Automated machine learning model for fundus image classification by health-care professionals with no coding experience.

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary outcomes from fundus images in ophthalmology, evaluating two distinct online-based platforms (Google Vertex and Amazon Rekognition), and two distinct datasets. Two publicly available datasets, Messidor-2 and BRSET, were utilized for model development. The Messidor-2 consists of fundus photographs from diabetic patients and the BRSET is a multi-label dataset. The CFDL platforms were used to create deep learning models, with no preprocessing of the images, by a single ophthalmologist without coding expertise. The performance metrics employed to evaluate the models were F1 score, area under curve (AUC), precision and recall. The performance metrics for referable diabetic retinopathy and macular edema were above 0.9 for both tasks and CDFL. The Google Vertex models demonstrated superior performance compared to the Amazon models, with the BRSET dataset achieving the highest accuracy (AUC of 0.994). Multi-classification tasks using only BRSET achieved similar overall performance between platforms, achieving AUC of 0.994 for laterality, 0.942 for age grouping, 0.779 for genetic sex identification, 0.857 for optic, and 0.837 for normality with Google Vertex. The study demonstrates the feasibility of using automated machine learning platforms for predicting binary outcomes from fundus images in ophthalmology. It highlights the high accuracy achieved by the models in some tasks and the potential of CFDL as an entry-friendly platform for ophthalmologists to familiarize themselves with machine learning concepts.

BRSET: A Brazilian Multilabel Ophthalmological Dataset of Retina Fundus Photos.

INTRODUCTION: The Brazilian Multilabel Ophthalmological Dataset (BRSET) addresses the scarcity of publicly available ophthalmological datasets in Latin America. BRSET comprises 16,266 color fundus retinal photos from 8,524 Brazilian patients, aiming to enhance data representativeness, serving as a research and teaching tool. It contains sociodemographic information, enabling investigations into differential model performance across demographic groups. METHODS: Data from three São Paulo outpatient centers yielded demographic and medical information from electronic records, including nationality, age, sex, clinical history, insulin use, and duration of diabetes diagnosis. A retinal specialist labeled images for anatomical features (optic disc, blood vessels, macula), quality control (focus, illumination, image field, artifacts), and pathologies (e.g., diabetic retinopathy). Diabetic retinopathy was graded using International Clinic Diabetic Retinopathy and Scottish Diabetic Retinopathy Grading. Validation used a ConvNext model trained during 50 epochs using a weighted cross entropy loss to avoid overfitting, with 70% training (20% validation), and 30% testing subsets. Performance metrics included area under the receiver operating curve (AUC) and Macro F1-score. Saliency maps were calculated for interpretability. RESULTS: BRSET comprises 65.1% Canon CR2 and 34.9% Nikon NF5050 images. 61.8% of the patients are female, and the average age is 57.6 (± 18.26) years. Diabetic retinopathy affected 15.8% of patients, across a spectrum of disease severity. Anatomically, 20.2% showed abnormal optic discs, 4.9% abnormal blood vessels, and 28.8% abnormal macula. A ConvNext V2 model was trained and evaluated BRSET in four prediction tasks: "binary diabetic retinopathy diagnosis (Normal vs Diabetic Retinopathy)" (AUC: 97, F1: 89); "3 class diabetic retinopathy diagnosis (Normal, Proliferative, Non-Proliferative)" (AUC: 97, F1: 82); "diabetes diagnosis" (AUC: 91, F1: 83); "sex classification" (AUC: 87, F1: 70). DISCUSSION: BRSET is the first multilabel ophthalmological dataset in Brazil and Latin America. It provides an opportunity for investigating model biases by evaluating performance across demographic groups. The model performance of three prediction tasks demonstrates the value of the dataset for external validation and for teaching medical computer vision to learners in Latin America using locally relevant data sources.

BRSET: A Brazilian Multilabel Ophthalmological Dataset of Retina Fundus Photos.

Introduction: The Brazilian Multilabel Ophthalmological Dataset (BRSET) addresses the scarcity of publicly available ophthalmological datasets in Latin America. BRSET comprises 16,266 color fundus retinal photos from 8,524 Brazilian patients, aiming to enhance data representativeness, serving as a research and teaching tool. It contains sociodemographic information, enabling investigations into differential model performance across demographic groups. Methods: Data from three São Paulo outpatient centers yielded demographic and medical information from electronic records, including nationality, age, sex, clinical history, insulin use, and duration of diabetes diagnosis. A retinal specialist labeled images for anatomical features (optic disc, blood vessels, macula), quality control (focus, illumination, image field, artifacts), and pathologies (e.g., diabetic retinopathy). Diabetic retinopathy was graded using International Clinic Diabetic Retinopathy and Scottish Diabetic Retinopathy Grading. Validation used Dino V2 Base for feature extraction, with 70% training and 30% testing subsets. Support Vector Machines (SVM) and Logistic Regression (LR) were employed with weighted training. Performance metrics included area under the receiver operating curve (AUC) and Macro F1-score. Results: BRSET comprises 65.1% Canon CR2 and 34.9% Nikon NF5050 images. 61.8% of the patients are female, and the average age is 57.6 years. Diabetic retinopathy affected 15.8% of patients, across a spectrum of disease severity. Anatomically, 20.2% showed abnormal optic discs, 4.9% abnormal blood vessels, and 28.8% abnormal macula. Models were trained on BRSET in three prediction tasks: "diabetes diagnosis"; "sex classification"; and "diabetic retinopathy diagnosis". Discussion: BRSET is the first multilabel ophthalmological dataset in Brazil and Latin America. It provides an opportunity for investigating model biases by evaluating performance across demographic groups. The model performance of three prediction tasks demonstrates the value of the dataset for external validation and for teaching medical computer vision to learners in Latin America using locally relevant data sources.

Transition from an in-person to a telemedicine diabetic retinopathy screening program.

PURPOSE: Timely screening and treatment are essential for preventing diabetic retinopathy blindness. Improving screening workflows can reduce waiting times for specialist evaluation and thus enhance patient outcomes. This study assessed different screening approaches in a Brazilian public healthcare setting. METHODS: This retrospective study evaluated a telemedicine-based diabetic retinopathy screening implemented during the COVID-19 pandemic and compared it with in-person strategies. The evaluation was conducted from the perspective of a specialized referral center in an urban area of Central-West Brazil. In the telemedicine approach, a trained technician would capture retinal images by using a handheld camera. These images were sent to specialists for remote evaluation. Patient variables, including age, gender, duration of diabetes diagnosis, diabetes treatment, comorbidities, and waiting time, were analyzed and compared. RESULTS: In total, 437 patients with diabetes mellitus were included in the study (mean age: 62.5 ± 11.0 years, female: 61.7%, mean diabetes duration: 15.3 ± 9.7 years, insulin users: 67.8%). In the in-person assessment group, the average waiting time between primary care referral and specialist evaluation was 292.3 ± 213.9 days, and the referral rate was 73.29%. In the telemedicine group, the average waiting time was 158.8 ± 192.4 days, and the referral rate was 29.38%. The telemedicine approach significantly reduced the waiting time (p<0.001) and significantly lowered the referral rate (p<0.001). CONCLUSION: The telemedicine approach significantly reduced the waiting time for specialist evaluation in a real-world setting. Employing portable retinal cameras may address the burden of diabetic retinopathy, especially in resource-limited settings.

Automated Identification of Different Severity Levels of Diabetic Retinopathy Using a Handheld Fundus Camera and Single-Image Protocol.

Purpose: To evaluate the performance of artificial intelligence (AI) systems embedded in a mobile, handheld retinal camera, with a single retinal image protocol, in detecting both diabetic retinopathy (DR) and more-than-mild diabetic retinopathy (mtmDR). Design: Multicenter cross-sectional diagnostic study, conducted at 3 diabetes care and eye care facilities. Participants: A total of 327 individuals with diabetes mellitus (type 1 or type 2) underwent a retinal imaging protocol enabling expert reading and automated analysis. Methods: Participants underwent fundus photographs using a portable retinal camera (Phelcom Eyer). The captured images were automatically analyzed by deep learning algorithms retinal alteration score (RAS) and diabetic retinopathy alteration score (DRAS), consisting of convolutional neural networks trained on EyePACS data sets and fine-tuned using data sets of portable device fundus images. The ground truth was the classification of DR corresponding to adjudicated expert reading, performed by 3 certified ophthalmologists. Main Outcome Measures: Primary outcome measures included the sensitivity and specificity of the AI system in detecting DR and/or mtmDR using a single-field, macula-centered fundus photograph for each eye, compared with a rigorous clinical reference standard comprising the reading center grading of 2-field imaging protocol using the International Classification of Diabetic Retinopathy severity scale. Results: Of 327 analyzed patients (mean age, 57.0 ± 16.8 years; mean diabetes duration, 16.3 ± 9.7 years), 307 completed the study protocol. Sensitivity and specificity of the AI system were high in detecting any DR with DRAS (sensitivity, 90.48% [95% confidence interval (CI), 84.99%-94.46%]; specificity, 90.65% [95% CI, 84.54%-94.93%]) and mtmDR with the combination of RAS and DRAS (sensitivity, 90.23% [95% CI, 83.87%-94.69%]; specificity, 85.06% [95% CI, 78.88%-90.00%]). The area under the receiver operating characteristic curve was 0.95 for any DR and 0.89 for mtmDR. Conclusions: This study showed a high accuracy for the detection of DR in different levels of severity with a single retinal photo per eye in an all-in-one solution, composed of a portable retinal camera powered by AI. Such a strategy holds great potential for increasing coverage rates of screening programs, contributing to prevention of avoidable blindness. Financial Disclosures: F.K.M. is a medical consultant for Phelcom Technologies. J.A.S. is Chief Executive Officer and proprietary of Phelcom Technologies. D.L. is Chief Technology Officer and proprietary of Phelcom Technologies. P.V.P. is an employee at Phelcom Technologies.

An emergency room influx and trauma cases prediction in a Brazilian ophthalmological hospital by an ophthalmologist without code experience / Predição do influxo de atendimentos e casos de trauma em um serviço de urgência oftalmológico brasileiro realizado por um oftalmologista sem experiência em programação

ABSTRACT Purpose: The emergency medical service is a fundamental part of healthcare, albeit crowded emergency rooms lead to delayed and low-quality assistance in actual urgent cases. Machine-learning algorithms can provide a smart and effective estimation of emergency patients' volume, which was previously restricted to artificial intelligence (AI) experts in coding and computer science but is now feasible by anyone without any coding experience through auto machine learning. This study aimed to create a machine-learning model designed by an ophthalmologist without any coding experience using AutoML to predict the influx in the emergency department and trauma cases. Methods: A dataset of 356,611 visits at Hospital da Universidade Federal de São Paulo from January 01, 2014 to December 31, 2019 was included in the model training, which included visits/day and the international classification disease code. The training and prediction were made with the Amazon Forecast by 2 ophthalmologists with no prior coding experience. Results: The forecast period predicted a mean emergency patient volume of 216.27/day in p90, 180.75/day in p50, and 140.35/day in p10, and a mean of 7.42 trauma cases/ day in p90, 3.99/day in p50, and 0.56/day in p10. In January of 2020, there were a total of 6,604 patient visits and a mean of 206.37 patients/day, which is 13.5% less than the p50 prediction. This period involved a total of 199 trauma cases and a mean of 6.21 cases/day, which is 55.77% more traumas than that by the p50 prediction. Conclusions: The development of models was previously restricted to data scientists' experts in coding and computer science, but transfer learning autoML has enabled AI development by any person with no code experience mandatory. This study model showed a close value to the actual 2020 January visits, and the only factors that may have influenced the results between the two approaches are holidays and dataset size. This is the first study to apply AutoML in hospital visits forecast, showing a close prediction of the actual hospital influx.

RESUMO Objetivo: Esse estudo tem como objetivo criar um modelo de Machine Learning por um oftalmologista sem experiência em programação utilizando auto Machine Learning predizendo influxo de pacientes em serviço de emergência e casos de trauma. Métodos: Um dataset de 366,610 visitas em Hospital Universitário da Universidade Federal de São Paulo de 01 de janeiro de 2014 até 31 de dezembro de 2019 foi incluído no treinamento do modelo, incluindo visitas/dia e código internacional de doenças. O treinamento e predição foram realizados com o Amazon Forecast por dois oftalmologistas sem experiência com programação. Resultados: O período de previsão estimou um volume de 206,37 pacientes/dia em p90, 180,75 em p50, 140,35 em p10 e média de 7,42 casos de trauma/dia em p90, 3,99 em p50 e 0,56 em p10. Janeiro de 2020 teve um total de 6.604 pacientes e média de 206,37 pacientes/dia, 13,5% menos do que a predição em p50. O período teve um total de 199 casos de trauma e média de 6,21 casos/dia, 55,77% mais casos do que a predição em p50. Conclusão: O desenvolvimento de modelos era restrito a cientistas de dados com experiencia em programação, porém a transferência de ensino com a tecnologia de auto Machine Learning permite o desenvolvimento de algoritmos por qualquer pessoa sem experiencia em programação. Esse estudo mostra um modelo com valores preditos próximos ao que ocorreram em janeiro de 2020. Fatores que podem ter influenciados no resultado foram feriados e tamanho do banco de dados. Esse é o primeiro estudo que aplicada auto Machine Learning em predição de visitas hospitalares com resultados próximos aos que ocorreram.

Transition from an in-person to a telemedicine diabetic retinopathy screening program

ABSTRACT Purpose: Timely screening and treatment are essential for preventing diabetic retinopathy blindness. Improving screening workflows can reduce waiting times for specialist evaluation and thus enhance patient outcomes. This study assessed different screening approaches in a Brazilian public healthcare setting. Methods: This retrospective study evaluated a telemedicine-based diabetic retinopathy screening implemented during the COVID-19 pandemic and compared it with in-person strategies. The evaluation was conducted from the perspective of a specialized referral center in an urban area of Central-West Brazil. In the telemedicine approach, a trained technician would capture retinal images by using a handheld camera. These images were sent to specialists for remote evaluation. Patient variables, including age, gender, duration of diabetes diagnosis, diabetes treatment, comorbidities, and waiting time, were analyzed and compared. Results: In total, 437 patients with diabetes mellitus were included in the study (mean age: 62.5 ± 11.0 years, female: 61.7%, mean diabetes duration: 15.3 ± 9.7 years, insulin users: 67.8%). In the in-person assessment group, the average waiting time between primary care referral and specialist evaluation was 292.3 ± 213.9 days, and the referral rate was 73.29%. In the telemedicine group, the average waiting time was 158.8 ± 192.4 days, and the referral rate was 29.38%. The telemedicine approach significantly reduced the waiting time (p<0.001) and significantly lowered the referral rate (p<0.001). Conclusion: The telemedicine approach significantly reduced the waiting time for specialist evaluation in a real-world setting. Employing portable retinal cameras may address the burden of diabetic retinopathy, especially in resource-limited settings.

Impact of SARS-CoV-2 pandemic on ophthalmological emergency visits: 1 year of experience / Impacto da pandemia de SARS-CoV-2 nas visitas ao serviço oftalmológico de emergência: experiência de 1 ano

ABSTRACT Purpose: The COVID-19 pandemic began in March 2020 and changed the healthcare system overall. The pandemic led to resource allocation changes, overloading of intensive care units, apprehensiveness of patients to seek medical care not related to COVID-19, and an abrupt reduction in all nonurgent consultations and surgeries. This study evaluated the impact on an ophthalmological emergency room for one year by assessing the correlation between societal lockdown phases and COVID-19 mortality. Methods: An observational, retrospective study was conducted that included all patients admitted to the Ophthalmology Emergency Department between January 1, 2019, and March 28, 2021. The visits were classified into prepandemic and pandemic groups that were then compared. Results: In the prepandemic period, the hospital registered a total of 71,485 visits with a mean of 194.78 ± 49.74 daily visits. In the pandemic group, there was a total of 41,791 visits with a mean of 114.18 ± 43.12 daily visits, which was a 41.4% decrease. A significant decrea­se (16.4 p<0.001) was observed in the prevalence of acute conjunctivitis, and a significant increase (6.4%; p<0.01) was observed in the prevalence of corneal foreign body disorders. A negative correlation was identified between the COVID-19 death rate and the ophthalmological inflow rates. Conclusion: This one-year analysis showed a reduction of 41.4% in emergency department visits and a significant decrease in infectious conditions. A change in hygiene habits and social distancing could explain this reduction, and the increased prevalence of trauma consultations highlighted the need for preventive and educative measures during these types of restrictive periods.

RESUMO Objetivos: A pandemia de COVID-19 foi iniciada em março de 2020 e mudou o sistema de saúde. Mudanças na alocação de recursos, sobrecarga de unidades de terapia intensiva, apreensão dos pacientes em procurar atendimento médico não relacionado ao COVID-19 e redução abrupta de todas as consultas e cirurgias não urgentes. Este estudo avalia o impacto em um pronto-socorro oftalmológico após 1 ano de pandemia, avaliando a correlação entre as fases de lockdown, a mortalidade do COVID-19 e as visitas ao pronto-socorro. Métodos: Estudo observacional retrospectivo que incluiu todos os pacientes admitidos no serviço de emergência oftalmológica do Hospital São Paulo, vinculado a UNIFESP/EPM, entre 1º de janeiro de 2019 e 28 de março de 2021. As visitas foram classificadas e comparadas em um grupo pré-pandemia e pandemia. Resultados: No período pré-pandemia, o hospital registrou um total de 71.485 atendimentos com média de 194,78 ± 49,74 atendimentos diários, e no grupo pandemia, um total de 41.791 com média de 114,18 ± 43,12 atendimentos diários, redução de 41,4%. Uma diminuição significativa de 16,4% (p<0,001) foi observada na prevalência de conjuntivite aguda e um aumento significativo de 6,4% (p<0,01) na prevalência de corpo estranho da córnea. Foi identificada uma correlação negativa entre a taxa de mortalidade do COVID-19 e as taxas de visita ao pronto-socorro. Conclusão: Esta análise de um ano mostrou uma redução de 41,4% nas visitas ao pronto-socorro, e uma diminuição significativa nas conjuntivites agudas. A mudança nos hábitos de higiene e o distanciamento social poderiam explicar essa redução, e o aumento da prevalência de traumas corneanos. Achados destacam a necessidade de medidas preventivas e educativas durante os períodos restritivos.

Ophthalmology emergency department visits in a Brazilian tertiary hospital over the last 11 years: data analysis / Análise dos dados de atendimentos de um serviço de emergência oftalmológica em um hospital terciário brasileiro nos últimos 11 anos

ABSTRACT Purpose: This study aimed to describe the visits profile to Hospital São Paulo's ophthalmology emergency department, a 24-hour public open-access tertiary-care service in São Paulo, Brazil, that belongs to Federal University of São Paulo, over the last 11 years. Methods: A cross-sectional retrospective study was conducted, including all patients (n=634,726) admitted to the ophthalmology emergency department of Hospital São Paulo between January 2009 and December 2019. Results: From 2009 to 2019, the number of patients' presentations increased to 39.2%, with considerable visits variation across the period. The median age was 38 ± 20.4 years. Males represented 53.3%, and single-visit patients represented 53.1%. A total of 79.5% of patients' presentations occurred from 7 am to 5 pm, and 80.8% of patients' presentations occurred during regular weekdays. The most frequent diagnoses were conjunctivitis, blepharitis, keratitis, hordeolum/chalazion, and corneal foreign body. Conclusions: Over the study period, presentations significantly increased in number, with nonurgent visits predominance, and a low number of single-visit patients. Our results demonstrate the ophthalmic visits profile and can lead to changes in the public health system to improve the quality of care and ophthalmology emergency access in São Paulo city.

RESUMO Objetivos: O objetivo do estudo é avaliar o perfil das visitas ao Pronto-Socorro de Oftalmologia (PS) do Hospital São Paulo, serviço público de atendimento terciário aberto 24 horas em São Paulo - Brasil, pertencente à Universidade Federal de São Paulo, nos últimos 11 anos. Métodos: Foi realizado um estudo transversal retrospectivo, com base em todos os pacientes (n=634.726) admitidos no pronto-socorro de oftalmologia do Hospital São Paulo entre janeiro de 2009 e dezembro de 2019. Resultados: De 2009 a 2019, houve um aumento no influxo de 39,2% com importante variação nos atendimentos ao longo dos anos, a mediana de idade foi de 38 ± 20,4 anos, o sexo masculino representou 53,3% e os pacientes únicos representaram 53,1%. Verificou-se que 79,5% das visitas ocorreram das 7h às 17h e 80,8% nos dias da semana. Os diagnósticos mais frequentes foram conjuntivite aguda seguida de blefarite, ceratite, hordéolo / calázio e corpo estranho corneano. Conclusão: Ao longo do período de análise do estudo, houve importante aumento nas apresentações, com predominância de atendimentos não urgentes e baixa proporção de pacientes com uma única visita. Nossos resultados evidenciam o perfil das consultas oftalmológicas, podendo gerar mudanças no sistema público de saúde visando a melhoria da qualidade do atendimento e acesso às emergências oftalmológicas na cidade de São Paulo.

Performance of ChatGPT-4 in answering questions from the Brazilian National Examination for Medical Degree Revalidation

SUMMARY OBJECTIVE: The aim of this study was to evaluate the performance of ChatGPT-4.0 in answering the 2022 Brazilian National Examination for Medical Degree Revalidation (Revalida) and as a tool to provide feedback on the quality of the examination. METHODS: A total of two independent physicians entered all examination questions into ChatGPT-4.0. After comparing the outputs with the test solutions, they classified the large language model answers as adequate, inadequate, or indeterminate. In cases of disagreement, they adjudicated and achieved a consensus decision on the ChatGPT accuracy. The performance across medical themes and nullified questions was compared using chi-square statistical analysis. RESULTS: In the Revalida examination, ChatGPT-4.0 answered 71 (87.7%) questions correctly and 10 (12.3%) incorrectly. There was no statistically significant difference in the proportions of correct answers among different medical themes (p=0.4886). The artificial intelligence model had a lower accuracy of 71.4% in nullified questions, with no statistical difference (p=0.241) between non-nullified and nullified groups. CONCLUSION: ChatGPT-4.0 showed satisfactory performance for the 2022 Brazilian National Examination for Medical Degree Revalidation. The large language model exhibited worse performance on subjective questions and public healthcare themes. The results of this study suggested that the overall quality of the Revalida examination questions is satisfactory and corroborates the nullified questions.

Comparison of choroidal thickness in normal eyes and different ocular pathologies in a Brazilian population

Abstract Objective: To evaluate the choroidal thickness (CT) in healthy Brazilian subjects using spectral-domain optical coherence tomography (SD-OCT) and to compare with choroidal thickness measured in Brazilian patients with diabetic macular edema (DME), neovascular age-related macular degeneration (AMD) and high myopia. Methods: A retrospective analysis of spectral domain optical coherence tomography (SD-OCT) images of 181 Brazilian subjects. A total of 74 eyes were included in the normal control group, 50 eyes in the nvAMD group, 44 eyes in the DME group and 13 eyes in the high myopia group. CT was measured from the posterior edge of the retinal pigment epithelium (RPE) to the choroid/sclera junction at the fovea and at 500 μm intervals temporal and nasal to the fovea. All measurements were performed by two independent observers and were averaged for analysis. The statistical analysis and comparison were performed using Mann Whitney (unpaired t-test). Results: Seventy-four eyes from 74 patients with a mean age of 51.4 years were analyzed in the normal group with a mean nasal, subfoveal and temporal choroidal thickness measurements were 301.30 ± 12.86 μm, 311.61 ± 12.62 μm and 309.28 ± 12.28 μm respectively. All groups with disease demonstrated a statistically significant choroidal thinning when compared with matched-aged normal eyes. The mean reduction in the nvAMD group compared to normal were 60.65 μm nasally, 59.77 μm temporally and 56.59 μm at subfoveal position. In the DME group, the subfoveal reduction was 51.10 μm, 63.03 μm and 46.30 μm, nasally and temporally. The patients with high myopia presented the greatest reduction in CT compared to normal eyes, with a mean reduction of 159.9 nasal, 159.98 subfoveal and 154.65 at temporal. Conclusions: The present study evaluated choroidal thickness in Brazilian subjects, with intense miscegenation. The results demonstrated a statistically significant decrease of the choroidal thickness in all subtypes of chorioretinal disease. The small sample size in this study was a limitation. Additional research with a larger study population to better understand these findings.

Resumo Objetivo: Avaliar a espessura da coróide (EC) de indivíduos brasileiros saudáveis utilizando tomografia de coerência ótica do domínio espectral (TCO-DE) e compará-la à espessura da coroide de pacientes brasileiros com edema macular diabético (EMD), degeneração macular neovascular relacionada à idade (DMRI) e miopia alta. Metodologia: Análise retrospectiva de imagens de tomografia de coerência ótica de domínio espectral (TOC-DE) de 181 indivíduos brasileiros. Um total de 74 olhos foram incluídos no grupo controle normal; 50, no grupo DMRI; 44, no grupo EMD; e 13, no grupo com miopia alta. A EC foi medida a partir da borda posterior do epitélio pigmentar da retina (EPR) até a junção coróide/esclera na fóvea e de intervalos de 500 μm, temporal e nasal, à fóvea. Todas as medidas foram realizadas por dois observadores independentes e as médias foram calculadas para análise. A análise estatística e a comparação das ECs foram realizadas usando o teste Mann Whitney (teste t não pareado). Resultados: Setenta e quatro olhos de 74 pacientes com idade média de 51,4 anos foram analisados no grupo normal, o qual apresentou espessura coróide nasal, subfoveal e temporal média igual a 301,30 ± 12,86 µm, 311,61 ± 12,62 µm e 309,28 ± 12,28 µm, respectivamente. Todos os grupos com doença demonstraram afinamento de coroide estatisticamente significativo quando comparados a olhos normais pareados por idade. A redução média de EC no grupo DMRI em comparação ao normal foi de 60,65 μm por via nasal, 59,77 μm por via temporal e 56,59 μm na posição subfoveal. O grupo EMD apresentou redução de EC igual a 51,10 μm em posição subfoveal, 63,03 μm por via nasal e 46,30 μm por via temporal. Pacientes com miopia alta apresentaram a maior redução de EC em relação aos olhos normais; os valores de redução média obtidos foram 159,9 por via nasal, 159,98 em posição subfoveal e 154,65 por via temporal. Conclusões: O presente estudo avaliou a espessura da coróide de indivíduos brasileiros com intensa miscigenação. Os resultados demonstraram reducção estatisticamente significativa da espessura da coróide em todos os subtipos de doença coriorretiniana. O pequeno tamanho da amostra foi uma limitação deste estudo. Pesquisas adicionais com população maior de estudo deveriam ser realizadas para ajudar a entender melhor esses achados.

Centration in refractive surgery / Centralização em cirurgia refrativa

ABSTRACT The point of centration for refractive surgery is a theme of great importance that generates considerable discussion among specialists and surgeons in the field. Notably, any changes in light can alter the size of the pupil, and the visual axis of the fixation line to the fovea is unique in each patient. A variety of options have been described in the literature with respect to centration in refractive surgery, and the results differ among these methods. No consensus has been established regarding the ideal refractive surgery technique for evaluation of centration in each patient that will yield a satisfactory surgical result.

RESUMO O ponto de centralização da cirurgia refrativa é tema de grande importância e gera muita discussão entre especialistas e cirurgiões da área. Afinal, qualquer alteração na luz pode alterar o tamanho da pupila, além disso, o eixo visual da linha de fixação para a fóvea é particular em cada paciente. Existem opções para centralização em cirurgia refrativa com resultados diferentes na literatura. Ainda não há consenso sobre a melhor técnica em cirurgia refrativa que avalie cada caso específico visando um resultado cirúrgico final satisfatório.

Large colloid drusen analyzed with structural en face optical coherence tomography / Análise de drusas grandes coloidais através de OCT en face estrutural

ABSTRACT Drusen are extracellular deposits between the basal lamina of the retinal pigment epithelium (RPE) and the inner collagenous layer of Bruch's membrane. Large colloid drusen (LCD) are located below the RPE and are characterized by multiple, large, dome-shaped RPE detachments, with marked attenuation of the ellipsoid zone overlaying the drusen. This report presents the structural en face optical coherence tomography (OCT) findings of LCD and relates them to findings from fluorescein and indocyanine green angiography. We describe the case of a 55-year-old woman who presented with the chief complaint of a 5-year history of progressively worsening vision. Her best-corrected visual acuities were 20/40 and 20/400 in the right eye and the left eye, respectively. Fundus examination showed large bilateral, symmetrical, sub-retinal, yellowish lesions compatible with LCD. We describe the structural en face OCT characteristics and angiographic findings from this patient.

RESUMO Drusas são depósitos extracelulares localizados entre a lâmina basal do epitélio pig mentado da retina (RPE) e a camada colágena interna da membrana de Bruch. Drusas grandes coloidais (LCD) estão localizadas abaixo do EPR, e são caracterizadas por múltiplos descolamentos cupuliformes do EPR com atenuação da zona elipsoide sobrejacente às drusas. O objetivo deste relato é apresentar os achados de tomografia de coerência óptica (OCT en face estrutural em uma paciente com LCD, bem como correlacioná-los com angiografia fluoresceínica e angiografia com indocianina verde. Descrevemos o caso de uma paciente do sexo feminino, 55 anos, que referiu baixa acuidade visual em ambos os olhos há 5 anos. Sua acuidade visual corrigida era de 20/40 no olho direito e 20/400 no olho esquerdo. Ao exame fundoscópico a paciente apresentava lesões compatíveis com drusas grandes coloidais. As características tomográficas e angiográficas também são descritas neste relato de caso.

Effect of intravitreal anti-VEGF on choroidal thickness in patients with diabetic macular edema using spectral domain OCT / Efeito de injeção intravítrea na espessura de coroide em pacientes com edema macular diabético utilizando OCT de domínio espectral

ABSTRACT Purpose: To evaluate choroidal thickness (CT) using spectral domain optical coherence tomography (SD-OCT) imaging at baseline and 6 months after intravitreal anti-vascular endothelial growth factor (anti-VEGF) treatment in patients with diabetic macular edema (DME). Methods: A retrospective chart review was performed to identify patients with DME who underwent intravitreal injection of anti-VEGF (bevacizumab or ranibizumab) in a pro re nata (PRN) regimen. Subfoveal choroidal thickness was compared between values obtained at baseline and at 6-month follow-up visits. Results: Thirty-nine eyes (15 females, 24 males) from 39 patients were enrolled (mean age, 62.43 ± 8.7 years; range, 44-79 years). Twenty-three and 16 eyes were treated with ranibizumab and bevacizumab respectively. The mean number of anti-VEGF injections was 2.28 ± 1.27 (range, 1-5). Mean nasal, subfoveal, and temporal choroidal thickness (CT) measurements at baseline were 234.10 ± 8.63 µm, 246.89 ± 8.94 µm, and 238.12 ± 8.20 µm, respectively, and those at 6 months post-treatment were 210.46 ± 8.00 µm, 215.66 ± 8.29 µm, and 212.43 ± 8.14 µm, respectively. Significant differences in CT were observed between baseline and the 6-month follow-up at all measured points (p=0.0327). Conclusions: Over a 6-month period, the use of intravitreal anti-VEGF was associated with significant thinning of the choroid in patients with DME. The clinical significance of a thinner choroid in DME is currently unknown; however, it may contribute to long-term adverse effects on choroidal and retinal function, representing an area requiring future investigation.

RESUMO Objetivos: Avaliar a espessura de coroide pré-tratamento e após 6 meses da injeção intravítrea de anti-fator de crescimento vascular endotelial (anti-VEGF) em pacientes com edema macular diabético (EMD), utilizando a tomografia de coerência óptica de domínio espectral (SD-OCT). Métodos: Análise retrospectiva, com revisão de prontuários, foi realizada para identificação de pacientes submetidos a tratamento com injeções intravítreas de anti-VEGF, no regime pro re nata, para tratamento de EMD. As medidas da espessura de coroide pré-tratamento foi comparada com as medidas após acompanhamento de 6 meses. Resultados: Trinta e nove olhos de 39 pacientes (15 femininos, 24 masculinos) foram incluídos, com idade média de 62,43 ± 8,7 anos (variando de 44-79 anos). Trinta e três olhos foram tratados com ranibizumab e 18 com bevacizumab. O número médio de injeções de anti-VEGF foi 2,28 ± 1,27 (variando de 1-5). A medida média pré-tratamento da espessura de coroide nasal, subfoveal e temporal foi 234,10 ± 8,63 µm, 246,89 ± 8,94 µm e 238,12± 8,20 µm, respectivamente. Após acompanhamento de 6 meses as medidas médias da espessura de coroide foram 210,46 ± 8,00 µm, 215,66 ± 8,29 µm e 212,43 ± 8,14 µm. A diferença entre as medidas médias pré e pós tratamento foi estatisticamente significante (p=0,0327) em todos os pontos medidos. Conclusão: Após um período de 6 meses, o uso de injeções intravítreas de anti-VEGF foi associado com diminuição significante da espessura de coroide nos pacientes com EMD. O significado clínico de uma coroide mais fina nos pacientes com EMD é desconhecido mas pode causar eventos adversos a longo prazo para função da coroide e retina, representando uma área para futura investigações.