Insights into systemic disease through retinal imaging-based oculomics. Trans Vis Sci Tech. 2020;9(2):6, https://doi. org/10.1167/tvst.9.2.6 Among the most noteworthy developments in ophthalmology over the last decade has been the emergence of quantifiable high-resolution imaging modalities, which are typically non-invasive, rapid and widely available. Such imaging is of unquestionable utility in the assessment of ocular disease however evidence is also mounting for its role in identifying ocular biomarkers of systemic disease, which we term oculomics. In this review, we highlight our current understanding of how retinal morphology evolves in two leading causes of global morbidity and mortality, cardiovascular disease and dementia. Population-based analyses have demonstrated the predictive value of retinal microvascular indices, as measured through fundus photography, in screening for heart attack and stroke. Similarly, the association between the structure of the neurosensory retina and prevalent neurodegenerative disease, in particular Alzheimer's disease, is now well-established. Given the growing size and complexity of emerging multimodal datasets, modern artificial intelligence techniques, such as deep learning, may provide the optimal opportunity to further characterize these associations, enhance our understanding of eye-body relationships and secure novel scalable approaches to the risk stratification of chronic complex disorders of ageing.
A number of large technology companies have created code-free cloud-based platforms that allow researchers and clinicians without coding experience to create deep learning algorithms. In this study, we comprehensively analyse the performance and featureset of six platforms, using four representative cross-sectional and en-face medical imaging datasets to create image classification models. The mean (s.d.) F1 scores across platforms for all model–dataset pairs were as follows: Amazon, 93.9 (5.4); Apple, 72.0 (13.6); Clarifai, 74.2 (7.1); Google, 92.0 (5.4); MedicMind, 90.7 (9.6); Microsoft, 88.6 (5.3). The platforms demonstrated uniformly higher classification performance with the optical coherence tomography modality. Potential use cases given proper validation include research dataset curation, mobile ‘edge models’ for regions without internet access, and baseline models against which to compare and iterate bespoke deep learning approaches.
Purpose: To apply a deep learning algorithm for automated, objective, and comprehensive quantification of OCT scans to a large real-world dataset of eyes with neovascular age-related macular degeneration (AMD) and make the raw segmentation output data openly available for further research.Design: Retrospective analysis of OCT images from the Moorfields Eye Hospital AMD Database.Participants: A total of 2473 first-treated eyes and 493 second-treated eyes that commenced therapy for neovascular AMD between June 2012 and June 2017.Methods: A deep learning algorithm was used to segment all baseline OCT scans. Volumes were calculated for segmented features such as neurosensory retina (NSR), drusen, intraretinal fluid (IRF), subretinal fluid (SRF), subretinal hyperreflective material (SHRM), retinal pigment epithelium (RPE), hyperreflective foci (HRF), fibrovascular pigment epithelium detachment (fvPED), and serous PED (sPED). Analyses included comparisons between firstand second-treated eyes by visual acuity (VA) and race/ethnicity and correlations between volumes.Main Outcome Measures: Volumes of segmented features (mm 3 ) and central subfield thickness (CST) (mm).Results: In first-treated eyes, the majority had both IRF and SRF (54.7%). First-treated eyes had greater volumes for all segmented tissues, with the exception of drusen, which was greater in second-treated eyes. In first-treated eyes, older age was associated with lower volumes for RPE, SRF, NSR, and sPED; in second-treated eyes, older age was associated with lower volumes of NSR, RPE, sPED, fvPED, and SRF. Eyes from Black individuals had higher SRF, RPE, and serous PED volumes compared with other ethnic groups. Greater volumes of the majority of features were associated with worse VA.Conclusions: We report the results of large-scale automated quantification of a novel range of baseline features in neovascular AMD. Major differences between firstand second-treated eyes, with increasing age, and between ethnicities are highlighted. In the coming years, enhanced, automated OCT segmentation may assist personalization of real-world care and the detection of novel structureefunction correlations. These data will be made publicly available for replication and future investigation by the AMD research community.
Purpose Single center, noninterventional cohort study to assess 10-year visual and anatomical outcomes following initiation of treatment with antivascular endothelial growth factor (anti-VEGF) agents in neovascular age-related macular degeneration (AMD) patients. Neovascular AMD patients initiated on intravitreal anti-VEGF injections in 2008–2009 and continued to be followed up for at least 10 years were included in this study. Methods The Moorfields OpenEyes database was searched for all patients who were initiated on anti-VEGF therapy for neovascular AMD in 2008–2009 and the visual acuity (VA) in Early Diabetic Retinopathy Study (ETDRS) letters and injection records were analyzed for those who have had at least 10-year follow-up. The spectral-domain optical coherence tomography (SD-OCT) scans, color fundus photos, and fundus fluorescein angiography (FA) were graded by two retinal physicians. The outcomes were also compared between those with good and poor VA outcomes based on pre-defined criteria. The primary end point was change in VA at 10 years; secondary outcomes included percentage with VA of 20/40 or better, 20/70 or better, VA gains and losses, anatomic outcomes and number of injections. Results After a mean of 10.04 years after initiation of anti-VEGF therapy, the mean decline in VA from baseline was −2.1 ETDRS letters (SD 19.9, p = 0.65). One hundred eyes (67.1%) achieved a VA threshold of 20/70 or better, 33.5% achieved a VA of 20/40 or better, and 76.5% eyes maintained VA defined as a loss of less than 15 letters. Fourteen percent of study eyes had VA of 20/200 or worse and 23.5% declined by 15 letters or more. 87.5% of eyes were switched from ranibizumab to aflibercept during the course of 10 years and the eyes received a mean of 52.2 (SD 18.1) injections over 10 years. From this cohort, 87 (58.3%) eyes are having on-going treatment. On OCT, 34.9% had persistent fluid at the last visit, 6.7% patients showed new onset atrophy compared to baseline, and 43.7% had increased area of macular atrophy. The mean area of atrophy at the final visit was 4.15 mm 2 . Comparison between the good and worse visual outcome groups showed lower baseline VA, fovea-involving atrophy and final area of atrophy had a statistically significant negative effect on the final visual outcome ( p < 0.05). Conclusions Regular monitoring and anti-VEGF treatment over 10 years reduce the risk of visual loss of 15 letters or more in patients with neovascular AMD. The most common cause of substantial visual decline was macular atrophy.
PurposeTo evaluate the utility of widefield optical coherence tomography angiography (WF-OCTA) compared with clinical examination in grading diabetic retinopathy in patients diagnosed clinically with proliferative diabetic retinopathy (PDR) or severe non-proliferative diabetic retinopathy (NPDR).DesignThis retrospective observational case series included patients diagnosed clinically with PDR or severe NPDR. Patients underwent standard clinical examination and WF-OCTA imaging (PLEX Elite 9000, Carl Zeiss Meditec AG) using 12×12 montage scans between August 2018 and January 2019. Two trained graders identified neovascularisation at the disc (NVD) and neovascularisation elsewhere (NVE) on WF-OCTA which were compared with the clinical examination, and to ultra-widefield fluorescein angiography (UWFA) when available.ResultsSeventy-nine eyes of 46 patients were evaluated. Of those, 57 eyes were diagnosed clinically with PDR, and 22 with severe NPDR. NVD was detected on OCTA-B scan as preretinal hyperreflective material (PRHM) in 39 eyes (100%) with evident flow signals in 79.5% compared with 51.3% detected clinically. We further classified NVD on OCTA into four subtypes and found that subtypes 1 and 2 could not be seen on clinical examination alone. WF-OCTA detected NVE in 81% of the cases compared with 55.7% detected clinically. Using WF-OCTA resulted in a higher percentage of PDR grading (88.6%) than on clinical examination (72.2%). When available, UWFA confirmed the WF-OCTA diagnosis in the majority of cases.ConclusionThis study demonstrates that WF-OCTA has a higher detection rate of PDR than clinical examination. This suggests that this modality could be used non-invasively for the purpose of early detection and characterisation of neovascularisation.
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