Age-related macular degeneration (AMD) is the leading cause of severe and irreversible visual loss in older adults aged 50 years and older in developed countries.1,2 Wet AMD emerges abruptly and progresses rapidly toward severe visual impairment if left untreated.3,4 Although fluorescein angiography (FA) visualizes leakage and accumulation of fluorescein molecules, the advent of spectral-domain optical coherence tomography (SD-OCT) has allowed more accurate visualization of intraretinal and subretinal layers, particularly at the level of the photoreceptors and the retinal pigment epithelium (RPE).5,6 Although choroidal neovascularization (CNV) activity can be determined by both FA and OCT, the two techniques provide different and potentially complementary information.6
Type 2 or classic CNV lesions, as described in FA-based CNV classifications, penetrate the RPE-Bruch’s membrane complex and proliferate in the subretinal space above the RPE monolayer.7 On OCT, such lesions appear as relatively hyperreflective membranes with either defined or poorly defined borders under the photoreceptor layer and above the RPE.8 With SD-OCT, the ellipsoid zone (EZ) of the photoreceptor layer can be assessed easily, as can the presence of intraretinal cysts.9,10 These improvements in OCT image resolution help in assessing the visual prognosis of diseased eyes and their response to treatment after anti-vascular endothelial growth factor (VEGF) therapy; most clinicians consider OCT evidence of persistent fluid a criterion for re-treatment.9–11
The use of intravitreal anti-VEGF therapy has been shown to improve visual acuity in patients with CNV associated with AMD,12,13 and it has been suggested that analysis of the subcomponents of the lesions on OCT could help predict visual function and visual outcomes in such patients.14–16 Changes in CNV volume and composition after anti-VEGF treatment could cause changes in the reflectivity or brightness patterns of CNV lesions (like subretinal hyperreflective material [SRHM]) on OCT.17 SRHM is defined on OCT as hyperreflective material in the subretinal space and has been correlated with classic CNV on FA.6 Although SRHM typically corresponds to fibrovascular tissue12 (as in type 2 CNV, a histologic definition used to denote neovascular tissue above the RPE but below the neurosensory retina), it also may include associated hemorrhage, lipid, or thick fibrin.18,19 Recent studies have indicated that the presence of SRHM (also termed subretinal tissue by some investigators) may show stronger correlations with visual acuity than other retinal parameters such as retinal thickness and thus may provide additional prognostic information.12,14,20 To better assess the importance of choroidal neovascular membrane reflectivity on OCT, we systematically computed the SRHM brightness in a series of eyes with CNV secondary to AMD. Our purpose was to assess the relationship between SRHM reflectivity and SRHM volume after treatment of neovascular AMD with anti-VEGF therapy.
Patients and Methods
Seventeen eyes of 16 treatment-naive patients diagnosed with CNV secondary to exudative AMD were enrolled in this retrospective, longitudinal study. Clinical data and SD-OCT volume scans of patients were obtained retrospectively from the tertiary medical retina practice at the Doheny Eye Institute. The study was approved by the institutional review board of the University of Southern California (the university affiliated with the Doheny Eye Institute at the time) and adhered to the tenets of the Declaration of Helsinki.
All of the patients were initiated on intravitreal anti-VEGF therapy (ranibizumab or bevacizumab) and underwent Cirrus SD-OCT (Carl Zeiss Meditec, Dublin, CA) imaging at baseline and 12 months after starting therapy. Potential patients for inclusion in the study were identified by reviewing the anti-VEGF therapy treatment logs for a period of 1 year. To be included, patients also had to meet study criteria (Table 1), including evidence of a component of type 2 CNV manifesting as SHRM. FA images for each case at baseline were graded for angiographic subtype classification, but FA findings (aside from the presence of leaking CNV and absence of non-AMD causes of CNV) were not used as eligibility criteria. All included eyes were treated with intravitreal ranibizumab or bevacizumab (no loading) following the Comparison of Age-Related Macular Degeneration Treatments Trials (CATT) as-needed treatment regimen.
Inclusion and Exclusion Criteria
SD-OCT Acquisition and Evaluation
All OCT imaging was obtained using the Cirrus HD-OCT with a 512 × 128 macular cube protocol covering a 6 × 6–mm macular area centered in the fovea. Acquisitions were obtained using standard Doheny Ophthalmic Imaging Unit procedures, including administration of artificial tears before scan acquisition to maximize image quality. Images with minimum signal strength greater than seven were considered adequate for the analysis.
For this study, we used 3D-OCTOR software21 that was developed at the Doheny Image Reading Center and described previously. The program allows raw OCT to be imported directly into the grading platform and allows the grader to draw or adjust the various boundaries on all 128 B-scans of each volume scan. After defining the different spaces and layers of interest, the software converts the pixel measurements into micrometers to yield thickness and volume measurements for each space.
As defined in previous reports, a total of six layers were segmented on all 128 B-scans: (1) internal limiting membrane, (2) outer borders of the photoreceptor outer segments, (3) inner border of the SRHM, (4) outer border of the SRHM (5) inner surface of the RPE, and (6) the inner border of the choroid. Using these conventions, the SHRM (which may correspond to type 2 CNV, akin to classic CNV on FA) would be defined and quantified as the space between boundaries three and four. Areas of pigment epithelial detachment (PED), which may correspond to type 1 CNV, akin to occult CNV on FA) would be defined and quantified as the space between boundaries five and six. Subretinal fluid (SRF) would be defined by the space between boundaries two and three. In B-scans without evidence of SRF, SRHM, or PED, the relevant boundaries noted above would be overlapping and thus be merged together. Lastly, the nerve fiber layer (NFL) boundaries (inner and outer) were segmented for the visible NFL nasal to the fovea (Figure 1). The temporal nerve fiber is thin and difficult to visualize or grade consistently, and thus was not segmented.
OCT B-scan of the left eye in a patient with type 2 choroidal neovascular membrane. (A) Original unsegmented OCT B-scan image. (B) OCT B-scan image following manual segmentation of the vitreous, nerve fiber layer, and subretinal hyperreflective material.
Segmentation was performed by two independent, masked graders (WC, MGN), and any discrepancies between graders were adjudicated by the Doheny Image Reading Center medical director (SRS) to yield a single final grading result for each case. Baseline and 12-month follow-up visits were graded by this same process in a masked fashion. All grading was performed according to a standardized grading protocol, whose reproducibility for grading SRHM, SRF, PED, and retinal thickness and volume has been well established in prior reports.18
Following segmentation and the definition of the borders of the structures, analogous to the OCT instrument software, the OCTOR software allows mean thickness of all segmented structures to be computed by converting the distance in pixels between the inner and outer boundaries of the structure to micrometers.22 In addition, the OCTOR software allows the mean reflectivity or brightness of the structure to be computed by averaging all pixels contained between the segmentation boundaries for that structure on all B-scans. The units of the measure for mean intensity are decibels, but the measure becomes unitless following normalization.
Despite the standardized acquisition techniques and the use of artificial tears to ameliorate ocular surface factors before scan acquisition, a variety of uncontrollable factors, such as media opacity, may still affect the signal quality and absolute brightness of structures visualized by OCT. We have previously described methods to normalize the signal between visits and patients to facilitate comparisons of tissue brightness or reflectivity.22,23 Our normalization strategy uses two reference structures, both a dark and a bright standard, the vitreous and the NFL. These two structures are our preferred references for AMD studies, as they are presumed to be relatively unaffected by the disease process.
To compute a normalized brightness value for any structure or pixel of interest in the B-scan image, first the mean brightness (or optical density [OD]) of the vitreous is subtracted, and the remainder is divided by the mean brightness of the nasal NFL. Thus, the resultant normalized brightness value for the pixels in the structure of interest are unitless (and generally less than one since the NFL tends to be one of the brightest structures in the image). For mean vitreous brightness, we only used those vitreous pixels in the A-scans containing the SRHM (Figure 1). Thus, SRHM reflectivity for each case was computed using the following formula:
The RPE layer was not used in the normalization formula because of the higher possibility of confounding error24 since the RPE can be affected by the disease process, and its reflectivity signal may be attenuated by overlying tissues.
Mean values for all variables were obtained at baseline and after 12 months of follow-up. Change was calculated for each parameter as the difference between the 12-month value and the baseline value. A paired t test was used for statistical analysis of variation in logarithm of the minimum angle of resolution (logMAR) acuity, retinal thickness, macular volume, SRHM volume and thickness, and SRHM reflectivity between visits at baseline and 12 months. Correlations between OCT parameters (eg, retinal thickness, volume, SRHM reflectivity, and SRHM volume) and logMAR acuity were tested using Spearman correlation coefficient. A P value of less than .05 was considered statistically significant. Statistical calculations were performed using SPSS for Windows version 18.0.
A total of 17 eyes from 16 eligible patients (six women and 10 men) were analyzed. The mean ± standard deviation age was 79 ± 8 years (range: 68 to 95 years). All 17 eyes had a newly diagnosed, untreated, active exudative AMD at baseline. Two cases (12%) were classified as predominantly classic membranes on FA; the remaining 15 cases (88%) were classified as minimally classic. All cases were confirmed to have leakage by FA at baseline.
Vitreous and NFL segments were used to normalize SRHM reflectivity; however, the absolute intensities showed no significant change from baseline to 12 months, perhaps reflecting consistency of the image acquisition by the imaging unit. Absolute reflectivity of the SRHM at baseline was significantly less than at month 12 (Table 2).
Reflectivity Values of OCT Study Parameters at Baseline and Month 12 Visits
Mean logMAR best corrected visual acuity (BCVA) was 0.74 at baseline (Snellen equivalent: 20/110) and improved to 0.47 (20/60) at month 12. The magnitude of the change was not statistically significant (P = .06), although the sample size was small. The mean number of anti-VEGF treatments per eye was 6.8 ± 3.5 injections (range: 1 to 12). The mean neurosensory retinal thickness decreased from 279.5 ± 18.9 µm to 260.8 ± 22.7 µm. The decrease was accompanied by a decrease in the retinal volume from 10.4 ± 0.8 mm3 to 9.6 ± 0.7 mm3; the change was statistically significant for both parameters (P = .01 and P = .02, respectively). A reduction in SRHM volume also was appreciated between baseline and month 12, from 0.33 ± 0.07 mm3 to 0.12 ± 0.05 mm3 (P < .001). This change was accompanied by an increase in the SRHM reflectivity from 0.48 ± 0.01 units to 0.64 ± 0.08 (P < .001) (Table 2, Figure 2).
OCT B-scans from an eye with a mixed choroidal neovascularization (CNV) with both type 1 (fibrovascular pigment epithelial detachment [PED]) and type 2 (subretinal hyperreflective material [SRHM]) components. Manually segmented B-scans with and without shading show the structures of interest (neurosensory retina [NSR]), nasal nerve fiber layer [NFL], overlying vitreous, SRHM, and PED). (A) At baseline, retinal volume = 10.16 mm3, subretinal fluid (SRF) volume = 0.13 mm3, SRHM volume = 0.21 mm3, and SRHM optical density ratio (ODR) = 0.472. (B) Segmentation of the same baseline OCT B-scan. (C) At a similar location 12 months later, after five as-needed bevacizumab injections. Retinal volume decreased to 9.42 mm3, with no SRF, and there was a reduction in SRHM volume to 0.08 mm3 with an increase in ODR to 0.648. (D) Segmentation of the same month 12 OCT B-scan.
We correlated total/combined macular neurosensory and SRF volume with the change in SRHM thickness, volume, and reflectivity (Table 3). There was a positive correlation between the total macular retinal volume change with the change in SRHM thickness (r = 0.86, P < .001) and SRHM volume (r = 0.80, P < .01). The change in SRHM reflectivity correlated negatively with the change in total retinal macular volume (r = −0.50, P = .04).
Correlations between change in study (Log MAR visual acuity and OCT) parameters
The SRHM reflectivity correlated at baseline with macular volume (r = −0.58, P = .02), SRHM thickness (r = −0.50, P = .04), and SRHM volume (r = −0.49, P = .04). At month 12, the SRHM reflectivity was correlated only with macular volume (r = −0.50, P = .04). The change in SRHM reflectivity correlated negatively with a change in retinal thickness (r = −0.57, P = .02) and macular volume (r = −0.50, P = .04); no statistically significant correlation was found with SRHM thickness change (r = −0.45, P = .07) or SRHM volume change (r = −0.37, P = .15).
LogMAR visual acuity at baseline correlated with logMAR acuity at month 12 (r = 0.685, P = .002). Log-MAR vision change was significantly correlated with changes in SRHM thickness (r = 0.494, P = .04) and SRHM volume (r = 0.48, P = .05), indicating that a decrease in SRHM thickness and volume after treatment correlates with an improvement in visual acuity. Other parameters, such as changes in retinal thickness, retinal volume, and SRHM reflectivity, showed no statistically significant correlation with logMAR acuity (P = .388, .208, and .678, respectively) (Table 3).
A correlation was found between the number of injections of anti-VEGF and the absolute change in SRHM volume (r = 0.50, P = .04), as well as the absolute change in SRHM thickness (r = 0.67, P =.003). No statistically significant correlation was found with the absolute change in SRHM reflectivity and the number of injections (r = 0.35, P =.17) (Table 4).
Correlation Between Number of Injections and Subretinal Hyperreflective Material OCT Parameters
We described a method for quantifying the reflectivity of brightness of SRHM (an OCT correlate of type 2 CNV) and demonstrated that it correlates with other OCT parameters of disease activity and response to therapy. FA, traditionally the gold standard imaging modality for diagnosis and evaluation of CNV activity, has been supplanted to a significant extent by OCT. Although FA is a dynamic technology that assesses the egress of dye through abnormal vessels and its accumulation in retinal spaces, OCT provides static cross-sectional images that show disruption of retinal architecture and accumulation of pockets of fluid in intraretinal, subretinal, or sub-RPE compartments.6
Assessment of CNV activity by OCT traditionally has been based on visualization of the morphologic effects of the lesion, such as retinal thickening, cystoid fluid accumulations, neurosensory detachment, and PED formation. These OCT features usually were corroborated by the presence of leakage on FA. Although the presence of fluid on OCT appears to be sensitive in detecting leaking FA lesions, the specificity is low.25,26 Neurosensory detachment was found to be associated with CNV leakage on FA, although a higher association was found with the presence of intraretinal flecks and low SRHM reflectivity.25
We examined the importance of SRHM reflectivity and its use as a parameter for the assessment of disease activity in eyes with neovascular AMD. We chose to evaluate the reflectivity of the SRHM specifically, rather than the sub-RPE component, as its reflectivity was less likely to be affected by changes in the overlying RPE or by the loss of signal with depth that is characteristic of SD-OCT systems.
Even limiting the analysis to SRHM, the OCT signal can still vary from patient to patient during a period of time due to various factors including media opacity, thus requiring a strategy for normalization. An advantage of our normalization approach compared to prior studies is that our use of both a dark and a bright reference structure allows for accounting both ends of the dynamic range. In addition, we chose the NFL as the bright structure reference rather than the RPE because it is less likely to be altered by the AMD disease process24 and because it is not as sensitive to the incidence angle of the light.23,27–29
In our cohort, after 12 months of anti-VEGF therapy, there was an expected increase in mean BCVA consistent with prior studies.30–32 In addition, similar to previous studies, the visual acuity did not correlate well with neurosensory retinal thickness.14 This perhaps is not surprising because visual acuity is affected by multiple factors aside from the presence of exudation, including the development of RPE-photoreceptor atrophy and fibrosis.14,33 Indeed, a decrease in retinal thickness after treatment could be associated with photoreceptor cell loss, and thus with decreased visual acuity, compared with thicker retinas. This confounds the ability to identify a linear correlation between macular thickness and visual acuity.14 This is a particular issue in our study, which specifically focused on eyes with type 2 CNV, as theoretically lesions in the subretinal space may be more likely to produce damage to the adjacent photoreceptors.34
However, we did observe a correlation between vision and SRHM, as a decrease in SRHM thickness and volume was associated with an increase in BCVA. This relationship between SRHM and vision also was observed in our previous studies14,35 and in the CATT trial.36 The decrease in SRHM thickness and volume during the 12 months of the study also was accompanied by an increase in the mean reflectivity of the SRHM. This increased reflectivity with treatment may reflect a progressive loss of fluid and vascular spaces with treatment and an increased proportion of fibrosis and scar tissue.17 The correlation between reflectivity and thickness at baseline was moderately significant (r = −0.50), indicating that thickness could account for only 25% of the variability in reflectivity. In addition, no significant correlations were observed between thickness and reflectivity at follow-up or between change in reflectivity and change in thickness. Thus, reflectivity appeared to carry information independent of thickness.
Changes in SRHM thickness and reflectivity also correlated with OCT measures of exudation. For example, a reduction in retinal and subretinal fluid was significantly associated with a reduction in the SRHM thickness and volume, correlating to a lesser extent with the increase in SRHM reflectivity.
Several limitations should be considered when assessing the results of our study. First, the cases were collected retrospectively and there is a potential for ascertainment bias. Second, the small sample size renders the study underpowered to detect small effects and differences. Manual segmentation of 128 B-scans is a laborious and time-intensive task, and was a limiting factor in the number of cases that could be evaluated. Third, we limited our analysis to SRHM reflectivity; because many CNV lesions only contain type 1 or occult CNV components, our findings would not be helpful or relevant to those cases. Fourth, in the normalization formula, we used the NFL in the nasal area of each scan rather than the NFL directly overlying the CNV and SRHM. Theoretically, any focal media opacities could artificially alter the reflectivity of the NFL in these areas. However, it is more difficult to reliably segment the NFL where it is much thinner, making the nasal NFL the best location for grading. Fifth, because measurements were obtained only at baseline and at 12 months, a detailed longitudinal time course of changes in lesion reflectivity could not be constructed. Finally, although the reflectivity signal of SRHM was less confounded than that of the sub-RPE space, overlying features such as intraretinal cystoid spaces, hard exudates, and pigment migration into the retina also may have affected SRHM reflectivity.
The strengths of our study include a standardized grading protocol with established reproducibility, the use of trained reading center graders, strict inclusion criteria, and detailed assessment and segmentation of dense volume scans. To our knowledge, this is the first study using SD-OCT imaging to evaluate the relationship between SRHM reflectivity and other parameters of exudation and visual acuity in eyes receiving anti-VEGF treatment.
In conclusion, anti-VEGF treatment for eyes with neovascular AMD improved visual acuity and decreased retinal fluid volume, SRF volume, and SRHM volume and thickness. Among these anatomic features, SRHM volume change was the most important predictor of change in visual acuity. SRHM reflectivity increased during the course of therapy in association with a reduction in the CNV activity. Although change in SRHM reflectivity appeared to parallel other measures of disease activity, it did not correlate with the change in SRHM volume, suggesting that it may be an independent parameter worthy of further evaluation.
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Inclusion and Exclusion Criteria
| Neovascular AMD undergoing treatment in at least one eye|
| Lesions required to have at least some classic component at baseline (manifest as type 2 CNV or subretinal hyperreflective material on OCT)|
|SD-OCT volume scan from the same machine (Cirrus OCT 512x128 cube) at baseline and month 12|
| The presence of neovascular membranes not related to AMD|
| Eyes with no baseline OCT or no follow-up within the first year after diagnosis|
| Study eyes with change of the OCT machine over the course of the disease|
| Eyes with nonvisible subretinal hyperreflective material on OCT|
| History of photodynamic therapy or focal laser therapy|
| Advanced glaucoma or any other condition causing deep visual impairment|
| Advanced CNV or severe hemorrhagic exudative AMD at baseline|
| History of macular surgery for diseases such as macular hole or epiretinal membrane|
Reflectivity Values of OCT Study Parameters at Baseline and Month 12 Visits
|Baseline Visit, mean ± SD (range)||Month 12 Visit, mean ± SD (range)||P Value|
|NFL reflectivity||0.44 ± 0.05 (0.33 – 0.50)||0.44 ± 0.04 (0.36 – 0.53)||.828|
|Vitreous reflectivity||0.18 ± 0.003 (0.18 – 0.19)||0.18 ± 0.002 (0.18 – 0.19)||.27|
|SRHM absolute reflectivity||0.39 ± 0.05 (0.30 – 0.46)||0.46 ± 0.03 (0.39 – 0.52)||< .001|
|Optical density of SRHM*||0.48 ± 0.01 (0.2 – 0.64)||0.64 ± 0.08 (0.46 – 0.79)||< .001|
Correlations between change in study (Log MAR visual acuity and OCT) parameters
|Δ LogMAR||Δ Retinal Thickness||Δ Retinal Volume||Δ SRHM Volume||Δ SRHM thickness||Δ ODR|
|Δ Retinal thickness||0.22||0.39|
|Δ Retinal volume||0.32||0.21||0.82||< .001|
|Δ SRHM volume||0.48||0.05||0.68||.003||0.87||< .001|
|Δ SRHM thickness||0.49||0.04||0.6||.01||0.76||< .001||0.8||< .001|
Correlation Between Number of Injections and Subretinal Hyperreflective Material OCT Parameters
|Abs Δ SRHM Volume||Abs Δ SRHM thickness||Abs Δ Optical Density|
|No. of injections||0.5||.04||0.67||.003||0.35||.17|