Abstract
Purpose :
To describe the vascular abnormalities in Best vitelliform macular dystrophy (BVMD) in patients using optical coherence tomography angiography (OCTA) .
Methods :
Twenty-two eyes of 11 consecutive patients with a clinical and genetic diagnosis of BVMD were enrolled. Thirteen healthy and age-matched patients was used as a control group. Clinical and conventional multimodal imaging data including fundus photography, fundus autofluorescence imaging, optical coherence tomography (OCT) and fluorescein angiography (FA) were collected for diagnosis and evaluate the presence of choroidal neovascularization (CNV). The BVMD patients were categorized into stages 1 to 5 and received OCTA examinations. The vascular morphology was assessed in different layers, and quantitative analysis was performed mainly focusing on superficial vascular (SV) network (fovea avascular zone, FAZ and flow density) and choriocapillary flow area (CFA) on both BVMD patients and controls. Moreover, we divided the BVMD patients into vitelliform group (VG, Stage 1-4) and post-vitelliform group (P-VG, Stage 5)and flow density in SV was compared between VG, P-VG and the controls. Finally, correlation analysis was done with SV density, FAZ, CFA and vision.
Results :
The mean age of the BVMD patients was 39.7 years (9-57 years old), and mean BCVA was 0.7±0.3logMar. Macular lesions in OCTA led to a loop-like capillary reconstruction and appearance of nonperfusion areas around the FAZ. Hyperintense signals of the subfoveal area were also shown in several patterns. The flow density of both SV and CFA showed a statistically significant reduction when comparing the patients with the controls. The SV density in P-VG patients was consistently lower than that of VG. Indexes in CFA and SV (FAZ and SV density) are found to be correlated.
Conclusions :
The vascular changes in BVMD were not only displayed in the choroid but also in the superficial retina. Quantifiable OCTA may represent a useful biomarker in monitoring the progression of BVMD.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.