Age-related macular degeneration (AMD): More than meets the eye. The role of multimodal imaging in today's management of AMD-A review

Multimodal imaging (MMI) allows a more granular grading of age-related macular degeneration (AMD) disease severity, with many novel risk factors having been recently identified. With this imaging information, we are better able to counsel our patients with more accurate and individualized progression scenarios. MMI also allows identification of anatomical features that increase our understanding of disease processes involved in progression to late AMD. Treatment protocols for neovascular AMD (nAMD) depend largely on the optical coherence tomography (OCT) appearance to determine disease activity, which allows us to individualize treatment. In geographic atrophy (GA), new intervention trials require the ability to define the extent of GA, so that GA growth rate can be determined. This is achieved through fundus autofluorescence (FAF) imaging, which allows greater accuracy of border identification, as well as revealing FAF patterns predictive of growth rates. As we strive to bring interventions earlier in the disease course, OCT imaging provides an ability to identify the first signs of atrophy, which may serve as novel surrogate biomarkers for GA, thereby facilitating trials. In the future, the use of artificial intelligence (AI) to automatically identify relevant features on MMI could further enhance our ability to determine disease severity, predict progression and assist in identifying disease activity parameters to support clinical decision making when treating nAMD. Newer developments may allow frequent, remote capturing of images, reducing clinic visits, detecting progression and monitoring neovascular activity in-between clinic visits. Being aware of these new imaging insights in AMD, greatly enhance our clinical management of AMD.