February 2015
Volume 56, Issue 2
Free
Retina  |   February 2015
Choroidal Thickness in Geographic Atrophy Secondary to Age-Related Macular Degeneration
Author Affiliations & Notes
  • Moritz Lindner
    Department of Ophthalmology, University of Bonn, Bonn, Germany
  • Athanasios Bezatis
    Department of Ophthalmology, University of Bonn, Bonn, Germany
  • Joanna Czauderna
    Department of Ophthalmology, University of Bonn, Bonn, Germany
  • Eva Becker
    Department of Ophthalmology, University of Bonn, Bonn, Germany
  • Christian K. Brinkmann
    Department of Ophthalmology, University of Bonn, Bonn, Germany
  • Steffen Schmitz-Valckenberg
    Department of Ophthalmology, University of Bonn, Bonn, Germany
  • Rolf Fimmers
    Institute of Biostatistics, University of Bonn, Bonn, Germany
  • Frank G. Holz
    Department of Ophthalmology, University of Bonn, Bonn, Germany
  • Monika Fleckenstein
    Department of Ophthalmology, University of Bonn, Bonn, Germany
Investigative Ophthalmology & Visual Science February 2015, Vol.56, 875-882. doi:10.1167/iovs.14-14933
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Moritz Lindner, Athanasios Bezatis, Joanna Czauderna, Eva Becker, Christian K. Brinkmann, Steffen Schmitz-Valckenberg, Rolf Fimmers, Frank G. Holz, Monika Fleckenstein; Choroidal Thickness in Geographic Atrophy Secondary to Age-Related Macular Degeneration. Invest. Ophthalmol. Vis. Sci. 2015;56(2):875-882. doi: 10.1167/iovs.14-14933.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose.: To analyze choroidal thickness (CT) in eyes with geographic atrophy (GA) secondary to age-related macular degeneration (AMD).

Methods.: A total of 72 eyes of 72 patients (mean age, 75.97 ± 7.09 years) with GA and 37 eyes of 37 healthy controls (73.89 ± 6.19 years) were examined by confocal scanning laser ophthalmoscopy and enhanced depth imaging (EDI) spectral-domain optical coherence tomography. Choroidal thickness was measured at 25 defined points in horizontal and vertical scans. Geographic atrophy size was determined in fundus autofluorescence (FAF) images and GA subtypes were classified based on abnormal FAF in the perilesional zone.

Results.: In GA, subfoveal CT (fCT) was significantly thinner compared to controls (173.03 ± 90.22 vs. 253.95 ± 69.19 μm, P < 0.001). Analysis of averaged measurements of all 25 points obtained per patient (mCT) revealed similar results (162.07 ± 76.26 vs. 228.00 ± 66.24 μm, P < 0.001). Spatial differences in CT between both groups were largest superior to the fovea. Addressing “diffuse-trickling” (n = 15) and “non–diffuse-trickling” (n = 57) GA independently, fCT was 114.67 ± 43.32 and 188.39 ± 93.26 μm, respectively (P = 0.002), with both groups being significantly thinner than controls (P < 0.001 for “diffuse-trickling” and P < 0.001 for “?non–diffuse-trickling”). Similar results were obtained for mCT, which was 110.21 ± 29.66 μm in “diffuse-trickling,” 175.72 ± 79.02 μm in “?non–diffuse-trickling” and 228.00 ± 66.24 μm in controls. Differences were significant with P = 0.002 between both GA groups and P ≤ 0.001 toward controls for each GA group.

Conclusions.: The results indicate that the choroid in eyes with GA is thinner compared to normal eyes of similar age. Hereby, the extent of thinning is most pronounced in a specific subtype of GA identified by FAF imaging (“diffuse trickling”). Such GA subtype–related differences in choroidal thickness may reflect heterogeneity in the pathogenesis of disease. (ClinicalTrials.gov number, NCT02051998.)

Introduction
Geographic atrophy (GA) represents a common late stage manifestation of various retinal diseases, including advanced age-related macular degeneration (AMD). While choroidal neovascularization (CNV) is a common cause of severe acute visual loss in AMD, approximately 20% of AMD patients who are legally blind have lost central vision due to GA.15 Although the exact pathogenetic mechanisms leading to GA still are poorly understood, chronic inflammatory processes, excessive lipofuscin accumulation in the RPE lysosomal compartment, complement system dysregulation, and vascular factors have been implicated in the development of AMD (see prior review6). 
Histologically, areas of GA are characterized by degeneration of the RPE, of outer layers of the neurosensory retina, and the choriocapillaris.7,8 In vivo visualization of cross-sectional morphology of the retina and the RPE/Bruch's membrane complex has become possible by the advent of optical coherence tomography (OCT).9,10 Recently implication of enhanced depth imaging (EDI) in spectral-domain OCT (SD-OCT) devices enabled the evaluation of structures beyond Bruch's membrane, in particular the entire choroid and the choroidoscleral interface, thereby reproducible measurement of choroidal thickness (CT) became possible.9,11 
Several studies have assessed CT in AMD.1224 Some investigators find that CT is generally thinned in patients with AMD.12,13,16 Results obtained by others additionally suggest that choroidal thinning is present already in early stages of AMD without GA or neovascularization.13,23 In contrast, the work of Jonas et al.21 with a remarkable high case number did not show significant difference in CT between patients with AMD without GA and controls, after correcting for known influence factors. Also, Lee et al.22 did not find significant thinning of CT in early AMD. Two recent studies have assessed CT in GA in particular and concordantly find that the choroid is thinned in eyes with this late stage manifestation of AMD.19,22 
Recent developments in retinal imaging allow for refined phenotyping of patients with GA. Based on abnormal patterns of fundus autofluorescence (FAF) in the perilesional zone of GA, different phenotypes have been identified in the context of the “Fundus-Autofluorescence imaging in Age-related Macular Degeneration” (FAM) study (NCT00393692).25,26 Preliminary observations by SD-OCT imaging suggest that the “diffuse-trickling” phenotype exhibits a significantly thinner subfoveal choroid compared to other GA subtypes.27 This phenotype is characterized by a lobular GA configuration and a significantly faster progression compared to other GA phenotypes.25,28 Recent data further suggest an association of cardiovascular diseases with this GA subtype.27 
In view of these findings, a more refined analysis of choroidal thickness in GA with a focus on this specific phenotype appears prudent. In the present study, we analyzed choroidal thickness at multiple locations in the macula and investigated topographic differences between “diffuse-trickling” GA, “non–diffuse-trickling” GA, and controls, respectively. Furthermore, we assessed the correlation between GA size and subfoveal choroidal thickness. 
Methods
Patients
Patients with GA secondary to AMD were recruited in the context of the “Directional Spread in Geographic Atrophy” (DSGA) study (NCT02051998), which represents an extension trial of the FAM study (NCT00393692). Patients without retinal disease (“controls”) of similar age were recruited at the Department of Ophthalmology, University of Bonn. The study protocol complied with the Declaration of Helsinki and was approved by the institutional review board (File No. 197/12). Informed consent was obtained from each participant after explanation of the study's nature and possible consequences of participation. 
Only patients above 55 years of age willing to undergo the examination procedure, and with clear ocular media that allowed FAF and OCT imaging were included into the study. For inclusion into the GA group, GA secondary to AMD had to be present in the study eye with no signs of exudation. For inclusion in the control group, the absence of any stage of AMD was required. 
General exclusion criteria were the presence of retinal diseases that could possibly confound the observations (e.g., diabetic retinopathy, retinal dystrophy, present or past exudative AMD, idiopathic serous chorioretinopathy), glaucoma, or refractive error > ±3 diopters (D) spherical equivalent (SE). In case of previous cataract surgery, SE before surgery must have fulfilled this criterion or, if SE was not available, axis length had to be within the limit of 22.5 ± 1 mm (determined by IOL Master; Carl Zeiss Meditec, Jena, Germany). If both eyes were eligible, the right eye was selected as study eye. 
Image Acquisition
The FAF images were obtained using Spectralis HRA+OCT (Heidelberg Engineering, Heidelberg, Germany) with an excitation wavelength of 488 nm and an emission spectrum of 500 to 700 nm in high speed mode. The field of view was set to 30° × 30° with a minimum resolution of 768 × 768 pixels and centered to the macula. Single FAF images were automatically aligned and averaged to maximize the signal-to-noise ratio using the manufacturer's software (ART-mode, Heidelberg Eye Explorer; Heidelberg Engineering). Horizontal and vertical SD-OCT scans through the fovea were performed with the same device using EDI mode. The OCT scans were averaged (up to 100 single images) by making advantage of the ART-mode to improve the signal-to-noise ratio. The OCT scans were controlled manually to be localized through the fovea (Fig. 1A). 
Figure 1
 
(A) Enhanced depth imaging OCT scans as obtained from a representative patient without (upper) and with (lower) geographic atrophy secondary to AMD, both included into this study. Vertical lines indicate locations where CT measurements were performed. (B, C) Box-and-whiskers plot illustrating the difference between the fCT (B) and mCT (mean of all 25 points measured for each patient, [C]) between controls and GA. Edges of the boxes represent the 25th and 75th percentiles, while the limits of the whiskers symbolize the 1.5-fold IQRs. Horizontal bars in the upper part of the diagram indicate significant differences between the groups (t-test for independent samples).
Figure 1
 
(A) Enhanced depth imaging OCT scans as obtained from a representative patient without (upper) and with (lower) geographic atrophy secondary to AMD, both included into this study. Vertical lines indicate locations where CT measurements were performed. (B, C) Box-and-whiskers plot illustrating the difference between the fCT (B) and mCT (mean of all 25 points measured for each patient, [C]) between controls and GA. Edges of the boxes represent the 25th and 75th percentiles, while the limits of the whiskers symbolize the 1.5-fold IQRs. Horizontal bars in the upper part of the diagram indicate significant differences between the groups (t-test for independent samples).
Image Grading
Image grading included measurements of choroidal thickness and of atrophy size. Furthermore, the GA phenotype was classified based on the perilesional FAF patterns according to Holz et al.25,26 All measurements were performed by two independent readers. 
Measurement of Choroidal Thickness.
In horizontal and vertical OCT scans, choroidal thickness was measured as the distance between the outer border of OCT band 4 (corresponding to the RPE/Bruch's membrane complex) to the inner scleral border11 using the Heidelberg Eye Explorer “distance tool” (Heidelberg Engineering). Measurements were performed subfoveally and in an interval of 500 μm up to 3 mm superior, inferior, nasal, and temporal of the fovea, respectively, resulting in 25 data points for each patient and eye. Points were measured and included into the analysis regardless of if the point was located right under an atrophic area or outside. If a reader considered a measurement to be impossible at one data point (e.g., due to insufficient imaging quality), this point was excluded from the analysis. When quality of the whole scan was considered insufficient for grading by at least one reader the whole eye was excluded. 
Measurement of Atrophy Size.
Semiautomated atrophy detection and quantification were performed based on FAF images using the RegionFinder software (version 1.7.1; Heidelberg Engineering). In case of discrepancy between the two readers (>0.15 mm2), a senior reader was asked for arbitration. If atrophy exceeded the image frame, making proper determination of GA area impossible, the eye was excluded from the subanalyses correlating GA size and CT. 
Statistical Analysis
Data were analyzed using SPSS 22 (IBM SPSS Statistics, Chicago, IL). Age, SE, and sex were compared between control and GA group using t-test for independent samples or Fisher's exact test, respectively. If only axis length, but not SE, was available, this eye was not included into the comparison of SE. 
With the data obtained from CT measurements, three separate analyses were performed: First, only the values obtained directly subfoveal (fCT) were analyzed. Second, the mean CT (mCT) calculated as the average of all 25 points measured was evaluated analogously. Interobserver agreements for fCT and mCT were assessed using the interclass correlation coefficient (ICC). The ICC was 0.98 for fCT and 0.99 for mCT. Finally, the peripheral data points were analyzed separately. Further analyses of fCT, mCT, and of the peripheral data points were based on the average between the two readers. Inter-reader averages were compared between the different groups. Comparison between the two groups “GA” and “control” was done using an unpaired Student's or Welch's t-test, respectively. Together with the control group, subsequent splitting of the “GA” group into a “diffuse-trickling” and a “non–diffuse-trickling” group resulted in a total of three independent groups. Differences among these three groups were assessed using a 2-way ANOVA followed by a pairwise group comparison in case a difference among the groups was found. Significance was assigned for P < 0.05. 
Finally, GA size was calculated as the average of the measurements of the two readers. In case the senior reader was called, it was calculated as the average between the senior reader and the reader with the closer results. The GA size then was compared between the “diffuse-trickling” and “non–diffuse-trickling GA” groups by an unpaired t-test. Cases where GA size could not be measured were excluded from this analysis. Pearson's correlation coefficient was calculated to test if CT correlated with GA size in the GA-group in general, and in the “diffuse-trickling” and “non–diffuse-trickling” groups independently. 
All obtained values are given as mean ± SD in the text. Median and interquartile range (IQR) are given where indicated. When represented in a box-and-whiskers plot, the upper and the lower edge of the box represent the 25th and the 75th percentiles, respectively. The black horizontal bar in each box represents the median, and upper and lower ends of the whiskers represent the 1.5-fold IQR below or above the 25th and 75th percentiles, respectively. Outliers are given as either circles (moderate outliers between 1.5 and 3 IQR) or asterisks (>3 IQR). 
Results
A total of 72 eyes of 72 patients with GA (22 men, 50 women) and 37 eyes of 37 patients without retinal diseases (“controls,” 15 men, 22 women) were included into the analysis. Two eyes of control participants had to be excluded before the analysis due to insufficient quality of the EDI SD-OCT scans. 
There was no significant difference in the mean age of the two groups (75.97 ± 7.09 vs. 73.89 ± 6.19 years, P = 0.14). Mean SE (recorded at the date of examination or, in pseudophakic eyes, before cataract surgery) in eyes with GA was 0.12 ± 1.56 and 1.10 ± 1.59 D in control eyes (P = 0.003). 
Of the 72 patients with GA, 36 were pseudophakic, while 12 of 37 control patients had undergone cataract surgery before their inclusion into the study. Table 1 gives an overview of the patients' characteristics. 
Table 1
 
Characteristics of Patients With GA and Controls
Table 1
 
Characteristics of Patients With GA and Controls
Control GA Patients
All “Diffuse-Trickling” “Non–Diffuse-Trickling”
Patients, n 37 72 15 57
SE, D (n) 1.10 ± 1.59 0.12 ± 1.56 (67) −0.27 ± 1.87 (14) 0.23 ± 1.47 (53)
Age, y 73.89 ± 6.19 75.97 ± 7.09 74.52 ± 9.53 76.35 ± 6.34
Male, n 15 22  4 18
Phakic, n 25 36  4 32
GA size, mm2 (n) 6.84 ± 5.80 (68) 12.69 ± 8.33 (13) 5.81 ± 4.67 (55)
fCT, μm 253.95 ± 69.19 173.03 ± 90.22 114.67 ± 43.32 188.39 ± 93.26
mCT, μm 228.00 ± 66.24 162.07 ± 76.26 110.22 ± 29.66 175.72 ± 79.02
Comparison of Choroidal Thickness Between Total GA Cohort and Controls
Measurement of CT at the 25 defined locations in all 109 eyes included into the analysis resulted in a total of 2725 points for which data were available from both readers. No data from both readers were available for 133 points (4.8% of total, 5.7% [103 of 1800] in eyes with GA, 3.2% [30 of 925] in controls). Measurement of fCT was possible in all 109 patients. 
In eyes with GA, mean fCT was significantly thinner compared to eyes without retinal diseases (173.03 ± 90.22 vs. 253.95 ± 69.19 μm, P < 0.001). Correspondingly, median fCT was 154.25 μm (IQR 115.63–199.63 μm) for eyes with GA and 260.00 μm (205.00–297.00 μm) for controls (Fig. 1B). 
There was no significant difference in fCT between male and female neither in the GA (162.47 ± 79.62 vs. 177.68 ± 94.89 μm, P = 0.51), nor in the control group (238.70 ± 66.44 vs. 264.34 ± 70.60 μm, P = 0.27). 
Analysis of averaged measurements in horizontal and vertical scans revealed that the choroid in eyes with GA was overall thinner compared to controls (mean mCT, 162.07 ± 76.26 vs. 228.00 ± 66.24 μm, P < 0.001). Median mCT was 147.87 μm (IQR, 119.70–196.19 μm) for eyes with GA and 230.28 μm (IQR, 179.72–271.56 μm) for controls (Fig. 1C). 
The mCT was 152.66 ± 62.06 μm for males and 166.22 ± 81.97 μm for females in the GA group (P = 0.49), and 209.37 ± 60.61 and 240.70 ± 68.24 μm in the control group (P = 0.16), respectively. In respect to location, largest differences in CT between both groups were seen superiorly of the fovea, while inferior and nasally from the fovea, the differences were smallest. The CT at all 25 data points obtained for both groups and their difference are given in Tables 2 and 3
Table 2
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in Horizontal EDI OCT Scans
Table 2
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in Horizontal EDI OCT Scans
Location CT GA, μm CT Control, μm P
T 3000 198.15 ± 58.48 220.93 ± 54.67 0.06
T 2500 184.13 ± 61.75 218.65 ± 55.16 0.006
T 2000 183.04 ± 61.19 222.63 ± 58.05 0.002
T 1500 177.84 ± 63.62 227.03 ± 63.99 <0.001
T 1000 179.94 ± 82.44 229.43 ± 67.50 0.002
T 500 178.69 ± 87.00 236.65 ± 67.92 0.001
fCT 173.03 ± 90.22 253.95 ± 69.19 0.001
N 500 164.71 ± 93.77 247.73 ± 80.37 <0.001
N 1000 152.72 ± 94.70 230.70 ± 87.87 <0.001
N 1500 136.92 ± 89.60 212.730 ± 86.21 <0.001
N 2000 115.87 ± 62.76 183.69 ± 77.52 <0.001
N 2500 100.75 ± 51.63 161.64 ± 78.01 <0.001
N 3000 90.22 ± 42.96 137.95 ± 73.42 0.002
Table 3
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 12 Locations Measured in Vertical EDI OCT Scans
Table 3
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 12 Locations Measured in Vertical EDI OCT Scans
CT GA CT Control P
S 3000 182.85 ± 72.12 261.70 ± 82.90 <0.001
S 2500 174.73 ± 71.65 257.84 ± 86.55 <0.001
S 2000 170.56 ± 84.70 262.53 ± 87.82 <0.001
S 1500 164.16 ± 78.82 264.76 ± 85.17 <0.001
S 1000 161.46 ± 86.93 255.31 ± 71.81 <0.001
S 500 163.98 ± 87.76 251.45 ± 76.81 <0.001
I 500 163.67 ± 90.39 242.92 ± 80.69 <0.001
I 1000 158.55 ± 91.45 228.06 ± 86.83 <0.001
I 1500 150.62 ± 69.79 227.96 ± 83.27 <0.001
I 2000 148.57 ± 61.87 213.40 ± 74.12 <0.001
I 2500 157.62 ± 63.65 205.37 ± 73.02 0.001
I 3000 154.42 ± 60.79 195.17 ± 67.18 0.002
Comparison of Choroidal Thickness Between “Diffuse-Trickling” GA, “Non–Diffuse-Trickling” GA and Controls, Respectively
Mean subfoveal CT (i.e., fCT) in eyes with “diffuse-trickling” GA (n = 15) was thinner compared to eyes with “non–diffuse-trickling” GA (n = 57, 114.67 ± 43.32 vs. 188.39 ± 93.26 μm, P = 0.002). Comparison with control eyes revealed a significantly thinner subfoveal choroid for both groups (“diffuse-trickling” GA versus controls, P < 0.001; “non–diffuse-trickling” GA versus controls, P < 0.001). As illustrated in Figure 2A, median fCT for “diffuse-trickling” GA was 105.50 μm (IQR 86.50−150.50 μm) and 174.50 μm (IQR, 133.25–233.00 μm) for “non–diffuse-trickling” GA. 
Figure 2
 
Box-and-whiskers plot illustrating the difference between fCT (A) and mCT (B) between controls and “diffuse-trickling” and “non–diffuse-trickling” GA. Edges of the boxes and whiskers represent 25th and 75th percentiles and 1.5-fold IQRs, respectively. Horizontal bars in the upper part of the diagram indicate significant differences between the groups. Note that the “control” boxes include the same values as in Figure 1.
Figure 2
 
Box-and-whiskers plot illustrating the difference between fCT (A) and mCT (B) between controls and “diffuse-trickling” and “non–diffuse-trickling” GA. Edges of the boxes and whiskers represent 25th and 75th percentiles and 1.5-fold IQRs, respectively. Horizontal bars in the upper part of the diagram indicate significant differences between the groups. Note that the “control” boxes include the same values as in Figure 1.
Analysis of averaged measurements in horizontal and vertical scans (i.e., mCT) revealed that in “diffuse-trickling” GA the choroid was overall thinner compared to “non–diffuse-trickling” GA (110.22 ± 29.66 vs. 175.72 ± 79.02 μm, P = 0.002) and controls (110.41 ± 30.10 vs. 228.00 ± 66.24 μm, P = 0.001), respectively. The difference between “non–diffuse-trickling” GA and controls was less pronounced, but also significant (P = 0.001). As given in Figure 2B, the median mCT of eyes with “diffuse-trickling” GA was 108.86 μm (IQR, 88.30–127.26 μm) while the median of eyes with “non–diffuse-trickling” GA was 156.45 μm (IQR, 130.85–204.08 μm). 
Analysis of the single CT measurements performed in the peripheral macula showed that differences in CT between controls and “non–diffuse-trickling” and “diffuse-trickling,” respectively, were most evident in the superior direction (Tables 215525). 
Table 4
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in the Horizontal EDI OCT Scans
Table 4
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in the Horizontal EDI OCT Scans
CT “Diffuse-Trickling” P , “Diffuse-Trickling” vs. Controls CT “Non–Diffuse-Trickling” P , “Non–Diffuse-Trickling” vs. Controls
T 3000 163.81 ± 29.60 <0.001 207.08 ± 60.98 0.29
T 2500 145.90 ± 26.81 <0.001 195.15 ± 64.67 0.08
T 2000 145.47 ± 33.73 <0.001 193.28 ± 63.17 0.03
T 1500 129.17 ± 37.19 <0.001 190.88 ± 63.095 0.01
T 1000 129.33 ± 46.21 <0.001 193.26 ± 84.95 0.03
T 500 129.63 ± 43.61 <0.001 191.61 ± 91.15 0.01
fCT 114.67 ± 43.32 <0.001 188.39 ± 93.26 <0.001
N 500 98.53 ± 45.30 <0.001 182.44 ± 95.68 0.001
N 1000 89.13 ± 43.75 <0.001 169.75 ± 97.61 0.003
N 1500 80.17 ± 33.60 <0.001 152.13 ± 93.89 0.002
N 2000 78.30 ± 35.15 <0.001 126.31 ± 64.94 <0.001
N 2500 72.87 ± 22.00 <0.001 108.50 ± 54.871 <0.001
N 3000 69.39 ± 19.57 <0.001 96.84 ± 46.30 0.004
Table 5
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 12 Locations Measured in the Vertical EDI OCT Scans
Table 5
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 12 Locations Measured in the Vertical EDI OCT Scans
CT “Diffuse-Trickling” P , “Diffuse-Trickling” vs. Controls CT “Non–Diffuse-Trickling” P , “Non–Diffuse-Trickling” vs. Controls
S 3000 136.29 ± 38.18 <0.001 196.43 ± 74.25 <0.001
S 2500 127.10 ± 42.85 <0.001 189.32 ± 72.64 <0.001
S 2000 113.50 ± 40.22 <0.001 187.02 ± 87.22 <0.001
S 1500 109.57 ± 35.39 <0.001 179.91 ± 81.04 <0.001
S 1000 103.20 ± 42.62 <0.001 177.95 ± 89.40 <0.001
S 500 104.18 ± 46.00 <0.001 179.20 ± 89.59 <0.001
I 500 110.82 ± 47.73 <0.001 177.12 ± 93.98 0.001
I 1000 99.23 ± 34.14 <0.001 174.44 ± 95.56 0.01
I 1500 95.70 ± 27.72 <0.001 166.46 ± 70.35 <0.001
I 2000 97.47 ± 28.65 <0.001 163.60 ± 61.09 0.001
I 2500 108.37 ± 36.71 <0.001 172.11 ± 62.83 0.03
I 3000 108.11 ± 25.02 <0.001 167.13 ± 61.66 0.05
Correlation Between GA Size and Choroidal Thickness
For 68 eyes with GA, lesions size could be determined (four eyes were not included into this subanalysis; in two eyes with “non–diffuse-trickling” GA, the lesion exceeded the image frame; in two “diffuse-trickling” GA eyes, FAF images were not available at the day of EDI SD-OCT imaging). 
Mean GA size at time of CT measurements was 6.84 ± 5.80 mm2, regardless of the GA subtype. In eyes with “diffuse-trickling” GA (n = 13, 12.69 ± 8.33 mm2), the atrophic lesions were significantly larger than in eyes with “non–diffuse-trickling” GA (n = 55, 5.45 ± 4.42 mm2, P < 0.001). 
Plotting fCT and mCT against GA size revealed a ρ of −0.226 for fCT (P = 0.06) and −0.222 (P = 0.07) for mCT, respectively (Figs. 3A, 3B). In the “diffuse-trickling” GA group ρ was −0.225 (P = 0.460) for fCT and −0.268 (P = 0.376) for mCT (Figs. 3A, 3B, open squares). In the “non–diffuse-trickling” GA group, ρ was −0.060 (P = 0.66) for fCT and −0.054 (P = 0.75) for mCT (Figs. 3A, 3B, black circles). 
Figure 3
 
Subfoveal CT (A) and mean CT (B) are plotted against GA size. “Diffuse-trickling” and “non–diffuse-trickling” GA data points are depicted as open squares and filled circles, respectively.
Figure 3
 
Subfoveal CT (A) and mean CT (B) are plotted against GA size. “Diffuse-trickling” and “non–diffuse-trickling” GA data points are depicted as open squares and filled circles, respectively.
Discussion
The present analysis reveals that CT in eyes with GA is thinner compared to control eyes without retinal disease and, therefore, is in concordance with previous studies.19,22 However, the current study indicated that choroidal thinning is related to the phenotypic variations of GA. Herein, “diffuse-trickling” GA shows a significantly thinner choroid compared to other GA subtypes. The fact that significance was achieved despite the relatively small number of participants illustrates the apparent strength of the effect. 
To assess whether choroidal thinning was a phenomenon equally distributed over the macula or was predominant only in certain regions of the macula, CT was analyzed at multiple locations superior, inferior, nasally, and temporally of the fovea. Analysis revealed that differences were most pronounced in the superior direction. 
The present analysis, in contrast with another recent study on 16 eyes that suggested a dependency between GA size and CT,22 did not reveal a clear correlation between those two parameters despite the considerably larger sample size in the current analysis. 
While choriocapillaris atrophy in GA has been shown by pathohistological studies,7 a more generalized involvement of the choroid is subject to ongoing debates. Thinning of the choroid by 19% in AMD eyes compared to normal age-adjusted eyes, though not significant, has been observed histologically,29 and Spraul et al.30 disclosed a rarefication of large choroidal vessels underneath GA. The present study supports the hypothesis of a thinning of the choroid in GA in general, and not just of the choriocapillaris. The choriocapillaris usually is considered to account for only <5% to 10% of the whole choroidal depth.21,31 In contrast, the mean loss of CT observed here was 32% (fCT) and 29% (mCT), respectively, for all GA and was even more pronounced in the “diffuse-trickling” phenotype. Thus, the loss of CT does not appear to be attributable to choriocapillary thinning only. 
The pronounced thinning of CT in “diffuse-trickling” GA indicated that impairment of large choroidal vessel layer is a feature predominant in this GA phenotype. Indeed, there is resemblance with funduscopic characteristics of “diffuse-trickling”27 to that described in a recently reported entity called “age-related choroidal atrophy.”32 An impaired blood supply due to an atrophic choroid in the elderly was assumed as source of the funduscopic changes. Compared to patients with “age-related choroidal atrophy,” patients of the FAM cohort with “diffuse-trickling” GA27 were considerably younger (mean age at the time of CT measurement was 68.2 ± 10.9 years). Therefore, ageing alone would unlikely be the reason for such changes in this phenotype that may manifest relatively early in life as reported in the original cohort.27 However, in the elder patients there might be a continuum between “diffuse-trickling” GA and “age-related choroidal atrophy.” 
Assessing CT in any disease requires careful control for possible confounders. Several influence factors on CT have been described. These include nutritive, environmental, and constitutional conditions.3341 In the present study, we controlled for age and myopia, two remarkably strong influencing factors.36,37 Concerning myopia, the GA patients in our collective were by 0.91 D more myopic than controls. The CT has been found to decrease by 8.7 to 15 μm per D myopia;36,37 therefore, the effect observed in the current study is unlikely to be explained by differences in refraction. In analog, per year of age, CT has been shown to decrease by 4.1 μm.37 Again, the effect expected by the difference in mean age between the groups can possibly not explain the remarkable thinner choroid in GA patients. Furthermore, in cohorts of younger patients recent studies found that CT was thinner in females than in males (though not significant),42,43 while other studies did not find differences.37 To investigate for a possible confounding effect of distinct sex distributions between the groups, we compared CT between males and females in the control and GA groups separately. In both groups, females exhibited a marginally thicker choroid than men, suggesting that the present findings will likely not have been biased by influences of different sex distribution. 
Influence of IOP or blood pressure on CT has been discussed previously. A recent study, however, showed that in a multivariate analysis no association between blood pressure or IOP in general to CT was found.37 Patients with glaucoma had been excluded from the current analysis because choroidal thickness changes are under debate in this disease.10 
Furthermore, changes in CT in a circadian fashion have been reported.33,35,44 In the present study, patients underwent OCT exams at various times of the day. However, time of examination mainly depended on the availability of a trained examiner and, thus, should not be systematically different between the groups. Also water, coffee, or nicotine administration has been reported to influence CT.3840 However, we did not control for these factors. 
Sympathetic nerve stimulation has been shown to reduce choroidal flow.45 However, little consensus has been achieved on the influence of the sympathetic and parasympathetic nervous system and data from humans, in particular OCT data are still missing. 
In view of the variety of factors potentially influencing CT, it is noteworthy that the variance within the group of “diffuse-trickling” GA was lower than the variance in the control group and in the “non–diffuse-trickling” group as well, which additionally points toward a particular role of the choroid in this group. 
Limitations of this study include that only 25 single loci of the choroid in the horizontal and vertical axes have been analyzed. Although we consider measurements at these points to be good estimates to reveal local changes in CT, analysis of choroidal thickness maps based on SD-OCT volume scans might be more significant. This is planned to be investigated in the ongoing study. Furthermore, only 15 eyes with the “diffuse-trickling” phenotype were included into the analysis. However, in a recent study, we have reported on a frequency of this phenotype of approximately 5% among eyes with GA.25 Therefore, the frequency of “diffuse-trickling” might even be overrepresented in the current analysis. 
Yet, the evidence for a correlation between CT and choroidal blood flow still has not been established to our knowledge (see review10). Hence, the pathophysiological relevance of “reduced choroidal thickness” is unclear. Application of new imaging devices, for example, Angio-OCT, may highly contribute to assess CT and choroidal blood flow correlation to elucidate the impact of choroidal thickness. 
Patients with GA, in particular if the fovea is involved, may have instable fixation. Despite the eye-tracking algorithm implemented in the Spectralis HRA+OCT device, instable fixation may lead to reduced imaging quality. The possible bias to exclude patients with a thick choroid as the choroidal/sclera interface cannot be identified in low quality SD-OCT images cannot be eliminated completely. However, measurement of fCT was possible in all eyes and the portion of peripheral points that were not measureable did not vary considerably between both groups. Therefore, systematically distinct imaging quality is unlikely to have had a strong impact on the data presented here. 
Finally, the present analysis represents a cross-sectional approach. In the ongoing study, we will assess the spatiotemporal relationship between GA development and choroidal thinning. 
In conclusion, the results herein indicated that the choroid in eyes with GA is thinner compared to controls. However, choroidal thickness appears to differ between certain GA subtypes based on abnormal FAF patterns in the perilesional zone. The “diffuse-trickling” phenotype is associated with extensive choroidal thinning. Refined phenotyping in GA including fundus-autofluorescence appears prudent in future studies in patients with AMD to further explore discriminating features. 
Acknowledgments
Supported by research grants from DFG (German Research Council): Ho 1926/1-3, FL 658/4-1; BONFOR 0-137-0012 (MF). The authors alone are responsible for the content and writing of the paper. 
Disclosure: M. Lindner, Heidelberg Engineering (F), Carl Zeiss Meditec (F), Optos (F), Genentech (F), Novartis (R); A. Bezatis, Heidelberg Engineering (F), Carl Zeiss Meditec (F), Optos (F); J. Czauderna, Heidelberg Engineering (F), Carl Zeiss Meditec (F), Optos (F); E. Becker, Heidelberg Engineering (F), Carl Zeiss Meditec (F), Optos (F); C.K. Brinkmann, Heidelberg Engineering (F), Carl Zeiss Meditec (F), Optos (F); S. Schmitz-Valckenberg, Heidelberg Engineering (F, R), Carl Zeiss Meditec (F), Optos (F, R), Genentech (F), Novartis (F, C, R), Bayer (F, R), Allergan (F), Merz (F), Roche (F), Quintiles Commercial (R); R. Fimmers, None; F.G. Holz, Heidelberg Engineering (F, C, R), Carl Zeiss Meditec (F), Optos (F, C), Genentech (F, C, R), Novartis (F, C, R), Bayer (F, C, R), Acucela (C), Allergan (C), Boehringer Ingelheim (C), Merz (C); M. Fleckenstein, Heidelberg Engineering (F, R), Carl Zeiss Meditec (F), Optos (F), Genentech (F, R), Merz (C), Novartis (R), Bayer (R), P 
References
Klein R Klein BE Tomany SC Meuer SM Huang GH. Ten-year incidence and progression of age-related maculopathy: the Beaver Dam eye study. Ophthalmology. 2002; 109: 1767–1779. [CrossRef] [PubMed]
Friedman DS O'Colmain BJ Munoz B Prevalence of age-related macular degeneration in the United States. Arch Ophthalmol. 2004; 122: 564–572. [CrossRef] [PubMed]
Klaver CC Wolfs RC Vingerling JR Hofman A de Jong PT. Age-specific prevalence and causes of blindness and visual impairment in an older population: the Rotterdam Study. Arch Ophthalmol. 1998; 116: 653–658. [CrossRef] [PubMed]
Mitchell P Smith W Attebo K Wang JJ. Prevalence of age-related maculopathy in Australia. The Blue Mountains Eye Study. Ophthalmology. 1995; 102: 1450–1460. [CrossRef] [PubMed]
Ferris FL 3rd Fine SL Hyman L. Age-related macular degeneration and blindness due to neovascular maculopathy. Arch Ophthalmol. 1984; 102: 1640–1642. [CrossRef] [PubMed]
Holz FG Strauss EC Schmitz-Valckenberg S van Lookeren Campagne M. Geographic atrophy: clinical features and potential therapeutic approaches. Ophthalmology. 2014; 121: 1079–1091. [CrossRef] [PubMed]
Green WR Key SN 3rd. Senile macular degeneration: a histopathologic study. Trans Am Ophthalmol Soc. 1977; 75: 180–254. [PubMed]
Sarks JP Sarks SH Killingsworth MC. Evolution of geographic atrophy of the retinal pigment epithelium. Eye (Lond). 1988; 2: 552–577. [CrossRef] [PubMed]
Spaide RF Koizumi H Pozzoni MC. Enhanced depth imaging spectral-domain optical coherence tomography. Am J Ophthalmol. 2008; 146: 496–500. [CrossRef] [PubMed]
Mrejen S Spaide RF. Optical coherence tomography: imaging of the choroid and beyond. Surv Ophthalmol. 2013; 58: 387–429. [CrossRef] [PubMed]
Margolis R Spaide RF. A pilot study of enhanced depth imaging optical coherence tomography of the choroid in normal eyes. Am J Ophthalmol. 2009; 147: 811–815. [CrossRef] [PubMed]
Chung SE Kang SW Lee JH Kim YT. Choroidal thickness in polypoidal choroidal vasculopathy and exudative age-related macular degeneration. Ophthalmology. 2011; 118: 840–845. [CrossRef] [PubMed]
Kim SW Oh J Kwon SS Yoo J Huh K. Comparison of choroidal thickness among patients with healthy eyes, early age-related maculopathy, neovascular age-related macular degeneration, central serous chorioretinopathy, and polypoidal choroidal vasculopathy. Retina. 2011; 31: 1904–1911. [CrossRef] [PubMed]
Koizumi H Yamagishi T Yamazaki T Kawasaki R Kinoshita S. Subfoveal choroidal thickness in typical age-related macular degeneration and polypoidal choroidal vasculopathy. Graef's Arch Clin Exp Ophthalmol. 2011; 249: 1123–1128. [CrossRef]
Manjunath V Goren J Fujimoto JG Duker JS. Analysis of choroidal thickness in age-related macular degeneration using spectral-domain optical coherence tomography. Am J Ophthalmol. 2011; 152: 663–668. [CrossRef] [PubMed]
Wood A Binns A Margrain T Retinal and choroidal thickness in early age-related macular degeneration. Am J Ophthalmol. 2011; 152: 1030–1038. [CrossRef] [PubMed]
Jirarattanasopa P Ooto S Nakata I Choroidal thickness, vascular hyperpermeability, and complement factor H in age-related macular degeneration and polypoidal choroidal vasculopathy. Invest Ophthalmol Vis Sci. 2012; 53: 3663–3672. [CrossRef] [PubMed]
Noori J Riazi Esfahani M, Hajizadeh F, Zaferani MM. Choroidal mapping; a novel approach for evaluating choroidal thickness and volume. J Ophthalmic Vis Res. 2012; 7: 180–185. [PubMed]
Adhi M Lau M Liang MC Waheed NK Duker JS. Analysis of the thickness and vascular layers of the choroid in eyes with geographic atrophy using spectral-domain optical coherence tomography. Retina. 2014; 34: 306–312. [CrossRef] [PubMed]
Coscas F Puche N Coscas G Comparison of macular choroidal thickness in adult onset foveomacular vitelliform dystrophy and age-related macular degeneration. Invest Ophthalmol Vis Sci. 2014; 55: 64–69. [CrossRef] [PubMed]
Jonas JB Forster TM Steinmetz P Schlichtenbrede FC Harder BC. Choroidal thickness in age-related macular degeneration. Retina. 2014; 34: 1149–1155. [CrossRef] [PubMed]
Lee JY Lee DH Yoon YH. Correlation between subfoveal choroidal thickness and the severity or progression of nonexudative age-related macular degeneration. Invest Ophthalmol Vis Sci. 2013; 54: 7812–7818. [CrossRef] [PubMed]
Sigler EJ Randolph JC. Comparison of macular choroidal thickness among patients older than age 65 with early atrophic age-related macular degeneration and normals. Invest Ophthalmol Vis Sci. 2013; 54: 6307–6313. [CrossRef] [PubMed]
Kang HM Kwon HJ Yi JH Lee CS Lee SC. Subfoveal choroidal thickness as a potential predictor of visual outcome and treatment response after intravitreal ranibizumab injections for typical exudative age-related macular degeneration. Am J Ophthalmol. 2014; 157: 1013–1021. [CrossRef] [PubMed]
Holz FG Bindewald-Wittich A Fleckenstein M Dreyhaupt J Scholl HP Schmitz-Valckenberg S. Progression of geographic atrophy and impact of fundus autofluorescence patterns in age-related macular degeneration. Am J Ophthalmol. 2007; 143: 463–472. [CrossRef] [PubMed]
Bindewald A Schmitz-Valckenberg S Jorzik JJ Classification of abnormal fundus autofluorescence patterns in the junctional zone of geographic atrophy in patients with age related macular degeneration. Br J Ophthalmol. 2005; 89: 874–878. [CrossRef] [PubMed]
Fleckenstein M Schmitz-Valckenberg S Lindner M The “diffuse-trickling” fundus autofluorescence phenotype in geographic atrophy. Invest Ophthalmol Vis Sci. 2014; 55: 2911–2920. [CrossRef] [PubMed]
Fleckenstein M Schmitz-Valckenberg S Martens C Fundus autofluorescence and spectral-domain optical coherence tomography characteristics in a rapidly progressing form of geographic atrophy. Invest Ophthalmol Vis Sci. 2011; 52: 3761–3766. [CrossRef] [PubMed]
Ramrattan RS van der Schaft TL Mooy CM de Bruijn WC Mulder PG de Jong PT. Morphometric analysis of Bruch's membrane, the choriocapillaris, and the choroid in aging. Invest Ophthalmol Vis Sci. 1994; 35: 2857–2864. [PubMed]
Spraul CW Lang GE Grossniklaus HE Lang GK. Histologic and morphometric analysis of the choroid, Bruch's membrane, and retinal pigment epithelium in postmortem eyes with age-related macular degeneration and histologic examination of surgically excised choroidal neovascular membranes. Surv Ophthalmol. 1999; 44 (suppl 1): S10–S32. [CrossRef] [PubMed]
Nickla DL Wallman J. The multifunctional choroid. Prog Retin Eye Res. 2010; 29: 144–168. [CrossRef] [PubMed]
Spaide RF. Age-related choroidal atrophy. Am J Ophthalmol. 2009; 147: 801–810. [CrossRef] [PubMed]
Tan CS Ouyang Y Ruiz H Sadda SR. Diurnal variation of choroidal thickness in normal, healthy subjects measured by spectral domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2012; 53: 261–266. [CrossRef] [PubMed]
Vance SK Imamura Y Freund KB. The effects of sildenafil citrate on choroidal thickness as determined by enhanced depth imaging optical coherence tomography. Retina. 2011; 31: 332–335. [CrossRef] [PubMed]
Brown JS Flitcroft DI Ying GS In vivo human choroidal thickness measurements: evidence for diurnal fluctuations. Invest Ophthalmol Vis Sci. 2009; 50: 5–12. [CrossRef] [PubMed]
Fujiwara T Imamura Y Margolis R Slakter JS Spaide RF. Enhanced depth imaging optical coherence tomography of the choroid in highly myopic eyes. Am J Ophthalmol. 2009; 148: 445–450. [CrossRef] [PubMed]
Wei WB Xu L Jonas JB Subfoveal choroidal thickness: the Beijing Eye Study. Ophthalmology. 2013; 120: 175–180. [CrossRef] [PubMed]
Mansouri K Medeiros FA Marchase N Tatham AJ Auerbach D Weinreb RN. Assessment of choroidal thickness and volume during the water drinking test by swept-source optical coherence tomography. Ophthalmology. 2013; 120: 2508–2516. [CrossRef] [PubMed]
Vural AD Kara N Sayin N Pirhan D Ersan HB. Choroidal thickness changes after a single administration of coffee in healthy subjects. Retina. 2014; 34: 1223–1228. [CrossRef] [PubMed]
Zengin MO Cinar E Kucukerdonmez C. The effect of nicotine on choroidal thickness. Br J Ophthalmol. 2014; 98: 233–237. [PubMed]
Johnstone J Fazio M Rojananuangnit K Variation of the axial location of Bruch's membrane opening with age, choroidal thickness, and race. Invest Ophthalmol Vis Sci. 2014; 55: 2004–2009. [CrossRef] [PubMed]
Li XQ Larsen M Munch IC. Subfoveal choroidal thickness in relation to sex and axial length in 93 Danish university students. Invest Ophthalmol Vis Sci. 2011; 52: 8438–8441. [CrossRef] [PubMed]
Sohrab M Wu K Fawzi AA. A pilot study of morphometric analysis of choroidal vasculature in vivo, using en face optical coherence tomography. PloS One. 2012; 7: e48631. [CrossRef] [PubMed]
Usui S Ikuno Y Akiba M Circadian changes in subfoveal choroidal thickness and the relationship with circulatory factors in healthy subjects. Invest Ophthalmol Vis Sci. 2012; 53: 2300–2307. [CrossRef] [PubMed]
Kur J Newman EA Chan-Ling T. Cellular and physiological mechanisms underlying blood flow regulation in the retina and choroid in health and disease. Prog Retin Eye Res. 2012; 31: 377–406. [CrossRef] [PubMed]
Figure 1
 
(A) Enhanced depth imaging OCT scans as obtained from a representative patient without (upper) and with (lower) geographic atrophy secondary to AMD, both included into this study. Vertical lines indicate locations where CT measurements were performed. (B, C) Box-and-whiskers plot illustrating the difference between the fCT (B) and mCT (mean of all 25 points measured for each patient, [C]) between controls and GA. Edges of the boxes represent the 25th and 75th percentiles, while the limits of the whiskers symbolize the 1.5-fold IQRs. Horizontal bars in the upper part of the diagram indicate significant differences between the groups (t-test for independent samples).
Figure 1
 
(A) Enhanced depth imaging OCT scans as obtained from a representative patient without (upper) and with (lower) geographic atrophy secondary to AMD, both included into this study. Vertical lines indicate locations where CT measurements were performed. (B, C) Box-and-whiskers plot illustrating the difference between the fCT (B) and mCT (mean of all 25 points measured for each patient, [C]) between controls and GA. Edges of the boxes represent the 25th and 75th percentiles, while the limits of the whiskers symbolize the 1.5-fold IQRs. Horizontal bars in the upper part of the diagram indicate significant differences between the groups (t-test for independent samples).
Figure 2
 
Box-and-whiskers plot illustrating the difference between fCT (A) and mCT (B) between controls and “diffuse-trickling” and “non–diffuse-trickling” GA. Edges of the boxes and whiskers represent 25th and 75th percentiles and 1.5-fold IQRs, respectively. Horizontal bars in the upper part of the diagram indicate significant differences between the groups. Note that the “control” boxes include the same values as in Figure 1.
Figure 2
 
Box-and-whiskers plot illustrating the difference between fCT (A) and mCT (B) between controls and “diffuse-trickling” and “non–diffuse-trickling” GA. Edges of the boxes and whiskers represent 25th and 75th percentiles and 1.5-fold IQRs, respectively. Horizontal bars in the upper part of the diagram indicate significant differences between the groups. Note that the “control” boxes include the same values as in Figure 1.
Figure 3
 
Subfoveal CT (A) and mean CT (B) are plotted against GA size. “Diffuse-trickling” and “non–diffuse-trickling” GA data points are depicted as open squares and filled circles, respectively.
Figure 3
 
Subfoveal CT (A) and mean CT (B) are plotted against GA size. “Diffuse-trickling” and “non–diffuse-trickling” GA data points are depicted as open squares and filled circles, respectively.
Table 1
 
Characteristics of Patients With GA and Controls
Table 1
 
Characteristics of Patients With GA and Controls
Control GA Patients
All “Diffuse-Trickling” “Non–Diffuse-Trickling”
Patients, n 37 72 15 57
SE, D (n) 1.10 ± 1.59 0.12 ± 1.56 (67) −0.27 ± 1.87 (14) 0.23 ± 1.47 (53)
Age, y 73.89 ± 6.19 75.97 ± 7.09 74.52 ± 9.53 76.35 ± 6.34
Male, n 15 22  4 18
Phakic, n 25 36  4 32
GA size, mm2 (n) 6.84 ± 5.80 (68) 12.69 ± 8.33 (13) 5.81 ± 4.67 (55)
fCT, μm 253.95 ± 69.19 173.03 ± 90.22 114.67 ± 43.32 188.39 ± 93.26
mCT, μm 228.00 ± 66.24 162.07 ± 76.26 110.22 ± 29.66 175.72 ± 79.02
Table 2
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in Horizontal EDI OCT Scans
Table 2
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in Horizontal EDI OCT Scans
Location CT GA, μm CT Control, μm P
T 3000 198.15 ± 58.48 220.93 ± 54.67 0.06
T 2500 184.13 ± 61.75 218.65 ± 55.16 0.006
T 2000 183.04 ± 61.19 222.63 ± 58.05 0.002
T 1500 177.84 ± 63.62 227.03 ± 63.99 <0.001
T 1000 179.94 ± 82.44 229.43 ± 67.50 0.002
T 500 178.69 ± 87.00 236.65 ± 67.92 0.001
fCT 173.03 ± 90.22 253.95 ± 69.19 0.001
N 500 164.71 ± 93.77 247.73 ± 80.37 <0.001
N 1000 152.72 ± 94.70 230.70 ± 87.87 <0.001
N 1500 136.92 ± 89.60 212.730 ± 86.21 <0.001
N 2000 115.87 ± 62.76 183.69 ± 77.52 <0.001
N 2500 100.75 ± 51.63 161.64 ± 78.01 <0.001
N 3000 90.22 ± 42.96 137.95 ± 73.42 0.002
Table 3
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 12 Locations Measured in Vertical EDI OCT Scans
Table 3
 
Mean Values of CT in the GA Group and in Controls as Obtained From Measurements at Each of the 12 Locations Measured in Vertical EDI OCT Scans
CT GA CT Control P
S 3000 182.85 ± 72.12 261.70 ± 82.90 <0.001
S 2500 174.73 ± 71.65 257.84 ± 86.55 <0.001
S 2000 170.56 ± 84.70 262.53 ± 87.82 <0.001
S 1500 164.16 ± 78.82 264.76 ± 85.17 <0.001
S 1000 161.46 ± 86.93 255.31 ± 71.81 <0.001
S 500 163.98 ± 87.76 251.45 ± 76.81 <0.001
I 500 163.67 ± 90.39 242.92 ± 80.69 <0.001
I 1000 158.55 ± 91.45 228.06 ± 86.83 <0.001
I 1500 150.62 ± 69.79 227.96 ± 83.27 <0.001
I 2000 148.57 ± 61.87 213.40 ± 74.12 <0.001
I 2500 157.62 ± 63.65 205.37 ± 73.02 0.001
I 3000 154.42 ± 60.79 195.17 ± 67.18 0.002
Table 4
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in the Horizontal EDI OCT Scans
Table 4
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 13 Locations (Including Subfoveally, fCT) Measured in the Horizontal EDI OCT Scans
CT “Diffuse-Trickling” P , “Diffuse-Trickling” vs. Controls CT “Non–Diffuse-Trickling” P , “Non–Diffuse-Trickling” vs. Controls
T 3000 163.81 ± 29.60 <0.001 207.08 ± 60.98 0.29
T 2500 145.90 ± 26.81 <0.001 195.15 ± 64.67 0.08
T 2000 145.47 ± 33.73 <0.001 193.28 ± 63.17 0.03
T 1500 129.17 ± 37.19 <0.001 190.88 ± 63.095 0.01
T 1000 129.33 ± 46.21 <0.001 193.26 ± 84.95 0.03
T 500 129.63 ± 43.61 <0.001 191.61 ± 91.15 0.01
fCT 114.67 ± 43.32 <0.001 188.39 ± 93.26 <0.001
N 500 98.53 ± 45.30 <0.001 182.44 ± 95.68 0.001
N 1000 89.13 ± 43.75 <0.001 169.75 ± 97.61 0.003
N 1500 80.17 ± 33.60 <0.001 152.13 ± 93.89 0.002
N 2000 78.30 ± 35.15 <0.001 126.31 ± 64.94 <0.001
N 2500 72.87 ± 22.00 <0.001 108.50 ± 54.871 <0.001
N 3000 69.39 ± 19.57 <0.001 96.84 ± 46.30 0.004
Table 5
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 12 Locations Measured in the Vertical EDI OCT Scans
Table 5
 
Mean Values of the “Diffuse-Trickling” GA and the “Non–Diffuse-Trickling” GA Groups as Obtained From Measurements at Each of the 12 Locations Measured in the Vertical EDI OCT Scans
CT “Diffuse-Trickling” P , “Diffuse-Trickling” vs. Controls CT “Non–Diffuse-Trickling” P , “Non–Diffuse-Trickling” vs. Controls
S 3000 136.29 ± 38.18 <0.001 196.43 ± 74.25 <0.001
S 2500 127.10 ± 42.85 <0.001 189.32 ± 72.64 <0.001
S 2000 113.50 ± 40.22 <0.001 187.02 ± 87.22 <0.001
S 1500 109.57 ± 35.39 <0.001 179.91 ± 81.04 <0.001
S 1000 103.20 ± 42.62 <0.001 177.95 ± 89.40 <0.001
S 500 104.18 ± 46.00 <0.001 179.20 ± 89.59 <0.001
I 500 110.82 ± 47.73 <0.001 177.12 ± 93.98 0.001
I 1000 99.23 ± 34.14 <0.001 174.44 ± 95.56 0.01
I 1500 95.70 ± 27.72 <0.001 166.46 ± 70.35 <0.001
I 2000 97.47 ± 28.65 <0.001 163.60 ± 61.09 0.001
I 2500 108.37 ± 36.71 <0.001 172.11 ± 62.83 0.03
I 3000 108.11 ± 25.02 <0.001 167.13 ± 61.66 0.05
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×