Fig 1.
Segmentation of en face OCTA’s superficial vascular plexus (SVP), intermediate capillary plexus (ICP), deep capillary plexus (DCP) in correlation to structure OCT layers’ ganglion cell layer (GCL), inner plexiform layer (IPL) and inner nuclear layer (INL) and outer plexiform layer (OPL).
Fig 2.
Analysis of covariance for BMO-MRW (a), RNFL (inner, b; middle, c; outer, d), and GCL (e) considering age and patients’ groups.
(a) a significant age effect on BMO-MRW was observed (p = 0.047); (b-d) age showed an impact on RFNL for the inner and middle scan; gender was significantly associated with RNFL of the outer scan; (e) a significant decrease of RGC was observed with increasing age for male and female persons (p = 0.0021).
Table 1.
Mean (a) and sectorial (1–12, b) vessel density in SVP, ICP, and DCP for controls, patients with OHT and pre-OAG.
Table 2.
Type III tests of fixed effects for SVP (a), ICP (b), and DCP (c): Diagnosis, OCT-A sector, age and the interaction diagnosis with sector is presented.
Fig 3.
Qualitative analysis of the number of significant interactions between vessel density of each sector (s1-s12) of macula OCT-A in SVP, ICP, and DCP by color coding (red, n = 8–12; pink, n = 6–7; orange, n = 5; yellow, n = 4; green, n = 2–3; grey, n = 0–1) in controls, OHT, and pre-OAG eyes, respectively (a) and between the groups (b) with age correction of the data: Notice the temporal emphasis in SVP and the nasal emphasis in DCP.
Fig 4.
Analysis of covariance for FAZ of ICP across age subdivided for gender and diagnosis (OHT, pre-OAG, controls).
Fig 5.
Receiver operating curves (ROC) of mean (a) and sectorial (b-d) vessel density in SVP, ICP, and DCP for differentiation between patients’ group and controls.
Table 3.
Area under the curve (AUC) for sectorial macula VD in SVP, ICP, and DCP (a) and glaucoma morphometric parameters (BMO-MRW, RNF (inner, middle, outer ring), GCL, INL, (b).