Visual Evoked Pottential
Visual Evoked Pottential
It is unknown if the increased incidence of GA found in certain trials after the use of anti-VEGF therapies for nAMD is due to the therapy or is part of the disease’s normal course. Furthermore, estimates of GA incidence vary across studies, which may be explained by changes in anti-VEGF agent, dosage, therapy, and follow-up regimens, as well as patient and ocular characteristics.
Given the uncertainty surrounding the incidence of GA following intravitreal agent treatment, Arshia Eshtiaghi et al. conducted a systematic review and meta-analysis recently published in Retina Journal to identify and synthesize all available evidence for estimating GA incidence and progression, as well as to investigate population and intervention characteristics that may have influenced these estimates.
They conducted a systematic evaluation of the available data on the occurrence and development of GA after repeated anti-VEGF injections in patients with nAMD. They evaluated data from 31 trials including a total of 4,609 eyes that had had anti-VEGF injections.
Over 35.2 months, eyes got an average of 17.7 shots. At baseline, the prevalence of GA was 9.7 percent. At the conclusion of follow-up, the pooled incidence of GA was 30.5 percent.
In aggregate, the prevalence of GA increased from 9.7 percent at baseline to 38.9 percent at end follow-up. There was a 30.5 percent incidence of new-onset GA among persons without GA at baseline.
The positive, moderate connection between the mean number of injections and the frequency of new onset GA suggests a relationship between intravitreal anti-VEGF medication and the development of GA, albeit this does not imply causality. Notably, none of the evaluated publications examined the causation of this association, which may be impacted by the normal course of nAMD. Indeed, more frequently injected eyes may have had more aggressive underlying nAMD, which is a risk factor for a faster natural development of GA. Additionally, several of the eyes that received a significant volume of injections were included in RCTs that required monthly injections in one research arm. Finally, patients who had a greater number of injections were observed for a longer length of time, which is related with an increased risk of GA.
Between the mean total number of injections and the GA incidence at final follow-up, there was a positive, moderate linear connection (R2 = 0.30; P = 0.01).
When extrapolated backwards, the regression line indicates that even in the absence of intravitreal anti-VEGF injections, GA formation occurs at a rate of roughly 20%. The Beaver Dam Eye Research, a pioneering epidemiological study undertaken prior to the development of anti-VEGF medication, revealed a cumulative GA incidence of 13.5 percent in eyes with AMD during a 15-year period.
Monthly therapy was significantly related with an increased chance of developing GA compared to pro re nata (relative risk = 1.40, 95 percent confidence range [1.21–1.61], P 0.001).
The anti-VEGF drug used was noted as a risk factor for the development of GA in many of the publications analysed.
AI in Diabetic Retinopathy
The primary goal of using AI for diabetic retinopathy (DR) is to screen for proliferative diabetic retinopathy (PDR) and diabetic macular edoema (DME), the two leading causes of significant vision loss in individuals with DR. For the majority of algorithms, the most significant predictor is the detection of referable diabetic retinopathy (RDR). RDR is defined as moderate nonproliferative diabetic retinopathy (NPDR) or greater and clinically significant macular oedema (CSME). Sight-threatening DR (STDR) is defined as the presence of severe NPDR, proliferative PDR, and/or DME.
Another research employing a different DL method produced an AUC of 0.980, with a sensitivity and specificity of 96.8 and 87.0 percent, respectively, in detecting referable DR. These studies demonstrate the potential use of DL in early detection of referable DR. Ting et al. conducted a large investigation in Singapore to validate DL using several retinal pictures acquired with conventional fundus cameras. This research demonstrated a high degree of sensitivity and specificity for DR detection. The possible hurdles and uncertainties include validating these DL systems in real-world DR screening programmes and determining their generalizability when applied to populations of various ethnic origins and employing retinal pictures obtained by various fundus cameras.
EyeArt by Eyenuk was utilised to train the AI algorithms for DR screening using the EyePACS tele-screening system and demonstrated a sensitivity and specificity of 90% and 63.2 percent, respectively. Additionally, it identified microaneurysms with a sensitivity of 100%. The algorithm analysed 40,542 pictures obtained from 5084 patients. Tufail et al. found that EyeArt was 94.7 percent sensitive for any DR, 93.8 percent sensitive for referable retinopathy, and 99.6 percent sensitive for PDR. Additionally, it assessed the findings of Retmarker, which shown sensitivities of 73.0% for any retinopathy, 85.00% for RDR, and 97.9% for PDR. Furthermore, Google Health revealed that it created a collection of 128,000 photos that scientists used to train a deep learning network for diabetic retinopathy.
OCT angiography is a novel technique with enormous potential in the areas of DR and DME. Numerous research publications have focused on the use of OCT angiography to quantify foveal avascular zone (FAZ) regions, changes in retinal microangiopathy (such as capillary tortuosity and dropouts), and retinal vascular density indices. The use of artificial intelligence to OCT angiography pictures remains in its infancy. There are just a few published publications describing the use of DL algorithms to determine vascular alterations detected by OCT angiography. Guo et al. devised a deep learning approach for segmenting and quantifying the capillary density of the superficial FAZ. A correlation coefficient of 0.997 was found between the area computed by the DL method and the area determined manually.
Heisler et al. classified DR on OCT angiography using ensemble learning approaches in conjunction with DL. After analysing 380 eyes, the authors determined that ensemble learning improves the prediction accuracy of CNNs for identifying RDR on OCT angiography. Lo et al. also used OCT angiography pictures to examine the superficial and deep capillary plexus of the retina using CNNs. Using CNNs, the programme accurately assessed the retinal microvasculature. Thus, OCT angiography is a valuable tool, and segmentation of the images using CNNs is an exciting field of study.
Although persistent placoid maculopathy (PPM) has several characteristics similar to APMPPE and macular serpiginous choroiditis (SC), it also has numerous distinguishing characteristics. The term PPM was coined in 2006, when six individuals aged 50 to 68 years were diagnosed with macular placoid lesions and a high rate of CNV development.
Patients with PPM may have a prodrome phase, including influenza-like symptoms, and the majority of patients report bilateral vision impairment, photopsia, and scotomas upon presentation.
Clinical examination reveals the lack of anterior uveitis and, in a minority of cases, uncommon vitreal cells, with the posterior pole being the primary location of inflammation.
The condition is typically self-resolving and monophasic in nature, and it always takes far longer to recover than APMPPE.
FAF results vary according on the level of RPE involvement. FA and ICGA exhibit early hypofluorescence in the active phase, remaining on ICGA and becoming hyperfluorescent on FA in the late phases, similar to the other placoids (FA–ICGA dissociation).
OCTA was used to demonstrate and validate perfusion deficiencies at the choriocapillaris level. Cross-sectional OCT results are phase-dependent and are often comparable to but less severe than those reported in APMPPE.
Cerebral vasculitis, like APMPPE, may exacerbate PPM. Thus, if any neurologic symptoms are present, neuro-imageing studies should be considered. PPM-like findings have also been found in two individuals aged 74 and 85 years with giant cell arteritis. These data imply that before to labelling a patient as PPM, systemic symptoms should be carefully considered.
Unlike APMPPE, which has multifocal lesions dispersed across the retina and often affects younger patients with a low risk of CNV, placoid lesions in PPM are exclusively situated at the posterior pole, the mean age of the patients is older, and CNV is common.
In contrast to tuberculous serpiginous-like choroiditis (SLC), where placoid lesions are often more prominent and extensive, PPM active lesions are typically more ill-defined with less opaque active margins, giving the appearance of a weaker inflammatory response driving the illness. This might explain the relatively mild influence on the outer retinal layers and hence on visual acuity initially.
Corticosteroid or other immunosuppressive therapy has been used to hasten illness recovery but does not seem to be effective in avoiding CNV over time. Intravitreal antivascular endothelial growth factor (VEGF) injections have been shown to improve results and minimise neovascular exudation in the presence of CNV. Early therapy seems to be beneficial, with return of CNV or atrophy after quiescence sometimes seen. Despite frequent injections, the formation of fibrosis may occur.
Euretina Highlights -2021
Special Thanks to Dr Hamid Riazi – Dr Nazanin Ebrahimi Adib – Dr Mojtaba Abrishami
Part 1 :
Part 2 :
Elias Khalili Pour
Outer Foveal Microdefects 26-7-2021