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.
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.
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).
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*).
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.
- Wybar KC. A study of the choroidal circulation of the eye in man. J Anat. 1954;88(1):94–98.13129174
- Bhutto I, Lutty G. Understanding age-related macular degeneration (AMD): relationships between the photoreceptor/retinal pigment epithelium/Bruch's membrane/choriocapillaris complex. Mol Aspects Med. 2012;33(4):295–317. doi:10.1016/j.mam.2012.04.005 [CrossRef]22542780
- Schlingemann RO. Role of growth factors and the wound healing response in age-related macular degeneration. Graefes Arch Clin Exp Ophthalmol. 2004;242(1):91–101. doi:10.1007/s00417-003-0828-0 [CrossRef]
- McLeod DS, Grebe R, Bhutto I, Merges C, Baba T, Lutty GA. Relationship between RPE and choriocapillaris in age-related macular degeneration. Invest Ophthalmol Vis Sci. 2009;50(10):4982–4991. doi:10.1167/iovs.09-3639 [CrossRef]19357355
- Holz FG, Strauss EC, Schmitz-Valckenberg S, van Lookeren Campagne M. Geographic atrophy: Cinical features and potential therapeutic approaches. Ophthalmology. 2014;121(5):1079–1091. doi:10.1016/j.ophtha.2013.11.023 [CrossRef]24433969
- Boyer DS, Schmidt-Erfurth U, van Lookeren Campagne M, Henry EC, Brittain C. The pathophysiology of geographic atrophy secondary to age-related macular degeneration and the complement pathway as a therapeutic target. Retina. 2017;37(5):819–835. doi:10.1097/IAE.0000000000001392 [CrossRef]
- Yehoshua Z, de Amorim Garcia Filho CA, Nunes RP, et al. Systemic complement inhibition with eculizumab for geographic atrophy in age-related macular degeneration: The COMPLETE study. Ophthalmology. 2014;121(3):693–701. doi:10.1016/j.ophtha.2013.09.044 [CrossRef]
- Petrou PA, Cunningham D, Shimel K, et al. Intravitreal sirolimus for the treatment of geographic atrophy: Results of a phase I/II clinical trial. Invest Ophthalmol Vis Sci. 2014;56(1):330–338. doi:10.1167/iovs.14-15877 [CrossRef]25525171
- Sarks SH, Arnold JJ, Killingsworth MC, Sarks JP. Early drusen formation in the normal and aging eye and their relation to age related maculopathy: A clinicopathological study. Br J Ophthalmol. 1999;83(3):358–368. doi:10.1136/bjo.83.3.358 [CrossRef]10365048
- Seddon JM, McLeod DS, Bhutto IA, et al. Histopathological insights into choroidal vascular loss in clinically documented cases of age-related macular degeneration. JAMA Ophthalmol. 2016;134(11):1272–1280. doi:10.1001/jamaophthalmol.2016.3519 [CrossRef]27657855
- Arya M, Sabrosa AS, Duker JS, Waheed NK. Choriocapillaris changes in dry age-related macular degeneration and geographic atrophy: A review. Eye Vis (Lond). 2018;5:22. doi:10.1186/s40662-018-0118-x [CrossRef]
- Moreira-Neto CA, Moult EM, Fujimota JG, Waheed NK, Ferrara D. Choriocapillaris loss in advanced age-related macular degeneration. J Ophthalmol. 2018;2018:8125267.29651346
- McLeod DS, Taomoto M, Otsuji T, Green WR, Sunness JS, Lutty GA. Quantifying changes in RPE and choroidal vasculature in eyes with age-related macular degeneration. Invest Ophthalmol Vis Sci. 2002;43(6):1986–1993.12037009
- An L, Subhush HM, Wilson DJ, Wang RK. High-resolution wide-field imaging of retinal and choroidal blood perfusion with optical microangiography. J Biomed Opt. 2010;15(2):026011. doi:10.1117/1.3369811 [CrossRef]20459256
- 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:10.1364/OL.35.001467 [CrossRef]20436605
- Choi W, Mohler KJ, Potsaid B, et al. Choriocapillaris and choroidal microvasculature imaging with ultrahigh speed OCT angiography. PLoS One. 2013;8(12):e81499. doi:10.1371/journal.pone.0081499 [CrossRef]24349078
- Kim DY, Fingler J, Zawadzki RJ, et al. Optical imaging of the chorioretinal vasculature in the living human eye. Proc Natl Acad Sci U S A. 2013;110(35):14354–14359. doi:10.1073/pnas.1307315110 [CrossRef]23918361
- Schwartz DM, Fingler J, Kim DY, et al. Phase-variance optical coherence tomography: A technique for noninvasive angiography. Ophthalmology. 2014;121(1):180–187. doi:10.1016/j.ophtha.2013.09.002 [CrossRef]
- Choi W, Moult EM, Waheed NK, et al. Ultrahigh-speed, swept-source optical coherence tomography angiography in nonexudative age-related macular degeneration with geographic atrophy. Ophthalmology. 2015;122(12):2532–2544. doi:10.1016/j.ophtha.2015.08.029 [CrossRef]26481819
- Moult EM, Waheed NK, Novais EA, et al. Swept source optical coherence tomography angiography reveals choriocapillaris alterations in eyes with nascent geographic atrophy and drusen-associated geographic atrophy. Retina. 2016;36Suppl 1:S2–S11. doi:10.1097/IAE.0000000000001287 [CrossRef]
- Gorczynska I, Migacz JV, Jonnal R, Zawadzki RJ, Poddar R, Werner JS. Imaging of the human choroid with a 1.7 MHz A-scan rate FDML swept source OCT system. Proc SPIE. 2017;10045:1004510. doi:10.1117/12.2251704 [CrossRef]
- Kashani AH, Chen CL, Gahm JK, et al. Optical coherence tomography angiography: A comprehensive review of current methods and clinical applications. Prog Retin Eye Res. 2017;60:66–100. doi:10.1016/j.preteyeres.2017.07.002 [CrossRef]28760677
- Nassisi M, Shi Y, Fan W, et al. Choriocapillaris impairment around the atrophic lesions in patients with geographic atrophy: A swept-source optical coherence tomography angiography study. Br J Ophthalmol. 2019;103(7):911–917. doi:10.1136/bjophthalmol-2018-312643 [CrossRef]
- Sacconi R, Corbelli E, Carnevali A, Querques L, Bandello F, Querques G. Optical coherence tomography angiography in geographic atrophy. Retina. 2018;38(12):2350–2355.
- Zhang Q, Chen CL, Chu Z, et al. Automated quantitation of choroidal neovascularization: A comparison study between spectral-domain and swept-source OCT angiograms. Invest Ophthalmol Vis Sci. 2017;58(3):1506–1513. doi:10.1167/iovs.16-20977 [CrossRef]28273317
- Copete S, Flores-Moreno I, Montero JA, Duker JS, Ruiz-Moreno JM. Direct comparison of spectral-domain and swept-source OCT in the measurement of choroidal thickness in normal eyes. Br J Ophthalmol. 2014;98(3):334–338. doi:10.1136/bjophthalmol-2013-303904 [CrossRef]
- Miller AR, Roisman L, Zhang Q, et al. Comparison between spectral-domain and swept-source optical coherence tomography angiographic imaging of choroidal neovascularization. Invest Ophthalmol Vis Sci. 2017;58(3):1499–1505. doi:10.1167/iovs.16-20969 [CrossRef]28273316
- Zhang Q, Zheng F, Motulsky EH, et al. A novel strategy for quantifying choriocapillaris flow voids using swept-source OCT angiography. Invest Ophthalmol Vis Sci. 2018;59(1):203–211. doi:10.1167/iovs.17-22953 [CrossRef]29340648
- Wang RK, Zhang A, Choi WJ, et al. Wide-field optical coherence tomography angiography enabled by two repeated measurements of B-scans. Opt Lett. 2016;41(10):2330–2333. doi:10.1364/OL.41.002330 [CrossRef]27176995
- Yin X, Chao JR, Wang RK. User-guided segmentation for volumetric retinal optical coherence tomography images. J Biomed Opt. 2014;19(8):086020. doi:10.1117/1.JBO.19.8.086020 [CrossRef]25147962
- Lane M, Moult EM, Novais EA, et al. Visualizing the choriocapillaris under drusen: comparing 1050-nm swept-source versus 840-nm spectral-domain optical coherence tomography angiography. Invest Ophthalmol Vis Sci. 2016;57(9):OCT585–OCT590. doi:10.1167/iovs.15-18915 [CrossRef]27547891