Quantitative assessment of retinal fluid in neovascular age-related macular degeneration under anti-VEGF therapy

Abstract

The retinal world has been revolutionized by optical coherence tomography (OCT) and anti-vascular endothelial growth factor (VEGF) therapy. The numbers of intravitreal injections are on a constant rise and management in neovascular age-related macular degeneration (nAMD) is mainly driven by the qualitative assessment of macular fluid as detected on OCT scans. The presence of macular fluid, particularly subretinal fluid (SRF) and intraretinal fluid (IRF), has been used to trigger re-treatments in clinical trials and the real world. However, large discrepancies can be found between the evaluations of different readers or experts and especially small amounts of macular fluid might be missed during this process. Pixel-wise detection of macular fluid uses an entire OCT volume to calculate exact volumes of retinal fluid. While manual annotations of such pixel-wise fluid detection are unfeasible in a clinical setting, artificial intelligence (AI) is able to overcome this hurdle by providing real-time results of macular fluid in different retinal compartments. Quantitative fluid assessments have been used for various post hoc analyses of randomized controlled trials, providing novel insights into anti-VEGF treatment regimens. Nonetheless, the application of AI-algorithms in a prospective patient care setting is still limited. In this review, we discuss the use of quantitative fluid assessment in nAMD during anti-VEGF therapy and provide an outlook to novel forms of patient care with the support of AI quantifications.

Functional and anatomical outcomes of brolucizumab for nAMD in a real-life setting

“…Toto et al 18 showed a reduction in IRF and subfoveal-SRF rates in type 1 MNV between baseline and week 12, respectively changing from 41.7 to 20.8% and from 62.5 to 4.2%. The greater amount of unresponsive fluid in the intraretinal compartment may represent a biomarker of degenerative cystoid processes 23 .…”

Progress in clinical research and applications of retinal vessel quantification technology based on fundus imaging

“…Quantitative analysis of retinal effusion secondary to retinal angiopathy facilitates evaluating disease progression and treatment responses in patients with retinal effusion like RVO, wAMD, and diabetes macular edema ( Farinha et al, 2020 ; Schmidt-Erfurth et al, 2020 ; Fuchs et al, 2022 ; Michl et al, 2022 ; Muste et al, 2022 ; Reiter and Schmidt-Erfurth, 2022 ; Coulibaly et al, 2023 ). Wu et al, 2021 proposed a new optimized segmentation and quantification algorithm for neovascularization based on OCTA, which has higher accuracy and effectively monitors changes in neovascularization.…”

Deep-Learning-Based Visualization and Volumetric Analysis of Fluid Regions in Optical Coherence Tomography Scans

“…Intraretinal Fluid (IRF), Subretinal Fluid (SRF), and Pigmented Epithelial Detachment (PED) are three of the most prevalent retinal pathologies [ 1 , 2 , 3 ]. Quantitative measures of retinal fluids are important biomarkers, and fluid volume computation from optical coherence tomography (OCT) scans by artificial intelligence (AI) algorithms can guide the treatment of exudative retinal conditions, such as Neovascular Age-related Macular Degeneration (NAMD).…”