Prognostic Value of Morphometric Parameters in the Evaluation of Neovascular Age-related Macular Degeneration Using Spectral Domain Optical Coherence Tomography

Abstract

Purpose: : Treatment of neovascular age-related macular degeneration (nAMD) with anti-angiogenic substances requires precise and non-invasive imaging techniques to optimize therapeutical efforts in highly efficient but cost intensive treatment regimen. This study has the aim to evaluate the prognostic value of different morphologic parameters in the initial treatment phase with ranibizumab.

Methods: : 20 consecutive patients with nAMD were treated with three monthly doses of ranibizumab (Novartis) and scanned with time and spectral domain optical coherence tomography (OCT). Stratus and Cirrus (both: Carl Zeiss Meditec) OCT systems were used to image patients. Best-corrected visual acuity (BCVA) was assessed monthly and correlated to different morphologic parameters at baseline to identify factors with prognostic relevance.

Results: : Retinal volume (RV) and retinal thickness (RT) correlated with BCVA at the time of examination (p<0.03) and enabled for precise documentation of therapeutic approaches. However, RV and RT at baseline did not show a correlation to BCVA in the follow-up phase, whereas the volume and central height of the neurosensory detachment due to subretinal fluid (SRF) correlated to BCVA during the first three months (p<0.01). Patients with higher values of SRF volume were more likely to gain more BCVA in the initial treatment phase (p<0.03).

Conclusions: : The results of this study show, that modern OCT imaging systems are capable to provide functionally relevant data to document the current retinal situation at the time of assessment. Nevertheless, it is noteworthy that the current analysis implemented in the standard OCT software showed a limited predictive value, whereas other parameters like the volume of SRF demonstrated significant prognostic potential.

Keywords: retina • age-related macular degeneration • imaging/image analysis: clinical