Intravitreal dexamethasone implant has better retinal perfusion than anti-vascular endothelial growth factor treatment for macular edema secondary to retinal vein occlusion: a five-year real-world study.

PURPOSE: To investigate the long-term effect of intravitreal dexamethasone (DEX) implant and anti-vascular endothelial growth factor (VEGF) injection on macular edema (ME) secondary to retinal vein occlusion (RVO) in a real-world setting. METHODS: The medical records of RVO-ME cases, with intravitreal injections and followed-up for at least 5 years, were retrospectively reviewed. Changes in best-corrected visual acuity (BCVA) and central macular thickness (CMT) were primary outcomes. Images of fluorescence angiography (FA) and swept-source optical coherence tomography angiography (OCTA) were analyzed. Foveal avascular zone (FAZ) metrics and perfusion density at the last visit were also compared between the two treatments. RESULTS: A total of 16 patients were recruited, 8 in the anti-VEGF group and 8 in the DEX group. At the 5th year, the BCVA and the CMT in the DEX group were not different from those in the anti-VEGF group (0.69 ± 0.36 LogMAR vs 0.57 ± 0.30 LogMAR, P = 0.574; 183.25 ± 97.31 µm vs 195.38 ± 40.92 µm, P = 0.442). Compared with the anti-VEGF group, the DEX group had higher FAZ circularity index (0.57 ± 0.14 vs 0.68 ± 0.14, P = 0.130) and higher retinal perfusion density (0.45 ± 0.02 vs 0.39 ± 0.03, P = 0.001), especially in the deep capillary plexus. CONCLUSION: DEX implant and anti-VEGF injection had comparative long-term effects on RVO-ME. Compared with the anti-VEGF treatment, the DEX treatment had advantages in maintaining retinal perfusion in patients with RVO.

A new handheld fundus camera combined with visual artificial intelligence facilitates diabetic retinopathy screening.

AIM: To explore the performance in diabetic retinopathy (DR) screening of artificial intelligence (AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional tabletop fundus cameras and the diagnostic accuracy of DR of the two modalities. METHODS: Overall, 630 eyes were included from three centers and screened by a handheld camera (Aurora, Optomed, Oulu, Finland) and a table-top camera. Image quality was graded by three masked and experienced ophthalmologists. The diagnostic accuracy of the handheld camera and AI system was evaluated in assessing DR lesions and referable DR. RESULTS: Under nonmydriasis status, the handheld fundus camera had better image quality in centration, clarity, and visible range (1.47, 1.48, and 1.40) than conventional tabletop cameras (1.30, 1.28, and 1.18; P<0.001). Detection of retinal hemorrhage, hard exudation, and macular edema were comparable between the two modalities, in principle, with the area under the curve of the handheld fundus camera slightly lower. The sensitivity and specificity for the detection of referable DR with the handheld camera were 82.1% (95%CI: 72.1%-92.2%) and 97.4% (95%CI: 95.4%-99.5%), respectively. The performance of AI detection of DR using the Phoebus Algorithm was satisfactory; however, Phoebus showed a high sensitivity (88.2%, 95%CI: 79.4%-97.1%) and low specificity (40.7%, 95%CI: 34.1%-47.2%) when detecting referable DR. CONCLUSION: The handheld Aurora fundus camera combined with autonomous AI system is well-suited in DR screening without mydriasis because of its high sensitivity of DR detection as well as its image quality, but its specificity needs to be improved with better modeling of the data. Use of this new system is safe and effective in the detection of referable DR in real world practice.

Retinal degeneration in mice lacking the cyclic nucleotide-gated channel subunit CNGA1.

Cyclic nucleotide-gated (CNG) channels are important mediators in the transduction pathways of rod and cone photoreceptors. Native CNG channels are heterotetramers composed of homologous A and B subunits. Biallelic mutations in CNGA1 or CNGB1 genes result in autosomal recessive retinitis pigmentosa (RP). To investigate the pathogenic mechanism of CNG channel-associated retinal degeneration, we developed a mouse model of CNGA1 knock-out using CRISPR/Cas9 technology. We observed progressive retinal thinning and a concomitant functional deficit in vivo as typical phenotypes for RP. Immunofluorescence and TUNEL staining showed progressive degeneration in rods and cones. Moreover, microglial activation and oxidative stress damage occurred in parallel. RNA-sequencing analysis of the retinae suggested down-regulated synaptic transmission and phototransduction as early as 9 days postnatal, possibly inducing later photoreceptor degeneration. In addition, the down-regulated PI3K-AKT-mTOR pathway indicated upregulation of autophagic process, and chaperone-mediated autophagy was further shown to coincide with the time course of photoreceptor death. Taken together, our studies add to a growing body of research exploring the mechanisms of photoreceptor death during RP progression and provide a novel CNGA1 knockout mouse model for potential development of therapies.