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OCT Angiography Features of Neovascularization as Predictive Factors for Frequent Recurrence in Age-Related Macular Degeneration
Journal Pre-proof OCT Angiography Features of Neovascularization as Predictive Factors for Frequent Recurrence in Age-Related Macular Degeneration Mihyun Choi, Seong-Woo Kim, Cheolmin Yun, Jaeryung Oh PII:
S0002-9394(20)30018-0
DOI:
https://doi.org/10.1016/j.ajo.2020.01.012
Reference:
AJOPHT 11198
To appear in:
American Journal of Ophthalmology
Received Date: 20 September 2019 Revised Date:
7 January 2020
Accepted Date: 8 January 2020
Please cite this article as: Choi M, Kim S-W, Yun C, Oh J, OCT Angiography Features of Neovascularization as Predictive Factors for Frequent Recurrence in Age-Related Macular Degeneration, American Journal of Ophthalmology (2020), doi: https://doi.org/10.1016/j.ajo.2020.01.012. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Inc.
ABSTRACT PURPOSE: To investigate the features of neovascularization (NV) in eyes with neovascular age-related macular degeneration (NVAMD) using optical coherence tomography angiography (OCTA) according to the treatment interval of intravitreal aflibercept injection (IVI). DESIGN: Retrospective, interventional, comparative case series. METHODS: Patients with type 1 NV treated with the “pro-re-nata” regimen after three loading IVI were classified into two groups based on the numbers of treatments during 12 months, specifically a stable group who required less than two injections and an unstable group who required more than three injections. Quantitative features of OCTA including NV area, NV length, NV density, endpoint density (open-ended vessels per unit length), junction density (vessel junction per unit length), lacunarity, and largest vessel caliber were compared between the two groups. RESULTS: Among 71 eyes, 38 and 33 eyes were classified into the stable and unstable groups, respectively. The unstable group had higher endpoint densities (stable vs. unstable: 2.74 vs. 3.08; p = 0.03) and higher levels of lacunarity (0.177 vs. 0.211; p = 0.028). The area, density, length of NV and junction density and largest vessel caliber were not different between the two groups (p= 0.057, p = 0.184, p = 0.062, p = 0.160, and p = 0.473). Endpoint density was correlated with the unstable group in both univariate and multivariate analyses (p = 0.004, p = 0.002, respectively). A predictive model with an endpoint index demonstrated a sensitivity of 93.75% and a negative predictive value of 89.47% for the unstable group. CONCLUSIONS: The characteristics of NV in eyes of exudative AMD with type 1 NV were different according to treatment requirements. Identifying the features of NV on OCTA might be helpful for predicting clinical outcomes and optimal treatment intervals.
OCT Angiography Features of Neovascularization as Predictive Factors for Frequent Recurrence in Age-Related Macular Degeneration MIHYUN CHOI, SEONG-WOO KIM, CHEOLMIN YUN, AND JAERYUNG OH
From the Department of Ophthalmology, Korea University College of Medicine, Seoul, Korea
Inquiries to Seong-Woo Kim, Department of Ophthalmology, Korea University Guro Hospital, 148, Gurodong-ro, Guro-gu, Seoul, Republic of Korea; e-mail: [email protected] Phone) 82-10-9001-6397; Fax.) 82-02-857-8580
Short title: Features of NV in frequently recurrent AMD
1
INTRODUCTION Age-related macular degeneration (AMD) is a leading cause of blindness among the elderly in developed countries,1 and recent research has suggested the prevalence of AMD to be 14.3% to 17.6% in those older than 65 years of age.2-5 The intravitreal injection of anti–vascular endothelial growth factor (VEGF) has been shown to make structural and clinical improvements in neovascular AMD (NVAMD) and has become the standard therapy for typical NVAMD.6-9 However, as the complete regression of neovascularization (NV) cannot be achieved with intravitreal anti-VEGF injection (IVI), many therapeutic regimens (e.g., monthly treatment, pro-re-nata, treat and extend) have been introduced to reduce the treatment burden.10-12 Predicting the optimal treatment interval in each patient is crucial in order to lower treatment burden while at the same time ensuring timely treatment before macular fluid accumulation occurs. Many studies have reported some concern that IVI may be associated with progression of geographic atrophy (GA) in long term follow up,13,14 particularly in post hoc analyses of the Comparison of Age-Related Macular degeneration Treatment Trial (CATT)15 and Inhibition of VEGF in Age-related choroidal Neovascularization (IVAN)16 prospective trials. In CATT and IVAN, GA rates were higher in monthly compared with discontinuous/PRN treatment arms. Also in post hoc analysis of the HARBOR study, monthly treatment trended toward a higher risk of GA compared with PRN.17 In those studies, receiving more injections did not seem to be related to GA development within the PRN treatment arms. Although there is still a lack of evidence for the association of IVI and GA, timely treatment regimens according to recurrence rate rather than fixed regimen(s) could benefit visual prognoses. Fluorescein angiography (FA) and indocyanine green angiography (ICGA) are generally used to diagnose and evaluate the efficacy of AMD treatment, and both require intravenous dye injection. By contrast, optical coherence tomography angiography (OCTA) is an imaging modality that enables researchers to perform qualitative and quantitative analyses of NV due to its depth-resolving capability. This noninvasive method with high-frequency scanning can visualize blood vessels at various depths in the retina and choroid without dye injection18-21; thus, it can be repeated frequently in outpatient clinics. Segmentation of OCTA images can be obtained in an automated manner and the device can be manually adjusted to effectively visualize NV under the retinal pigment epithelium (RPE) or pigment epithelial detachment (PED). The activity of NV has an obvious correlation with disease activity and many researchers have found that OCTA can be used to predict disease activity based on morphologic features, enabling optimal decision-making regarding retreatment for NVAMD.22,23 However, there is still a shortage of OCTA studies about NV characteristics correlated with a high recurrence of exudation, and a few reports have shared inconsistent results and limitations in applying the technology in the real world.24,25 Further, proven methods for the automated detection and quantitative analysis of NV are lacking, mostly due to projection and foreground imaging artifacts.26 In this study, we evaluated qualitative and quantitative NV features using OCTA 2
among patients who required IVI more than three times in 12 months and those who required a lesser number of IVIs to assess the status of NV in both groups and elucidate the potential predictive value for high recurrence of exudation and frequent treatment requirements in AMD. MATERIALS AND METHODS This was a retrospective, interventional, comparative case series review of 89 consecutive patients with NVAMD followed for one year at the Korea University Guro Hospital between March 2018 and July 2019. The Institutional Review Board of Korea University Medical Center approved this study, and all research and data collection were conducted in accordance with the tenets of the Declaration of Helsinki. Our Institutional Review Board waived the need for written informed consent from the participants, because of the study’s retrospective design. STUDY POPULATION: Inclusion criteria for this study included age greater than 50 years, subfoveal type 1 NVAMD, treatment with aflibercept (Eylea; Regeneron Pharmaceuticals, Tarrytown, NY, USA), and visual acuity better than 20/100. Further, patients who already had received a loading dose of three monthly IVI injections (at baseline, 1, and 2 or baseline, 1, and 3 months27-28) with response to IVI29 before March 2018 and who showed recurrence of macular fluid on spectral-domain OCT were enrolled. Study participants were additionally required to complete at least one year of follow-up examinations. Exclusion criteria for the study included types 2 and 3 NV or polypoidal choroidal vasculopathy, a history of central serous chorioretinopathy, NV fibrotic scarring, atrophic changes at the fovea, or any concurrent progressive retinal disease. Patients previously treated with photodynamic therapy and IVIs other than aflibercept during the analysis period or up to six months prior to the analysis were also excluded. Patients with poor auto segmentation of NV on OCTA including large PED and subfoveal hemorrhage were also excluded. The treatment protocol applied was “pro-re-nata” and was based on structural OCT findings. All patients were followed up for four to eight weeks. At each visit, best-corrected visual acuity (BCVA), slit-lamp examination, and dilated funduscopic examination were performed, and OCT images were obtained. An IVI was given only in the case of evidence of activity on spectral-domain OCT including the presence of intraretinal fluid, subretinal fluid, and/or subretinal pigment epithelial fluid.30 DATA SOURCES: All patients underwent a comprehensive eye examination performed by a retinal specialist (S. W. K.) to determine their disease status including a complete ophthalmologic examination and multimodal imaging including fluorescein angiography (FA), indocyanine green angiography (ICGA) (Heidelberg Engineering, Heidelberg, Germany), and structural OCT and OCTA (Spectralis OCT2; Heidelberg Engineering, Heidelberg, Germany). FA and ICGA were obtained before the first IVI to determine the presence and type of NV. The patient’s characteristics including age, sex, follow-up duration, and number of previous IVIs were also obtained. IMAGE ANALYSIS ACQUISITION: OCTA was obtained via a spectral-domain OCT device (Spectralis OCT2; Heidelberg Engineering, Heidelberg, Germany) set to scan 3
an area of 4.3 × 4.3 mm (15° × 15°). The device was operated with a central wavelength of 870 nm, an acquisition speed of 85,000 A-scans per second (highspeed mode), and 384 B-scans, with a lateral resolution of 11.4 µm/pixels and axial resolution of 3.87 µm/pixels. Central retinal thickness (CRT) measurements were obtained on a thickness map (circle diameter of 1 mm) and subfoveal choroidal thickness (SFCT) measurements were manually measured in the Spectralis software as described in a previous study.31-33 Automatic segmentation was performed using the software (HEYEX; Heidelberg Engineering, Heidelberg, Germany) and slab boundaries were defined based on the minima of the flow-density profiles.34,35 In fusion images of structural OCT section images and the corresponding blood flow information (structural OCT + OCTA), direct visual correlation of structural and flow information was established and manual segmentation by the user was also possible. We manually chose two horizontal segmentation lines to set boundaries of NV containing slabs from the external limiting membrane to the line of Bruch’s membrane (Figure 1.A, Figure 2.A). The methods for defining the NV slab in AMD have varied in past studies.18,36-39 We set the external limiting membrane as the upper segmentation line to reduce inaccuracies due to segmentation errors and confirmed that there was no blood flow signal from the lower margin of the outer plexiform layer to above the RPE layer in the fusion images (structural OCT + OCTA) to ensure that type 2 or 3 NV were not included. Projection artifact removal algorithms were applied to remove artifacts from OCTA images of the outer retina (Figure 1.B, Figure 2.B). In the next stage, the avascular complex was processed using the free and open-source GNU Image Manipulation Program (GIMP 2.8.14) to manually eliminate projection artifacts and subthreshold signals (Figure 1.C, Figure 2.C). After processing the OCTA images, all NV images were analyzed by morphological qualitative and quantitative features of NV chosen based on previous papers.39,40 Before analysis, the images were assigned unique numbers, and testers (M. C. and S. W. K.) were blinded to information on the study participants. We considered four OCTA criteria to qualitatively describe a neovascular lesion, as described by Coscas et al23 (Figure 3): (1) presence of tiny branching vessels (thin, tangled capillaries) versus mature vessels (linear filamentous capillaries); (2) presence of an anastomotic arcade (peripheral connection, lacy wheel appearance); (3) presence of inner loops (inner anastomoses), and (4) presence of perilesional hypointense halo (hypointense area around NV, local choriocapillaris alteration). Criteria were graded in a binary method (awarded one point for presence and zero points for absence). For the largest vessel caliber measurement, images were magnified 300% in GIMP and the pixel of the largest vessel caliber was evaluated using a measurement tool and calculated in micrometers (Figure 1.D, Figure 2.D). For quantitative analysis, we used the open-source software AngioTool version 0.6a,19,24,41-43 with the following threshold parameters: 30 and 255, vessel thickness: 5, and removal of small particles: 80. AngioTool, a software program for the quantitative analysis of angiogenesis with a user-friendly interface, can identify vascular configurations based on user-defined parameters such as vessel diameter and intensity. AngioTool analyses vessel structure following the latter’s enhancement with multiscale Hessian analysis and smoothing with a recursive Gaussian filter and, after optimizing the parameters, it delineates the vascular structure and skeletonizes and analyzes the following parameters43 (Figure 1.E, Figure 2.E): (1) explant area 4
(the area occupied by the convex hull containing the vessels), (2) vessel area (the area of the segmented vessels), (3) total number of junctions (number of junctions in segmented vessels), (4) total number of endpoints (the number of open-ended segments), (5) total length of vessel (the sum of Euclidean distances between the pixels of all the vessels in the image), and (6) mean lacunarity (mean lacunarity among all-sized boxes).24 Although the vessel percentage area (vessel area/explant area) is provided within the software, the vessel length density (total length of vessel/vessel area) (mm/mm2)44 was calculated instead of using the vessel percentage area as the vessel density since the image analysis was obtained after skeletonization using the AngioTool. The junction density (total number of vessel junctions/total length of vessel) (n/mm) and endpoint density (total number of openended segments/total length of vessel) (n/mm) were calculated in the same manner as that in previous studies.19 For subgroup analysis, subjects were divided into two groups according to number of IVIs during the 12 months of follow-up, including a stable group who required IVI less than three times in 12 months and an unstable group who requiring IVI more than three times in 12 months. All patients completed 3 times of loading injection before analysis period, and loading injections are NOT included in IVI numbers in 12 months of follow up. All demographic, clinical, and structural OCT/OCTA measurements were tabulated in Microsoft Excel 2013 software (Microsoft Corp., Armonk, NY, USA). STATISTICAL ANALYSIS: Statistical analyses included a Student’s t-test to evaluate the variables of interest between two subgroups. Univariate and multivariate binary logistic regression (stable vs. unstable) results for each parameter were also evaluated and compared. To consider multiplicity in statistical comparisons, the Bonferroni correction was applied after multivariate binary logistic regression. These procedures were performed using SPSS version 20 (IBM Corp., Armonk, NY, USA). Receiver operating characteristic (ROC) curve analysis of the built predictive model was performed using MedCalc version 19.0.6 (MedCalc Software bvba, Ostend, Belgium). Results with p values less than 0.05 were considered statistically significant.
RESULTS A total of 89 patients met the inclusion criteria; 18 were excluded for either poor image quality or ungradable OCT images. A total of 71 patients (51 males) were included with a mean age of 72.7 (range: 61–90) years. The mean follow-up period and IVI number before baseline were 30.4 ± 32.6 months and 6.47 ± 3.84 (including three loading injections). The mean logMAR BCVA was 0.39 ± 0.31 at baseline and 0.37 ± 0.31 at one year (p = 0.505). The CRT and SFCT were 275 ± 62 µm and 205 ± 80 µm, respectively. Baseline demographical and clinical characteristics of the two groups (stable and unstable) are summarized in Table 1. The unstable group received a higher number of IVI treatments within 12 months (p < 0.001) and also of previous IVI treatments before the analysis period (p = 0.029). There were no significant differences in age, sex, follow-up period, or visual acuity. CRT and SFCT 5
were 271.93 µm and 202.93 µm in the stable group and 279.14 µm and 208.57 µm in the unstable group, without any significant differences between the two groups (p = 0.660 and p = 0.789, respectively) (Table 1). OCTA FINDINGS: Morphologic OCTA image analysis in all subjects showed the occurrence of the aforementioned four different parameters was distributed as follows: tiny branching vessels in 71.8% (51 eyes), a peripheral anastomotic arcade in 53.5% (38 eyes), vascular loops in 28.2% (20 eyes), and a perilesional hypointense halo in 67.6% (48 eyes). The comparisons between morphologic and quantitative features of NV in OCTA in the two groups are summarized in Table 2. No statistical difference was found in the presence of tiny branching vessels (p = 0.293), arcade (p = 0.342), loops (p = 0.190), or perilesional hypointense halo (p = 0.209) between the two groups. Regarding quantitative features, the unstable group had a larger NV area (stable vs. unstable: 1.327 mm2 vs. 1.778 mm2; p = 0.057) and longer total NV length (stable vs. unstable: 21.06 mm vs. 27.94 mm; p = 0.062) than the stable group, although statistical significance was not reached. The vessel length density (mm/mm2) was 15.72 in the stable group and 16.34 in the unstable group (p = 0.184), while junction density (n/mm) was 2.74 in the stable group and 3.08 in the unstable group (p = 0.160). Further, endpoint density (n/mm) was 2.72 and 3.18, respectively, which was statistically different (p = 0.003). Mean lacunarity was 0.177 in the stable group and 0.211 in the unstable group (p = 0.028). The largest vessel caliber was 42.78 µm in the stable group and 39.52 µm in the unstable group (p = 0.179). Univariate and multivariate binary logistic regression analysis findings for OCTA variables associated with the unstable group are summarized in Table 3. In the univariate analysis, only endpoint index was associated with the unstable group (p = 0.004); there was no association between the unstable group and NV area (p = 0.095), NV density (p = 0.283), total NV length (p = 0.179), junction density (p = 0.161), mean lacunarity (p = 0.212), or largest vessel diameter (p = 0.466). The variables that had an association in the univariate logistic regression analysis (p < 0.2) were included in the multivariate analysis using the backward stepwise selection method to establish a proper multivariate model. Eventually, NV area, total NV length, junction density, and endpoint density were included in the multivariate model. Endpoint density and junction density were statistically correlated with the unstable group and after Bonferroni correction, endpoint density had a strong association with the unstable group among the OCTA NV variables. The ROC curve for endpoint density to predict the unstable group at baseline is described in Figure 4. The area under the curve was 0.689 (p = 0.002) and the recommended cutoff value was 2.25 (n/mm) according to MedCalc, which showed the unstable group demonstrated a 93.75% rate of sensitivity and 39.53% rate of specificity. Although this value cannot provide high specificity, a high negative predictive value (high true negative rate) was 89.47%, which is a crucial requirement to be a sensitive predictive factor.
DISCUSSION 6
Recently, many studies have shown that OCTA enables the noninvasive identification of NV in morphologic features and reported many characteristics associated with NV of exudative (active) AMD compared to nonexudative (inactive, quiescent) AMD (e.g., a seafan or lacy wheel shape, the presence of tiny capillaries, anastomoses and vessel loops, tiny branching vessels, a peripheral arcade, and a hypo-intense halo around the lesion).23,24,37 However, most of these morphological features are very subjective in nature, making it difficult to reach a consensus as to their applicability. Further, there is still a lack of the study of analysis between ‘high recurrence’ and ‘low recurrence’ both in active AMD, with differences in treatment requirements. Therefore, we aimed to elucidate more objective, automated, and quantitative approaches to determine the activity in exudative AMD. The patients included in this study all had active (exudative) type 1 NVAMD lesions at baseline and had no difference in age, sex, CRT, or SFCT, which were previously reported as prognostic factors for AMD.9,45,46 Previous studies have shown that type 1 NVs have relatively mature vessels and large-caliber trunk vessels than type 2 NVs.36,47 Nagano et al36 also recently reported higher junction density in type 2 NVs than type 1 NVs using OCTA, which also suggests that the two types of NV might differ in maturity. And it is also known that type 1 CNV tends to be resistant against anti-VEGF treatment compared to type 2 and type 3 NVs because of RPE covering type 1 CNVs may block penetration of anti-VEGF drugs48 which can make a difference in the number of IVIs in the follow-up period. As our study included treated eyes (not treatment naïve eyes), we only included type 1 NVAMD because of concerns that these differences might affect the analysis. In a previous study of NV morphologic features, the presence of tiny branching vessels and a peripheral anastomotic arcade were suggested to be biomarkers of active lesions compared to quiescent ones and were suggested as a predictive model for treatment decisions by Coscas et al23 in a study of 126 eyes that predicted an exudative lesion with a sensitivity of 97.6%. In our study, 71.8% of all subjects had tiny branching vessels and 53.5% had peripheral arcade, yet the morphologic appearance of NV did not differ significantly between the two groups. However, all of our subjects had active AMD at baseline, which showed as exudative lesions on OCT and needed IVI treatment, and this may help to explain the morphologically active features in both groups. Further, this implies that morphologic biomarkers may help differentiate an active versus quiescent lesion but may not be as effective in guiding treatment intervals for patients with active lesions. As known, the mechanisms in the creation of new vascular networks include angiogenesis and arteriogenesis. Angiogenesis is the formation of new capillaries from preexisting vessels (sprouting) mediated by VEGF and arteriogenesis is the expansion of previously formed vessels largely stimulated by increased flow through the remaining vessels.49-51 Anti-VEGF treatment prunes back the newly growing vessels but cannot affect the pericyte-covered larger vessels and it concludes a higher flow in the remaining vascular network, which stimulates arteriogenesis. In 2015, Spaide suggested the morphological transition of NV in repeated anti-VEGF treatment should be called “abnormalization”52 and many researchers have reported results that support this hypothesis.18,19,53 He suggested that repeated IVIs might 7
affect major feeder vessels growing larger with fewer branching points and more vascular anastomotic connections by periodic pruning of angiogenic vascular sprouts and called this morphological transition as “abnormalization”. From this point of view, we speculated that the more pruned back vessels that exist, the higher the transmural pressure generated after IVI will be, which can lead to arteriogenesis (resprouting) by VEGF withdrawal and subsequent leakage and exudation in active AMD. AngioTool software, which offers semiautomated quantitative information on vessels and junction points, indicates internal branching and anastomotic connections in vascular networks and endpoints in open-ended vessels and could represent surrogate parameters for sprouting vessels without anastomosis. We calculated junction density and endpoint density by the numbers per total vessel length, which can be interpreted as a measure of anastomotic and sprouting activity in proportion to the total NV length. Lacunarity is the parameter of inhomogeneity of lesions and reflects the complexity and aggressiveness of a structure; it has been suggested also as a parameter for vascular networks in drug-treated specimens or pathological vasculature.54 In a simple quantitative comparison of our study, patients in the unstable group had neovascularization of a higher endpoint density and higher lacunarity than did those of the stable group. Endpoint density was the only parameter to show a statistically significant association with the unstable group in both the univariate and multivariate analyses. In our study, the sprouting activity and complexity of NV peripheral lesions represented by endpoint density and lacunarity were higher in the unstable group, and endpoint density could possibly be used as a predictive factor for frequent treatment requirements (high recurrence) after IVI. Sarraf et al quantitatively assessed active and quiescent NV and reported prominent and larger central vessels were more closely associated with the quiescent NV group. He also reported the fractal dimension of NV was lower in quiescent NV than in active NV and was reduced after IVI in active NV.25 This suggested that the pattern of NV lesions after treatment might be less complex due to the attenuation and pruning of small-caliber vessels. Nesper et al retrospectively explored the three-dimensional complexity of NV lesions in 51 eyes with NVAMD and found that poor responders were treated more frequently than at six-week intervals and had a greater number of NV flow layers.55 The higher endpoint density and lacunarity in the unstable group in our research are in line with the outcomes of these prior studies. Previously, studies about NV density in active and quiescent patients suggested there was no difference between the two groups19,25 and we also found that there was no difference in NV density between stable and unstable group. Roberts et al (2017) also used the AngioTool to evaluate 23 eyes with NVAMD for quantitative features on OCTA images between good responders treated less frequently than six weeks versus poor responders and reported a higher vessel density in the good responders group (51.11% vs. 37.80%; p = 0.097) with no difference among other parameters.24 However, in their study, the study population was too small to accurately compare these parameters and they did not evaluate endpoint density considering sprouting vessel per vessel length. The larger sample size and more strict criteria for stable group in our study might help explain the meaningful results compared with the previous study. Limitations of this study include the relatively small number of subjects as well as its 8
retrospective nature and possibility of selection bias, not only from the inclusion criteria but also due to our subgroup division. Subjects in the unstable group had more IVI treatments previous to the analysis period, but this was in line with the definitions of both groups. In previous studies, there was an inconsistency in the definitions of poor responders to IVI, which varies from six weeks to 12 weeks for the treatment interval.19,24,25,40 The SEVEN-UP study which assessed long-term outcomes 7 to 8 years after initiation of ranibizumab therapy reported that patients had received a mean of 6.8 IVIs during the mean 3.4-year interval (2 IVIs/year)56 since exit from the HORIZON study.57 As the patients included in this study, those patients had a mean follow-up period of 30.4 months and had been treated with IVI. As a result, to find predictive factors, we defined the unstable group as those who needed IVI more than three times in 12 months. And for the reasons already described above, this study included only type 1 AMD, but further study on type 2, type 1 & 2 mixed, and type 3 needed in more large population study. Depending on the type, different conclusions can be drawn, which may require attention for proper interpretation. This study quantitatively analyzed the NV en face images of OCTA as well as morphological analysis. Poorly segmented or visualized images due to large PDE, submacular hemorrhage, or NV larger than the measurement area were excluded and was 18 (20.22%) out of 89. Farecki et al reported the detectable rate of NV lesions in auto-segmentation OCTA as 92.2% in choriocapillaris slabs and 34.5% in RPE slabs (this included minor and sharp demarcations)38 and in the studies by Uchida et al40 and Takeuchi et al19 who also reported quantitative analysis of NV in AMD by OCTA, 11 in 40 (28%) eyes and 7 in 22 (32%) eyes were not able to be analyzed respectively because of indistinct vessel morphology. The buried data in this study might have affected the results but the ratio is comparable with previous studies. Also, the use of swept-source OCTA using longer wavelengths (~1,050 nm) and greater laser power, which allows for deeper penetration, may have better delineated the existence and morphology of NV, as prior studies demonstrated that NV size as determined by swept-source OCTA was larger than that found by spectral-domain OCTA as used in this study.58-60 However, the Spectralis OCT2 device used in our study had a relatively longer wavelength (870 nm) and denser scan pattern and has TruTrack Active Eye Tracking technology, which corrects for displacement by performing the reacquisition of OCT images at the correct retinal locations in realtime and by performing repeated scans (four to seven times) to obtain more accurate images in the case of abrupt or saccadic eye movements, which can cause motion artifacts. Also, Corvis et al reported that Spectralis OCTA was the closest to ICGA with the lowest limits of agreement compared to PlexElite (Carl Zeiss Meditec, Dublin, CA, USA).61 In AngioTool, the signal threshold is set by the user (it was 30 in our study) to remove artifacts from the NV slab, which could be a limitation of our study in that finer vessels may not have been included and this might have caused an underestimation of the endpoint. However, we still found a significant correlation between endpoint density and high recurrence in NVAMD. In conclusion, OCT angiography is a promising imaging modality that helps with guiding physicians to predict the patient’s response to anti-VEGF treatment with NVAMD. Further studies 9
using automated, accessible, and quantitative methods like Angiotool are needed to obtain standardized criteria to decide the optimal treatment interval in various regimens.
10
ACKNOWLEDGMENTS/DISCLOSURE: a. Funding/Support: The authors indicate no financial support or financial conflict of interest. b. Financial Disclosures: J.O. is a consultant of Topcon Corporation. Other authors certify that they have no financial disclosures. c. Other Acknowledgments: None
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Study for Neovascular Age-Related Macular Degeneration. Ophthalmology 2018;125(6):878-886. Pilotto E, Frizziero L, Daniele AR, et al. Early OCT angiography changes of type 1 CNV in exudative AMD treated with anti-VEGF. Br J Ophthalmol 2019;103(1):67-71. Takeuchi J, Kataoka K, Ito Y, et al. Optical Coherence Tomography Angiography to Quantify Choroidal Neovascularization in Response to Aflibercept. Ophthalmologica 2018;240(2):90-98. Xu D, Dávila JP, Rahimi M, et al. Long-term Progression of Type 1 Neovascularization in Age-related Macular Degeneration Using Optical Coherence Tomography Angiography. Am J Ophthalmol 2018;187:10-20. Miere A, Oubraham H, Amoroso F, et al. Optical Coherence Tomography Angiography to Distinguish Changes of Choroidal Neovascularization after Anti-VEGF Therapy: Monthly Loading Dose versus Pro Re Nata Regimen. J Ophthalmol 2018;2018:3751702. Malamos P, Tsolkas G, Kanakis M, et al. OCT-Angiography for monitoring and managing neovascular age-related macular degeneration. Curr Eye Res 2017;42(12):1689-1697. Coscas F, Lupidi M, Boulet JF, et al. Optical coherence tomography angiography in exudative age-related macular degeneration: a predictive model for treatment decisions. Br J Ophthalmol 2019;103(9):1342-1346. Roberts PK, Nesper PL, Gill MK, Fawzi AA. SEMIAUTOMATED QUANTITATIVE APPROACH TO CHARACTERIZE TREATMENT RESPONSE IN NEOVASCULAR AGE-RELATED MACULAR DEGENERATION: A Real-World Study. Retina 2017;37(8):1492-1498. Al-Sheikh M, Iafe NA, Phasukkijwatana N, Sadda SR, Sarraf D. BIOMARKERS OF NEOVASCULAR ACTIVITY IN AGE-RELATED MACULAR DEGENERATION USING OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY. Retina 2018;38(2):220-230. Zhang M, Hwang TS, Campbell JP, et al. Projection-resolved optical coherence tomographic angiography. Biomed Opt Express 2016;7(3):816-828. Holz FG, Amoaku W, Donate J, et al. Safety and efficacy of a flexible dosing regimen of ranibizumab in neovascular age-related macular degeneration: the SUSTAIN study. Ophthalmology 2011;118(4):663-671. Schmidt-Erfurth U, Chong V, Loewenstein A, et al. Guidelines for the management of neovascular age-related macular degeneration by the European Society of Retina Specialists (EURETINA). Br J Ophthalmol 2014;98(9):1144-1167. Hara C, Wakabayashi T, Toyama H, et al. Characteristics of patients with neovascular age-related macular degeneration who are non-responders to intravitreal aflibercept. Br J Ophthalmol 2018. Busbee BG, Ho AC, Brown DM, et al. Twelve-month efficacy and safety of 0.5 mg or 2.0 mg ranibizumab in patients with subfoveal neovascular age-related macular degeneration. Ophthalmology 2013;120(5):1046-1056. 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(5):811-815. 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(9):1904-1911. 13
33. Bae K, Noh SR, Kang SW, Kim ES, Yu SY. Angiographic Subtypes of Neovascular Age-related Macular Degeneration in Korean: A New Diagnostic Challenge. Sci Rep 2019;9(1):9701. 34. Campbell JP, Zhang M, Hwang TS, et al. Detailed Vascular Anatomy of the Human Retina by Projection-Resolved Optical Coherence Tomography Angiography. Sci Rep 2017;7:42201. 35. Hirano T, Chanwimol K, Weichsel J, Tepelus T, Sadda S. Distinct Retinal Capillary Plexuses in Normal Eyes as Observed in Optical Coherence Tomography Angiography Axial Profile Analysis. Sci Rep 2018;8(1):9380. 36. Nakano Y, Kataoka K, Takeuchi J, et al. Vascular maturity of type 1 and type 2 choroidal neovascularization evaluated by optical coherence tomography angiography. PLoS One 2019;14(4):e0216304. 37. Coscas GJ, Lupidi M, Coscas F, Cagini C, Souied EH. OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY VERSUS TRADITIONAL MULTIMODAL IMAGING IN ASSESSING THE ACTIVITY OF EXUDATIVE AGE-RELATED MACULAR DEGENERATION: A New Diagnostic Challenge. Retina 2015;35(11):2219-2228. 38. Farecki ML, Gutfleisch M, Faatz H, et al. Characteristics of type 1 and 2 CNV in exudative AMD in OCT-Angiography. Graefes Arch Clin Exp Ophthalmol 2017;255(5):913-921. 39. Liakopoulos S, Ongchin S, Bansal A, et al. Quantitative optical coherence tomography findings in various subtypes of neovascular age-related macular degeneration. Invest Ophthalmol Vis Sci 2008;49(11):5048-5054. 40. Uchida A, Hu M, Babiuch A, et al. Optical coherence tomography angiography characteristics of choroidal neovascularization requiring varied dosing frequencies in treat-and-extend management: An analysis of the AVATAR study. PLoS One 2019;14(6):e0218889. 41. Munk MR, Giannakaki-Zimmermann H, Berger L, et al. OCT-angiography: A qualitative and quantitative comparison of 4 OCT-A devices. PLoS One 2017;12(5):e0177059. 42. Sugano Y, Sekiryu T, Furuta M, et al. Morphometrical evaluation of the choriocapillaris imaged by swept-source optical coherence tomography angiography. Clin Ophthalmol 2018;12:2267-2276. 43. Zudaire E, Gambardella L, Kurcz C, Vermeren S. A computational tool for quantitative analysis of vascular networks. PLoS One 2011;6(11):e27385. 44. Hikichi T, Agarie M. Reduced Vessel Density of the Choriocapillaris during AntiVascular Endothelial Growth Factor Therapy for Neovascular Age-Related Macular Degeneration. Invest Ophthalmol Vis Sci 2019;60(4):1088-1095. 45. Cheung CMG, Gan A, Yanagi Y, Wong TY, Spaide R. Association between Choroidal Thickness and Drusen Subtypes in Age-Related Macular Degeneration. Ophthalmol Retina 2018;2(12):1196-1205. 46. Kumar JB, Wai KM, Ehlers JP, Singh RP, Rachitskaya AV. Subfoveal choroidal thickness as a prognostic factor in exudative age-related macular degeneration. Br J Ophthalmol 2019;103(7):918-921. 47. Kuehlewein L, Bansal M, Lenis TL, et al. Optical Coherence Tomography Angiography of Type 1 Neovascularization in Age-Related Macular Degeneration. Am J Ophthalmol 2015;160(4):739-748.e732. 14
48. Suzuki M, Nagai N, Izumi-Nagai K, et al. Predictive factors for non-response to intravitreal ranibizumab treatment in age-related macular degeneration. Br J Ophthalmol 2014;98(9):1186-1191. 49. Schierling W, Troidl K, Troidl C, Schmitz-Rixen T, Schaper W, Eitenmüller IK. The role of angiogenic growth factors in arteriogenesis. J Vasc Res 2009;46(4):365-374. 50. Wu S, Wu X, Zhu W, Cai WJ, Schaper J, Schaper W. Immunohistochemical study of the growth factors, aFGF, bFGF, PDGF-AB, VEGF-A and its receptor (Flk-1) during arteriogenesis. Mol Cell Biochem 2010;343(1-2):223-229. 51. Rajabi M, Mousa SA. The role of angiogenesis in cancer treatment. Biomedicines 2017;5(2). 52. Spaide RF. Optical Coherence Tomography Angiography Signs of Vascular Abnormalization With Antiangiogenic Therapy for Choroidal Neovascularization. Am J Ophthalmol 2015;160(1):6-16. 53. Mastropasqua L, Toto L, Borrelli E, Carpineto P, Di Antonio L, Mastropasqua R. OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY ASSESSMENT OF VASCULAR EFFECTS OCCURRING AFTER AFLIBERCEPT INTRAVITREAL INJECTIONS IN TREATMENT-NAIVE PATIENTS WITH WET AGE-RELATED MACULAR DEGENERATION. Retina 2017;37(2):247-256. 54. Gould DJ, Vadakkan TJ, Poché RA, Dickinson ME. Multifractal and lacunarity analysis of microvascular morphology and remodeling. Microcirculation 2011;18(2):136-151. 55. Nesper PL, Soetikno BT, Treister AD, Fawzi AA. Volume-Rendered ProjectionResolved OCT Angiography: 3D Lesion Complexity Is Associated With Therapy Response in Wet Age-Related Macular Degeneration. Invest Ophthalmol Vis Sci 2018;59(5):1944-1952. 56. Rofagha S, Bhisitkul RB, Boyer DS, Sadda SR, Zhang K. Seven-year outcomes in ranibizumab-treated patients in ANCHOR, MARINA, and HORIZON: a multicenter cohort study (SEVEN-UP). Ophthalmology 2013;120(11):2292-2299. 57. Singer MA, Awh CC, Sadda S, et al. HORIZON: an open-label extension trial of ranibizumab for choroidal neovascularization secondary to age-related macular degeneration. Ophthalmology 2012;119(6):1175-1183. 58. 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. 59. Cicinelli MV, Cavalleri M, Consorte AC, et al. SWEPT-SOURCE AND SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY VERSUS DYE ANGIOGRAPHY IN THE MEASUREMENT OF TYPE 1 NEOVASCULARIZATION. Retina 2019. 60. Novais EA, Adhi M, Moult EM, et al. Choroidal Neovascularization Analyzed on Ultrahigh-Speed Swept-Source Optical Coherence Tomography Angiography Compared to Spectral-Domain Optical Coherence Tomography Angiography. Am J Ophthalmol 2016;164:80-88. 61. Corvi F, Cozzi M, Barbolini E, et al. COMPARISON BETWEEN SEVERAL OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY DEVICES AND INDOCYANINE GREEN ANGIOGRAPHY OF CHOROIDAL NEOVASCULARIZATION. Retina 2019.
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FIGURE LEGENDS FIGURE 1. Multimodal imaging of a 77-year-old male patient suffering from NVAMD in the stable group. A: Section image shows structural OCT in the background and OCTA blood flow as a yellow overlay. The red dotted line in the inset is the manual segmentation boundary (upper: external limiting membrane, lower: Bruch’s membrane). B: The en-face OCT angiogram in the NV slab shows the “Lacy wheel” shape of type 1 NV. C: Manually cropped image of NV to remove projection artifacts. D: NV image magnified 300%, pixels between O to X were calculated to measure the vessel caliber. E: AngioTool analysis, skeletonized vessel (red line), junction point (blue dot), vessel area (outer green line), endpoint (point of the open-ended vessel).
FIGURE 2. Multimodal imaging of a 67-year-old male patient diagnosed with type 1 NVAMD in the unstable group. A: Fusion image of structural OCT and OCTA data as a yellow overlay. The red dotted line in the inset is the manual segmentation boundary (same as FIGURE 1). B: The en-face OCT angiogram in the NV slab shows the “medusa pattern” of type 1 NV. C: Manually cropped image of NV to remove projection artifacts. D: NV image magnified 300%, pixels between O to X were calculated to measure the vessel caliber. E :AngioTool analysis (overlay is same as FIGURE 1).
FIGURE 3. Qualitative assessment of NV detected by OCT-A. A: Lacy wheel pattern containing numerous tiny branches (white arrowhead) with peripheral arcade (anastomoses) at the vessel termini (yellow dashed line). B: Partial long filamentous linear vessels with a central prominent feeder vessel (*) and inner loop (white arrow) surrounded by a dark perilesional halo (white dashed line). This NV also has a peripheral arcade at the superior part (yellow dashed line). (C) Sea-fan shape NV shows numerous tiny branches (white arrowhead) and a peripheral arcade (yellow dashed line) with perilesional halo (white dashed line) and prominent central feeder vessels (*). D: Dead-tree-shaped NV has a central vessel (*).
FIGURE 4. The ROC curve between the sensitivity and specificity showed that the endpoint density of neovascularization from OCTA correctly predicts the unstable group with a high sensitivity and high negative predictive value (AUC, area under the curve).
16
TABLE 1. Patient demographics Stable Unstable p-value (n = 38) (n = 33) Mean age (SD) 73.59 (7.61) 71.03 (5.80) 0.153 Sex (M/F) 27/11 24/9 0.876 Follow-up period before analysis, 25.18 36.48 0.188 Mean (SD) (29.54) (35.28) No. of anti-VEGF treatments, Mean 1.47 (0.98) 4.57 (1.45) < 0.001 (SD) Previous anti-VEGF treatments, Mean 4.93 (5.3) 8.21 (6.8) 0.029 (SD) LogMAR BCVA, Mean (SD) Baseline 0.42 (0.31) 0.36 (0.31) 0.398 12 months 0.37 (0.29) 0.32 (0.32) 0.240 CRT (µm), Mean (SD) 271.93 279.14 0.660 (60.39) (64.99) SFCT (µm), Mean (SD) 202.93 208.57 0.789 (76.72) (85.48) SD = standard deviation; VEGF = vascular endothelial growth factor; BCVA = best=corrected visual acuity; CRT = central retinal thickness; SFCT = subfoveal choroidal thickness.
TABLE 2. Morphologic and quantitative features of NV at baseline Stable Unstable p-value (n = 38) (n = 33) Morphological feature, n (%) Tiny branching 25 (65.8) 26 (78.79) 0.293 Arcade 18 (47.37) 20 (60.61) 0.342 Loops 8 (21.05) 12 (36.36) 0.190 Halo 23 (60.53) 25 (75.76) 0.209 Quantitative features, mean (SD) NV area (mm2) 1.327 (0.695) 1.778 (1.064) 0.057 NV density (mm/mm2) 15.72 (1.89) 16.34 (1.61) 0.184 Total NV length (mm) 21.06 (11.12) 27.94 (17.14) 0.062 Junction density (n/mm) 2.74 (1.08) 3.08 (0.69) 0.160 Endpoint density (n/mm) 2.72 (0.89) 3.18 (0.60) 0.03 Mean lacunarity 0.177 (0.061) 0.211 (0.065) 0.028 Largest vessel caliber (µm) 42.78 (8.85) 39.52 (9.06) 0.473
TABLE 3. Quantitative variables of NV associated with the unstable group using binary logistic regression analysis Univariate Multivariatea Variables OR (95 % CI) pOR (95 % CI) p-value value NV area (mm2) 1.57 (0.970–2.672) 0.095 1.213 (0.751– 0.431 1.959) NV density(mm/ mm2) 1.226 (0.909– 0.283 NA NA 1.653) Total NV length (mm) 1.020 (0.992– 0.179 0.838 (0.632– 0.219 1.048) 1.111) 0.034 Junction density 1.520 (0.846– 0.161 0.838 (0.632– (n/mm) 2.730) 1.111) Endpoint density 2.633 (1.370– 0.004 3.691 (1.633– 0.002 (n/mm) 5.062) 8.346) Mean lacunarity 1.103 (1.009– 0.212 NA NA 1.207) 0.980 (0.929– 0.466 NA NA Largest vessel caliber 1.034) (µm) a Multivariate model summary ;Hosmer and Lemeshow test; chi-squared test = 2.795, p = 0.903, −2log likelihood = 70.649.
Highlights Neovascularization (NV) with higher open-ended vessels related to frequent recurrence of nAMD. In exudative nAMD, recurrence rate could be predicted by evaluating features of NV. By considering features of NV, optimal treatment interval could be modulated.
Biosketch Mihyun Choi, MD, PhD is a first year vitreoretinal clinical fellow in the Department of Ophthalmology at Korea University Guro Hospital, Seoul, Korea. Dr. Choi completed her medical school at Chonnam National University School of Medicine and Ophthalmology Residency at Catholic University Medical Center. Her interests include retinal and choroidal imaging, age-related macular degeneration.
Table of Contents Statement This study quantitatively analyzed neovascularization in optical coherence tomography angiography of neovascular Age-related macular degeneration. Authors found a significant correlation between endpoint density of neovascularization and frequent recurrence in neovascular Age-related macular degeneration. Endpoint density might represent the sprouting activity of neovascularization and could possibly be used as a predictive factor for frequent treatment requirements of antivascular endothelial growth factor.
Credit Author Statement MIHYUN CHOI: Conceptualization, Methodology, Software, Writing - Original Draft. SEONG-WOO KIM: Conceptualization, Validation, Writing - Review & Editing, Supervision. CHEOLMIN YUN: Writing - Review & Editing. JAERYUNG OH: Writing - Review & Editing
S0002-9394(20)30018-0
DOI:
https://doi.org/10.1016/j.ajo.2020.01.012
Reference:
AJOPHT 11198
To appear in:
American Journal of Ophthalmology
Received Date: 20 September 2019 Revised Date:
7 January 2020
Accepted Date: 8 January 2020
Please cite this article as: Choi M, Kim S-W, Yun C, Oh J, OCT Angiography Features of Neovascularization as Predictive Factors for Frequent Recurrence in Age-Related Macular Degeneration, American Journal of Ophthalmology (2020), doi: https://doi.org/10.1016/j.ajo.2020.01.012. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Inc.
ABSTRACT PURPOSE: To investigate the features of neovascularization (NV) in eyes with neovascular age-related macular degeneration (NVAMD) using optical coherence tomography angiography (OCTA) according to the treatment interval of intravitreal aflibercept injection (IVI). DESIGN: Retrospective, interventional, comparative case series. METHODS: Patients with type 1 NV treated with the “pro-re-nata” regimen after three loading IVI were classified into two groups based on the numbers of treatments during 12 months, specifically a stable group who required less than two injections and an unstable group who required more than three injections. Quantitative features of OCTA including NV area, NV length, NV density, endpoint density (open-ended vessels per unit length), junction density (vessel junction per unit length), lacunarity, and largest vessel caliber were compared between the two groups. RESULTS: Among 71 eyes, 38 and 33 eyes were classified into the stable and unstable groups, respectively. The unstable group had higher endpoint densities (stable vs. unstable: 2.74 vs. 3.08; p = 0.03) and higher levels of lacunarity (0.177 vs. 0.211; p = 0.028). The area, density, length of NV and junction density and largest vessel caliber were not different between the two groups (p= 0.057, p = 0.184, p = 0.062, p = 0.160, and p = 0.473). Endpoint density was correlated with the unstable group in both univariate and multivariate analyses (p = 0.004, p = 0.002, respectively). A predictive model with an endpoint index demonstrated a sensitivity of 93.75% and a negative predictive value of 89.47% for the unstable group. CONCLUSIONS: The characteristics of NV in eyes of exudative AMD with type 1 NV were different according to treatment requirements. Identifying the features of NV on OCTA might be helpful for predicting clinical outcomes and optimal treatment intervals.
OCT Angiography Features of Neovascularization as Predictive Factors for Frequent Recurrence in Age-Related Macular Degeneration MIHYUN CHOI, SEONG-WOO KIM, CHEOLMIN YUN, AND JAERYUNG OH
From the Department of Ophthalmology, Korea University College of Medicine, Seoul, Korea
Inquiries to Seong-Woo Kim, Department of Ophthalmology, Korea University Guro Hospital, 148, Gurodong-ro, Guro-gu, Seoul, Republic of Korea; e-mail: [email protected] Phone) 82-10-9001-6397; Fax.) 82-02-857-8580
Short title: Features of NV in frequently recurrent AMD
1
INTRODUCTION Age-related macular degeneration (AMD) is a leading cause of blindness among the elderly in developed countries,1 and recent research has suggested the prevalence of AMD to be 14.3% to 17.6% in those older than 65 years of age.2-5 The intravitreal injection of anti–vascular endothelial growth factor (VEGF) has been shown to make structural and clinical improvements in neovascular AMD (NVAMD) and has become the standard therapy for typical NVAMD.6-9 However, as the complete regression of neovascularization (NV) cannot be achieved with intravitreal anti-VEGF injection (IVI), many therapeutic regimens (e.g., monthly treatment, pro-re-nata, treat and extend) have been introduced to reduce the treatment burden.10-12 Predicting the optimal treatment interval in each patient is crucial in order to lower treatment burden while at the same time ensuring timely treatment before macular fluid accumulation occurs. Many studies have reported some concern that IVI may be associated with progression of geographic atrophy (GA) in long term follow up,13,14 particularly in post hoc analyses of the Comparison of Age-Related Macular degeneration Treatment Trial (CATT)15 and Inhibition of VEGF in Age-related choroidal Neovascularization (IVAN)16 prospective trials. In CATT and IVAN, GA rates were higher in monthly compared with discontinuous/PRN treatment arms. Also in post hoc analysis of the HARBOR study, monthly treatment trended toward a higher risk of GA compared with PRN.17 In those studies, receiving more injections did not seem to be related to GA development within the PRN treatment arms. Although there is still a lack of evidence for the association of IVI and GA, timely treatment regimens according to recurrence rate rather than fixed regimen(s) could benefit visual prognoses. Fluorescein angiography (FA) and indocyanine green angiography (ICGA) are generally used to diagnose and evaluate the efficacy of AMD treatment, and both require intravenous dye injection. By contrast, optical coherence tomography angiography (OCTA) is an imaging modality that enables researchers to perform qualitative and quantitative analyses of NV due to its depth-resolving capability. This noninvasive method with high-frequency scanning can visualize blood vessels at various depths in the retina and choroid without dye injection18-21; thus, it can be repeated frequently in outpatient clinics. Segmentation of OCTA images can be obtained in an automated manner and the device can be manually adjusted to effectively visualize NV under the retinal pigment epithelium (RPE) or pigment epithelial detachment (PED). The activity of NV has an obvious correlation with disease activity and many researchers have found that OCTA can be used to predict disease activity based on morphologic features, enabling optimal decision-making regarding retreatment for NVAMD.22,23 However, there is still a shortage of OCTA studies about NV characteristics correlated with a high recurrence of exudation, and a few reports have shared inconsistent results and limitations in applying the technology in the real world.24,25 Further, proven methods for the automated detection and quantitative analysis of NV are lacking, mostly due to projection and foreground imaging artifacts.26 In this study, we evaluated qualitative and quantitative NV features using OCTA 2
among patients who required IVI more than three times in 12 months and those who required a lesser number of IVIs to assess the status of NV in both groups and elucidate the potential predictive value for high recurrence of exudation and frequent treatment requirements in AMD. MATERIALS AND METHODS This was a retrospective, interventional, comparative case series review of 89 consecutive patients with NVAMD followed for one year at the Korea University Guro Hospital between March 2018 and July 2019. The Institutional Review Board of Korea University Medical Center approved this study, and all research and data collection were conducted in accordance with the tenets of the Declaration of Helsinki. Our Institutional Review Board waived the need for written informed consent from the participants, because of the study’s retrospective design. STUDY POPULATION: Inclusion criteria for this study included age greater than 50 years, subfoveal type 1 NVAMD, treatment with aflibercept (Eylea; Regeneron Pharmaceuticals, Tarrytown, NY, USA), and visual acuity better than 20/100. Further, patients who already had received a loading dose of three monthly IVI injections (at baseline, 1, and 2 or baseline, 1, and 3 months27-28) with response to IVI29 before March 2018 and who showed recurrence of macular fluid on spectral-domain OCT were enrolled. Study participants were additionally required to complete at least one year of follow-up examinations. Exclusion criteria for the study included types 2 and 3 NV or polypoidal choroidal vasculopathy, a history of central serous chorioretinopathy, NV fibrotic scarring, atrophic changes at the fovea, or any concurrent progressive retinal disease. Patients previously treated with photodynamic therapy and IVIs other than aflibercept during the analysis period or up to six months prior to the analysis were also excluded. Patients with poor auto segmentation of NV on OCTA including large PED and subfoveal hemorrhage were also excluded. The treatment protocol applied was “pro-re-nata” and was based on structural OCT findings. All patients were followed up for four to eight weeks. At each visit, best-corrected visual acuity (BCVA), slit-lamp examination, and dilated funduscopic examination were performed, and OCT images were obtained. An IVI was given only in the case of evidence of activity on spectral-domain OCT including the presence of intraretinal fluid, subretinal fluid, and/or subretinal pigment epithelial fluid.30 DATA SOURCES: All patients underwent a comprehensive eye examination performed by a retinal specialist (S. W. K.) to determine their disease status including a complete ophthalmologic examination and multimodal imaging including fluorescein angiography (FA), indocyanine green angiography (ICGA) (Heidelberg Engineering, Heidelberg, Germany), and structural OCT and OCTA (Spectralis OCT2; Heidelberg Engineering, Heidelberg, Germany). FA and ICGA were obtained before the first IVI to determine the presence and type of NV. The patient’s characteristics including age, sex, follow-up duration, and number of previous IVIs were also obtained. IMAGE ANALYSIS ACQUISITION: OCTA was obtained via a spectral-domain OCT device (Spectralis OCT2; Heidelberg Engineering, Heidelberg, Germany) set to scan 3
an area of 4.3 × 4.3 mm (15° × 15°). The device was operated with a central wavelength of 870 nm, an acquisition speed of 85,000 A-scans per second (highspeed mode), and 384 B-scans, with a lateral resolution of 11.4 µm/pixels and axial resolution of 3.87 µm/pixels. Central retinal thickness (CRT) measurements were obtained on a thickness map (circle diameter of 1 mm) and subfoveal choroidal thickness (SFCT) measurements were manually measured in the Spectralis software as described in a previous study.31-33 Automatic segmentation was performed using the software (HEYEX; Heidelberg Engineering, Heidelberg, Germany) and slab boundaries were defined based on the minima of the flow-density profiles.34,35 In fusion images of structural OCT section images and the corresponding blood flow information (structural OCT + OCTA), direct visual correlation of structural and flow information was established and manual segmentation by the user was also possible. We manually chose two horizontal segmentation lines to set boundaries of NV containing slabs from the external limiting membrane to the line of Bruch’s membrane (Figure 1.A, Figure 2.A). The methods for defining the NV slab in AMD have varied in past studies.18,36-39 We set the external limiting membrane as the upper segmentation line to reduce inaccuracies due to segmentation errors and confirmed that there was no blood flow signal from the lower margin of the outer plexiform layer to above the RPE layer in the fusion images (structural OCT + OCTA) to ensure that type 2 or 3 NV were not included. Projection artifact removal algorithms were applied to remove artifacts from OCTA images of the outer retina (Figure 1.B, Figure 2.B). In the next stage, the avascular complex was processed using the free and open-source GNU Image Manipulation Program (GIMP 2.8.14) to manually eliminate projection artifacts and subthreshold signals (Figure 1.C, Figure 2.C). After processing the OCTA images, all NV images were analyzed by morphological qualitative and quantitative features of NV chosen based on previous papers.39,40 Before analysis, the images were assigned unique numbers, and testers (M. C. and S. W. K.) were blinded to information on the study participants. We considered four OCTA criteria to qualitatively describe a neovascular lesion, as described by Coscas et al23 (Figure 3): (1) presence of tiny branching vessels (thin, tangled capillaries) versus mature vessels (linear filamentous capillaries); (2) presence of an anastomotic arcade (peripheral connection, lacy wheel appearance); (3) presence of inner loops (inner anastomoses), and (4) presence of perilesional hypointense halo (hypointense area around NV, local choriocapillaris alteration). Criteria were graded in a binary method (awarded one point for presence and zero points for absence). For the largest vessel caliber measurement, images were magnified 300% in GIMP and the pixel of the largest vessel caliber was evaluated using a measurement tool and calculated in micrometers (Figure 1.D, Figure 2.D). For quantitative analysis, we used the open-source software AngioTool version 0.6a,19,24,41-43 with the following threshold parameters: 30 and 255, vessel thickness: 5, and removal of small particles: 80. AngioTool, a software program for the quantitative analysis of angiogenesis with a user-friendly interface, can identify vascular configurations based on user-defined parameters such as vessel diameter and intensity. AngioTool analyses vessel structure following the latter’s enhancement with multiscale Hessian analysis and smoothing with a recursive Gaussian filter and, after optimizing the parameters, it delineates the vascular structure and skeletonizes and analyzes the following parameters43 (Figure 1.E, Figure 2.E): (1) explant area 4
(the area occupied by the convex hull containing the vessels), (2) vessel area (the area of the segmented vessels), (3) total number of junctions (number of junctions in segmented vessels), (4) total number of endpoints (the number of open-ended segments), (5) total length of vessel (the sum of Euclidean distances between the pixels of all the vessels in the image), and (6) mean lacunarity (mean lacunarity among all-sized boxes).24 Although the vessel percentage area (vessel area/explant area) is provided within the software, the vessel length density (total length of vessel/vessel area) (mm/mm2)44 was calculated instead of using the vessel percentage area as the vessel density since the image analysis was obtained after skeletonization using the AngioTool. The junction density (total number of vessel junctions/total length of vessel) (n/mm) and endpoint density (total number of openended segments/total length of vessel) (n/mm) were calculated in the same manner as that in previous studies.19 For subgroup analysis, subjects were divided into two groups according to number of IVIs during the 12 months of follow-up, including a stable group who required IVI less than three times in 12 months and an unstable group who requiring IVI more than three times in 12 months. All patients completed 3 times of loading injection before analysis period, and loading injections are NOT included in IVI numbers in 12 months of follow up. All demographic, clinical, and structural OCT/OCTA measurements were tabulated in Microsoft Excel 2013 software (Microsoft Corp., Armonk, NY, USA). STATISTICAL ANALYSIS: Statistical analyses included a Student’s t-test to evaluate the variables of interest between two subgroups. Univariate and multivariate binary logistic regression (stable vs. unstable) results for each parameter were also evaluated and compared. To consider multiplicity in statistical comparisons, the Bonferroni correction was applied after multivariate binary logistic regression. These procedures were performed using SPSS version 20 (IBM Corp., Armonk, NY, USA). Receiver operating characteristic (ROC) curve analysis of the built predictive model was performed using MedCalc version 19.0.6 (MedCalc Software bvba, Ostend, Belgium). Results with p values less than 0.05 were considered statistically significant.
RESULTS A total of 89 patients met the inclusion criteria; 18 were excluded for either poor image quality or ungradable OCT images. A total of 71 patients (51 males) were included with a mean age of 72.7 (range: 61–90) years. The mean follow-up period and IVI number before baseline were 30.4 ± 32.6 months and 6.47 ± 3.84 (including three loading injections). The mean logMAR BCVA was 0.39 ± 0.31 at baseline and 0.37 ± 0.31 at one year (p = 0.505). The CRT and SFCT were 275 ± 62 µm and 205 ± 80 µm, respectively. Baseline demographical and clinical characteristics of the two groups (stable and unstable) are summarized in Table 1. The unstable group received a higher number of IVI treatments within 12 months (p < 0.001) and also of previous IVI treatments before the analysis period (p = 0.029). There were no significant differences in age, sex, follow-up period, or visual acuity. CRT and SFCT 5
were 271.93 µm and 202.93 µm in the stable group and 279.14 µm and 208.57 µm in the unstable group, without any significant differences between the two groups (p = 0.660 and p = 0.789, respectively) (Table 1). OCTA FINDINGS: Morphologic OCTA image analysis in all subjects showed the occurrence of the aforementioned four different parameters was distributed as follows: tiny branching vessels in 71.8% (51 eyes), a peripheral anastomotic arcade in 53.5% (38 eyes), vascular loops in 28.2% (20 eyes), and a perilesional hypointense halo in 67.6% (48 eyes). The comparisons between morphologic and quantitative features of NV in OCTA in the two groups are summarized in Table 2. No statistical difference was found in the presence of tiny branching vessels (p = 0.293), arcade (p = 0.342), loops (p = 0.190), or perilesional hypointense halo (p = 0.209) between the two groups. Regarding quantitative features, the unstable group had a larger NV area (stable vs. unstable: 1.327 mm2 vs. 1.778 mm2; p = 0.057) and longer total NV length (stable vs. unstable: 21.06 mm vs. 27.94 mm; p = 0.062) than the stable group, although statistical significance was not reached. The vessel length density (mm/mm2) was 15.72 in the stable group and 16.34 in the unstable group (p = 0.184), while junction density (n/mm) was 2.74 in the stable group and 3.08 in the unstable group (p = 0.160). Further, endpoint density (n/mm) was 2.72 and 3.18, respectively, which was statistically different (p = 0.003). Mean lacunarity was 0.177 in the stable group and 0.211 in the unstable group (p = 0.028). The largest vessel caliber was 42.78 µm in the stable group and 39.52 µm in the unstable group (p = 0.179). Univariate and multivariate binary logistic regression analysis findings for OCTA variables associated with the unstable group are summarized in Table 3. In the univariate analysis, only endpoint index was associated with the unstable group (p = 0.004); there was no association between the unstable group and NV area (p = 0.095), NV density (p = 0.283), total NV length (p = 0.179), junction density (p = 0.161), mean lacunarity (p = 0.212), or largest vessel diameter (p = 0.466). The variables that had an association in the univariate logistic regression analysis (p < 0.2) were included in the multivariate analysis using the backward stepwise selection method to establish a proper multivariate model. Eventually, NV area, total NV length, junction density, and endpoint density were included in the multivariate model. Endpoint density and junction density were statistically correlated with the unstable group and after Bonferroni correction, endpoint density had a strong association with the unstable group among the OCTA NV variables. The ROC curve for endpoint density to predict the unstable group at baseline is described in Figure 4. The area under the curve was 0.689 (p = 0.002) and the recommended cutoff value was 2.25 (n/mm) according to MedCalc, which showed the unstable group demonstrated a 93.75% rate of sensitivity and 39.53% rate of specificity. Although this value cannot provide high specificity, a high negative predictive value (high true negative rate) was 89.47%, which is a crucial requirement to be a sensitive predictive factor.
DISCUSSION 6
Recently, many studies have shown that OCTA enables the noninvasive identification of NV in morphologic features and reported many characteristics associated with NV of exudative (active) AMD compared to nonexudative (inactive, quiescent) AMD (e.g., a seafan or lacy wheel shape, the presence of tiny capillaries, anastomoses and vessel loops, tiny branching vessels, a peripheral arcade, and a hypo-intense halo around the lesion).23,24,37 However, most of these morphological features are very subjective in nature, making it difficult to reach a consensus as to their applicability. Further, there is still a lack of the study of analysis between ‘high recurrence’ and ‘low recurrence’ both in active AMD, with differences in treatment requirements. Therefore, we aimed to elucidate more objective, automated, and quantitative approaches to determine the activity in exudative AMD. The patients included in this study all had active (exudative) type 1 NVAMD lesions at baseline and had no difference in age, sex, CRT, or SFCT, which were previously reported as prognostic factors for AMD.9,45,46 Previous studies have shown that type 1 NVs have relatively mature vessels and large-caliber trunk vessels than type 2 NVs.36,47 Nagano et al36 also recently reported higher junction density in type 2 NVs than type 1 NVs using OCTA, which also suggests that the two types of NV might differ in maturity. And it is also known that type 1 CNV tends to be resistant against anti-VEGF treatment compared to type 2 and type 3 NVs because of RPE covering type 1 CNVs may block penetration of anti-VEGF drugs48 which can make a difference in the number of IVIs in the follow-up period. As our study included treated eyes (not treatment naïve eyes), we only included type 1 NVAMD because of concerns that these differences might affect the analysis. In a previous study of NV morphologic features, the presence of tiny branching vessels and a peripheral anastomotic arcade were suggested to be biomarkers of active lesions compared to quiescent ones and were suggested as a predictive model for treatment decisions by Coscas et al23 in a study of 126 eyes that predicted an exudative lesion with a sensitivity of 97.6%. In our study, 71.8% of all subjects had tiny branching vessels and 53.5% had peripheral arcade, yet the morphologic appearance of NV did not differ significantly between the two groups. However, all of our subjects had active AMD at baseline, which showed as exudative lesions on OCT and needed IVI treatment, and this may help to explain the morphologically active features in both groups. Further, this implies that morphologic biomarkers may help differentiate an active versus quiescent lesion but may not be as effective in guiding treatment intervals for patients with active lesions. As known, the mechanisms in the creation of new vascular networks include angiogenesis and arteriogenesis. Angiogenesis is the formation of new capillaries from preexisting vessels (sprouting) mediated by VEGF and arteriogenesis is the expansion of previously formed vessels largely stimulated by increased flow through the remaining vessels.49-51 Anti-VEGF treatment prunes back the newly growing vessels but cannot affect the pericyte-covered larger vessels and it concludes a higher flow in the remaining vascular network, which stimulates arteriogenesis. In 2015, Spaide suggested the morphological transition of NV in repeated anti-VEGF treatment should be called “abnormalization”52 and many researchers have reported results that support this hypothesis.18,19,53 He suggested that repeated IVIs might 7
affect major feeder vessels growing larger with fewer branching points and more vascular anastomotic connections by periodic pruning of angiogenic vascular sprouts and called this morphological transition as “abnormalization”. From this point of view, we speculated that the more pruned back vessels that exist, the higher the transmural pressure generated after IVI will be, which can lead to arteriogenesis (resprouting) by VEGF withdrawal and subsequent leakage and exudation in active AMD. AngioTool software, which offers semiautomated quantitative information on vessels and junction points, indicates internal branching and anastomotic connections in vascular networks and endpoints in open-ended vessels and could represent surrogate parameters for sprouting vessels without anastomosis. We calculated junction density and endpoint density by the numbers per total vessel length, which can be interpreted as a measure of anastomotic and sprouting activity in proportion to the total NV length. Lacunarity is the parameter of inhomogeneity of lesions and reflects the complexity and aggressiveness of a structure; it has been suggested also as a parameter for vascular networks in drug-treated specimens or pathological vasculature.54 In a simple quantitative comparison of our study, patients in the unstable group had neovascularization of a higher endpoint density and higher lacunarity than did those of the stable group. Endpoint density was the only parameter to show a statistically significant association with the unstable group in both the univariate and multivariate analyses. In our study, the sprouting activity and complexity of NV peripheral lesions represented by endpoint density and lacunarity were higher in the unstable group, and endpoint density could possibly be used as a predictive factor for frequent treatment requirements (high recurrence) after IVI. Sarraf et al quantitatively assessed active and quiescent NV and reported prominent and larger central vessels were more closely associated with the quiescent NV group. He also reported the fractal dimension of NV was lower in quiescent NV than in active NV and was reduced after IVI in active NV.25 This suggested that the pattern of NV lesions after treatment might be less complex due to the attenuation and pruning of small-caliber vessels. Nesper et al retrospectively explored the three-dimensional complexity of NV lesions in 51 eyes with NVAMD and found that poor responders were treated more frequently than at six-week intervals and had a greater number of NV flow layers.55 The higher endpoint density and lacunarity in the unstable group in our research are in line with the outcomes of these prior studies. Previously, studies about NV density in active and quiescent patients suggested there was no difference between the two groups19,25 and we also found that there was no difference in NV density between stable and unstable group. Roberts et al (2017) also used the AngioTool to evaluate 23 eyes with NVAMD for quantitative features on OCTA images between good responders treated less frequently than six weeks versus poor responders and reported a higher vessel density in the good responders group (51.11% vs. 37.80%; p = 0.097) with no difference among other parameters.24 However, in their study, the study population was too small to accurately compare these parameters and they did not evaluate endpoint density considering sprouting vessel per vessel length. The larger sample size and more strict criteria for stable group in our study might help explain the meaningful results compared with the previous study. Limitations of this study include the relatively small number of subjects as well as its 8
retrospective nature and possibility of selection bias, not only from the inclusion criteria but also due to our subgroup division. Subjects in the unstable group had more IVI treatments previous to the analysis period, but this was in line with the definitions of both groups. In previous studies, there was an inconsistency in the definitions of poor responders to IVI, which varies from six weeks to 12 weeks for the treatment interval.19,24,25,40 The SEVEN-UP study which assessed long-term outcomes 7 to 8 years after initiation of ranibizumab therapy reported that patients had received a mean of 6.8 IVIs during the mean 3.4-year interval (2 IVIs/year)56 since exit from the HORIZON study.57 As the patients included in this study, those patients had a mean follow-up period of 30.4 months and had been treated with IVI. As a result, to find predictive factors, we defined the unstable group as those who needed IVI more than three times in 12 months. And for the reasons already described above, this study included only type 1 AMD, but further study on type 2, type 1 & 2 mixed, and type 3 needed in more large population study. Depending on the type, different conclusions can be drawn, which may require attention for proper interpretation. This study quantitatively analyzed the NV en face images of OCTA as well as morphological analysis. Poorly segmented or visualized images due to large PDE, submacular hemorrhage, or NV larger than the measurement area were excluded and was 18 (20.22%) out of 89. Farecki et al reported the detectable rate of NV lesions in auto-segmentation OCTA as 92.2% in choriocapillaris slabs and 34.5% in RPE slabs (this included minor and sharp demarcations)38 and in the studies by Uchida et al40 and Takeuchi et al19 who also reported quantitative analysis of NV in AMD by OCTA, 11 in 40 (28%) eyes and 7 in 22 (32%) eyes were not able to be analyzed respectively because of indistinct vessel morphology. The buried data in this study might have affected the results but the ratio is comparable with previous studies. Also, the use of swept-source OCTA using longer wavelengths (~1,050 nm) and greater laser power, which allows for deeper penetration, may have better delineated the existence and morphology of NV, as prior studies demonstrated that NV size as determined by swept-source OCTA was larger than that found by spectral-domain OCTA as used in this study.58-60 However, the Spectralis OCT2 device used in our study had a relatively longer wavelength (870 nm) and denser scan pattern and has TruTrack Active Eye Tracking technology, which corrects for displacement by performing the reacquisition of OCT images at the correct retinal locations in realtime and by performing repeated scans (four to seven times) to obtain more accurate images in the case of abrupt or saccadic eye movements, which can cause motion artifacts. Also, Corvis et al reported that Spectralis OCTA was the closest to ICGA with the lowest limits of agreement compared to PlexElite (Carl Zeiss Meditec, Dublin, CA, USA).61 In AngioTool, the signal threshold is set by the user (it was 30 in our study) to remove artifacts from the NV slab, which could be a limitation of our study in that finer vessels may not have been included and this might have caused an underestimation of the endpoint. However, we still found a significant correlation between endpoint density and high recurrence in NVAMD. In conclusion, OCT angiography is a promising imaging modality that helps with guiding physicians to predict the patient’s response to anti-VEGF treatment with NVAMD. Further studies 9
using automated, accessible, and quantitative methods like Angiotool are needed to obtain standardized criteria to decide the optimal treatment interval in various regimens.
10
ACKNOWLEDGMENTS/DISCLOSURE: a. Funding/Support: The authors indicate no financial support or financial conflict of interest. b. Financial Disclosures: J.O. is a consultant of Topcon Corporation. Other authors certify that they have no financial disclosures. c. Other Acknowledgments: None
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FIGURE LEGENDS FIGURE 1. Multimodal imaging of a 77-year-old male patient suffering from NVAMD in the stable group. A: Section image shows structural OCT in the background and OCTA blood flow as a yellow overlay. The red dotted line in the inset is the manual segmentation boundary (upper: external limiting membrane, lower: Bruch’s membrane). B: The en-face OCT angiogram in the NV slab shows the “Lacy wheel” shape of type 1 NV. C: Manually cropped image of NV to remove projection artifacts. D: NV image magnified 300%, pixels between O to X were calculated to measure the vessel caliber. E: AngioTool analysis, skeletonized vessel (red line), junction point (blue dot), vessel area (outer green line), endpoint (point of the open-ended vessel).
FIGURE 2. Multimodal imaging of a 67-year-old male patient diagnosed with type 1 NVAMD in the unstable group. A: Fusion image of structural OCT and OCTA data as a yellow overlay. The red dotted line in the inset is the manual segmentation boundary (same as FIGURE 1). B: The en-face OCT angiogram in the NV slab shows the “medusa pattern” of type 1 NV. C: Manually cropped image of NV to remove projection artifacts. D: NV image magnified 300%, pixels between O to X were calculated to measure the vessel caliber. E :AngioTool analysis (overlay is same as FIGURE 1).
FIGURE 3. Qualitative assessment of NV detected by OCT-A. A: Lacy wheel pattern containing numerous tiny branches (white arrowhead) with peripheral arcade (anastomoses) at the vessel termini (yellow dashed line). B: Partial long filamentous linear vessels with a central prominent feeder vessel (*) and inner loop (white arrow) surrounded by a dark perilesional halo (white dashed line). This NV also has a peripheral arcade at the superior part (yellow dashed line). (C) Sea-fan shape NV shows numerous tiny branches (white arrowhead) and a peripheral arcade (yellow dashed line) with perilesional halo (white dashed line) and prominent central feeder vessels (*). D: Dead-tree-shaped NV has a central vessel (*).
FIGURE 4. The ROC curve between the sensitivity and specificity showed that the endpoint density of neovascularization from OCTA correctly predicts the unstable group with a high sensitivity and high negative predictive value (AUC, area under the curve).
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TABLE 1. Patient demographics Stable Unstable p-value (n = 38) (n = 33) Mean age (SD) 73.59 (7.61) 71.03 (5.80) 0.153 Sex (M/F) 27/11 24/9 0.876 Follow-up period before analysis, 25.18 36.48 0.188 Mean (SD) (29.54) (35.28) No. of anti-VEGF treatments, Mean 1.47 (0.98) 4.57 (1.45) < 0.001 (SD) Previous anti-VEGF treatments, Mean 4.93 (5.3) 8.21 (6.8) 0.029 (SD) LogMAR BCVA, Mean (SD) Baseline 0.42 (0.31) 0.36 (0.31) 0.398 12 months 0.37 (0.29) 0.32 (0.32) 0.240 CRT (µm), Mean (SD) 271.93 279.14 0.660 (60.39) (64.99) SFCT (µm), Mean (SD) 202.93 208.57 0.789 (76.72) (85.48) SD = standard deviation; VEGF = vascular endothelial growth factor; BCVA = best=corrected visual acuity; CRT = central retinal thickness; SFCT = subfoveal choroidal thickness.
TABLE 2. Morphologic and quantitative features of NV at baseline Stable Unstable p-value (n = 38) (n = 33) Morphological feature, n (%) Tiny branching 25 (65.8) 26 (78.79) 0.293 Arcade 18 (47.37) 20 (60.61) 0.342 Loops 8 (21.05) 12 (36.36) 0.190 Halo 23 (60.53) 25 (75.76) 0.209 Quantitative features, mean (SD) NV area (mm2) 1.327 (0.695) 1.778 (1.064) 0.057 NV density (mm/mm2) 15.72 (1.89) 16.34 (1.61) 0.184 Total NV length (mm) 21.06 (11.12) 27.94 (17.14) 0.062 Junction density (n/mm) 2.74 (1.08) 3.08 (0.69) 0.160 Endpoint density (n/mm) 2.72 (0.89) 3.18 (0.60) 0.03 Mean lacunarity 0.177 (0.061) 0.211 (0.065) 0.028 Largest vessel caliber (µm) 42.78 (8.85) 39.52 (9.06) 0.473
TABLE 3. Quantitative variables of NV associated with the unstable group using binary logistic regression analysis Univariate Multivariatea Variables OR (95 % CI) pOR (95 % CI) p-value value NV area (mm2) 1.57 (0.970–2.672) 0.095 1.213 (0.751– 0.431 1.959) NV density(mm/ mm2) 1.226 (0.909– 0.283 NA NA 1.653) Total NV length (mm) 1.020 (0.992– 0.179 0.838 (0.632– 0.219 1.048) 1.111) 0.034 Junction density 1.520 (0.846– 0.161 0.838 (0.632– (n/mm) 2.730) 1.111) Endpoint density 2.633 (1.370– 0.004 3.691 (1.633– 0.002 (n/mm) 5.062) 8.346) Mean lacunarity 1.103 (1.009– 0.212 NA NA 1.207) 0.980 (0.929– 0.466 NA NA Largest vessel caliber 1.034) (µm) a Multivariate model summary ;Hosmer and Lemeshow test; chi-squared test = 2.795, p = 0.903, −2log likelihood = 70.649.
Highlights Neovascularization (NV) with higher open-ended vessels related to frequent recurrence of nAMD. In exudative nAMD, recurrence rate could be predicted by evaluating features of NV. By considering features of NV, optimal treatment interval could be modulated.
Biosketch Mihyun Choi, MD, PhD is a first year vitreoretinal clinical fellow in the Department of Ophthalmology at Korea University Guro Hospital, Seoul, Korea. Dr. Choi completed her medical school at Chonnam National University School of Medicine and Ophthalmology Residency at Catholic University Medical Center. Her interests include retinal and choroidal imaging, age-related macular degeneration.
Table of Contents Statement This study quantitatively analyzed neovascularization in optical coherence tomography angiography of neovascular Age-related macular degeneration. Authors found a significant correlation between endpoint density of neovascularization and frequent recurrence in neovascular Age-related macular degeneration. Endpoint density might represent the sprouting activity of neovascularization and could possibly be used as a predictive factor for frequent treatment requirements of antivascular endothelial growth factor.
Credit Author Statement MIHYUN CHOI: Conceptualization, Methodology, Software, Writing - Original Draft. SEONG-WOO KIM: Conceptualization, Validation, Writing - Review & Editing, Supervision. CHEOLMIN YUN: Writing - Review & Editing. JAERYUNG OH: Writing - Review & Editing