Ophthalmic Surgery, Lasers and Imaging Retina

Clinical Science 

Quantifying Choriocapillaris Flow Voids in Patients With Geographic Atrophy Using Swept-Source OCT Angiography

Nicholas T. Rinella, BS, MA; Hao Zhou, PhD; Qinqin Zhang, PhD; Cathrine Keiner, BS; Catherine E. Oldenburg, PhD; Jacque L. Duncan, MD; Ruikang K. Wang, PhD; Daniel M. Schwartz, MD

Abstract

BACKGROUND AND OBJECTIVE:

To compare choriocapillaris (CC) flow voids (FVs) throughout the macula in patients with age-related macular degeneration (AMD) and geographic atrophy (GA) to age-similar controls using swept-source optical coherence tomography angiography (SS-OCTA).

PATIENTS AND METHODS:

In this cross-sectional study, 12 subjects with GA secondary to nonexudative AMD and 12 age-similar controls participated. SS-OCTA was performed using a 6 mm × 6 mm scanning pattern. CC FVs were calculated using a one-standard deviation thresholding method developed from a normal database.

RESULTS:

CC FVs were significantly increased in patients with GA compared with age-similar controls (P < .001). FVs within 2° of GA were significantly increased compared with the area outside 2° (P < .001). FVs beyond 2° of GA were significantly increased compared with age-similar controls (P < .001).

CONCLUSIONS:

FV analysis of in vivo CC images revealed diffuse CC perfusion deficits throughout the macular region in subjects with GA secondary to nonexudative AMD.

[Ophthalmic Surg Lasers Imaging Retina. 2019;50:e229–e235.]

Abstract

BACKGROUND AND OBJECTIVE:

To compare choriocapillaris (CC) flow voids (FVs) throughout the macula in patients with age-related macular degeneration (AMD) and geographic atrophy (GA) to age-similar controls using swept-source optical coherence tomography angiography (SS-OCTA).

PATIENTS AND METHODS:

In this cross-sectional study, 12 subjects with GA secondary to nonexudative AMD and 12 age-similar controls participated. SS-OCTA was performed using a 6 mm × 6 mm scanning pattern. CC FVs were calculated using a one-standard deviation thresholding method developed from a normal database.

RESULTS:

CC FVs were significantly increased in patients with GA compared with age-similar controls (P < .001). FVs within 2° of GA were significantly increased compared with the area outside 2° (P < .001). FVs beyond 2° of GA were significantly increased compared with age-similar controls (P < .001).

CONCLUSIONS:

FV analysis of in vivo CC images revealed diffuse CC perfusion deficits throughout the macular region in subjects with GA secondary to nonexudative AMD.

[Ophthalmic Surg Lasers Imaging Retina. 2019;50:e229–e235.]

Introduction

The choriocapillaris (CC) is a thin capillary meshwork located adjacent to Bruch's membrane (BM) and the retinal pigment epithelium (RPE) at the inner boundary of the choroid.1 A symbiotic relationship exists between the CC and the RPE.2 The CC supplies the RPE and outer retina with nutrients and provides metabolic exchange; the RPE produces growth factors, such as vascular endothelial growth factor (VEGF), that act as survival factors for choroidal endothelial cells.3,4 In advanced age-related macular degeneration (AMD), there is progressive loss of the CC, RPE, and overlying photoreceptors in the macular region, resulting in geographic atrophy (GA).5 GA is irreversible, and there are currently no approved therapies to arrest its progression.6 There have been attempts to prevent the progression of GA through anti-inflammatory therapies targeting the complement pathway (NCT00935883, NCT01229215, NCT01445548, NCT00541333, and NCT02503332); however, many of these clinical trials have been largely unsuccessful, suggesting that additional mechanisms may be responsible for GA pathogenesis.7,8

Previously, it has been difficult to image the CC in vivo because dye-based angiographies cannot adequately resolve the dense capillary meshwork. Histopathologic study of early and intermediate stages of AMD reveal loss of CC; further attenuation of the choriocapillaris is seen in advanced AMD.4,9–11 In an elegant histologic study, Seddon et al. found that CC perfusion was decreased at the margins of GA and suggested previous clinical observations of AMD have underestimated the involvement and loss of the CC.10 Additional studies have suggested that choriocapillaris loss may precede RPE changes in exudative neovascular AMD.4,10,12–13

Optical coherence tomography angiography (OCTA) is a recently developed noninvasive technology that enables visualization of the CC in vivo.14–25 OCTA imaging works by separating the flow of red blood cells from stationary retinal structures through multiple OCT scans at the same position.14–18 Studies utilizing OCTA have begun to confirm CC flow deficits at the margins of GA in patients with dry AMD.23,24 These areas of reduced CC flow may be the result of CC dropout or slow vessel flow that falls below the detectable motion threshold of the OCTA device. Recent studies have attempted to quantify the CC perfusion through the evaluation of dark areas on en face CC images, known as flow voids (FVs) or flow deficits. Sacconi et al. used spectral-domain OCTA to investigate CC perfusion at the margin of GA compared with surrounding control areas.24 They used a vessel density method that binarized the automatic-segmentation, machine-output CC images using a mean threshold and found that there was significant CC impairment at the margin of GA compared with the surrounding control area. Nassisi et al. recently used a swept-source (SS) OCTA to examine flow voids at the margin of GA in the “para-atrophy” and “peri-atrophy” zones and found that FV are increased at the GA border compared with the surrounding area.23 These intrapatient analyses suggest that CC impairment at the GA margin precedes GA expansion and that OCTA will be a useful tool in the evaluation of GA progression.

Despite these advances in CC imaging and analysis, there remains a lack of a standardized method for FV quantification and an understanding of how the CC is affected throughout the macula in patients with GA secondary to AMD, not just at the margin of GA alone. Recently, Zhang et al. published a method using a SS-OCTA device that quantifies the CC with a high degree of repeatability using a one-standard deviation thresholding method based on a database of normal subjects.28 Advantages of this quantification strategy include compensation for signal attenuation caused by the RPE/BM complex and the use of a threshold based on a database of artifact-free en face angiograms obtained from normal controls rather than the standard deviation from an individual image. This thresholding method would be especially useful for quantifying en face CC images of eyes with GA because the threshold level is not susceptible to hyperreflectivity or other commonly present imaging artifacts.

Although previous analyses show increased CC FVs at the margin of GA, it has not been determined if there are also increased FVs extending beyond the margin of GA throughout the remainder of the macular region. To better understand how CC perfusion is affected throughout the macula in eyes with GA, it would be useful to compare these FV values to age-similar, normal control eyes. In this study, we used SS-OCTA to examine the CC in vivo in patients with GA secondary to nonexudative AMD and quantified CC perfusion using the methods developed by Zhang et al.28 Using this novel method, we quantified CC perfusion both in a region within 2° of the GA border and over the remaining imaged macular region. FVs in these two regions were compared with overall FVs in images taken from age-similar normal controls. By using healthy eyes without AMD as our controls, rather than the surrounding areas within the same eye, we were able to examine how the CC is affected throughout the entire macula.

Patients and Methods

We performed a prospective, cross-sectional study. Twelve subjects (19 eyes) with GA secondary to nonexudative AMD and 12 age-similar normal controls (12 eyes) were enrolled.

This study was approved by the institutional review board of the University of California, San Francisco. Written informed consent was obtained from all subjects before performing any study procedures. The study was performed in accordance with the tenets of the Declaration of Helsinki and compliant with the Health Insurance Portability and Accountability Act.

OCTA Image Acquisition

This study utilized a SS-OCTA system (PLEX Elite 9000; Carl Zeiss Meditec, Dublin, CA), running at a speed of 100 kHz and central wavelength of 1,060 nm. A scan pattern with a field of view of 6 mm × 6 mm centered on the fovea was used for all subjects. This scan contains 500 A-scans × 500 B-scans with two repeated scans consecutively at each location, with a scanning depth of 3 mm over 1,536 pixels and transverse pixel spacing of 12 μm. The FastTrac (Carl Zeiss Meditec, Dublin, CA) motion-correction software was used while images were acquired. OCTA images were generated using the complex optical microangiography (OMAGc) algorithm.29 OMAGc identifies differences in intensity and phase information of B-scans repeated at the same location to produce the motion signal, an indication of blood flow.16–18

En face images of the CC were evaluated in this study. A validated semiautomated segmentation algorithm was used to identify the CC slab, utilizing manual corrections to ensure accuracy of the segmentation.30 The CC slab was defined as a layer starting at the outer boundary of BM to approximately 20 μm below BM. OCTA images with significant motion or shadowing artifacts, a signal strength less than 7 as defined by the manufacturer, or signs of exudative AMD or other macular pathologies were excluded.

Geographic Atrophy and Drusen Identification

Fundus autofluorescence (FAF) images were obtained to identify the presence of GA (Spectralis HRA+OCT; Heidelberg Engineering, Heidelberg, Germany). Regions of GA were identified by reduced autofluorescence on FAF images due to RPE loss, and a manually traced border was applied in Adobe Photoshop CC (Version 2017.1.1; Adobe Systems, San Jose, CA). An additional border was automatically generated extending 2° from the border of GA, creating two separate regions: within 2° of the GA border and outside 2° of the GA border. The FAF images were superimposed onto the en face CC images using vascular landmarks, and regions of GA were excluded from further analysis. The area of GA was expressed as mm2.

Drusen are associated with increased FV due to shadowing artifacts from the elevated RPE/BM complex or an actual reduction in underlying CC flow.4,9,31 To exclude their influence on analysis, drusen were identified on the OCT scans by another segmentation layer, from the RPE to BM, of the structural data set to create drusen maps. These drusen maps were applied to the en face CC images, and choriocapillaris perfusion in these regions also was excluded from further analysis.

Evaluation of Choriocapillaris Flow Voids

CC FVs were evaluated using a recently validated, one standard deviation thresholding method obtained from a database of 20 normal controls.28 FVs were defined in Zhang et al. as a ratio (expressed as percentage) of FV regions divided by the total scanned region.28 In our study, the total analyzed region is the entire 6 mm × 6 mm image, excluding regions of GA and CC underlying drusen. A compensation method utilizing the en face structural CC image was used to account for signal attenuation due to structural changes in the RPE/BM complex.28 A FV segmentation image was generated where green color identifies areas of FV. Three CC FV percentages were generated for eyes with GA: an overall FV percentage, FV percentage within 2° of GA, and FV percentage outside 2° from GA. A single overall FV percentage was quantified for age-similar normal control eyes. Figure 1 illustrates overall FV analysis in a GA eye with drusen and an age-similar normal control. Figure 2 illustrates the analysis with the additional outline extending 2° from the GA border.

Flow void (FV) analysis on an age-similar normal control eye (A and B) and geographic atrophy (GA) eye with drusen (C to F). En face choriocapillaris images (A, E) were obtained using a swept-source optical coherence tomography (OCT) angiography system with a 6 mm × 6 mm scanning pattern. The fundus autofluorescence (FAF) image (C) had regions of GA identified manually with a red outline. Drusen were identified with an automated algorithm based upon the structural OCT dataset with a segmentation layer from the retinal pigment epithelium to Bruch's membrane and outlined in red to create a drusen map (D). FV segmentation images (B, F) for each subject were generated using a one standard deviation thresholding method developed from a normal database. Green color represents FV regions, orange color represents superimposed drusen regions excluded from analysis, and red color represents superimposed GA regions excluded from analysis. Corresponding overall FV percentages for the normal control and GA eye were included on the FV segmentations.

Figure 1.

Flow void (FV) analysis on an age-similar normal control eye (A and B) and geographic atrophy (GA) eye with drusen (C to F). En face choriocapillaris images (A, E) were obtained using a swept-source optical coherence tomography (OCT) angiography system with a 6 mm × 6 mm scanning pattern. The fundus autofluorescence (FAF) image (C) had regions of GA identified manually with a red outline. Drusen were identified with an automated algorithm based upon the structural OCT dataset with a segmentation layer from the retinal pigment epithelium to Bruch's membrane and outlined in red to create a drusen map (D). FV segmentation images (B, F) for each subject were generated using a one standard deviation thresholding method developed from a normal database. Green color represents FV regions, orange color represents superimposed drusen regions excluded from analysis, and red color represents superimposed GA regions excluded from analysis. Corresponding overall FV percentages for the normal control and GA eye were included on the FV segmentations.

Example of flow void (FV) analysis with additional border extending 2° from the geographic atrophy (GA) boundary. Fundus autofluorescence (FAF) image (A) had regions of GA manually identified with a red outline. En face choriocapillaris image (B) was obtained using a swept-source optical coherence tomography angiography system with a 6 mm × 6 mm scanning pattern. FV segmentation image was generated (C, D). Overall FV analysis (C) was performed in which green color represents FV regions and red outline represents excluded GA regions superimposed from FAF images. Additional 2° border analysis (D) was performed in which white outline represents the 2° border, blue color represents FV within 2° of GA, and yellow color represents FV outside 2° of GA. Corresponding FV percentages for each region were included on the FV segmentations.

Figure 2.

Example of flow void (FV) analysis with additional border extending 2° from the geographic atrophy (GA) boundary. Fundus autofluorescence (FAF) image (A) had regions of GA manually identified with a red outline. En face choriocapillaris image (B) was obtained using a swept-source optical coherence tomography angiography system with a 6 mm × 6 mm scanning pattern. FV segmentation image was generated (C, D). Overall FV analysis (C) was performed in which green color represents FV regions and red outline represents excluded GA regions superimposed from FAF images. Additional 2° border analysis (D) was performed in which white outline represents the 2° border, blue color represents FV within 2° of GA, and yellow color represents FV outside 2° of GA. Corresponding FV percentages for each region were included on the FV segmentations.

Statistical Analysis

Descriptive statistics were calculated with means and standard deviations in GA subjects and age-similar normal controls. We compared CC FVs in GA subjects and age-similar normal controls using a linear regression model with standard errors clustered by patient to account for within-patient clustering. Results of quantitative analysis were expressed as mean values ± standard deviations and include 95% confidence intervals. For all analyses, P values less than .05 were considered statistically significant. Analyses were conducted in Stata 14.1 (StataCorp, College Station, TX).

Results

The mean age of the GA subjects and age-similar controls was 80.7 years ± 6.4 years old and 79.3 years ± 5.6 years old, respectively. The mean area of the GA lesion was 5.17 ± 4.47 mm2. Of the 19 GA eyes analyzed, 14 eyes had drusen in which the underlying choriocapillaris was excluded from analysis.

The en face angiograms revealed more extensive overall CC FVs in eyes with GA compared with age-similar normal controls (FV: 19.75 ± 4.38%, 95% confidence interval [CI]: 17.63% to 21.86% and 9.78 ± 1.84%, 95% CI: 8.61% to 10.95 %, respectively [P < .001]) (Figure 3). CC FVs inside the 2° border were significantly increased compared with outside the 2° border (FV: 27.56 ± 10.24%, 95% CI: 22.63% to 32.50% and 17.44 ± 4.36%, 95% CI: 15.33% to 19.54%, respectively [P < .001]. FVs in both the inside and outside 2° border regions were significantly increased compared with age-similar normal controls (P < .001 and P < .001, respectively). There was no significant correlation between FV percentage and GA size or the presence of drusen.

Mean flow void percentages for age-similar normal controls and geographic atrophy (GA) eyes, additionally broken down by 2° region, with 95% confidence interval error bars (P < .001*).

Figure 3.

Mean flow void percentages for age-similar normal controls and geographic atrophy (GA) eyes, additionally broken down by 2° region, with 95% confidence interval error bars (P < .001*).

Discussion

Using SS-OCTA to compare flow voids in patients with GA and age-similar normal controls, we found that there were significantly more extensive choriocapillaris perfusion defects throughout the macular region, including regions extending beyond 2° from the GA border, in patients with nonexudative AMD and GA compared with age-similar control eyes. The extent of FV regions did not correlate with either GA area or the presence of drusen, although this study was not powered for these analyses.

Recent studies utilizing OCTA systems and intrapatient analysis have likewise shown increased CC defects at the margins of GA.19–31,23–24 We extend the results of these studies by examining CC FVs throughout the macula, excluding regions of CC underlying drusen, and comparing CC perfusion levels to age-similar normal controls. The method we used to quantify CC perfusion in the present study has been shown to have high levels of repeatability, compensates for signal loss from the RPE/BM complex, and uses a threshold based on a database of normal subjects. By using age-similar normal subjects as our control, instead of the surrounding area outside the GA margin, we were able to quantify CC perfusion levels throughout the posterior pole. Our results show that there is significant CC impairment throughout the macular region in eyes with GA, including regions greater than 2° from the border of GA.

Like Sacconi et al. and Nassisi et al., we did not see a correlation between CC perfusion and GA size.23,24 It is worth noting that we did not see a correlation between CC perfusion and the presence of drusen despite previous studies reporting CC defects in subjects with drusen alone.2,9,31 This may be due to our small sample size or the exclusion of the CC underneath drusen from FV analysis, as drusen can create shadow artifacts that may affect estimates of CC perfusion.

OCTA is an in vivo technique that visualizes blood flow within CC vessels. Static structure of intact but nonfunctioning CC vessels or choriocapillaris vessels with slow flow may not be visible using OCTA. As highlighted by Choi et al. in their study of CC flow impairments using variable interscan time analysis outside the margin of GA, it is difficult to determine which CC FVs are the result of flow impairment or atrophy using OCTA.19 Previous histological studies of CC structure in patients with nonexudative AMD have observed CC dropout outside the margins of GA. Further, since FV analysis of the choriocapillaris was performed in areas where FAF showed non-atrophic RPE, the results suggest that choriocapillaris hypoperfusion may occur independently of RPE cell loss. These results, in combination with previous studies, lead us to believe that CC ischemia may contribute to the pathology of nonexudative AMD.4,9–10,13,19–24,31

In conclusion, this study demonstrates significantly greater CC hypoperfusion throughout the macular region in patients with GA secondary to nonexudative AMD when compared with age-similar normal control patients. Further investigation is needed to understand the complex relationship between the CC, RPE, and overlying photoreceptors. Similar FV analysis of the CC in longitudinal studies involving early and intermediate-stage AMD could provide additional insight into a potential ischemic pathogenesis of AMD. The ability to quantify CC perfusion using SS-OCTA should prove to be a valuable tool in evaluating the development, progression, and response to therapy of nonexudative AMD.

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Authors

From the Department of Ophthalmology, University of California, San Francisco (NTR, CK, CEO, JLD, DMS); the Department of Bioengineering, University of Washington, Seattle (HZ, QZ, RKW); and the Francis I. Proctor Foundation, University of California, San Francisco (CEO).

Supported by the National Institutes of Health (EY002162, EY024239, EY24158), U.S. Food and Drug Administration (R01-41001), L.L. Hillblom Foundation Research Network Grant, That Man May See, Inc., Foundation Fighting Blindness, Research to Prevent Blindness, Bernard A. Newcomb Macular Degeneration Fund, Hope for Vision, Beckman Initiative for Macular Research [1201], Claire Giannini Fund, Hedco Foundation, Pritzker Foundation, and Advanced Retina Imaging Network.

Zhang and Wang report a patent with the University of Washington. Duncan reports grants from the L.L. Hillblom Foundation during the conduct of the study, as well as grants and personal fees from Foundation Fighting Blindness; nonfinancial support from Ocugen; and personal fees from Editas, AGTC, Spark Therapeutics, SparingVision, ProQR Therapeutics, and Imagine Eyes outside the submitted work. Wang reports grants from the National Eye Institute; grants, nonfinancial support, and other funding from Carl Zeiss Meditec; and grants from Moptim during the conduct of the study, as well as grants from the National Institutes of Health, Colgate-Palmolive Company, and Facebook Technologies outside the submitted work. Schwartz reports grants from the L.L. Hillblom Foundation during the conduct of the study, as well as personal fees from RxSight and Varocto outside the submitted work. In addition, Schwartz has a patent for OCTA technology issued. The remaining authors report no relevant financial disclosures.

Address correspondence to Daniel M. Schwartz, MD, 10 Koret Way, San Francisco, CA 94117; email: Dan.Schwartz@ucsf.edu.

Received: November 30, 2018
Accepted: March 22, 2019

10.3928/23258160-20190905-14

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