Diabetic macular edema (DME), defined as retinal thickening near, or involving the fovea caused by fluid accumulation in the retina, can lead to vision impairment and blindness in patients with diabetes. Current knowledge of retina anatomy and function and DME pathophysiology has taken great advantage of the availability of several techniques for visualizing the retina. Combining these techniques in a multimodal imaging approach to DME is recommended to improve diagnosis and to guide treatment decisions. We review the recent literature about the following retinal imaging technologies: optical coherence tomography (OCT), OCT angiography (OCTA), wide-field and ultrawide-field techniques applied to fundus photography, fluorescein angiography, and OCTA. The emphasis will be on characteristic DME features identified by these imaging technologies and their potential or established role as diagnostic, prognostic, or predictive biomarkers. The role of artificial intelligence in the assessment and interpretation of retina images is also discussed.
Multimodal imaging in diabetic retinopathy and macular edema: An update about biomarkers
Grassi, Maria Oliva;
2024-01-01
Abstract
Diabetic macular edema (DME), defined as retinal thickening near, or involving the fovea caused by fluid accumulation in the retina, can lead to vision impairment and blindness in patients with diabetes. Current knowledge of retina anatomy and function and DME pathophysiology has taken great advantage of the availability of several techniques for visualizing the retina. Combining these techniques in a multimodal imaging approach to DME is recommended to improve diagnosis and to guide treatment decisions. We review the recent literature about the following retinal imaging technologies: optical coherence tomography (OCT), OCT angiography (OCTA), wide-field and ultrawide-field techniques applied to fundus photography, fluorescein angiography, and OCTA. The emphasis will be on characteristic DME features identified by these imaging technologies and their potential or established role as diagnostic, prognostic, or predictive biomarkers. The role of artificial intelligence in the assessment and interpretation of retina images is also discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.