Survey of ophthalmology最新文献

Retinal vein occlusion (RVO) and cerebrovascular disease share common risk factors and may be independently associated; however, the strength and nature of this association remain unclear. We conducted a systematic review and meta-analysis, informed by studies from PubMed, Scopus, EMBASE, Web of Science, and Google Scholar until January 6, 2024, aimed to clarify this relationship. Eligible studies included cohorts observing stroke incidence in RVO patients for over a year. Pooled effect estimates were calculated using random-effects models, with subgroup analyses evaluating associations between RVO types (central and branch) and stroke subtypes (ischemic and hemorrhagic). Ten cohort studies with a total of 428,650 participants (86,299 RVO patients) were included. Compared to controls, RVO patients exhibited a significantly increased risk of stroke (pooled risk ratio [RR]=1.38, 95 % confidence interval (95 %CI)=1.34–1.41). Subgroup analyses indicated elevated risk for both ischemic (RR=1.37, 95 %CI=1.32–1.42) and hemorrhagic (RR=1.55, 95 %CI=1.08–2.22) strokes in RVO patients. Additionally, both central (RR=1.50, 95 %CI=1.27–1.78) and branch (RR=1.41, 95 %CI=1.32–1.50) RVO were associated with stroke risk. Sensitivity analyses confirmed consistent results across various criteria, and funnel plots indicated no publication bias. RVO significantly increases the risk of both ischemic and hemorrhagic stroke, regardless of RVO type, suggesting a strong independent association between these conditions.

The science of diabetes care has progressed to provide a better understanding of the oxidative and inflammatory lesions and pathophysiology of the neurovascular unit within the retina (and brain) that occur early in diabetes, even prediabetes. Screening for retinal structural abnormalities, has traditionally been performed by fundus examination or color fundus photography; however, these imaging techniques detect the disease only when there are sufficient lesions, predominantly hemorrhagic, that are recognized to occur late in the disease process after significant neuronal apoptosis and atrophy, as well as microvascular occlusion with alterations in vision. Thus, interventions have been primarily oriented toward the later-detected stages, and clinical trials, while demonstrating a slowing of the disease progression, demonstrate minimal visual improvement and modest reduction in the continued loss over prolonged periods. Similarly, vision measurement utilizing charts detects only problems of visual function late, as the process begins most often parafoveally with increasing number and progressive expansion, including into the fovea. While visual acuity has long been used to define endpoints of visual function for such trials, current methods reviewed herein are found to be imprecise. We review improved methods of testing visual function and newer imaging techniques with the recommendation that these must be utilized to discover and evaluate the injury earlier in the disease process, even in the prediabetic state. This would allow earlier therapy with ocular as well as systemic pharmacologic treatments that lower the and neuro-inflammatory processes within eye and brain. This also may include newer, micropulsed laser therapy that, if applied during the earlier cascade, should result in improved and often normalized retinal function without the adverse treatment effects of standard photocoagulation therapy.

Cystoid macular edema (CME) is a sight-threatening condition often associated with inflammatory and diabetic diseases. Early detection is crucial to prevent irreversible vision loss. Artificial intelligence (AI) has shown promise in automating CME diagnosis through optical coherence tomography (OCT) imaging, but its utility needs critical evaluation. This systematic review assesses the application of AI to diagnosis CME, specifically focusing on disorders like postoperative CME (Irvine Gass syndrome) and retinitis pigmentosa without obvious vasculopathy, using OCT imaging. A comprehensive search was conducted across 6 databases (PubMed, Scopus, Web of Science, Wiley, ScienceDirect, and IEEE) from 2018 to November, 2023. Twenty-three articles met the inclusion criteria and were selected for in-depth analysis. We evaluate AI's role in CME diagnosis and its performance in “detection”, “classification”, and “segmentation” of OCT retinal images. We found that convolutional neural network (CNN)-based methods consistently outperformed other machine learning techniques, achieving an average accuracy of over 96 % in detecting and identifying CME from OCT images. Despite certain limitations such as dataset size and ethical concerns, the synergy between AI and OCT, particularly through CNNs, holds promise for significantly advancing CME diagnostics.

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.

Vitreous, one of the largest components of the human eye, mostly contains water. Despite decades of studying the vitreous structure, numerous unanswered questions still remain, fueling ongoing active research. We attempt to provide a comprehensive overview of the current understanding of the development, morphology, biochemical composition, and function of the vitreous. We emphasize the impact of the vitreous structure and composition on the distribution of drugs. Fast-developing imaging technologies, such as modern optical coherence tomography, unlocked multiple new approaches, offering the potential for in vivo study of the vitreous structure. They allowed to analyze in vivo a range of vitreous structures, such as posterior precortical vitreous pockets, Cloquet canal, channels that interconnect them, perivascular vitreous fissures, and cisterns. We provide an overview of such imaging techniques and their principles and of some challenges in visualizing vitreous structures. Finally, we explores the potential of combining the latest technologies and machine learning to enhance our understanding of vitreous structures.

A 71-year-old woman developed sudden, painful, decreased vision in the left eye accompanied by progressive instability. Initial examination revealed left optic disc edema, and macular optical coherence tomography confirmed the presence of intraretinal and subretinal fluid, as well as hyperreflective material under the retinal pigment epithelium. Subsequent investigations, including brain magnetic resonance imaging and a comprehensive serological analysis, ruled out infectious and autoimmune causes, further complicating the diagnostic picture. The patient's vision in both eyes continued to deteriorate, prompting empirical corticosteroid treatment. While the vision improved, the case took an unexpected turn with worsening neurological symptoms. Ultimately a brain biopsy was consistent with diffuse large B-cell lymphoma.

We assessed risk factors for complications associated with resident-performed cataract surgery. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines, we searched 4databases in September, 2023. We included peer-reviewed, full-text, English-language articles assessing risk factors for complications in resident performed cataract surgery. We excluded studies describing cataract surgeries performed by fellows, combined surgeries, and studies with insufficient information. Our initial search yielded 6244 articles; 15 articles were included after title/abstract and full-text review. Patient-related risk factors included older age, hypertension, prior vitrectomy, zonular pathology, pseudoexfoliation, poor preoperative visual acuity, small pupils, and selected types of cataracts. Surgeon-related risk factors included resident postgraduate year and surgeon right-handedness. Other risk factors included absence of supervision, long phacoemulsification time, and phacoemulsification with high power and torsion. The quality of the studies was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation; most studies graded as moderate, primarily due to risk of bias. When assigning cases to residents, graduate medical educators should consider general and resident-specific risk factors to facilitate teaching and preserve patient safety.