MAPLES-DR: MESSIDOR Anatomical and Pathological Labels for Explainable Screening of Diabetic Retinopathy.

Reliable automatic diagnosis of Diabetic Retinopathy (DR) and Macular Edema (ME) is an invaluable asset in improving the rate of monitored patients among at-risk populations and in enabling earlier treatments before the pathology progresses and threatens vision. However, the explainability of screening models is still an open question, and specifically designed datasets are required to support the research. We present MAPLES-DR (MESSIDOR Anatomical and Pathological Labels for Explainable Screening of Diabetic Retinopathy), which contains, for 198 images of the MESSIDOR public fundus dataset, new diagnoses for DR and ME as well as new pixel-wise segmentation maps for 10 anatomical and pathological biomarkers related to DR.

Comparing code-free deep learning models to expert-designed models for detecting retinal diseases from optical coherence tomography.

Background: Code-free deep learning (CFDL) is a novel tool in artificial intelligence (AI). This study directly compared the discriminative performance of CFDL models designed by ophthalmologists without coding experience against bespoke models designed by AI experts in detecting retinal pathologies from optical coherence tomography (OCT) videos and fovea-centered images.

Methods: Using the same internal dataset of 1,173 OCT macular videos and fovea-centered images, model development was performed simultaneously but independently by an ophthalmology resident (CFDL models) and a postdoctoral researcher with expertise in AI (bespoke models).

Assessing the feasibility, acceptability, and fidelity of a tele-retinopathy-based intervention to encourage greater attendance to diabetic retinopathy screening in immigrants living with diabetes from China and African-Caribbean countries in Ottawa, Canada: a protocol.

Background: Diabetic retinopathy is a leading cause of preventable blindness in Canada. Clinical guidelines recommend annual diabetic retinopathy screening for people living with diabetes to reduce the risk and progression of vision loss. However, many Canadians with diabetes do not attend screening.

MBT: Model-Based Transformer for retinal optical coherence tomography image and video multi-classification.

Background And Objective: The detection of retinal diseases using optical coherence tomography (OCT) images and videos is a concrete example of a data classification problem. In recent years, Transformer architectures have been successfully applied to solve a variety of real-world classification problems. Although they have shown impressive discriminative abilities compared to other state-of-the-art models, improving their performance is essential, especially in healthcare-related problems.

Focused Attention in Transformers for interpretable classification of retinal images.

Vision Transformers have recently emerged as a competitive architecture in image classification. The tremendous popularity of this model and its variants comes from its high performance and its ability to produce interpretable predictions. However, both of these characteristics remain to be assessed in depth on retinal images.

Assessment of Training Outcomes of Nurse Readers for Diabetic Retinopathy Telescreening: Validation Study.

Background: With the high prevalence of diabetic retinopathy and its significant visual consequences if untreated, timely identification and management of diabetic retinopathy is essential. Teleophthalmology programs have assisted in screening a large number of individuals at risk for vision loss from diabetic retinopathy. Training nonophthalmological readers to assess remote fundus images for diabetic retinopathy may further improve the efficiency of such programs.

Compliance to follow-up care after urban diabetic retinopathy tele-screening.

Background: Although many diabetic retinopathy (DR) tele-screening projects have shown effectiveness for DR, timely follow-up care after screening is essential to achieve the expected visual benefits of screening.

Objective: To better understand the possible factors of non-compliance to follow-up care in diabetics after tele-screening for DR.

Method: This cross-sectional retrospective descriptive study analyses the data of 148 diabetics referred to follow-up care following screening of 1185 diabetics through an urban community-based DR Teleophthalmology Project aimed at Type 2 diabetes.

Urban diabetic retinopathy teleophthalmology screening: results and impact at the service corridor.

Objective: To assess real-world results and the impact on a hospital service corridor for screening for DR through an urban community teleophthalmology service.

Methods: Retrospective analysis at the hospital service corridor of 148 diabetics referred to it following DR teleophthalmology screening of 1185 type II diabetics.

Results: Of the screened diabetics, 87.

Contemporary management of diabetic retinopathy in Canada: from guidelines to algorithm guidance.

Recent advances in the therapeutic options and approaches for diabetic retinopathy (DR) and diabetic macular edema (DME) have resulted in improved visual outcomes for many patients with diabetes. Yet, they have also created many clinical dilemmas for treating ophthalmologists and retina specialists, including treatment selection, initiation, frequency and duration. With this in mind, a panel of Canadian retina specialists met and discussed the current clinical evidence as well as specific situations and scenarios commonly encountered in daily practice.

Teleophthalmology screening for diabetic retinopathy through mobile imaging units within Canada.

Background: This study aimed to describe and measure the health results of a Category 3 teleophthalmology screening project for diabetic retinopathy (DR). Implemented through mobile screening imaging units located within pharmacies, the project had the goal of reaching unscreened diabetic patients in urban communities while lowering barriers to screening and saving medical resources.

Methods: Image capture of both eyes of 3505 known diabetic individuals was performed in the provinces of Quebec, British Columbia, Alberta, Manitoba, and Saskatchewan.

Comparison of two, three and four 45 degrees image fields obtained with the Topcon CRW6 nonmydriatic camera for screening for diabetic retinopathy.

Background: The use of the nonmydriatic camera is gaining increasing acceptance for the detection of diabetic retinopathy when integrated into a community-tailored program. We performed a study to evaluate the optimal number and positioning of photographic fields necessary to screen for diabetic retinopathy with the Topcon CRW6 nonmydriatic camera.

Methods: In this prospective masked cross-sectional comparative study, we compared the assessment of diabetic retinopathy using two, three or four 45 degrees fundus images (centred respectively on the disc and the macula; on the disc, on the macula and temporal to the macula; and on the disc, on the macula, temporal to the macula and superotemporal to the macula, including the superior temporal vein) acquired with the Topcon CRW6 nonmydriatic camera, with the grading of the seven standard stereoscopic 30 degrees field photographs (7SF).

Effectiveness and safety of screening for diabetic retinopathy with two nonmydriatic digital images compared with the seven standard stereoscopic photographic fields.

Background: The use of nonmydriatic cameras, which offer ease of screening and 45 degrees immediate imaging of the fundus, is gaining increasing acceptance for screening programs tailored to diverse conditions. We performed a study to evaluate the effectiveness and safety of screening for diabetic retinopathy with two nonmydriatic camera images compared with the seven standard stereoscopic 30 degrees fields (7SF). We also wished to determine whether safe screening guidelines could be established to identify patients needing referral to an ophthalmologist.