Defining Cystoid Macular Degeneration in Diabetic Macular Edema: An OCT-Based Single-center Study

Ultrastructural imaging biomarkers in diabetic macular edema: A major review

Diabetic macular edema (DME) is a vision-threatening complication of diabetic retinopathy and causes significant morbidity in patients. Anti-vascular endothelial growth factor (VEGF) agents are the mainstay of treatment for DME, with steroid implants being used for the treatment of anti-VEGF resistant eyes. Over the years, several classification systems have been devised to describe the patterns of DME using optical coherence tomography (OCT). With the advent of effective treatments, it has become imperative that imaging cues are not merely used for classifying the disease but also as biomarkers for prognostication of disease activity and treatment response. In this aspect, newer imaging findings such as hyperreflective dots, photoreceptor integrity, and disorganization of retinal inner layers have been characterized in detail by several authors. Macular perfusion analysis using OCT angiography is the latest in the armamentarium for imaging DME. In this narrative review, we have summarized all relevant literature related to the ultrastructural imaging-based biomarkers of DME and their correlation to treatment.

Oct biomarkers for early prognosis in diabetic macular edema treatment with ranibizumab

BACKGROUND

Diabetic macular edema is the main cause of vision loss in patients with diabetic retinopathy. In this work, we aimed to assess the role of Optical Coherence Tomography (OCT) biomarkers in patients treated with ranibizumab.

METHODS

A prospective study enrolling 46 eyes with DME under ranibizumab intravitreal therapy with 12 months of follow-up. The primary endpoint was to assess the association between OCT biomarkers at baseline and the type of treatment response.

RESULTS

Good responders, compared with partial/non responders, had lower number of inner nuclear layer cysts (INLc) at baseline, (26.5% vs 73.5%, p = 0.035) and presented, at 12 months of follow-up, lower percentage of disorganization of retinal inner layers (12.0% vs 88.0%, p = 0.001), lower disruption of outer plexiform layer (8.7% vs 91.3%, p < 0.001) and lower outer nuclear layer cysts (17.4% vs 82.6%, p = 0.013). At the end of follow-up, it was observed a higher frequency of inner nuclear layer cysts in patients with higher glycated haemoglobin (p = 0.028).

CONCLUSION

This study showed the value and importance of OCT parameters, such as absence of INLc, as a prognostic therapeutic response. A normalization of the macular anatomy with ranibizumab is more likely to happen in early complete responders. The association between INLc and higher glycated haemoglobin levels showed the importance of systemic metabolic control in systemic diabetic manifestations. Clinicaltrials.gov NCT04387604.

Switching to an Intravitreal Dexamethasone Implant after Intravitreal Anti-VEGF Therapy for Diabetic Macular Edema: A Review

Among working-age people, diabetic retinopathy and diabetic macular edema are currently considered the main causes of blindness. Nowadays, intravitreal injections are widely acknowledged as a significant milestone in ophthalmology, especially for the treatment of several retinal diseases, including diabetic macular edema. In particular, anti-vascular endothelial growth factor (VEGF) agents are typically the first line of treatment; however, monthly injections are required, at least, during the loading dosage. Notably, an intravitreal 0.7 mg dexamethasone (DEX) implant (Ozurdex®, AbbVie Inc., North Chicago, IL, USA) is considered a legitimate substitute treatment for diabetic eyes that have not responded to anti-VEGF treatment. In fact, clinical trials and real-life studies have demonstrated the effectiveness and safety of an intravitreal DEX implant in treating such conditions over a period of three to six months. For this reason, wisely selecting diabetic patients might be crucial to decreasing the load of injections in clinics and hospitals. The purpose of this review is to analyze the available scientific literature to highlight the benefits, efficacy, and clinical criteria for choosing whether to switch from intravitreal anti-VEGF therapy to an intravitreal DEX implant in diabetic macular edema.

Difference of central foveal thickness measurement in patients with macular edema using optical coherence tomography in different display modes

Purpose

To assess the differences in the measurement of central foveal thickness (CFT) in patients with macular edema (ME) between two display modes (1:1 pixel and 1:1 micron) on optical coherence tomography (OCT).

Design

This is a retrospective, cross-sectional study.

Methods

Group A consisted of participants with well-horizontal OCT B-scan images and group B consisted of participants with tilted OCT B-scan. We manually measured the CFT under the two display modes, and the values were compared statistically using the paired t-test. Spearman's test was used to assess the correlations between the OCT image tilting angle (OCT ITA) and the differences in CFT measurement. The area under the curve (AUC) was calculated to define the OCT ITA cutoff for a defined CFT difference.

Results

In group A, the mean CFT in the 1:1 pixel display mode was 420.21 ± 130.61 µm, similar to the mean CFT of 415.27 ± 129.85 µm in the 1:1 micron display mode. In group B, the median CFT in the 1:1 pixel display mode is 409.00 μm (IQR: 171.75 μm) and 368.00 μm (IQR: 149.00 μm) in the 1:1 micron display mode. There were significant differences between the two display modes with the median (IQR) absolute difference and median (IQR) relative difference of 38.00 μm (75.00 μm) and 10.19% (21.91%) (all p = 0.01). The differences in CFT measurement between the two display modes were correlated with the OCT ITA (absolute differences, r = 0.88, p < 0.01; relative differences, r = 0.87, p < 0.01). The AUC for a predefined CFT difference was 0.878 (10 μm), 0.933 (20 μm), 0.938 (30 μm), 0.961 (40 μm), 0.962 (50 μm), and 0.970 (60 μm).

Conclusion

In patients with DM, when the OCT B-scan images were well-horizontal, manual CFT measurements under the two display modes were similar, but when the B-scan images were tilted, the CFT measurements were different under the two display modes, and the differences were correlated to the OCT ITA.

Morphological changes of foveal cysts as a predictor for visual response to anti-vascular endothelial growth factor treatments in diabetic macular edema : Degenerative cyst in DME

PURPOSE

To investigate morphological changes of intraretinal cyst in association with visual acuity following treatment for diabetic macular edema.

METHODS

This retrospective study enrolled 105 eyes from 105 treatment naïve patients with diabetic macular edema following anti-vascular endothelial growth factor injections. Best-corrected visual acuity (BCVA) and optical coherence tomography (OCT) data were obtained at baseline, 1, 3, 6, and 12 months. The width and height of the largest intraretinal cyst (IRC) at all different visits were measured and were correlated to final visual acuity by receiver operating characteristic curve. The exudative feature was defined by the presence of hard exudates. Multivariate logistic regression was used to select the independent predictor for visual outcomes.

RESULTS

Intraretinal cyst width but not the cyst height after treatment at 1 month independently predicted final visual loss of ten letters or more (multivariate P = 0.009). The optimal cutoff value was 196 um with a sensitivity of 0.889 and a specificity of 0.656. Eyes with large IRC width using this cutoff were consistently larger than those with small IRC width through 12 months (P = 0.008, Mann-Whitney U test). Small IRC width < 196 um at 1 month was more likely to coexist with exudative feature (P = 0.011, Fisher's exact test). Among baseline factors, large IRC width predicted IRC width ≥ 196 um at 1 month (multivariate P < 0.001).

CONCLUSION

Cyst morphology following intravitreal injection predicts visual outcomes. Eyes with IRC width ≥ 196 um after treatment at 1 month tends to be more degenerative, and less likely to coexist with exudative feature.

Generating OCT B-Scan DME images using optimized Generative Adversarial Networks (GANs)

Diabetic Macular Edema (DME) represents a significant visual impairment among individuals with diabetes, leading to a dramatic reduction in visual acuity and potentially resulting in irreversible vision loss. Optical Coherence Tomography (OCT), a technique that produces high-resolution retinal images, plays a vital role in the clinical assessment of this condition. Physicians typically rely on OCT B-Scan images to evaluate DME severity. However, manual interpretation of these images is susceptible to errors, which can lead to detrimental consequences, such as misdiagnosis and improper treatment strategies. Hence, there is a critical need for more reliable diagnostic methods. This study aims to address this gap by proposing an automated model based on Generative Adversarial Networks (GANs) to generate OCT B-Scan images of DME. The model synthesizes images from patients' baseline OCT B-Scan images, which could potentially enhance the robustness of DME detection systems. We employ five distinct GANs in this study: Deep Convolutional GAN, Conditional GAN, CycleGAN, StyleGAN2, and StyleGAN3, drawing comparisons across their performance. Subsequently, the hyperparameters of the best-performing GAN are fine-tuned using Particle Swarm Optimization (PSO) to produce more realistic OCT images. This comparative analysis not only serves to improve the detection of DME severity using OCT images but also provides insights into the appropriate choice of GANs for the effective generation of realistic OCT images from the baseline OCT datasets.

Fuzzy Logic-Based System for Identifying the Severity of Diabetic Macular Edema from OCT B-Scan Images Using DRIL, HRF, and Cystoids

Diabetic Macular Edema (DME) is a severe ocular complication commonly found in patients with diabetes. The condition can precipitate a significant drop in VA and, in extreme cases, may result in irreversible vision loss. Optical Coherence Tomography (OCT), a technique that yields high-resolution retinal images, is often employed by clinicians to assess the extent of DME in patients. However, the manual interpretation of OCT B-scan images for DME identification and severity grading can be error-prone, with false negatives potentially resulting in serious repercussions. In this paper, we investigate an Artificial Intelligence (AI) driven system that offers an end-to-end automated model, designed to accurately determine DME severity using OCT B-Scan images. This model operates by extracting specific biomarkers such as Disorganization of Retinal Inner Layers (DRIL), Hyper Reflective Foci (HRF), and cystoids from the OCT image, which are then utilized to ascertain DME severity. The rules guiding the fuzzy logic engine are derived from contemporary research in the field of DME and its association with various biomarkers evident in the OCT image. The proposed model demonstrates high efficacy, identifying images with DRIL with 93.3% accuracy and successfully segmenting HRF and cystoids from OCT images with dice similarity coefficients of 91.30% and 95.07% respectively. This study presents a comprehensive system capable of accurately grading DME severity using OCT B-scan images, serving as a potentially invaluable tool in the clinical assessment and treatment of DME.

The Role of Intravitreal Corticosteroids in the Treatment of DME: Predictive OCT Biomarkers

This work aims to summarize predictive biomarkers to guide treatment choice in DME. Intravitreal anti-VEGF is considered the gold standard treatment for centers involving DME, while intravitreal steroid treatment has been established as a second-line treatment in DME. However, more than 1/3 of the patients do not adequately respond to anti-VEGF treatment despite up to 4-weekly injections. Not surprisingly, insufficient response to anti-VEGF therapy has been linked to low-normal VEGF levels in the serum and aqueous humor. These patients may well benefit from an early switch to intravitreal steroid treatment. In these patients, morphological biomarkers visible in OCT may predict treatment response and guide treatment decisions. Namely, the presence of a large amount of retinal and choroidal hyperreflective foci, disruption of the outer retinal layers and other signs of chronicity such as intraretinal cysts extending into the outer retina and a lower choroidal vascular index are all signs suggestive of a favorable treatment response of steroids compared to anti-VEGF. This paper summarizes predictive biomarkers in DME in order to assist individual treatment decisions in DME. These markers will help to identify DME patients who may benefit from primary dexamethasone treatment or an early switch.

Indicators of Visual Prognosis in Diabetic Macular Oedema

Diabetic macular oedema (DMO) is an important cause of moderate vision loss in people with diabetes. Advances in imaging technology have shown that a significant proportion of patients with DMO respond sub-optimally to existing treatment options. Identifying associations and predictors of response before treatment is initiated may help in explaining visual prognosis to patients and aid the development of personalized treatment strategies. Imaging features, such as central subfoveal thickness, photoreceptor integrity, disorganization of retinal inner layers, choroidal changes, and macular perfusion, have been reported to be prognostic factors of visual acuity (VA) in DMO. In this review we evaluated each risk factor to understand their relative importance in visual prognostication of DMO eyes post-treatment. Although individually, some of these factors may not be significant predictors, in combination they may form phenotypes that can inform visual prognosis. Stratification based on these phenotypes needs to be developed to progress to personalized medicine for DMO.