Diabetes mellitus (DM) is a major expanding health problem with increasing prevalence and rising healthcare burden globally. According to the International Diabetes Federation, the global prevalence of diabetes is 9.3% (463 million people) in 2019, rising to 10.9 % (700 million) by 2045. The eye is a reflection to systemic diseases and one of the first presentations of DM. For example, the retinal vascular fractals reflect long-term microvasculopathy, the pathological and morphological changes of corneal nerve reflect severity of diabetic neuropathy. Early prevention and intervention can significantly reduce the morbidity, caused by ocular complications associated diabetes.
Diabetic retinopathy (DR) is the most common and specific ocular complications of DM and is the leading cause of blindness in working age population in both developed and developing countries. Early diagnosis and prompt intervention are essential to achieve good visual outcome in most patients with DR. Molecular and imaging biomarkers, artificial intelligence (AI), as well as gene and stem cell therapy are critical for early prevention and management of DR.
While DR and diabetic cataract are well-known complications of DM, diabetic ocular surface diseases, including dry eye disease (DED) are also common in the diabetic population. The reported prevalence of DED in diabetes is 15-33% and increases with age and is 50% more common in women than in men. Lacrimal Functional Unit dysfunction, abnormal tear dynamics, diabetic neuropathy and film dysfunction have been implicated in the pathogenesis of DED. Topical insulin has been compared with artificial tears. The results show that they are equally efficacious. Other diabetic ocular conditions include glaucoma, cataract and diabetic papillopathy.
This Research Topic aims to provide the wide spectrum and latest advancements in basic and clinical concepts to the diagnosis, progression, treatment outcomes, and the application of AI techniques in clinical research for DR and other ocular conditions associated with DM. In this Research Topic, we welcome original research and review articles to address the pathogenesis, imaging, cellular and molecular biomarkers, artificial intelligence in DR, diabetic macular edema (DME), and other diabetic ocular complications. Subtopics include, but not limited to the following:
• The epidemiology of diabetic retinopathy
• Application of AI techniques, such as machine learning and deep learning, in automated screening/diagnosis/prognosis prediction of DR and DME
• Novel diagnostic tools for early diagnosis and its consequences of the diabetic ocular complications: biomarkers and imaging
• Prognostic models for diabetic retinopathy.
• Current prevention and treatment options for DR and other ocular complications of DM.
• Novel therapeutic approaches for the diabetic ocular complications: gene therapy, exosomes, miRNA, incretins, bioengineering approaches, etc
• Tackling DR as a global health issue.
Diabetes mellitus (DM) is a major expanding health problem with increasing prevalence and rising healthcare burden globally. According to the International Diabetes Federation, the global prevalence of diabetes is 9.3% (463 million people) in 2019, rising to 10.9 % (700 million) by 2045. The eye is a reflection to systemic diseases and one of the first presentations of DM. For example, the retinal vascular fractals reflect long-term microvasculopathy, the pathological and morphological changes of corneal nerve reflect severity of diabetic neuropathy. Early prevention and intervention can significantly reduce the morbidity, caused by ocular complications associated diabetes.
Diabetic retinopathy (DR) is the most common and specific ocular complications of DM and is the leading cause of blindness in working age population in both developed and developing countries. Early diagnosis and prompt intervention are essential to achieve good visual outcome in most patients with DR. Molecular and imaging biomarkers, artificial intelligence (AI), as well as gene and stem cell therapy are critical for early prevention and management of DR.
While DR and diabetic cataract are well-known complications of DM, diabetic ocular surface diseases, including dry eye disease (DED) are also common in the diabetic population. The reported prevalence of DED in diabetes is 15-33% and increases with age and is 50% more common in women than in men. Lacrimal Functional Unit dysfunction, abnormal tear dynamics, diabetic neuropathy and film dysfunction have been implicated in the pathogenesis of DED. Topical insulin has been compared with artificial tears. The results show that they are equally efficacious. Other diabetic ocular conditions include glaucoma, cataract and diabetic papillopathy.
This Research Topic aims to provide the wide spectrum and latest advancements in basic and clinical concepts to the diagnosis, progression, treatment outcomes, and the application of AI techniques in clinical research for DR and other ocular conditions associated with DM. In this Research Topic, we welcome original research and review articles to address the pathogenesis, imaging, cellular and molecular biomarkers, artificial intelligence in DR, diabetic macular edema (DME), and other diabetic ocular complications. Subtopics include, but not limited to the following:
• The epidemiology of diabetic retinopathy
• Application of AI techniques, such as machine learning and deep learning, in automated screening/diagnosis/prognosis prediction of DR and DME
• Novel diagnostic tools for early diagnosis and its consequences of the diabetic ocular complications: biomarkers and imaging
• Prognostic models for diabetic retinopathy.
• Current prevention and treatment options for DR and other ocular complications of DM.
• Novel therapeutic approaches for the diabetic ocular complications: gene therapy, exosomes, miRNA, incretins, bioengineering approaches, etc
• Tackling DR as a global health issue.
