The Architecture of Macular Neovascularizations Predicts Treatment Responses to Anti-VEGF Therapy in Neovascular AMD

Updates on novel and traditional OCT and OCTA biomarkers in nAMD

Predictivity of optical coherence tomography (OCT) examination for the development of neovascular age-related macular degeneration (nAMD) was demonstrated to be superior compared to other methods, suggesting it as an elective method for screening purposes. Moreover, OCT and OCT angiography (OCTA) have enabled us to provide accurate prognostic information to nAMD patients. Along with well-known prognostic biomarkers, such as the presence of reticular pseudodrusen, the volume of the pigment epithelial detachment (PED), subretinal fluid (SRF), intraretinal fluid (IRF) and hyperreflective foci (HRF), emerging parameters show promising results and may allow a further refinement of prediction and customization of treatment and follow up strategies. This review of the literature discusses the main OCT and OCTA biomarkers reported in literature for nAMD, with a special focus on recent updates on the subject. Future perspectives of clinical applications include the development of artificial intelligence models considering all the described biomarkers to allow automatic and detailed characterization of each lesion based on imaging information.

The Vascular Architecture of Macular Neovascularization in Age-Related Macular Degeneration as a Predictor of Therapy Requirements: A 3-Year Longitudinal Analysis

Background: Anti-Vascular Endothelial Growth Factor (VEGF) therapy is an effective therapy for improving and stabilizing the vision of patients with neovascular age-related macular degeneration (nAMD). However, the treatment requirements, particularly the number of intraocular injections, can vary significantly among patients. This study aimed to analyze the vascular characteristics of macular neovascularizations (MNVs) to identify potential biomarkers that could predict the required injection frequency throughout the disease course. Methods: In all patients, the initial diagnosis of nAMD was confirmed using optic coherence tomography (OCT), fluorescein angiography, and OCT angiography (OCTA). MNVs detected using OCTA were subjected to quantitative vascular analysis of their area, total vascular length (sumL), fractal dimension (FD), and flow density. These results were then correlated with the number of intravitreal anti-VEGF treatments administered during the first 3 years of treatment. Additionally, the relationship between the parameters and visual acuity progression was analyzed. Results: A total of 68 treatment-naïve eyes were included in the study, comprising 31 eyes with type 1 MNV, 19 eyes with type 2 MNV, and 18 eyes with type 3 MNV. The average MNV area at baseline was 1.11 mm2 ± 1.18 mm2, the mean total vascular length was 12.95 mm ± 14.24 mm, the mean fractal dimension was 1.26 ± 0.14, and the mean flow density was 41.19 ± 5.87. On average, patients in our cohort received 19.8 ± 8.5 intravitreal injections (IVIs). A significant correlation was found between the number of administered IVIs in the first 3 treatment years and the MNV area (p < 0.005), sumL (p < 0.005), and FD (p < 0.05), while no correlation was found with flow density. Additionally, there was no significant association between MNV type and treatment requirements, nor between MNV vascular architecture and visual acuity progression. Conclusions: The results suggest that the specific vascular structure of untreated MNV may serve as a predictor of long-term treatment demand. With the emergence of new drug classes and advancements in imaging techniques, these parameters could offer valuable insights for forecasting treatment requirements.

Optical coherence tomography angiography in neovascular age-related macular degeneration: comprehensive review of advancements and future perspective

Optical coherence tomography angiography (OCTA) holds promise in enhancing the care of various retinal vascular diseases, including neovascular age-related macular degeneration (nAMD). Given nAMD's vascular nature and the distinct vasculature of macular neovascularization (MNV), detailed analysis is expected to gain significance. Research in artificial intelligence (AI) indicates that en-face OCTA views may offer superior predictive capabilities than spectral domain optical coherence tomography (SD-OCT) images, highlighting the necessity to identify key vascular parameters. Analyzing vasculature could facilitate distinguishing MNV subtypes and refining diagnosis. Future studies correlating OCTA parameters with clinical data might prompt a revised classification system. However, the combined utilization of qualitative and quantitative OCTA biomarkers to enhance the accuracy of diagnosing disease activity remains underdeveloped. Discrepancies persist regarding the optimal biomarker for indicating an active lesion, warranting comprehensive prospective studies for validation. AI holds potential in extracting valuable insights from the vast datasets within OCTA, enabling researchers and clinicians to fully exploit its OCTA imaging capabilities. Nevertheless, challenges pertaining to data quantity and quality pose significant obstacles to AI advancement in this field. As OCTA gains traction in clinical practice and data volume increases, AI-driven analysis is expected to further augment diagnostic capabilities.

OCT Angiography of Type 1 Macular Neovascularization in AMD: A Morphometric Evaluation

Purpose

To determine biomarkers of macular neovascularization (MNV) in neovascular age-related macular degeneration through the application of an automatic algorithm based optical coherence tomography angiography (OCTA) analysis.

Methods

In this retrospective, observational, single-center, cross-sectional study, patients with a diagnosis of age-related macular degeneration complicated by type 1 MNV were included. MNV was detected with OCTA and scans were analyzed with a qualitative and quantitative open-source image processing package. For each analyzed image, we automatically acquired the following data: Total MNV area, vessel area, vessel density (VD), total number of branches, total number of vascular junctions, mean vessel length, mean vessel diameter, fractal dimension (FD), junction density, and vessel tortuosity.

Results

The following morphological parameters revealed a significant negative correlation with best-corrected visual acuity: MNV area - Spearman ρ = -0.309 (P = 0.002); vessel area - Spearman ρ = -0.315 (P = 0.002); total number of vascular junctions - Spearman ρ = -0.285 (P = 0.005), and VL - Spearman ρ = -0.304 (P = 0.003). Immature MNV lesions were significantly associated with better vessel area than mature and hypermature lesions.

Conclusions

Several automated MNV-associated morphological parameters can correlate with the best-corrected visual acuity. Further studies are warranted to determine if these OCTA biomarkers can be applied to guide anti-vascular endothelial growth factor therapy and predict response to treatment.

Translational Relevance

The analysis of MNV biomarkers may have prognostic value in terms of visual function.

Self-supervised based clustering for retinal optical coherence tomography images

BACKGROUND

In response to the inadequacy of manual analysis in meeting the rising demand for retinal optical coherence tomography (OCT) images, a self-supervised learning-based clustering model was implemented.

METHODS

A public dataset was utilized, with 83,484 OCT images with categories of choroidal neovascularization (CNV), diabetic macular edema (DME), drusen, and normal fundus. This study employed the Semantic Pseudo Labeling for Image Clustering (SPICE) framework, a self-supervised learning-based method, to cluster unlabeled OCT images into binary and four categories, and the performances were compared with baseline models. We also analysed feature distribution using t-SNE, and explored the cluster centers, attention maps, and misclassified images. In addition, DME and CNV subsets were clustered binarily, and the results were interpreted by two retinal specialists.

RESULTS

SPICE demonstrated superior performance in binary and four categories classification tasks, achieving the accuracy of 0.886 and 0.846, respectively. In t-SNE analysis, the four types exhibited significant clustering into distinct groups. The cluster centers corresponded to the human labels, and the heat map revealed that the model focused on important biomarkers. The misclassified images exposed similar features to the inaccurate classes. The model also grouped DME and CNV into two distinct categories respectively.

CONCLUSIONS

Self-supervised clustering effectively distinguished disease variances and revealed common features, with a notable capability to detect disease heterogeneity through biomarkers.

Nomogram for predicting short-term response to anti-vascular endothelial growth factor treatment in neovascular age-related macular degeneration: An observational study

BACKGROUND

Anti-vascular endothelial growth factor (anti-VEGF) therapy is critical for managing neovascular age-related macular degeneration (nAMD), but understanding factors influencing treatment efficacy is essential for optimizing patient outcomes.

AIM

To identify the risk factors affecting anti-VEGF treatment efficacy in nAMD and develop a predictive model for short-term response.

METHODS

In this study, 65 eyes of exudative AMD patients after anti-VEGF treatment for ≥ 1 mo were observed using optical coherence tomography angiography. Patients were classified into non-responders (n = 22) and responders (n = 43). Logistic regression was used to determine independent risk factors for treatment response. A predictive model was created using the Akaike Information Criterion, and its performance was assessed with the area under the receiver operating characteristic curve, calibration curves, and decision curve analysis (DCA) with 500 bootstrap re-samples.

RESULTS

Multivariable logistic regression analysis identified the number of junction voxels [odds ratio = 0.997, 95% confidence interval (CI): 0.993-0.999, P = 0.010] as an independent predictor of positive anti-VEGF treatment outcomes. The predictive model incorporating the fractal dimension, number of junction voxels, and longest shortest path, achieved an area under the curve of 0.753 (95%CI: 0.622-0.873). Calibration curves confirmed a high agreement between predicted and actual outcomes, and DCA validated the model's clinical utility.

CONCLUSION

The predictive model effectively forecasts 1-mo therapeutic outcomes for nAMD patients undergoing anti-VEGF therapy, enhancing personalized treatment planning.

Linking disease activity with optical coherence tomography angiography in neovascular age related macular degeneration using artificial intelligence

To investigate quantitative associations between AI-assessed disease activity and optical coherence tomography angiography (OCTA)-derived parameters in patients with neovascular age-related macular degeneration (nAMD) undergoing anti-VEGF therapy. OCTA and SD-OCT images obtained from multicenter, randomized study data were evaluated. A deep learning algorithm (RetInSight) was used to detect and quantify macular fluid on SD-OCT. Mixed effects models were applied to evaluate correlations between fluid volumes, macular neovascularization (MNV)-type and OCTA-derived MNV parameters; lesion size (LS) and vessel area (NVA). 230 patients were included. A significant positive correlation was observed between SRF and NVA (estimate = 199.8 nl/mm2, p = 0.023), while a non-significant but negative correlation was found between SRF and LS (estimate = - 71.3 nl/mm2, p = 0.126). The presence of Type I and Type II MNV was associated with significantly less intraretinal fluid (IRF) compared to Type III MNV (estimate type I:- 52.1 nl, p = 0.019; estimate type II:- 51.7 nl, p = 0.021). A significant correlation was observed between pigment epithelial detachment (PED) and the interaction between NVA and LS (estimate:28.97 nl/mm2; p = 0.012). Residual IRF at week 12 significantly correlated to baseline NVA (estimate:38.1 nl/mm2; p = 0.015) and LS (estimate:- 22.6 nl/mm2; p = 0.012). Fluid in different compartments demonstrated disparate associations with MNV OCTA features. While IRF at baseline was most pronounced in type III MNV, residual IRF was driven by neovascular MNV characteristics. Greater NVA in proportion to LS was associated with higher amounts of SRF and PED. The correlation between these parameters may represent MNV maturation and can be used as a biomarker for resolution of disease activity. AI-based OCT analysis allows for a deeper understanding of neovascular disease in AMD and the potential to adjust therapeutic strategies to optimize outcomes through precision medicine.

Comparative quantitative analysis of optical coherence tomography angiography in varied morphologies of macular neovascularization following intravitreal conbercept and ranibizumab treatments for neovascular age‑related macular degeneration

The present study aimed to examine the optical coherence tomography angiography (OCTA) parameters associated with macular neovascularization (MNV) in patients diagnosed with neovascular age-related macular degeneration (nAMD) and treated with either intravitreal conbercept (IVC) or ranibizumab (IVR). It enrolled 39 nAMD patients presenting with MNV, including 23 in the IVC group and 16 in the IVR group. All participants were treatment-naïve with intravitreal therapy and they underwent treatment following a '3+PRN' regimen. The MNV patterns identified through OCTA were categorized as Medusa, tangled, seafan and other variations. Key outcome measures encompassed best-corrected visual acuity (BCVA), MNV vascular area (MNV-VA), MNV vascular density (MNV-VD) ratio and central macular thickness (CMT). In the present study, 44 eyes were included, with 28 eyes undergoing treatment with IVC and 18 eyes with IVR. On day 90, there was a statistically significant improvement in mean BCVA from baseline among all patients treated with IVC (P=0.002). Notably, improved outcomes were observed in those with the 'tangled' pattern compared with the other three patterns (P=0.007). CMT exhibited a significant decrease from baseline (P=0.007), with consistent improvement observed across all four patterns (P=0.052) on day 90. The mean MNV-VA decreased in all patients, reaching statistical significance for the Medusa pattern (P=0.008), although the improvement in visual acuity was deemed unsatisfactory. Patients with the seafan pattern treated with IVR improved significantly in BCVA (P=0.042). The mean CMT significantly improved from baseline (P=0.001), consistent across the four patterns (P=0.114). Significant improvements were noted in the mean MNV-VA for the seafan pattern and in the mean MNV-VD ratio for the other patterns. The two regimens had no significant differences regarding BCVA, CMT, and MNV parameters. Conbercept emerged as a viable treatment option for patients presenting with tangled MNV patterns. On the other hand, ranibizumab might be considered an effective intervention for individuals with seafan MNV patterns. Notably, the Medusa MNV pattern was associated with a morphologic configuration indicative of a poor prognosis.

[Prognosis criteria of optical coherence tomography angiography for the long-term efficacy of anti-VEGF therapy of neovascular age-related macular degeneration]

PURPOSE

The study aimed to determine the most significant optical coherence tomography angiography (OCTA) parameters in terms of predicting anti-VEGF therapy effectiveness during long-term (3-year) follow-up of patients with neovascular age-related macular degeneration (nAMD).

MATERIAL AND METHODS

The study included 122 patients (122 eyes) with mean age of 73.4±6.6 years who were diagnosed with nAMD. Subgroup analysis included 50 patients (50 eyes) with detailed OCT angiography examination of macular neovascularization (MNV) characteristics and their changes in the course of the follow-up, which lasted 144 weeks. All patients were treated by angiogenesis inhibitor (aflibercept 2 mg), most of them - according to Treat-and-Extend protocol.

RESULTS

Treatment response (either 'good' or 'partial') was achieved in all patients, and the proportion of the response types was similar in both types 1 and 2 MNV. Key OCTA parameters associated with the number of injections, as well as morphological and functional response (best-corrected visual acuity, retinal neuroepithelium and pigment epithelium detachment), were vascular network area and MNV area assessed at baseline and three months after treatment initiation. Both of these parameters were closely related in both MNV types during the follow-up. Key parameter with maximum number of clinically significant correlations ('very high' strength, p<0.05) in eyes with 'good' response was MNV area, in eyes with 'partial' response - vascular density and greatest vascular caliber.

CONCLUSIONS

Vascular network area and MNV area assessed at baseline and after three loading doses were determined as the most significant OCTA characteristics for predicting the number of injections and treatment response based on functional and morphological parameters. MNV area was found to be the most clinically significant marker in 'good' response, vascular density and greatest vascular caliber - in 'partial' response.