Hyperreflective foci as biomarkers for inflammation in diabetic macular edema: Retrospective analysis of treatment naïve eyes from south India

Does dexamethasone implant combination with aflibercept monotherapy affect one-year outcomes in treatment-naive diabetic macular edema with inflammatory biomarkers?

PURPOSE

To compare the anatomical and functional outcomes of the combination of aflibercept and dexamethasone implant (CT) against aflibercept monotherapy (AM) in treatment-naive diabetic macular edema (DME) patients with serous macular detachment and hyperreflective foci.

METHODS

This study included 82 eyes of 82 patients with treatment-naive DME who completed the follow-up period of 12 months. All patients had optical coherence tomography biomarkers of an inflammatory DME phenotype. Patients were consecutively selected and classified into two groups: The CT group consisted of 39 eyes treated with aflibercept therapy and initially combined with a single-dose dexamethasone implant. The AM group consisted of 43 eyes treated with aflibercept alone. The primary outcome measures of the study were the mean reduction of the central macular thickness (CMT) and total macular volume parameters (TMV) and improvement in best-corrected visual acuity.

RESULTS

In both groups, the patient characteristics, including age, gender, duration of diabetes, HbA1c levels, phakic percentage, and diabetic retinopathy status were similar (P > 0.05). The mean reduction in CMT and TMV was significantly higher in the CT group compared to the AM group (P < 0.001 and P = 0.002, respectively). In contrast, mean letter gains were not significantly higher (P = 0.240) at the end of the study. In the CT group, 20.5% of patients showed a transient IOP increase, and 18% developed cataracts. In subgroup analysis, the mean letter gain in pseudophakic eyes was significantly higher (12.5 in the CT vs. 9.3 in the AM group, P = 0.027).

CONCLUSION

The CT, where inflammation is prominent, can provide faster recovery. The pseudophakic eyes seem to be the ideal patient group for CT.

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 Inflammation and Therapeutic Concepts in Diabetic Retinopathy-A Short Review

Diabetic retinopathy (DR) as a microangiopathy is the most common complication in patients with diabetes mellitus (DM) and remains the leading cause of blindness among adult population. DM in its complicated pathomechanism relates to chronic hyperglycemia, hypoinsulinemia, dyslipidemia and hypertension-all these components in molecular pathways maintain oxidative stress, formation of advanced glycation end-products, microvascular changes, inflammation, and retinal neurodegeneration as one of the key players in diabetes-associated retinal perturbations. In this current review, we discuss the natural history of DR with special emphasis on ongoing inflammation and the key role of vascular endothelial growth factor (VEGF). Additionally, we provide an overview of the principles of diabetic retinopathy treatments, i.e., in laser therapy, anti-VEGF and steroid options.

Proinflammatory Cytokines Trigger the Onset of Retinal Abnormalities and Metabolic Dysregulation in a Hyperglycemic Mouse Model

Purpose

Recent evidence has shown that retinal inflammation is a key player in diabetic retinopathy (DR) pathogenesis. To further understand and validate the metabolic biomarkers of DR, we investigated the effect of intravitreal proinflammatory cytokines on the retinal structure, function, and metabolism in an in vivo hyperglycemic mouse model.

Methods

C57Bl/6 mice were rendered hyperglycemic within one week of administration of a single high-dose intraperitoneal injection of streptozotocin, while control mice received vehicle injection. After confirming hyperglycemia, the mice received an intravitreal injection of either proinflammatory cytokines (TNF-α and IL-1β) or vehicle. Similarly, control mice received an intravitreal injection of either proinflammatory cytokines or vehicle. The retinal structure was evaluated using fundus imaging and optical coherence tomography, and retinal function was assessed using a focal electroretinogram (ERG), two days after cytokine injection. Retinas were collected for biochemical analysis to determine key metabolite levels and enzymatic activities.

Results

Hyperglycemic mice intraocularly injected with cytokines developed visible retinal vascular damage and intravitreal and intraretinal hyper-reflective spots two days after the cytokines injection. These mice also developed a significant functional deficit with reduced a-wave and b-wave amplitudes of the ERG at high light intensities compared to control mice. Furthermore, metabolic disruption was evident in these mice, with significantly higher retinal glucose, lactate, ATP, and glutamine levels and a significant reduction in glutamate levels compared with control mice. Minimal or no metabolic changes were observed in hyperglycemic mice without intraocular cytokines or in control mice with intraocular cytokines at 2 days post hyperglycemia.

Conclusions

Proinflammatory cytokines accelerated the development of vascular damage in the eyes of hyperglycemic mice. Significant changes were observed in retinal structure, function, and metabolic homeostasis. These findings support the idea that with the onset of inflammation in DR, there is a deficit in metabolism. Therefore, early intervention to prevent inflammation-induced retinal changes in diabetic patients may improve the disease outcome.

Neurovascular injury associated non-apoptotic endothelial caspase-9 and astroglial caspase-9 mediate inflammation and contrast sensitivity decline

Retinal neurovascular injuries are a leading cause of vision loss in young adults presenting unmet therapeutic needs. Neurovascular injuries damage homeostatic communication between endothelial, pericyte, glial, and neuronal cells through signaling pathways that remain to be established. To understand the mechanisms that contribute to neuronal death, we use a mouse model of retinal vein occlusion (RVO). Using this model, we previously discovered that after vascular damage, there was non-apoptotic activation of endothelial caspase-9 (EC Casp9); knock-out of EC Casp9 led to a decrease in retinal edema, capillary ischemia, and neuronal death. In this study, we aimed to explore the role of EC Casp9 in vision loss and inflammation. We found that EC Casp9 is implicated in contrast sensitivity decline, induction of inflammatory cytokines, and glial reactivity. One of the noted glial changes was increased levels of astroglial cl-caspase-6, which we found to be activated cell intrinsically by astroglial caspase-9 (Astro Casp9). Lastly, we discovered that Astro Casp9 contributes to capillary ischemia and contrast sensitivity decline after RVO (P-RVO). These findings reveal specific endothelial and astroglial non-apoptotic caspase-9 roles in inflammation and neurovascular injury respectively; and concomitant relevancy to contrast sensitivity decline.

[Treatment response to Conbercept of different types of diabetic macular edema classified based on optical coherence tomography]

OBJECTIVE

To compare different types of diabetic macular edema (DME) classified based on optical coherence tomography (OCT) for their responses to Conbercept injection and analyze the factors that affect the treatment responses.

METHODS

We retrospectively analyzed the clinical data of 65 patients (76 eyes) with DME diagnosed and treated with intravitreal injection of Conbercept (1+PRN) in our hospital from February, 2019 to February, 2021. According to OCT findings, DME in these patients was classified into cystic macular edema (CME; 28 eyes), serous retinal detachment (SRD; 33 eyes), and diffuse retinal thickening (DRT; 15 eyes). The best corrected visual acuity (BCVA) and central retinal thickness (CRT) were measured before and at 3 months after the first treatment. The baseline OCT characteristics of different types of DME were compared, and the correlation of these OCT characteristics with the treatment response to Conbercept was analyzed.

RESULTS

All the patients showed significant improvement of the BCVA 3 months after the treatment (P < 0.05). For all the 3 types of DME, the CRT at 3 months after the first treatment was significantly reduced as compared to the baseline (P < 0.05). The number of hyperreflective foci (HF) in the outer retina and the proportion of ellipsoid zone (EZ) interruption were the greatest in SRD group (P < 0.05). The baseline outer retinal HF was significantly correlated with the baseline CRT, CRT changes and CRT after treatment (all P < 0.05). The patients with baseline outer limiting membrane (ELM)/ EZ disruption had poorer baseline BCVA, greater baseline CRT, greater variation of CRT and poorer BCVA at 3 months after treatment (all P < 0.05).

CONCLUSION

For all the 3 types of DME, treatment with intravitreal injection of Conbercept can significantly improve the BCVA and CRT of the patients. DME of the SRD type has the best morphological response to Conbercept, while the DRT type has a relatively poor response. A greater number of HF at baseline may indicate a better morphological response to Conbercept treatment, and baseline ELM/EZ disruption may suggest a poor visual prognosis at 3 months after treatment.