This cross-sectional study investigates the microcirculation changes in the peripapillary retinal nerve fiber layer in eyes with glaucoma and single-hemifield visual field loss by using optical coherence tomography–based microangiography.
Key Points
Question
Are differences measurable in the microcirculation of the retinal nerve fiber layer in hemispheres between normal eyes and those with glaucoma and visual field damage confined to a single hemifield?
Findings
In this cross-sectional study of 41 patients, the hemisphere without visual field defects showed reduced blood flow in the eyes with glaucoma compared with normal eyes, whereas no difference in retinal nerve fiber layer thickness was detected.
Meaning
In the pathophysiology of glaucoma, vascular microcirculation defects may precede structural changes in the retinal nerve fiber layer. Additional longitudinal studies would be of value to confirm or refute these findings.
Abstract
Importance
Understanding the differences in vascular microcirculation of the peripapillary retinal nerve fiber layer (RNFL) between the hemispheres in eyes with glaucoma with single-hemifield visual field (VF) defects may provide insight into the pathophysiology of glaucoma.
Objective
To investigate the changes in the microcirculation of the peripapillary RNFL of eyes with glaucoma by using optical microangiography.
Design, Setting, and Participants
Eyes with glaucoma and single-hemifield VF defect and normal eyes underwent scanning using an optical microangiography system covering a 6.7 × 6.7-mm2 area centered at the optic nerve head. The RNFL microcirculation was measured within an annulus region centered at the optic nerve head divided into superior and inferior hemispheres. Blood flux index (the mean flow signal intensity in the vessels) and vessel area density (the percentage of the detected vessels in the annulus) were measured.
Main Outcomes and Measures
Differences in microcirculation between the hemispheres in eyes with glaucoma and normal eyes and correlations among blood flow metrics, VF thresholds, and clinical optical coherence tomography structural measurements were assessed.
Results
Twenty-one eyes from 21 patients with glaucoma (7 men and 14 women; mean [SD] age, 63.7 [9.9] years) and 20 eyes from 20 healthy control individuals (9 men and 11 women; mean [SD] age, 68.3 [10.7] years) were studied. In eyes with glaucoma, the abnormal hemisphere showed a thinner RNFL (mean [SE] difference, 23.5 [4.5] μm; 95% CI, 15.1-32.0 µm; P < .001), lower RNFL blood flux index (mean [SE] difference, 0.04 [0.01]; 95% CI, 0.02-0.05; P < .001), and less vessel area density (mean [SE] difference, 0.08% [0.02%]; 95% CI, 0.05%-0.10%; P < .001) than did the normal hemisphere. Compared with normal eyes, reduced RNFL microcirculation was found in the normal hemisphere of eyes with glaucoma, measured by mean [SE] differences in blood flux index (0.06 [0.01]; 95% CI, 0.04-0.09; P < .001) and vessel area density (0.04% [0.02%]; 95% CI, 0.02%-0.08%; P = .003) but not in RNFL thickness (3.4 [4.7] μm; 95% CI, −6.2 to 12.9 µm; P = .48). Strong correlations were found between the blood flux index and VF mean deviation (Spearman ρ = 0.44; P = .045) and RNFL thickness (Spearman ρ = 0.65; P = .001) in the normal hemisphere of the eye with glaucoma.
Conclusions and Relevance
Reduced RNFL microcirculation was detected in the normal hemisphere of eyes with glaucoma, with strong correspondence with VF loss and RNFL thinning. Although the results suggest that vascular dysfunction precedes structural changes seen in glaucoma, longitudinal studies would be needed to confirm this finding.
Introduction
Glaucoma is a leading cause of irreversible blindness worldwide and is characterized by the degeneration of retinal ganglion cells, characteristic changes of the optic nerve head (ONH) and retinal nerve fiber layer (RNFL), and associated visual field (VF) defects. Although the pathogenesis of glaucoma is still not fully understood, elevated intraocular pressure (IOP) and impairment of ocular blood flow have been recognized as 2 major contributing factors to its development and progression. Significant reduction in ocular blood flow in eyes with glaucoma compared with normal eyes has been reported in the ONH, retina, and choroid. Furthermore, eyes with progression of glaucoma have shown significantly lower ONH perfusion compared with eyes with glaucoma without progression.
Optical coherence tomography (OCT) angiography is an imaging technique that generates 3-dimensional information about the blood flow and microstructure in the retina and choroid without the need for dye injection. Optical microangiography (OMAG) is an OCT angiography technique that uses red blood cells as the intrinsic contrast agent and thereby provides information on blood flow and vascular distribution of the eye noninvasively.
In a previous study, we showed that OMAG measures the blood flow in the peripheral RNFL region with high repeatability and reproducibility and found a significant reduction in RNFL microcirculation in eyes with suspected glaucoma and glaucoma compared with normal eyes. In the present study, we use OMAG to compare the peripapillary RNFL vascular microcirculation between hemispheres in eyes with glaucoma and VF defects confined to a single hemifield and compare these hemispheres with those of normal eyes.
Methods
Subjects
This study followed the tenets of the Declaration of Helsinki and was conducted in compliance with the Health Insurance Portability and Accountability Act. This study was approved by the Human Subjects Division of the University of Washington, and written informed consent was obtained from all patients before imaging.
Patients with the diagnosis of open-angle glaucoma (including primary open-angle glaucoma and normal-tension glaucoma) or normal optic discs were prospectively enrolled at the University of Washington Medicine Eye Institute. Inclusion criteria were best-corrected visual acuity of 20/40 or better and refractive error ranging from −6.0- to +3.0-diopter spherical equivalent. Exclusion criteria were significant media opacity preventing high-quality imaging, any ocular disease other than glaucoma or cataract, and previous intraocular surgical procedures other than uncomplicated glaucoma or cataract surgery. Individuals with normal eyes also were excluded for a previous diagnosis of migraine.
The diagnosis of open-angle glaucoma was based on characteristic optic disc findings, an abnormal RNFL thickness on spectral-domain (SD)–OCT, and a corresponding glaucomatous VF defect in the presence of an open angle on gonioscopy. All participants underwent a comprehensive ophthalmologic examination at the time of enrollment, and patients with glaucoma received VF examinations to determine mean deviation (MD) and pattern standard deviation. All VF tests were performed on a Humphrey Field Analyzer II (Carl Zeiss Meditec), and only reliable tests were included (≤33% fixation losses and false-negative and false-positive results). All glaucomatous eyes had VF defects confined to a single hemifield. The normal hemifield required having no test location worse than P < .01 on the pattern deviation plot. The glaucomatous hemifield required a cluster of 3 contiguous test locations at P < .05 on the pattern deviation plot, with 1 test location at P < .01. One eye from each participant was included in this study. A single eye was randomly selected if both were eligible.
Blood pressure (BP) measurements were acquired at the same visit after the OMAG scan for a subgroup of participants within each group to calculate mean ocular perfusion pressure (MOPP). We defined MOPP as 2/3 times (mean arterial pressure) minus IOP, where mean arterial pressure is equal to diastolic BP plus 1/3 times (systolic BP minus diastolic BP).
Image Acquisition and Scanning Protocol
All eyes underwent scanning using a 68-kHz OMAG prototype system (center wavelength at 840 nm; Cirrus HD-OCT 5000; Carl Zeiss Meditec, Inc) with active motion-tracking capability. The same OMAG montage scanning pattern as previously reported was used to acquire volumetric data sets at the center of the ONH. The montage scanning protocol covered a 6.7 × 6.7-mm2 area with 2 sampling points located approximately 9.8 µm apart in the transverse and longitudinal directions. Four B-scans were acquired at each transverse location.
A regular OCT raster cube scan of the optic disc was acquired using the same prototype device at the same visit to obtain a 3-dimensional structural data set for RNFL thickness and ONH structural measurements. The scanning protocol collected 200 × 200 sampling points from a 6 × 6-mm2 area centered on the optic disc. Imaging data were considered to be poor quality and were omitted from further analysis if the signal strength fell below the manufacturer-recommended cutoff (signal strength <6) or if significant eye movement occurred.
OMAG Processing
All the acquired volumetric scans were processed with a previously described complex OCT signal-based and feature space–based OMAG algorithm by calculating the OCT signal differences between consecutive B-scan pairs to extract the blood flow signals. The RNFL was segmented with proprietary semiautomatic retinal layer segmentation software. The segmented RNFL boundary results were applied to OMAG vascular images to obtain the microvascular image in the RNFL. The RNFL vascular en face images were generated with maximum intensity projection in the RNFL. The ONH margin was manually delineated from the structural en face image by identifying the end of the Bruch membrane and locating the center of the ONH.
Peripapillary RNFL Microcirculation Measurements
We evaluated the peripapillary RNFL blood flux index and vessel area density within an annulus centered at the ONH (2.5-mm inner and 3.7-mm outer diameter) with the exclusion of large retinal vessels because the RNFL is supplied by the microcirculation coming from the retinal radial peripapillary capillaries. The methods for large retinal vessel removal and blood flow metrics have been described previously. In brief, a multiscale Hessian filter was developed to detect blood vessels with various diameters. After vessel detection and removal of large vessels of more than 32 μm, the RNFL blood flux index was measured by calculating the mean flow intensity in the vessel area, where the blood flow signal was normalized to 0 to 1 by dividing by the full dynamic range of blood flow signal intensity and thus was presented as a unitless ratio. The vessel area density measured the percentage of the area of the annulus occupied by the retinal radial peripapillary capillaries. The RNFL blood flux index and vessel area density were measured for the entire annulus and for the superior (0°-179°) and inferior (180°-359°) hemispheres.
Statistical Analysis
We used 2-tailed, independent-sample t tests to compare the peripapillary RNFL flow metrics between normal eyes and those with glaucoma. Bonferroni adjustment was applied to maintain the overall type I error at 5% for multiple comparisons. Paired t tests were used to compare between the hemispheres corresponding to the normal and abnormal hemifields in the same eye of the same patient with glaucoma. Spearman nonparametric models were used to investigate the correlation between RNFL blood flow metrics with VF variables and OCT biometrics. P < .05 indicates statistical significance for these comparisons. P < .025 indicates statistical significance when comparing the RNFL thickness, blood flux index, and vessel area density of hemispheres among normal eyes and the normal and abnormal hemispheres in the eyes with glaucoma.
Results
Twenty-one eyes with glaucoma from 21 patients (7 men and 14 women; mean [SD] age, 63.7 [9.9] years) and 20 normal eyes from 20 age- and sex-matched control individuals (9 men and 11 women; mean [SD] age, 68.3 [10.7] years) were enrolled. The glaucoma group included 14 white, 5 Asian, 1 African American, and 1 native Hawaiian patient, and the control group included 17 white and 3 Asian participants (Table 1). In the glaucoma group, the mean (SD) of the VF MD was −5.04 dB (2.77; range, −11.20 to −0.58 dB), and the mean (SD) VF pattern standard deviation was 7.37 (3.83 dB; range, 0.16 to 13.75 dB). Fifteen eyes with glaucoma had mild and 6 had moderate glaucoma according to the Hodapp-Parrish-Anderson scale. Among them, 3 had undergone previous glaucoma surgery. Normal eyes showed higher mean (SD) IOP compared with eyes with glaucoma (13.7 [3.1; range, 8.0-20.0] vs 11.6 [2.8; range, 7.0-16.0] mm Hg). All controls had an IOP of less than 21 mm Hg, whereas 17 of 21 patients with glaucoma were using IOP-lowering treatments. Eleven controls and 12 patients with glaucoma underwent BP measurement after the OMAG imaging session. No differences were detected in systolic BP, diastolic BP, and MOPP between groups. For the structural measurements from the OCT image, eyes with glaucoma showed thinner RNFL, a smaller rim area, and larger cup-disc ratio than did normal eyes.
Table 1. Baseline Demographic Information and OCT Biometric Variables in the RNFL and Optic Nerve Heada.
| Variable | Normal Eyes (n = 20) |
Eyes With Glaucoma (n = 21) |
|---|---|---|
| Age, mean (SD) [95% CI], y | 68.3 (10.7) [63.6-73.0] |
63.7 (9.9) [59.1-68.2] |
| No. of men/women | 9/11 | 7/14 |
| Ethnicity, No. (%) | ||
| White | 17 (85) | 14 (67) |
| Asian | 3 (15) | 5 (24) |
| African American | 0 | 1 (5) |
| Native Hawaiian | 0 | 1 (5) |
| IOP, mean (SD) [95% CI], mm Hg | 13.7 (3.1) [12.3-15.1] |
11.6 (2.8) [10.2-12.9] |
| Systolic BP, mean (SD) [95% CI], mm Hgb | 136.6 (15.3) [127.3-146.0] |
130.8 (14.4) [121.9-139.8] |
| Diastolic BP, mean (SD) [95% CI], mm Hgb | 82.1 (6.9) [77.1-87.1] |
76.8 (8.8) [72.0-81.6] |
| MOPP, mean (SD) [95% CI], mm Hgb | 52.9 (5.5) [49.2-56.6] |
51.7 (6.2) [48.2-55.3] |
| Diabetes, No. (%) | 2 (10) | 1 (5) |
| Systemic hypertension, No. (%) | 7 (35) | 6 (29) |
| Taking systemic antihypertensive medication, No. (%) | 6 (30) | 6 (29) |
| Taking ocular antihypertensive eye drops, No. (%) | 0 | 17 (81) |
| Glaucoma surgery, No. (%) | 0 | 3 (14) |
| Glaucoma staging, No. (%)c | ||
| Mild | NA | 15 (71) |
| Moderate | NA | 6 (29) |
| Severe | NA | 0 |
| RNFL thickness, mean (SD) [95% CI], μm | 95.4 (11.8) [90.7-100.1] |
70.4 (9.0) [65.8-75.0] |
| Rim area, mean (SD) [95% CI], mm2 | 1.33 (0.19) [1.24-1.42] |
0.83 (0.20) [0.74-0.92] |
| Cup-disc ratio, mean (SD) [95% CI] | 0.40 (0.17) [0.34-0.46] |
0.73 (0.10) [0.67-0.79] |
Abbreviations: BP, blood pressure; IOP, intraocular pressure; MOPP, mean ocular perfusion pressure; NA, not applicable; OCT, optical coherence tomography; RNFL, retinal nerve fiber layer.
Percentages have been rounded and may not total 100.
Includes 11 normal eyes and 12 eyes with glaucoma.
Mild indicates visual field mean deviation of greater than −6 dB; moderate, −12 dB to −6 dB; and severe, no greater than −12 dB.
The Figure shows the vascular microcirculation en face images in the peripapillary RNFL of a normal eye and one with glaucoma. The normal eye had peripapillary RNFL thickness in a normal range, as observed in the RNFL thickness measurements, structural en face image, and RNFL thickness map (Figure, A-C). The retinal radial peripapillary capillaries were intact and distributed densely and evenly in the superior and inferior hemispheres by subjective qualitative evaluation and quantitative analysis (Figure, D-E). In the eye with glaucoma, reduced RNFL thickness, fewer retinal radial peripapillary capillaries, and lower blood flow metrics were observed in the inferior hemisphere compared with the superior hemisphere (Figure, F and H-K), which corresponded to the glaucomatous VF defects shown in the superior hemifield in the total and pattern deviation plots (Figure, G).
Figure. Examples of Study Eyes.
In the normal eye (top), the retinal radial peripapillary capillaries were intact and distributed densely and evenly in the superior and inferior hemispheres by subjectively qualitative evaluation and quantitative analysis. In the eye with glaucoma (bottom), reduced retinal nerve fiber layer (RNFL) thickness, fewer retinal radial peripapillary capillaries, and lower blood flow metrics were observed in the inferior hemisphere compared with the superior hemisphere, which corresponded to the glaucomatous visual field defects shown in the superior hemifield in the total and pattern deviation plots. Blood flux index is calculated as the mean flow intensity in the vessel area, where the blood flow signal was normalized to 0 to 1 by dividing by the full dynamic range of blood flow signal intensity; vessel area density, the percentage of the detected vessels within the annulus. In the Cirrus RNFL thickness deviation maps, areas with RNFL thickness thinner than the fifth percentile and the first percentile of the normative database were marked in yellow and in red, respectively. GHT indicates glaucoma hemifield test; I, inferior; MD, median deviation; N, nasal; PSD, pattern standard deviation; S, superior; T, temporal; VFI, visual field index.
For vascular microcirculation between groups, eyes with glaucoma showed a lower mean (SD) blood flux index (0.66 [0.03] vs 0.74 [0.03]) and vessel area density (0.38% [0.06%] vs 0.47% [0.04%]) compared with normal eyes (P < .001) (Table 2). Table 3 summarizes the comparison results among hemispheres corresponding to the normal hemifields and hemifields with VF defects in eyes with glaucoma and normal eyes. Fifteen eyes with glaucoma showed VF defects confined to the superior hemifield. In eyes with glaucoma, the mean (SD) RNFL was thinner in the hemisphere corresponding to the hemifield with the VF defect than the hemisphere corresponding to the normal hemifield (mean [SE] difference, 23.5 [4.5] μm; 95% CI, 15.1-32.0 μm; P < .001). Lower blood flux index (mean [SE] difference, 0.04 [0.01]; 95% CI, 0.02-0.05; P < .001) and vessel area density (mean [SE] difference, 0.08% [0.02%]; 95% CI, 0.05%-0.10%; P < .001) also were found in the abnormal hemisphere compared with the normal hemisphere. In normal eyes, no statistically significant differences were detected between the superior and inferior hemispheres in RNFL thickness (mean [SE] difference, 4.0 [3.1] μm; 95% CI, −2.5 to 10.5 μm; P = .21), blood flux index (mean [SE] difference, 0.01 [0.01]; 95% CI, −0.01 to 0.03; P = .32), and vessel area density (mean [SE] difference, 0.003% [0.0048%]; 95% CI, −0.01% to 0.01%; P = .56).
Table 2. Global Blood Flux Index and Vessel Area Density in Peripapillary RNFL Between Normal and Glaucoma Groups.
| Global Variable | Mean (SD) | Difference, Mean (SE) [95% CI] | P Valuea | |
|---|---|---|---|---|
| Normal Eyes (n = 20) |
Eyes With Glaucoma (n = 21) |
|||
| Blood flux indexb | 0.74 (0.03) | 0.66 (0.03) | 0.08 (0.01) [0.06-0.10] | <.001 |
| Vessel area density, % | 0.47 (0.04) | 0.38 (0.06) | 0.09 (0.02) [0.06-0.12] | <.001 |
Abbreviation: RNFL, retinal nerve fiber layer.
Calculated as 2-sample t tests, with P < .05 considered to be statistically significant.
Calculated as the mean flow intensity in the vessel area, where the blood flow signal was normalized to 0 to 1 by dividing by the full dynamic range of blood flow signal intensity.
Table 3. Blood Flux Index and Vessel Area Density in Peripapillary RNFL in the Hemispheres Corresponding to the Normal Hemifield and the Hemifield With the VF Defect in Eyes With Glaucoma and Normal Eyes.
| Variable | Mean (SD) | Difference, Mean (SE) [95% CI] | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Eyes With Glaucoma | Normal Eyes | ||||||||
| Normal Hemisphere | Abnormal Hemisphere | Normal vs Abnormal Hemispheres of Eyes With Glaucomaa | P Value | Normal Hemisphere of Eyes With Glaucoma vs Normal Eyesb | P Value | Abnormal Hemisphere of Eyes With Glaucoma vs Normal Eyesb | P Value | ||
| RNFL thickness, μm | 92.0 (17.7) | 68.5 (10.5) | 95.4 (11.8) | 23.5 (4.5) [15.1 to 32.0] |
<.001 | 3.4 (4.7) [−6.2 to 12.9] |
.48 | 26.9 (3.5) [19.8 to 33.9] |
<.001 |
| Blood flux indexc | 0.67 (0.04) | 0.64 (0.03) | 0.74 (0.03) | 0.04 (0.01) [0.02 to 0.05] |
<.001 | 0.06 (0.01) [0.04 to 0.09] |
<.001 | 0.10 (0.01) [0.08 to 0.12] |
<.001 |
| Vessel area density, % | 0.42 (0.06) | 0.35 (0.07) | 0.47 (0.04) | 0.08 (0.02) [0.05 to 0.10] |
<.001 | 0.04 (0.02) [0.02 to 0.08] |
.003 | 0.13 (0.02) [0.09 to 0.16] |
<.001 |
Abbreviations: RNFL, retinal nerve fiber layer; VF, visual field.
Paired t tests were used to compare the variables between the normal hemisphere and the hemisphere corresponding to the VF defect in the same eye with glaucoma. P < .05 is considered to be statistically significant.
Two-sample t tests were used to compare the variables between normal eyes and eyes with glaucoma (normal and abnormal hemispheres, respectively). With Bonferroni adjustment for multiple comparisons, P < .025 is considered to be statistically significant.
Calculated as the mean flow intensity in the vessel area, where the blood flow signal was normalized to 0 to 1 by dividing by the full dynamic range of blood flow signal intensity.
Although the RNFL thickness in the normal hemisphere (without VF defect) in the glaucoma group did not differ from the RNFL thickness in the normal group (mean [SE] difference, 3.4 [4.7] μm; 95% CI, −6.2 to 12.9 μm; P = .48), the normal hemisphere of the glaucoma group had a lower blood flux index (mean [SE] difference, 0.06 [0.01]; 95% CI, 0.04-0.09; P < .001) and vessel area density (mean [SE] difference, 0.04% [0.02%]; 95% CI, 0.02%-0.08%; P = .003) than the normal group (Table 3). A thinner RNFL (mean [SE] difference, 26.9 [3.5] μm; 95% CI, 19.8-33.9 μm; P < .001) and lower blood flux index (mean [SE] difference, 0.10 [0.01]; 95% CI, 0.08-0.12; P < .001) and vessel area density (mean [SE] difference, 0.13 [0.02]; 95% CI, 0.09-0.16; P < .001) were detected in the abnormal hemisphere of the glaucoma group compared with the control group (Table 3).
Positive correlations between VF MD and blood flux index (Spearman’s ρ = 0.44; 95% CI, −0.13 to 0.66; P = .045) and between RNFL thickness and blood flow metrics (ρ = 0.65; 95% CI, 0.49 to 0.90; P = .001) were detected in the hemisphere corresponding to the normal hemifield but not between other combinations. No correlation was detected between blood flow metrics and functional and structural measurements for the glaucoma group (Table 4).
Table 4. Summary of Correlations Between Blood Flux Index and Vessel Area Density and Functional and Structural Measurements for the Abnormal and Normal Hemifield in Eyes With Glaucoma.
| Variable | Correlation Variable | Hemisphere Corresponding to the Abnormal Hemifield | Hemisphere Corresponding to the Normal Hemifield | ||
|---|---|---|---|---|---|
| Spearman ρ (95% CI) | P Value | Spearman ρ (95% CI) | P Value | ||
| Blood flux indexa | VF MD | 0.02 (−0.36 to 0.49) | .94 | 0.44 (−0.13 to 0.66) | .045 |
| RNFL thicknessb | 0.43 (−0.07 to 0.69) | .05 | 0.65 (0.49 to 0.90) | .001 | |
| Vessel area density, % | VF MD | 0.28 (−0.21 to 0.61) | .21 | 0.29 (−0.13 to 0.66) | .20 |
| RNFL thicknessb | 0.13 (−0.35 to 0.51) | .59 | 0.35 (−0.06 to 0.70) | .13 | |
Abbreviations: RNFL, retinal nerve fiber layer; VF, visual field; VF MD, VF mean deviation.
Calculated as the mean flow intensity in the vessel area, where the blood flow signal was normalized to 0 to 1 by dividing by the full dynamic range of blood flow signal intensity.
Measured in superior (46°-135°) and inferior (226°-315°) quadrants.
Discussion
In this study, we investigated the peripapillary RNFL microcirculation changes in eyes with glaucoma and VF defects confined to a single hemifield by using OMAG. In eyes with glaucoma, a lower blood flux index and vessel area density and a thinner RNFL were found in the abnormal hemisphere compared with the normal hemisphere and compared with the control group. Although the normal hemispheres in the glaucoma group also showed reduced blood flux index and vessel area density compared with the control group, similar RNFL thickness was found between the normal hemispheres in eyes with glaucoma and normal eyes. In addition, correlations among blood flux index and VF MD and RNFL thickness were detected in the normal hemispheres of eyes with glaucoma.
In the glaucoma group, we found that the abnormal hemisphere showed a lower blood flux index and vessel area density compared with the normal hemisphere. Decreased blood velocities in the retrobulbar vessels have been shown in the worse hemisphere in eyes with glaucoma showing asymmetric VF defects. Reduced retinal blood flow was found in the hemisphere corresponding to the abnormal hemifield using Doppler SD-OCT. A significant reduction in the peripapillary vessel density also was found in the abnormal hemisphere compared with the normal hemisphere in eyes without high myopia and with inferior hemifield VF defects by using OCT angiography with the split-spectrum amplitude-decorrelation angiography algorithm. Our results agree with these findings, although this association was not limited to eyes with inferior hemifield VF defects in our study.
Furthermore, compared with normal eyes, we found a lower blood flux index and vessel area density in the normal hemisphere of the eyes with glaucoma, whereas no difference in RNFL thickness was detected. Other authors have reported similar results, albeit with different modalities of blood flow measurement. Decreased blood velocities in the retrobulbar vessels and ONH and juxtapapillary retinal capillary blood flow were found in eyes with glaucoma with normal or borderline VF defects by using color Doppler imaging and scanning laser Doppler flowmetry. Reduced retinal blood flow was detected in the hemisphere with normal VF values compared with normal eyes using Doppler SD-OCT. Our findings agree with these results except that, in the above-mentioned studies, thinner RNFL also was found in the normal hemisphere in the eyes with glaucoma, whereas the RNFL thickness in the normal hemisphere was not different from that of the corresponding hemisphere in normal eyes in our results. Other authors have reported similar findings by using time-domain OCT.
Debate remains whether impairments in blood flow are a result or a cause of glaucoma. Several studies reported significant narrowing of the retinal vessels with associated RNFL defects in the hemisphere without VF defects in eyes with glaucoma and concluded that their findings supported the hypothesis that retinal arteriolar change may result from loss of retinal neurons secondary to glaucoma. However, diminished optic nerve blood flow has been detected in eyes with suspected glaucoma, normal VF examination findings, and normal to suspicious optic nerve appearance (no definitive localized notching, saucerization, generalized rim loss, or progression was noted), which suggests that vascular change may precede glaucomatous optic neuropathy. In our study, blood flux and vessel density were decreased in the normal hemisphere of eyes with glaucoma compared with normal eyes, whereas the RNFL thicknesses were not different, suggesting that vascular dysfunction may precede the structural changes seen in glaucoma. A prospective finding that these patients develop thinning of the corresponding RNFL and form VF defects would add credence to the theory that vascular compromise is found before structural changes, such as RNFL thinning, in glaucoma.
Lower blood flux index and vessel area density were detected in eyes with glaucoma compared with eyes in age-matched normal controls. Similar results were found in our previous study and coincide with other findings in the literature. We have also found that eyes with suspected glaucoma showed a reduction in the blood flux index compared with normal eyes. Liu et al compared the peripapillary retinal perfusion in the entire retinal tissue, including big retinal vessels, between normal eyes and those with glaucoma by using a split-spectrum amplitude-decorrelation angiography algorithm–based OCT angiography technique and found a reduction in retinal perfusion in glaucomatous eyes. Using the same technique, Yarmohammadi et al compared the vessel density in healthy patients with suspected glaucoma with that in patients with glaucoma. They found the lowest vessel density in patients with glaucoma, followed by those with suspected glaucoma and then healthy controls, after adjusting for age differences among groups. Although we cannot directly compare our results with the results using the split-spectrum amplitude-decorrelation angiography algorithm, both techniques indicated that OCT angiography differentiates the changes in peripapillary microvascular perfusion among eyes with glaucoma, eyes with suspected glaucoma, and normal eyes. Prospective studies would show whether such perfusion differences were a harbinger of further structural and functional loss.
We found correlations among VF MD, RNFL thickness, and blood flux index in the normal hemisphere of eyes with glaucoma but not in other combinations. We presumed the negative results were attributable to the mismatched regions among the functional and structural measures and the mean effect when we calculated the variables in the entire area. The hemifield evaluation in the VF examination covered half of a 6 × 6-mm2 area, whereas the blood flow metrics were calculated in a self-defined annulus. Calculating the mean may dilute the degree of defect and thus result in a nonsignificant correlation. In addition, VF examinations and blood flow measurements were not calibrated to the horizontal meridian passing through the foveola and the center of the disc. Further investigation is warranted.
Limitations
Owing to the design of our study, we were not able to judge whether VF defect leads to the reduction of the demand of blood flow or whether the reduced blood flow leads to the damage of retinal tissues and causes the VF defect. Prospective longitudinal studies are needed to reveal the pathophysiologic mechanism of glaucoma. We did not obtain visual field testing in our healthy controls. However, all controls underwent a comprehensive ocular examination and were found to have healthy optic nerves, statistically normal peripapillary RNFL thickness, and normal optic disc measures using SD-OCT. Third, medication used by patients with glaucoma was not taken into account. Ocular antihypertensive eye drops are known to decrease the IOP but may also increase the blood flow in the ONH. In addition, animal studies have shown that systemic drugs may influence the blood flow. Among our patients with glaucoma, 17 (81%) were using antihypertensive eye drops, and 6 (29%) were using systemic antihypertensive medication; the effects of their medications on ONH perfusion are unknown. However, we found no difference between patients with glaucoma who were and were not taking antihypertensive eye drops in blood flux index (mean [SD] difference, −0.01 [0.02]; 95% CI, −0.05 to 0.03; P = .46) or in vessel area density (mean [SD] difference, 0.01% [0.03%]; 95% CI, −0.06 to 0.08; P = .80) or who were or were not taking systemic antihypertensive medication in blood flux index (mean [SD] difference, 0.01 [0.02]; 95% CI, −0.02 to 0.05; P = .55) or in vessel area density (mean [SD] difference, 0.01% [0.03%]; 95% CI, −0.05 to 0.07; P = .74). Fourth, MOPP was used to estimate the arteriovenous pressure gradient with the assumption that the central retinal vein pressure could be approximated based on the IOP. Retinal venous pressure is known to be increased in eyes with glaucoma and therefore may change the measured MOPP.
Conclusions
In eyes with glaucoma, lower RNFL microcirculation was detected in the abnormal hemisphere compared with the normal hemisphere. Although the RNFL thickness was not different between the normal hemisphere of eyes with glaucoma and normal eyes, the normal hemisphere of eyes with glaucoma demonstrated decreased microcirculation measurements. Even though our results suggest that vascular dysfunction may precede structural changes seen in glaucoma, longitudinal studies are needed to confirm this finding.
References
- 1.Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006;90(3):262-267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Leske MC, Connell AM, Wu SY, Hyman LG, Schachat AP. Risk factors for open-angle glaucoma: the Barbados Eye Study. Arch Ophthalmol. 1995;113(7):918-924. [DOI] [PubMed] [Google Scholar]
- 3.Venkataraman ST, Flanagan JG, Hudson C. Vascular reactivity of optic nerve head and retinal blood vessels in glaucoma—a review. Microcirculation. 2010;17(7):568-581. [DOI] [PubMed] [Google Scholar]
- 4.Quigley HA, Addicks EM, Green WR. Optic nerve damage in human glaucoma, III: quantitative correlation of nerve fiber loss and visual field defect in glaucoma, ischemic neuropathy, papilledema, and toxic neuropathy. Arch Ophthalmol. 1982;100(1):135-146. [DOI] [PubMed] [Google Scholar]
- 5.Quigley HA, Dunkelberger GR, Green WR. Retinal ganglion cell atrophy correlated with automated perimetry in human eyes with glaucoma. Am J Ophthalmol. 1989;107(5):453-464. [DOI] [PubMed] [Google Scholar]
- 6.Sommer A, Tielsch JM, Katz J, et al. Relationship between intraocular pressure and primary open angle glaucoma among white and black Americans: the Baltimore Eye Survey. Arch Ophthalmol. 1991;109(8):1090-1095. [DOI] [PubMed] [Google Scholar]
- 7.Flammer J, Orgül S. Optic nerve blood-flow abnormalities in glaucoma. Prog Retin Eye Res. 1998;17(2):267-289. [DOI] [PubMed] [Google Scholar]
- 8.Flammer J, Orgül S, Costa VP, et al. The impact of ocular blood flow in glaucoma. Prog Retin Eye Res. 2002;21(4):359-393. [DOI] [PubMed] [Google Scholar]
- 9.Hwang JC, Konduru R, Zhang X, et al. Relationship among visual field, blood flow, and neural structure measurements in glaucoma. Invest Ophthalmol Vis Sci. 2012;53(6):3020-3026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Flammer J, Mozaffarieh M. Autoregulation, a balancing act between supply and demand. Can J Ophthalmol. 2008;43(3):317-321. [DOI] [PubMed] [Google Scholar]
- 11.Gherghel D, Orgül S, Gugleta K, Gekkieva M, Flammer J. Relationship between ocular perfusion pressure and retrobulbar blood flow in patients with glaucoma with progressive damage. Am J Ophthalmol. 2000;130(5):597-605. [DOI] [PubMed] [Google Scholar]
- 12.Stewart WC, Kolker AE, Sharpe ED, et al. Factors associated with long-term progression or stability in primary open-angle glaucoma. Am J Ophthalmol. 2000;130(3):274-279. [DOI] [PubMed] [Google Scholar]
- 13.Schumann J, Orgül S, Gugleta K, Dubler B, Flammer J. Interocular difference in progression of glaucoma correlates with interocular differences in retrobulbar circulation. Am J Ophthalmol. 2000;129(6):728-733. [DOI] [PubMed] [Google Scholar]
- 14.Wang RK. Optical microangiography: a label free 3D imaging technology to visualize and quantify blood circulations within tissue beds in vivo. IEEE J Sel Top Quantum Electron. 2010;16(3):545-554. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Wang RK, An L, Francis P, Wilson DJ. Depth-resolved imaging of capillary networks in retina and choroid using ultrahigh sensitive optical microangiography. Opt Lett. 2010;35(9):1467-1469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.An L, Shen TT, Wang RK. Using ultrahigh sensitive optical microangiography to achieve comprehensive depth resolved microvasculature mapping for human retina. J Biomed Opt. 2011;16(10):106013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Chen CL, Zhang A, Bojikian KD, et al. Peripapillary retinal nerve fiber layer vascular microcirculation in glaucoma using optical coherence tomography–based microangiography. Invest Ophthalmol Vis Sci. 2016;57(9):OCT475-OCT485. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.World Medical Association World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191-2194. [DOI] [PubMed] [Google Scholar]
- 19.Sehi M, Goharian I, Konduru R, et al. Retinal blood flow in glaucomatous eyes with single-hemifield damage. Ophthalmology. 2014;121(3):750-758. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zhang Q, Huang Y, Zhang T, et al. Wide-field imaging of retinal vasculature using optical coherence tomography-based microangiography provided by motion tracking. J Biomed Opt. 2015;20(6):066008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Zhang A, Wang RK. Feature space optical coherence tomography based micro-angiography. Biomed Opt Express. 2015;6(5):1919-1928. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Yin X, Chao JR, Wang RK. User-guided segmentation for volumetric retinal optical coherence tomography images. J Biomed Opt. 2014;19(8):086020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Hodapp E, Parrish RK, Anderson DR. Clinical Decisions in Glaucoma. St Louis, MO: Mosby; 1993:52-61. [Google Scholar]
- 24.Nicolela MT, Drance SM, Rankin SJ, Buckley AR, Walman BE. Color Doppler imaging in patients with asymmetric glaucoma and unilateral visual field loss. Am J Ophthalmol. 1996;121(5):502-510. [DOI] [PubMed] [Google Scholar]
- 25.Akagi T, Iida Y, Nakanishi H, et al. Microvascular density in glaucomatous eyes with hemifield visual field defects: an optical coherence tomography angiography study. Am J Ophthalmol. 2016;168:237-249. [DOI] [PubMed] [Google Scholar]
- 26.Michelson G, Langhans MJ, Groh MJ. Perfusion of the juxtapapillary retina and the neuroretinal rim area in primary open angle glaucoma. J Glaucoma. 1996;5(2):91-98. [PubMed] [Google Scholar]
- 27.Kee C, Cho C. Evaluation of retinal nerve fiber layer thickness in the area of apparently normal hemifield in glaucomatous eyes with optical coherence tomography. J Glaucoma. 2003;12(3):250-254. [DOI] [PubMed] [Google Scholar]
- 28.Kim JM, Sae Kim M, Ju Jang H, Ho Park K, Caprioli J. The association between retinal vessel diameter and retinal nerve fiber layer thickness in asymmetric normal tension glaucoma patients. Invest Ophthalmol Vis Sci. 2012;53(9):5609-5614. [DOI] [PubMed] [Google Scholar]
- 29.Hall JK, Andrews AP, Walker R, Piltz-Seymour JR. Association of retinal vessel caliber and visual field defects in glaucoma. Am J Ophthalmol. 2001;132(6):855-859. [DOI] [PubMed] [Google Scholar]
- 30.Mitchell P, Leung H, Wang JJ, et al. Retinal vessel diameter and open-angle glaucoma: the Blue Mountains Eye Study. Ophthalmology. 2005;112(2):245-250. [DOI] [PubMed] [Google Scholar]
- 31.Russo A, Costagliola C, Rizzoni D, Ghilardi N, Turano R, Semeraro F. Arteriolar diameters in glaucomatous eyes with single-hemifield damage. Optom Vis Sci. 2016;93(5):504-509. [DOI] [PubMed] [Google Scholar]
- 32.Piltz-seymour JR, Grunwald JE, Hariprasad SM, Dupont J. Optic nerve blood flow is diminished in eyes of primary open-angle glaucoma suspects. Am J Ophthalmol. 2001;132(1):63-69. [DOI] [PubMed] [Google Scholar]
- 33.Liu L, Jia Y, Takusagawa HL, et al. Optical coherence tomography angiography of the peripapillary retina in glaucoma. JAMA Ophthalmol. 2015;133(9):1045-1052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Yarmohammadi A, Zangwill LM, Diniz-Filho A, et al. Optical coherence tomography angiography vessel density in healthy, glaucoma suspect, and glaucoma eyes. Invest Ophthalmol Vis Sci. 2016;57(9):OCT451-OCT459. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Ishibashi S, Hirose N, Tawara A, Kubota T. Effect of latanoprost on the diurnal variations in the intraocular and ocular perfusion pressure in normal tension glaucoma. J Glaucoma. 2006;15(5):354-357. [DOI] [PubMed] [Google Scholar]
- 36.Liu CJ, Ko YC, Cheng CY, et al. Changes in intraocular pressure and ocular perfusion pressure after latanoprost 0.005% or brimonidine tartrate 0.2% in normal-tension glaucoma patients. Ophthalmology. 2002;109(12):2241-2247. [DOI] [PubMed] [Google Scholar]
- 37.Grieshaber MC, Flammer J. Is the medication used to achieve the target intraocular pressure in glaucoma therapy of relevance? an exemplary analysis on the basis of two beta-blockers. Prog Retin Eye Res. 2010;29(1):79-93. [DOI] [PubMed] [Google Scholar]
- 38.McGrath P. Further observations on the pharyngeal hypophysis and the postsphenoid in the mature male rat. J Anat. 1976;121(pt 1):193-201. [PMC free article] [PubMed] [Google Scholar]
- 39.Van Keer K, Breda JB, Pinto LA, Stalmans I, Vandewalle E. Estimating mean ocular perfusion pressure using mean arterial pressure and intraocular pressure. Invest Ophthalmol Vis Sci. 2016;57(4):2260. [DOI] [PubMed] [Google Scholar]
- 40.Flammer J, Konieczka K. Retinal venous pressure: the role of endothelin. EPMA J. 2015;6:21. [DOI] [PMC free article] [PubMed] [Google Scholar]