GDx VCC, 33 of 64 (52%) sectors presented a significant Pearson correlation coefficient between RNFL thickness and RVD values, with a mean R value of 0.187±0.135 (P<0.05). Conclusions:Peripapillary RNFL thickness profiles correlate with the RVD over 50% of the sectors and might explain up to 26% of the interindividual variance of the peripapillary RNFL thickness values as measured with GDx VCC. To our opinion, taking into account RVD might reduce interindividual variation in peripapillary RNFL thickness profiles measured with scanning laser polarimetry.

Multivariate Model of the Intersubject Variability of the Retinal Nerve Fiber Layer Thickness in Healthy Subjects.

PURPOSE We present and validate a multivariate model that partially compensates for retinal nerve fiber layer (RNFL) intersubject variability. METHODS A total of 202 healthy volunteers randomly attributed to a training (TS) and a validation (VS) sample underwent complete ophthalmic examination, including Fourier-domain optical coherence tomography (FD-OCT). We acquired FD-OCT data centered at the optic disc (OD) and the macula. Two-dimensional (2D) projection images were computed and registered, to determine the distance between fovea and OD centers (FD) and their respective angle (FA). Retinal vessels were automatically segmented in the projection images and used to calculate the circumpapillary retinal vessel density (RVD) profile. Using the TS, a multivariate model was calculated for each of 256 sectors of the RNFL, including OD ratio, orientation and area, RVD, FD, FA, age, and refractive error. Model selection was based on Akaike Information Criteria. The compensation effect was determined for 12 clock hour sectors, comparing the coefficients of variation (CoV) of measured and model-compensated RNFL thicknesses. The model then was applied to the VS, and CoV was calculated. RESULTS The R value for the multivariate model was, on average 0.57 (max = 0.68). Compensation reduced the CoV on average by 18%, both for the TS and VS (up to 23% and 29%), respectively. CONCLUSIONS We have developed and validated a comprehensive multivariate model that may be used to create a narrower range of normative RNFL data, which could improve diagnostic separation between early glaucoma and healthy subjects. This, however, remains to be demonstrated in future studies.

Comparison of optic disc parameters using spectral domain cirrus high-definition optical coherence tomography and confocal scanning laser ophthalmoscopy in normal eyes.

Purpose:  To compare Cirrus HD – optical coherence tomography (HD‐OCT) with confocal scanning laser ophthalmoscopy (HRT 3) for analysis of optic disc parameters in healthy eyes.

A Functional Regression Model of the Retinal Nerve Fiber Layer Thickness in Healthy Subjects

Purpose A new functional regression model is presented to explain the intersubject variability of the circumpapillary retinal nerve fiber layer (RNFL) thickness in healthy subjects. Methods To evaluate the functional regression approach we used data from 202 healthy volunteers, divided equally into training samples (TS) and validation samples (VS). Covariates included RNFL, fovea distance, fovea angle, optic disk ratio, orientation and area provided by Fourier-domain–optical coherence tomography, age, and refractive error. Root mean square errors (RMSE) were calculated for each of the 256 sectors and for the 12 clock-hour sectors in the TS and VS and were compared to the RMSE of the previous model and the standard deviation of the raw data. Results With the functional regression approach, we were able to explain on average 27.4% of the variation in the TS and 25.1% of the variation in the VS. The new model performed better compared to a multivariate linear regression model. It performed best in the superior-temporal and inferior-temporal clock-hour sectors where the percentage of RMSE reduction ranged between 26.3% and 44.1% for the TS and between 20.6% and 35.4% for the VS. Conclusions The new functional regression approach improves on the multivariate linear regression model and allows an even larger reduction of the amount of intersubject variability, while at the same time using a substantially smaller number of parameters to be estimated. Translational Relevance The demonstrated reduction of interindividual variation is expected to translate into an improved diagnostic separation between healthy and glaucomatous subjects, but this remains to be demonstrated in further studies.

Optic nerve head morphology in primary open-angle glaucoma and nonarteritic anterior ischaemic optic neuropathy measured with spectral domain optical coherence tomography

Optic nerve head (ONH) parameters as well as circumpapillary retinal nerve fibre layer (RNFL) thickness values measured with two different spectral domain optical coherence tomography (SD‐OCT) machines (Spectralis® and Cirrus® OCT) have been compared between two patient groups, primary open‐angle glaucoma (POAG), nonarteritic anterior ischaemic optic neuropathy (NAION) and healthy controls. A comparison of the performance of the two OCT machines was made.

Defects in macular‐retinal layer analysis of glaucoma patients compared to normative database

Purpose High‐resolution optical coherence tomography (HR‐OCT) enables a quantitative analysis of the configuration of retinal layers. The aim of this study was to analyze the topographic distribution of pathologic thinning of specific macular retinal layers of glaucoma patients.