Performance of classification systems for age-related macular degeneration in the rotterdam study

Purpose: To compare frequently used classification systems for age-related macular degeneration(AMD) in their abilty to predictlate AMD. Methods:Intotal,9066participantsfromthepopulation-basedRotterdamStudywere followedupforprogressionofAMDduringastudyperiodupto30years.AMDlesions weregradedoncolorfundusphotographsafterconfirmationonotherimagemodalities andgroupedatbaselineaccordingtosixclassificationsystems.LateAMDwasdefinedas geographicatrophyorchoroidalneovascularization.Incidencerate(IR)andcumulative incidence(CuI)oflateAMDwerecalculated,andKaplan-Meierplotsandareaunderthe operating characteristics curves(AUCs)wereconstructed. Results: A total of 186 persons developed incident late AMD during a mean follow-up timeof8.7years.TheAREDSsimplifiedscaleshowedthehighestIRforlateAMDat104 cases/1000 py for ages 75 years. The 3-Continent harmonization classification provided the most stable progression. Drusen area >10% ETDRS grid (hazard ratio 30.05, 95% confidence interval [CI] 19.25–46.91) was most prognostic of progression. The highest AUC of late AMD (0.8372, 95% CI: 0.8070-0.8673) was achieved when all AMD features present at base line were included. Conclusions: Highest turnover rates from intermediate to late AMD were provided by the AREDS simplified scale and the Rotterdam classification. The 3-Continent harmonization classification showed the most stable progression. All features, especially drusenarea,contribute to late AMD prediction. Translational Relevance: Findings will help stakeholders select appropriate classification systems for screening,deep learning algorithms, or trials

CD4(+) T-cell responses mediate progressive neurodegeneration in experimental ischemic retinopathy

Retinal ischemic events, which result from occlusion of the ocular vasculature share similar causes as those for central nervous system stroke and are among the most common cause of acute and irreversible vision loss in elderly patients. Currently, there is no established treatment, and the condition often leaves patients with seriously impaired vision or blindness. The immune system, particularly T-cell- mediated responses, is thought to be intricately involved, but the exact roles remain elusive. We found that acute ischemia-reperfusion injury to the retina induced a prolonged phase of retinal ganglion cell loss that continued to progress during 8 weeks after the procedure. This phase was accompanied by microglial activation and CD4+ T-cell infiltration into the retina. Adoptive transfer of CD4+ T cells isolated from diseased mice exacerbated retinal ganglion cell loss in mice with retinal reperfusion damage. On the other hand, T-cell deficiency or administration of T-cell or interferon-gamma-neutralizing antibody attenuated retinal ganglion cell degeneration and retinal function loss after injury. These findings demonstrate a crucial role for T-cell-mediated responses in the pathogenesis of neural ischemia. These findings point to novel therapeutic targets of limiting or preventing neuron and function loss for currently untreatable conditions of optic neuropathy and/or central nervous system ischemic stroke.Ophthalmic researc

Neuroinflammation and microglia in glaucoma: time for a paradigm shift

Ophthalmic researc

[Artificial intelligence for eye care]

Contains fulltext : 229079.pdf (Publisher’s version ) (Closed access)Technological developments in ophthalmic imaging and artificial intelligence (AI) create new possibilities for diagnostics in eye care. AI has already been applied in ophthalmic diabetes care. AI-systems currently detect diabetic retinopathy in general practice with a high sensitivity and specificity. AI-systems for the screening, monitoring and treatment of age-related macular degeneration and glaucoma are promising and are still being developed. AI-algorithms, however, only perform tasks for which they have been specifically trained and highly depend on the data and reference-standard that were used to train the system in identifying a certain abnormality or disease. How the data and the gold standard were established and determined, influences the performance of the algorithm. Furthermore, interpretability of deep learning algorithms is still an ongoing issue. By highlighting on images the areas that were critical for the decision of the algorithm, users can gain more insight into how algorithms come to a particular result

Performance of Classification Systems for Age-Related Macular Degeneration in the Rotterdam Study

Contains fulltext : 225990.pdf (publisher's version ) (Open Access)PURPOSE: To compare frequently used classification systems for age-related macular degeneration (AMD) in their abilty to predict late AMD. METHODS: In total, 9066 participants from the population-based Rotterdam Study were followed up for progression of AMD during a study period up to 30 years. AMD lesions were graded on color fundus photographs after confirmation on other image modalities and grouped at baseline according to six classification systems. Late AMD was defined as geographic atrophy or choroidal neovascularization. Incidence rate (IR) and cumulative incidence (CuI) of late AMD were calculated, and Kaplan-Meier plots and area under the operating characteristics curves (AUCs) were constructed. RESULTS: A total of 186 persons developed incident late AMD during a mean follow-up time of 8.7 years. The AREDS simplified scale showed the highest IR for late AMD at 104 cases/1000 py for ages 75 years. The 3-Continent harmonization classification provided the most stable progression. Drusen area >10% ETDRS grid (hazard ratio 30.05, 95% confidence interval [CI] 19.25-46.91) was most prognostic of progression. The highest AUC of late AMD (0.8372, 95% CI: 0.8070-0.8673) was achieved when all AMD features present at baseline were included. CONCLUSIONS: Highest turnover rates from intermediate to late AMD were provided by the AREDS simplified scale and the Rotterdam classification. The 3-Continent harmonization classification showed the most stable progression. All features, especially drusen area, contribute to late AMD prediction. TRANSLATIONAL RELEVANCE: Findings will help stakeholders select appropriate classification systems for screening, deep learning algorithms, or trials

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice

An increasing number of artificial intelligence (AI) systems are being proposed in ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as their potential benefits at the different stages of patient care. Despite achieving close or even superior performance to that of experts, there is a critical gap between development and integration of AI systems in ophthalmic practice. This work focuses on the importance of trustworthy AI to close that gap. We identify the main aspects or challenges that need to be considered along the AI design pipeline so as to generate systems that meet the requirements to be deemed trustworthy, including those concerning accuracy, resiliency, reliability, safety, and accountability. We elaborate on mechanisms and considerations to address those aspects or challenges, and define the roles and responsibilities of the different stakeholders involved in AI for ophthalmic care, i.e., AI developers, reading centers, healthcare providers, healthcare institutions, ophthalmological societies and working groups or committees, patients, regulatory bodies, and payers. Generating trustworthy AI is not a responsibility of a sole stakeholder. There is an impending necessity for a collaborative approach where the different stakeholders are represented along the AI design pipeline, from the definition of the intended use to post-market surveillance after regulatory approval. This work contributes to establish such multi-stakeholder interaction and the main action points to be taken so that the potential benefits of AI reach real-world ophthalmic settings

The inflammatory potential of diet is associated with the risk of age-related eye diseases

Background & aimsInflammation is involved in the pathogenesis of cataract, age-related macular degeneration (AMD), and possibly open-angle glaucoma (OAG). We assessed whether the inflammatory potential of diet (quantified using the dietary inflammatory index; DII) affects the incidence of these common blinding age-related eye diseases. Serum inflammation markers were investigated as possible mediators.MethodsParticipants aged >45 years were selected from the prospective, population-based Rotterdam Study. From 1991 onwards, every 4–5 years, participants underwent extensive eye examinations. At baseline, blood samples and dietary data (using food frequency questionnaires) were collected. The DII was adapted based on the data available. Of the 7436 participants free of eye diseases at baseline, 4036 developed incident eye diseases during follow-up (cataract = 2895, early-intermediate AMD = 891, late AMD = 81, OAG = 169).ResultsThe adapted DII (aDII) ranged from −4.26 (i.e., anti-inflammatory) to 4.53 (i.e., pro-inflammatory). A higher aDII was significantly associated with increased inflammation. A higher neutrophil-lymphocyte ratio (NLR) was associated with an increased risk of cataract and AMD. Additionally, complement component 3c (C3c) and systemic immune-inflammation index (SII) were associated with increased risks of cataract and late AMD, respectively. Every point increase in the aDII was associated with a 9% increased risk of cataract (Odds ratio [95% confidence interval]: 1.09 [1.04–1.14]). The NLR and C3c partly mediated this association. We also identified associations of the aDII with risk of AMD (early-intermediate AMD, OR [95% CI]: 1.11 [1.03–1.19]; late AMD, OR [95% CI]: 1.24 [1.02–1.53]). The NLR partly mediated these associations. The aDII was not associated with OAG.ConclusionsA pro-inflammatory diet was associated with increased risks of cataract and AMD. Particularly the NLR, a marker of subclinical inflammation, appears to be implicated. These findings are relevant for patients with AMD and substantiate the current recommendations to strive for a healthy lifestyle to prevent blindness.</div

Design, implementation and initial findings of COVID-19 research in the Rotterdam Study

The Rotterdam Study is an ongoing prospective, population-based cohort study that started in 1989 in the city of Rotterdam, the Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. It focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. In response to the COVID-19 pandemic, a substudy was designed and embedded within the Rotterdam Study. On the 20th of April, 2020, all living non-institutionalized participants of the Rotterdam Study (n = 8732) were invited to participate in this sub-study by filling out a series of questionnaires administered over a period of 8 months. These questionnaires included questions on COVID-19 related symptoms and risk factors, characterization of lifestyle and mental health changes, and determination of health care seeking and health care avoiding behavior during the pandemic. As of May 2021, the questionnaire had been sent out repeatedly for a total of six times with an overall response rate of 76%. This article provides an overview of the rationale, design, and implementation of this sub-study nested within the Rotterdam Study. Finally, initial results on participant characteristics and prevalence of COVID-19 in this community-dwelling population are shown.</p