Purpose
Choriocapillaris (CC) imaging of normal eyes with swept-source optical coherence tomographic angiography (SS-OCTA) was performed, and the percentage of CC flow deficits (FD%) and the average area of CC flow deficits (FDa) were compared within the given macular regions.
Design
A prospective, cross-sectional study.
Methods
Subjects with normal eyes ranging in age from their 20s through their 80s were imaged with SS-OCTA (PLEX Elite 9000; Carl Zeiss Meditec, Dublin, California, USA) using both 3×3-mm and 6×6-mm macular scan patterns. The CC images were generated using a previously published and validated algorithm. In both 3×3-mm and 6×6-mm scans, the CC FD% and FDa were measured in circular regions centered on the fovea with diameters as 1 mm and 2.5 mm (C 1 and C 2.5 ). In 6×6-mm scans, the FD% and FDa were measured within an additional circular region with diameter as 5 mm (C 5 ). The correlations between FD% and FDa from each region were analyzed with Pearson correlation coefficients.
Results
A total of 164 eyes were analyzed. There was excellent correlation between CC FDa and FD% measurements from each region. In the 3×3-mm scans, the correlations in the C 1 and C 2.5 regions were 0.83 and 0.90, respectively. In the 6×6-mm scans, the correlations in C 1 , C 2.5 , and C 5 regions were 0.90, 0.89, and 0.89, respectively.
Conclusions
When measuring CC FDs, we found excellent correlations between FDa and FD% in regions from 3×3-mm and 6×6-mm scans. Further studies are needed to determine if one parameter is more useful when studying diseased eyes.
The choriocapillaris (CC) is a single capillary layer located under Bruch membrane (BM) and provides metabolic support for the outer retina, retinal pigment epithelium, and choroidal stroma. , In a histopathologic study using autopsy eyes, Ramrattan and associates found that the CC vascular density decreased with age in normal eyes. With the advent of optical coherence tomographic angiography (OCTA), CC can be visualized and quantified in vivo. Consistent with the histologic findings, OCTA studies have confirmed an age-dependent CC flow impairments with the greatest impairment in the central macula. , , In addition, CC flow impairments evaluated using OCTA has been reported in eyes with diseases such as age-related macular degeneration (AMD), diabetic retinopathy, central serous chorioretinopathy, retinitis pigmentosa, idiopathic epiretinal membrane, Vogt-Koyanagi-Harada disease, and Alport syndrome. , However, the extent of CC flow impairments reported from different studies have been difficult to compare because different instruments and algorithms have been used to generate and analyze the CC en face flow images and because the capillaries of the CC are beyond the resolution of commercial OCTA instruments, so investigators lack the ground truth evidence that they are truly imaging the CC in vivo based on OCTA images. , ,
Different terms have been used to evaluate CC flow and flow impairments such as CC vessel flow density, vessel density, vessel diameter index, perfusion density, vessel length density, flow voids, gray value, signal voids, percentage choriocapillaris area of nonperfusion, , , but we prefer to use the term flow deficits (FDs), since these areas represent regions of undetectable CC flow when using a particular instrument and algorithm rather than the absolute absence of physiological CC flow, because flow might be detectable under different circumstances. ,
We recently reported the age-dependent CC FD percentage (FD%) changes within the macula using SS-OCTA imaging. Overall, the CC FD% was found to be increased with age, but the greatest increase was found in the 1-mm circle (C 1 ) region centered on the fovea. Later, we performed a study to explore the relationship between the annual enlargement rates (ERs) of geographic atrophy (GA) in late nonexudative AMD and the CC FDs around the GA. We found a good linear correlation between ERs and the CC FD%, but there was an even stronger linear correlation between ERs and the average area of individual CC flow deficits (FDa). Even though both CC FD% and FDa measurements were highly correlated with each other in eyes with GA, they represent different parameters that are not mutually exclusive. Based on processed CC binary images, FD% is defined as the number of pixels that represent areas with an undetected flow signal divided by the total pixels in a giving area. CC FDa is defined instead as the average area of the pixels representing flow deficits in a giving area. Our previous findings were that both FD% and FDa were correlated with GA growth and that FDa had a stronger correlation with GA growth. Because an enlarging FD area may have a greater detrimental effect on the overlying retinal pigment epithelium and photoreceptors than multiple smaller FDs and have a greater influence on the growth of GA, especially at the margins of GA, we wanted to explore if these enlarging FD areas also had a stronger correlation with aging when compared with FD% in our normative database. After all, if we want to compare the CC FDs in diseased eyes with age-matched normal control eyes to determine if any disease-specific differences exist, then we need to know how all the different parameters used to measure CC FDs behave in normal eyes. This current study reports on the comparison between these 2 CC FD parameters, FD% and FDa, in normal eyes over 7 decades of life.
Methods
This prospective study was approved by the institutional review board of University of Miami Miller School of Medicine. Informed consent was obtained from each enrolled subject. The study was performed in accordance with the tenets of the Declaration of Helsinki and complied with the Health Insurance Portability and Accountability Act of 1996.
Subjects with normal eyes from their 20s through their 80s were enrolled in this study at the Bascom Palmer Eye Institute from November 2016 through February 2018 as described previously. Both eyes from each subject were scanned using SS-OCTA (PLEX Elite 9000; Carl Zeiss Meditec, Dublin, California, USA), and the right eye was the default eye unless the image quality was poor as a result of gross eye movements or weak signal strength (less than 7) as defined by the manufacturer. Subjects with uncontrolled hypertension and diabetes mellitus even without any evidence of diabetic retinopathy were excluded from the study. Eyes with any history of ocular disease, retinal or choroidal pathology, a refractive error ≥ −6.0 diopters or axial length (AL) ≥26.00 mm were excluded. AL was measured on each eye using a noncontact biometry instrument (IOL Master; Carl Zeiss Meditec).
SS-OCTA images were obtained using the instrument with a scanning rate of 100,000 A-scans per second, a central wavelength of 1,060 nm, and a full width at half-maximum axial resolution of ~5 μm in tissue. Both 3×3-mm and 6×6-mm scan patterns centered on the fovea were performed on each eye. FastTrack motion correction software was used during image acquisition. Each 3×3-mm scan consisted of 300 A scans per B scan with 4 repeats at each position before moving to the next sequential B scan location, which results in a homogenous sampling grid with an A scan and B scan separation of 10 μm. Each 6×6-mm scan consisted of 500 A scans per B scan. Two repeated B scans were performed at each position, resulting in a homogenous sampling grid with a separation of 12 μm.
Flow images were generated by applying the complex optical microangiography (OMAG c ) algorithm and first normalized to reach a signal strength of 9 before further analysis. We recently investigated the CC in normal eyes over a range of ages using SS-OCTA. CC flow was detected using the OMAG c algorithm as previously described. , The CC en face flow images were generated using a semiautomatic segmentation method using a 20-μm-thick slab that followed the contour of the BM and was about 10 μm under the BM. , , A compensation strategy using the corresponding CC en face structural images was adopted to adjust for any signal loss in the CC en face flow images due to the overlying anatomy. , Retinal vessel projection artifacts were removed and a global thresholding method (standard deviations of the CC from 20 young subjects) was applied to the CC en face flow images to generate the CC FD binary maps. , The final step was to remove the isolated segmented regions with an equivalent diameter smaller than 24 μm from the CC FD binary maps, as they were presumed to be smaller than the estimated ICD and thus most likely represent noise. , CC FDa was measured based on the final processed CC binary maps. Although CC FD% was defined as the number of pixels representing FDs divided by the total pixels within a given region, the CC FDa was defined as the total area of all the pixels that represent CC FDs divided by the number of FDs within a given region ( Figure 1 ). For 3×3-mm scan patterns, we analyzed CC FDa in circles centered on the fovea with diameters as 1 mm (C 1 ) and 2.5 mm (C 2.5 ), and we analyzed an additional circle region with diameter as 5 mm (C 5 ) in the 6×6-mm scan pattern as described in our previous study.
The mean and normal range of CC FDa from each region and each decade was calculated and analyzed using a linear regression model. We then compared the CC FDa measurements with the CC FD% measurements from the same regions and age groups, which were reported in our previous study. The correlations between the CC FDa and FD% measurements were analyzed using Pearson correlation coefficients. In addition, the CC FDa measurements from the C 1 and C 2.5 regions in the 3×3-mm and 6×6-mm scans were compared and correlated. Statistical analyses were performed using the IBM Statistical Package for the Social Sciences (SPSS) software version 24 (IBM Corporation, Armonk, New York, USA), with a P value of <.05 considered to be statistically significant.
Results
A total of 164 normal eyes from 164 participants were included in this study with a mean AL of 23.00 mm (SD = 1.0 mm). The mean age of the patients was 56 years (SD = 19 years, range 19-88), and women comprised 56% of the study population.
There were no correlations between CC FDa measurements and AL in normal eyes (all | r | < 0.15, all P > .05). The CC FDa measurements from all the regions were increased with age in both the 3×3-mm and 6×6-mm scans. The mean of the CC FDa measurements, their SDs, and their ranges in each decade of life and within each region from the 3×3-mm scans are shown in Table 1 . The age-related CC FDa increases were greater in the C 1 region compared with the C 2.5 region from 3×3-mm scans. Table 2 shows the FDa measurements for the 6×6-mm scans. Consistent with the results from the 3×3-mm scans, the age-related CC FDa measurements were greater in the C 1 region compared with the C 2.5 and C 5 regions from the 6×6-mm scans. For each region in each scan pattern, linear regression models using FDa with respect to age were fitted, and highly significant relationships for each parameter were found (all P < .001).
| Region Quantified | Age Group | ||||||
|---|---|---|---|---|---|---|---|
| 19-29 (n= 18) | 30-39 (n = 23) | 40-49 (n = 22) | 50-59 (n = 23) | 60-69 (n = 28) | 70-79 (n = 31) | 80-89 (n = 19) | |
| 1-mm circle, mm 2 mean (SD) [range] | 0.0008 (0.0003) [0.0005-0.0014] | 0.0010 (0.0003) [0.0006-0.0020] | 0.0012 (0.0003) [0.0006-0.0018] | 0.0015 (0.0004) [0.0008-0.0025] | 0.0015 (0.0005) [0.0008-0.0024] | 0.0022 (0.0010) [0.0008-0.0049] | 0.0028 (0.0029) [0.0010-0.0137] |
| 2.5-mm circle, mm 2 mean (SD) [range] | 0.0009 (0.0001) [0.0007-0.0013] | 0.0010 (0.0002) [0.0007-0.0017] | 0.0012 (0.0004) [0.0007-0.0025] | 0.0014 (0.0002) [0.0010-0.0019] | 0.0013 (0.0003) [0.0009-0.0020] | 0.0016 (0.0004) [0.0008-0.0025] | 0.0017 (0.0005) [0.0012-0.0034] |
| Region Quantified | Age Group | ||||||
|---|---|---|---|---|---|---|---|
| 19-29 (n =18) | 30-39 (n =23) | 40-49 (n =22) | 50-59 (n =23) | 60-69 (n =28) | 70-79 (n =31) | 80-89 (n =19) | |
| 1-mm circle, mm 2 , mean (SD) [range] | 0.0012 (0.0003) [0.0008-0.0019] | 0.0013 (0.0003) [0.0006-0.0018] | 0.0015 (0.0005) [0.0009-0.0031] | 0.0023 (0.0009) [0.0009-0.0042] | 0.0020 (0.0006) [0.0012-0.0032] | 0.0027 (0.0016) [0.0010-0.0090] | 0.0031 (0.0020) [0.0012-0.0088] |
| 2.5-mm circle, mm 2 , mean (SD) [range] | 0.0013 (0.0003) [0.0009-0.0022] | 0.0015 (0.0004) [0.0009-0.0024] | 0.0016 (0.0004) [0.0010-0.0027] | 0.0021 (0.0007) [0.0011-0.0047] | 0.0019 (0.0004) [0.0013-0.0027] | 0.0021 (0.0006) [0.0013-0.0044] | 0.0023 (0.0006) [0.0016-0.0041] |
| 5-mm circle, mm 2 , mean (SD) [range] | 0.0012 (0.0002) [0.0010-0.0016] | 0.0014 (0.0003) [0.0010-0.0021] | 0.0015 (0.0002) [0.0010-0.0018] | 0.0017 (0.0003) [0.0011-0.0028] | 0.0017 (0.0003) [0.0012-0.0028] | 0.0018 (0.0003) [0.0012-0.0027] | 0.0019 (0.0003) [0.0014-0.0023] |
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