The Disorganization of Retinal Inner Layers Is Correlated to Müller Cells Impairment in Diabetic Macular Edema: An Imaging and Omics Study

Evaluation of Anatomical and Tomographic Biomarkers as Predictive Visual Acuity Factors in Eyes with Retinal Vein Occlusion Treated with Dexamethasone Implant

Background: This prospective study evaluated the impact of anatomical and tomographic biomarkers on clinical outcomes of intravitreal dexamethasone implants in patients with macular edema secondary to retinal vein occlusion (RVO). Methods: The study included 46 patients (28 with branch RVO (BRVO) and 18 with central RVO (CRVO)). Best corrected visual acuity (BCVA) significantly improved from a mean baseline of 0.817 ± 0.220 logMAR to 0.663 ± 0.267 logMAR at six months and 0.639 ± 0.321 logMAR at twelve months (p < 0.05). Central retinal thickness (CRT) showed a significant reduction from 666.2 ± 212.2 µm to 471.1 ± 215.6 µm at six months and 467 ± 175.7 µm at twelve months (p < 0.05). No significant differences were found in OCT biomarkers between baseline and follow-ups. Results: The study analysed improvements in visual acuity relative to baseline biomarkers. At six months, ellipsoid zone disruption (EZD) was significant for all subgroups. Disorganization of retinal inner layers (DRIL), external limiting membrane (ELM) disruption, macular ischemia (MI), CRT, and BRVO showed significance for any improvement, while DRIL and ELM were significant for changes greater than 0.3 logMAR (p < 0.05). At twelve months, EZD remained significant for all subgroups. ELM, MI, CRT, and BRVO were significant for any improvement, while MI and BRVO were significant for changes greater than 0.3 logMAR (p < 0.05). Hyperreflective foci were not statistically significant at either time point (p > 0.05). Conclusions: The regression model suggested that MI and CRVO could be negative predictive factors for visual outcomes, while ELM and EZD were associated with BCVA improvement one-year post-treatment.

Role of inflammation in diabetic macular edema and neovascular age-related macular degeneration

Diabetic macular edema (DME) and neovascular age-related macular degeneration (nAMD) are multifactorial disorders that affect the macula and cause significant vision loss. Although inflammation and neoangiogenesis are hallmarks of DME and nAMD, respectively, they share some biochemical mediators. While inflammation is a trigger for the processes that lead to the development of DME, in nAMD inflammation seems to be the consequence of retinal pigment epithelium and Bruch membrane alterations. These pathophysiologic differences may be the key issue that justifies the difference in treatment strategies. Vascular endothelial growth factor inhibitors have changed the treatment of both diseases, however, many patients with DME fail to achieve the established therapeutic goals. From a clinical perspective, targeting inflammatory pathways with intravitreal corticosteroids has been proven to be effective in patients with DME. On the contrary, the clinical relevance of addressing inflammation in patients with nAMD has not been proven yet. We explore the role and implication of inflammation in the development of nAMD and DME and its therapeutical relevance.

Multimodal imaging in diabetic retinopathy and macular edema: An update about biomarkers

Diabetic macular edema (DME), defined as retinal thickening near, or involving the fovea caused by fluid accumulation in the retina, can lead to vision impairment and blindness in patients with diabetes. Current knowledge of retina anatomy and function and DME pathophysiology has taken great advantage of the availability of several techniques for visualizing the retina. Combining these techniques in a multimodal imaging approach to DME is recommended to improve diagnosis and to guide treatment decisions. We review the recent literature about the following retinal imaging technologies: optical coherence tomography (OCT), OCT angiography (OCTA), wide-field and ultrawide-field techniques applied to fundus photography, fluorescein angiography, and OCTA. The emphasis will be on characteristic DME features identified by these imaging technologies and their potential or established role as diagnostic, prognostic, or predictive biomarkers. The role of artificial intelligence in the assessment and interpretation of retina images is also discussed.

Global research trends and future directions in diabetic macular edema research: A bibliometric and visualized analysis

BACKGROUND

Diabetic Macular Edema (DME) significantly impairs vision in diabetics, with varied patient responses to current treatments like anti-vascular endothelial growth factor (VEGF) therapy underscoring the necessity for continued research into more effective strategies. This study aims to evaluate global research trends and identify emerging frontiers in DME to guide future research and clinical management.

METHODS

A qualitative and quantitative analysis of publications related to diabetic macular edema retrieved from the Web of Science Core Collection (WoSCC) between its inception and September 4, 2023, was conducted. Microsoft Excel, CiteSpace, VOSviewer, Bibliometrix Package, and Tableau were used for the bibliometric analysis and visualization. This encompasses an examination of the overall distribution of annual output, major countries, regions, institutions, authors, core journals, co-cited references, and keyword analyses.

RESULTS

Overall, 5624 publications were analyzed, indicating an increasing trend in DME research. The United States was identified as the leading country in DME research, with the highest h-index of 135 and 91,841 citations. Francesco Bandello emerged as the most prolific author with 97 publications. Neil M. Bressler has the highest h-index and highest total citation count of 46 and 9692, respectively. The journals "Retina - the Journal of Retinal and Vitreous Diseases" and "Ophthalmology" were highlighted as the most prominent in this field. "Retina" leads with 354 publications, a citation count of 11,872, and an h-index of 59. Meanwhile, "Ophthalmology" stands out with the highest overall citation count of 31,558 and the highest h-index of 90. The primary research focal points in diabetic macular edema included "prevalence and risk factors," "pathological mechanisms," "imaging modalities," "treatment strategies," and "clinical trials." Emerging research areas encompassed "deep learning and artificial intelligence," "novel treatment modalities," and "biomarkers."

CONCLUSION

Our bibliometric analysis delineates the leading role of the United States in DME research. We identified current research hotspots, including epidemiological studies, pathophysiological mechanisms, imaging advancements, and treatment innovations. Emerging trends, such as the integration of artificial intelligence and novel therapeutic approaches, highlight future directions. These insights underscore the importance of collaborative and interdisciplinary approaches in advancing DME research and clinical management.

Severity of Disorganization of Retinal Layers and Visual Function Impairment in Diabetic Retinopathy

PURPOSE

To evaluate best-corrected visual acuity (BCVA), retina sensitivity (RS), and fixation impairment by microperimetry (MP) due to the presence and severity of disorganization of retinal inner and outer layers (DRIL/DROL) and ischemia in OCT/OCT angiography (OCTA) in diabetic retinopathy (DR).

DESIGN

Retrospective case-control study.

SUBJECTS

Seventy-six eyes (65 patients) with DR were analyzed. Major exclusion criteria were: center-involving diabetic macular edema (DME), significant media opacity, nondiabetic macular pathology, and active proliferative DR. Patients with DRIL and DROL within central 3 mm were enrolled as cases. Patients with DR and no retina disorganization were considered as controls.

METHODS

A detailed grading of MP and OCT/OCTA images using Image J software, and specific Image Manipulation Program was applied to colocalize the presence of retina disorganization and RS. Best-corrected visual acuity and RS were correlated with the disorganization of retina layers' characteristics and grading (grade 1-DRIL; grade 2-DROL; grade 3-DROL plus, with involvement of the ellipsoid zone). The same procedure of colocalization was applied to the vascular layers on OCTA using MATLAB.

MAIN OUTCOME MEASURES

Correlation between BCVA and MP parameters with disorganization of retina layers grading and OCTA parameters.

RESULTS

Best-corrected visual acuity, mean RS within 1 mm and central 3 mm (overall RS [oRS]), perfusion density, vessel density, and geometric perfusion deficit in intermediate and deep capillary plexuses were lower in cases versus controls (P < 0.001). Mean RS within 1 mm (21.4 decibels [dB] ± 2.4 vs. 13.8 dB ± 5.4, P = 0.002), oRS (22.0 dB ± 2.1 vs. 14.4 dB ± 4.6, P < 0.001), and BCVA (76.1 ± 7.4 vs. 61.2 ± 20.4 ETDRS letters; P = 0.02), had a significant decrease from grade 1 to grade 3 retina disorganization. Choriocapillaris flow voids (CC-FVs) increased from grade 1 to grade 3 (DROL plus) (P = 0.004). Overall retina sensitivity and CC-FV were identified as significant predictors of retina disorganization grade with an adjusted coefficient of determination, R2 = 0.45. Cases had more dense scotomas (P = 0.03) than controls with a positive correlation between the worsening of fixation stability and the severity of DRIL/DROL (P = 0.04).

CONCLUSIONS

Microperimetry and BCVA documented a reduction in visual function in patients with DR and disorganization of retina layers at different grades, with greater functional impairment when outer retina layers and photoreceptors are involved. The severity of retina disorganization and the presence of ischemia could serve as a potential biomarker of functional impairment.

FINANCIAL DISCLOSURES

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Intravitreal injection of conbercept for diabetic macular edema complicated with diabetic nephropathy

AIM

To observe the therapeutic effect of conbercept on diabetic macular edema (DME) complicated with diabetic nephropathy (DN).

METHODS

In this retrospective study, 54 patients (54 eyes) that diagnosed as DME from January 2017 to October 2021 were collected. The patients were divided into two groups: DME patients with DN (25 eyes), and DME patients without DN (29 eyes). General conditions were collected before treatment, laboratory tests include fasting blood glucose, HbA1c, microalbumin/creatinine, serum creatinine. Optical coherence tomography (OCT) was used to check the ellipsoidal zone (EZ) and external limiting membrane (ELM) integrity. Central macular thickness (CMT), best corrected visual acuity (BCVA), and retinal hyperreflective foci (HF) as well as numbers of injections were recorded.

RESULTS

There were significant differences between fasting blood glucose, HbA1c, serum creatinine, urinary microalbumin/creatinine, and estimated glomerular filtration rate (eGFR) between the two groups (all P<0.05). EZ and ELM continuity in the DME+DN group was worse than that in the DME group (P<0.05). BCVA (logMAR) in the DME group was significantly better than that in the DME+DN group at the same time points during treatment (all P<0.05). CMT and HF values were significantly higher in the DME+DN group than that in the DME group at the all time points (all P<0.05) and significantly decreased in both groups with time during treatment. At 6mo after treatment, the mean number of injections in the DME+DN and DME group was 4.84±0.94 and 3.79±0.86, respectively.

CONCLUSION

Conbercept has a significant effect in short-term treatment of DME patients with or without DN, and can significantly ameliorate BCVA, CMT and the number of HF, treatment efficacy of DME patients without DN is better than that of DME patients with DN.

Improving OCT Image Segmentation of Retinal Layers by Utilizing a Machine Learning Based Multistage System of Stacked Multiscale Encoders and Decoders

Optical coherence tomography (OCT)-based retinal imagery is often utilized to determine influential factors in patient progression and treatment, for which the retinal layers of the human eye are investigated to assess a patient's health status and eyesight. In this contribution, we propose a machine learning (ML)-based multistage system of stacked multiscale encoders and decoders for the image segmentation of OCT imagery of the retinal layers to enable the following evaluation regarding the physiological and pathological states. Our proposed system's results highlight its benefits compared to currently investigated approaches by combining commonly deployed methods from deep learning (DL) while utilizing deep neural networks (DNN). We conclude that by stacking multiple multiscale encoders and decoders, improved scores for the image segmentation task can be achieved. Our retinal-layer-based segmentation results in a final segmentation performance of up to 82.25±0.74% for the Sørensen-Dice coefficient, outperforming the current best single-stage model by 1.55% with a score of 80.70±0.20%, given the evaluated peripapillary OCT data set. Additionally, we provide results on the data sets Duke SD-OCT, Heidelberg, and UMN to illustrate our model's performance on especially noisy data sets.