Introduction: This study aims to investigate the changes of retinal vascular system in primary angle closure glaucoma (PACG) and acute primary angle closure (APAC) by optical coherence tomography (OCT) angiograph (OCTA) and to evaluate the diagnostic ability of changes of vessel density (VD) in different sectors and layers of optic disc and macular area in APAC and PACG. Methods: In this cross-sectional, observational study, 21 APAC patients (22 eyes) and 21 PACG patients (27 eyes) along with 17 healthy people were enrolled from August 2018 to March 2019. Optic disc region and macular region were imaged using swept-source OCTA system. VD of the macular region was quantified by Image J (1.52a, USA) and Matlab 2018a. The circumpapillary retinal nerve fiber layer (cpRNFL) thickness and ganglion cell complex thickness were obtained by spectral-domain OCT. Results: Compared with the healthy group, the cpRNFL thickness in superior sector was thicker in the APAC group, and this area had the most diffuse microvascular dropout as well. The difference in the macular superficial capillary plexus (SCP) VD between APAC and the control group was not statistically significant. The area under the ROC curves (AUC) of the total optic disc VD in the radial peripapillary capillary (RPC) layer was higher than the AUC of the papillary VD in the optic nerve head (ONH) layer. Compared to the control group, the total optic disc VD, peripapillary VD, and each quadrant of peripapillary VD were decreased in PACG (p < 0.01). In PACG macular region, SCP VD, and deep capillary plexus (DCP) VD, parafovea VD (except temporal sectors) decreased (p < 0.01). The PACG eyes had a greater decrease percentage of VD in total ONH than total macula. The diagnostic value of the VD in the ONH layer and the RPC layer was similar. The diagnostic value of the SCP VD in the macula was greater than the DCP VD in the macula. The AUC was no significant difference between cpRNFL thickness and the total optic disc VD AUC. Conclusion: Elevated intraocular pressure preferentially affects vascular perfusion in the optic disc region more than the macular region in APAC and PACG. In the APAC eyes, there was a perfusion defect in the optic disc region and an increase in RNFL thickness. In this study, the OCTA vascular parameters have similar performance to the OCT structural parameters for glaucoma diagnosis in PACG.

Glaucoma is still an important cause of irreversible blindness worldwide [1]. Compared with primary open-angle glaucoma (POAG), primary angle closure glaucoma (PACG) has a higher risk of binocular visual impairment [2]. Therefore, the research on PACG is of great value. Although the pathogenesis of glaucoma is not fully understood, there has been an increase in interest in the vascular components of glaucoma in recent years. Optical coherence tomography angiography (OCTA) is a novel and noninvasive blood flow imaging technique, which can not only provide structure information but also quantitatively measure the retina and choroid perfusion [3]. Previous studies have found that papillary perfusion may be one of the causes of pathology in POAG. Most studies have shown that papillary and macular perfusions in POAG were defective compared with normal subjects. It was reported that the diagnostic abilities of OCTA parameters increased along with glaucoma progression [4, 5]. Radial peripapillary capillaries (RPCs) are unique capillary plexus located on the posterior pole. Histological studies [6] have shown that RPC plays an important role in glaucoma pathogenesis. There is a lack of studies evaluating the role of RPC in the PACG by OCTA. Compared with POAG, PACG is considered to be a more purely intraocular pressure (IOP)-dependent disease, which provides a better model for the study of retinal vascular and structural damage caused by IOP [7]. However, few research focus on vessel parameters of OCTA in eyes with PACG. This study aimed to investigate the changes in the retinal vascular system between acute primary angle closure (APAC) and PACG, to evaluate the diagnostic ability of the papillary and macular vessel density (VD) in different sectors and layers on OCTA in PACG and APAC, and to compare these with peripapillary RNFL thickness and ganglion cell complex (GCC) thickness measured by spectral-domain OCT.

Experimental Design

This was a cross-sectional study. The study was approved by the Ethics Committee of Joint Shantou International Eye Center (JSIEC) of Shantou University and the Chinese University of Hong Kong (Shantou City, China) and was conducted in accordance with Good Clinical Practice within the tenets of the Declaration of Helsinki. Each subject was required to sign an informed consent form before being enrolled in the study and prior to any measurements being taken.

Study Subjects

22 eyes of 21 subjects with APAC, 27 eyes of 21 subjects with PACG, and 17 eyes of age-matched normal subjects were included in this study. These subjects were enrolled from Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong from August 2018 to March 2019.

APAC [8] was diagnosed on the basis of characteristic changes as follows: (1) acute elevated IOP (almost higher than 30 mm Hg), with two or more symptoms including nausea, vomiting, vision loss, eye pain, headache, rainbow around a light, (2) typical signs by slit-lamp examination including shallow anterior chamber, ciliary congestion, corneal epithelial edema, dilated pupil, (3) closed angles more than three quadrants by gonioscopy in the primary position, and (4) similar anatomical structure in the fellow eye. PACG [9] was diagnosed on the basis of characteristic anatomical structure and optic nerve damage of the structure and function. These characteristic changes included shallow anterior chamber, elevated IOP, iridotrabecular contact in three or more quadrants by gonioscopy, glaucomatous optic neuropathy (glaucomatous optic disc cupping, peripapillary atrophy, edge-shaped defects of RNFL adjacent to the edge of optic disc, and hemorrhages on the optic disc boundary), and glaucomatous visual field (VF) defects.

Healthy subjects as control group were enrolled on the basis as follows: IOP <21 mm Hg, normal anterior chamber, normal VF, and no family history of glaucoma. The exclusion criteria included the following: history of trauma or inflammatory eye diseases (such as uveitis), history of any intraocular surgery, and retinopathy.

All subjects underwent a detailed medical history, best-corrected visual acuity, IOP measurement by Goldmann tonometry, slit-lamp bio-microscopy, VF examination. Vessel parameters and structural measurement parameters of all subjects were performed by Swept Source DRI OCT Triton (Topcon Corporation, Japan); all APAC eyes were performed within 6 weeks.

Optical Coherence Tomography Imaging

Peripapillary RNFL thickness measurements and macular were performed with Swept Source DRI OCT Triton (Topcon Corporation, Japan), RNFL and GCC thicknesses were calculated by the manufacturer’s released software. Peripapillary RNFL was equally divided into 4 equal sectors: superior, temporal, nasal, and Inferior. GCC thickness was measured from the outer boundary of the RNFL and the outer boundary of the inner plexiform layer (IPL) [10]. Images quality were checked and filtered after each scan. Images with significant motion artifacts, or poor image clarity were excluded.

OCTA Examination and Image Processing

OCTA imaging was performed using Swept Source DRI OCT Triton (Topcon Corporation, Japan) without pupillary dilatation. This instrument scans the optic disc and macula using a 1,050 nm laser source, with an A-scan rate of 100,000 scans per second. OCTA images were analyzed using the Topcon full-spectrum amplitude decorrelation angiography algorithm. Scan range of optic disc image is 4.5 × 4.5 mm, macula image scan covering 6 × 6 mm [11]. Images with a signal strength index < 40, with residual motion artifacts were excluded for the analysis. Macular retinal scans were automated segment into the superficial capillary plexus (SCP) and deep capillary plexus (DCP) by built-in software (ImageNet V 0.6). Automated segmentation of optic disc scans into optic nerve head (ONH) microvascular plexuses and RPC. SCP was defined as extending from the inner boundary of internal limiting membrane (ILM) to the outer boundary of IPL. DCP was defined as extending from the outer boundary of IPL to the outer boundary of outer plexiform layer. The ONH layer was set from the inner surface ILM to 130 μm below the ILM. The RPC layer was set from the inner surface ILM to 70.2 μm below the ILM.

The ONH and RPC image were transferred to a computer for analysis by Image J (1.52a, USA). The original OCTA en face image was transferred from 8-bit into RGB first. Then the image was divided into three channels (red, green, and blue). Red channel image was chosen as the reference. The set of the adjust threshold tool was default, the dark-background option was selected, then greyscale image was transformed into binarized image (Fig. 1c). The white areas represent vessels; the dark areas represent background [12]. VD was measured using the following formula:

Fig. 1.

The process of calculating the VD of the optic disc area. a The original OCTA en face image of the ONH layer in the normal eye. b The peripapillary area diagram. c Binarized image. d The peripapillary area. e Superior, temporal, Nasal, Inferior sector of the peripapillary area.

Fig. 1.

The process of calculating the VD of the optic disc area. a The original OCTA en face image of the ONH layer in the normal eye. b The peripapillary area diagram. c Binarized image. d The peripapillary area. e Superior, temporal, Nasal, Inferior sector of the peripapillary area.

Close modal

Vesseldensity=pixelareasofvessels/pixelareasoftotalarea

MATLAB (MathWorks version R 2018a) was used for calculating VD via the following procedures: (1) Getting a binarized image mask which has the same size pixels compared to the binarized image processed by Image J, the outer diameter of annulus was 3.45 mm around ONH, the inner circle was chosen to be at 1.95 mm annulus diameter around ONH, the 0.50 mm-wide annulus was defined as the peripapillary area; (2) multiplying this mask with the binarized image (Fig. 1d); (3) the peripapillary region was equally divided into 4 equal sectors, which were designated as superior, temporal, nasal, and inferior (Fig. 1e); and (4) calculating the VD of every sector.

For macular OCTA images (Fig. 2a), it was inverted into binarized image(Fig. 2b) by Image J. (1) Use Gaussians filter reduce noise, (2) FAZ area was restored and colored to pure white by function fsrRegiongrow (Fig. 2c). (3) The macular VD was calculated as: VD = pixel areas of vessels/(pixel areas of total area-pixel areas of FAZ) [10].

Fig. 2.

The process of calculating the VD of the macular area. a The original OCTA en face image of the macular superficial layer in the normal eye. b Binarized image. c The white area represents the FAZ area. d The parafoveal area is defined as an annulus centered on the macular fovea which the outer diameter is 3 mm and the inner diameter is 1 mm. VD is automatically calculated by software.

Fig. 2.

The process of calculating the VD of the macular area. a The original OCTA en face image of the macular superficial layer in the normal eye. b Binarized image. c The white area represents the FAZ area. d The parafoveal area is defined as an annulus centered on the macular fovea which the outer diameter is 3 mm and the inner diameter is 1 mm. VD is automatically calculated by software.

Close modal

The parafoveal area was defined as an annulus centered on the macular fovea which the outer diameter is 3 mm and the inner diameter is 1 mm. The parafovea area was equally divided into 4 equal sectors, automate calculate VD by a built-in software (Fig. 2d).

Statistical Analysis

22 eyes of 21 subjects with APAC, 27 eyes of 21 subjects with PACG and 17 eyes of age-matched normal subjects were included in this study. We used SPSS (version 16.0; SPSS Inc, Chicago, IL, USA) and MedCalc (version 18.2.1; SAS Institute Inc., Cary, NC, USA) for all statistical analysis. p value of <0.05 was considered to be of statistical significance.

All variables were tested using the Kolmogorov-Smirnov test to confirm normal distribution. Continuous variables followed normal distribution was presented as means standard deviation. Analysis of variance (ANOVA) was used to evaluate differences among the controls, APAC, and PACG groups; post-analysis Bonferroni test was used to compare the difference among groups. Variables unfollowed normal distribution were presented as median [25, 75 percentiles]. Kruskal-Wallis ANOVA test was used to evaluate differences among the groups. χ2 test was used to evaluate the difference among groups by age and sex distributions, proportion of hypertension, and diabetes.

Receiver operating characteristic (ROC) curves were plotted to calculate the area under the ROC curves (AUCs) and describe the ability of OCTA and retinal structure parameters to discriminate APAC eyes and PACG eyes from healthy eyes.

Table 1 shows the demographic and clinical characteristics of all subjects. Mean age was there was no significant difference in age (p = 0.200), sex (p = 0.259), proportion of hypertension (p = 0.485), and diabetes (p = 0.284) among the three groups. IOP was similar in APAC subjects and the control subjects (p = 0.575). There was no significant difference between the PACG subject and the control subject (p = 0.155), but the APAC group had lower IOP than PACG group (p = 0.003). The APAC group had thicker circumpapillary retinal nerve fiber layer (cpRNFL) (p = 0.012), superior sector of cpRNFL (p = 0.018) than the control group. But GCC thickness and nasal, inferior, temporal sector of cpRNFL thickness were similar in the control group and APAC group. Compared with the control group, the APAC group had lower VD in total ONH, peripapillary areas ONH, superior, inferior sector of peripapillary areas ONH, total RPC, peripapillary areas RPC, superior, inferior sector of peripapillary areas RPC, but there was no significant difference between the APAC group and the control group in macular areas (p > 0.05), nasal, temporal sector of peripapillary RPC VD and ONH VD (p > 0.05). The PACG group had thinner cpRNFL thickness and GCC thickness than the control group. Compared with the control group, the PACG group had significantly lower vascular perfusion than the control group in every sector of the optic disc area and macular area (except the nasal sector of parafoveal, p = 0.825). The PACG eye had a greater decrease percentage of VD in total ONH (13.85%) than total macula (6.49%) (p < 0.050).

Table 1.

Comparison of clinical and ocular parameters of eyes among control, APAC, and PACG groups

Control groupAPAC groupPACG groupp valuep value1p value2p value3
Age, years 64±6.06 60±6.16 63±8.35 0.200    
Gender (male: female) 7:10 5:16 10:11 0.259    
IOP, mm Hg 14.50 (12.00, 18.00) 11.00 (8.00, 21.00) 17.00 (15.00, 26.00) 0.004 0.575 0.155 0.003 
BCVA (LogMAR) 0.15±0.12 0.36±0.20 0.26±0.21 0.001 0.001 0.128 0.161 
Hypertension (yes:no) 4:13 3:18 2:19 0.485    
Diabetes mellitus (yes:no) 0:17 3:18 2:19 0.284    
OCT parameters, μm 
 cpRNFL thickness 112±8.53 130±30.09 60±14.95 <0.001 0.012 <0.001 <0.001 
 Superior sector 143±14.98 167±42.00 68±22.44 <0.001 0.018 <0.001 <0.001 
 Inferior sector 143±13.05 156±56.13 64±20.21 <0.001 0.682 <0.001 <0.001 
 Nasal sector 80±12.07 99±29.80 54±16.86 <0.001 0.420 <0.001 <0.001 
 Temporal sector 83±13.55 90±15.00 55±16.41 <0.001 0.137 <0.001 <0.001 
GCC thickness 102±7.03 99±9.66 73±12.05 <0.001 0.517 <0.001 <0.001 
ONH OCTA parameter, % 
 Total area 34.39±2.94 30.23±4.40 20.54±3.14 <0.001 0.001 <0.001 <0.001 
 Peripapillary VD 42.44±4.84 34.74±4.64 24.34±5.35 <0.001 <0.001 <0.001 <0.001 
  Superior sector 55.03±7.86 42.12±7.98 30.95±7.17 <0.001 0.007 <0.001 0.003 
  Inferior sector 49.37±7.16 38.03±6.98 30.68±6.66 <0.001 0.004 <0.001 0.016 
  Nasal sector 27.02±8.41 25.93±8.91 17.32±5.20 <0.001 1.000 <0.001 <0.001 
  Temporal sector 38.34±11.92 32.87±8.52 18.40±7.04 <0.001 0.160 <0.001 <0.001 
RPC OCTA parameter, % 
 Total area 37.74±2.13 33.37±3.53 24.32±4.98 <0.001 <0.001 <0.001 <0.001 
 Peripapillary VD 41.48±5.78 33.51±4.42 26.94±6.20 <0.001 0.004 <0.001 0.011 
  Superior sector 46.98±5.94 37.02±8.33 32.33±7.39 <0.001 <0.001 <0.001 0.085 
  Inferior sector 41.61±6.42 33.25±6.78 32.01±5.71 <0.001 <0.001 <0.001 1.000 
  Nasal sector 33.8±12.02 30.43±7.88 21.79±7.09 <0.001 0.604 0.001 0.001 
  Temporal sector 40.54±8.30 33.36±8.04 21.29±8.50 <0.001 0.127 <0.001 0.001 
Macular SCP VD, % 
 Total area 28.86±3.13 28.37±3.18 22.37±3.25 <0.001 1.000 <0.001 <0.001 
 Parafovea VD 47.41±1.50 46.88±2.29 44.75±2.86 <0.001 1.000 0.001 0.007 
  Superior sector 48.78±2.43 48.64±3.08 45.67±2.74 <0.001 1.000 0.001 0.001 
  Inferior sector 48.63±1.97 46.15±4.35 44.33±3.79 <0.001 0.078 <0.001 0.303 
  Nasal sector 45.25±2.07 45.30±2.84 45.53±2.24 0.825    
  Temporal sector 46.96±2.17 47.41±2.66 43.46±6.52 0.004 1.000 0.024 0.009 
Macular DCP VD, % 32.37±2.11  30.67±2.17 0.008    
Control groupAPAC groupPACG groupp valuep value1p value2p value3
Age, years 64±6.06 60±6.16 63±8.35 0.200    
Gender (male: female) 7:10 5:16 10:11 0.259    
IOP, mm Hg 14.50 (12.00, 18.00) 11.00 (8.00, 21.00) 17.00 (15.00, 26.00) 0.004 0.575 0.155 0.003 
BCVA (LogMAR) 0.15±0.12 0.36±0.20 0.26±0.21 0.001 0.001 0.128 0.161 
Hypertension (yes:no) 4:13 3:18 2:19 0.485    
Diabetes mellitus (yes:no) 0:17 3:18 2:19 0.284    
OCT parameters, μm 
 cpRNFL thickness 112±8.53 130±30.09 60±14.95 <0.001 0.012 <0.001 <0.001 
 Superior sector 143±14.98 167±42.00 68±22.44 <0.001 0.018 <0.001 <0.001 
 Inferior sector 143±13.05 156±56.13 64±20.21 <0.001 0.682 <0.001 <0.001 
 Nasal sector 80±12.07 99±29.80 54±16.86 <0.001 0.420 <0.001 <0.001 
 Temporal sector 83±13.55 90±15.00 55±16.41 <0.001 0.137 <0.001 <0.001 
GCC thickness 102±7.03 99±9.66 73±12.05 <0.001 0.517 <0.001 <0.001 
ONH OCTA parameter, % 
 Total area 34.39±2.94 30.23±4.40 20.54±3.14 <0.001 0.001 <0.001 <0.001 
 Peripapillary VD 42.44±4.84 34.74±4.64 24.34±5.35 <0.001 <0.001 <0.001 <0.001 
  Superior sector 55.03±7.86 42.12±7.98 30.95±7.17 <0.001 0.007 <0.001 0.003 
  Inferior sector 49.37±7.16 38.03±6.98 30.68±6.66 <0.001 0.004 <0.001 0.016 
  Nasal sector 27.02±8.41 25.93±8.91 17.32±5.20 <0.001 1.000 <0.001 <0.001 
  Temporal sector 38.34±11.92 32.87±8.52 18.40±7.04 <0.001 0.160 <0.001 <0.001 
RPC OCTA parameter, % 
 Total area 37.74±2.13 33.37±3.53 24.32±4.98 <0.001 <0.001 <0.001 <0.001 
 Peripapillary VD 41.48±5.78 33.51±4.42 26.94±6.20 <0.001 0.004 <0.001 0.011 
  Superior sector 46.98±5.94 37.02±8.33 32.33±7.39 <0.001 <0.001 <0.001 0.085 
  Inferior sector 41.61±6.42 33.25±6.78 32.01±5.71 <0.001 <0.001 <0.001 1.000 
  Nasal sector 33.8±12.02 30.43±7.88 21.79±7.09 <0.001 0.604 0.001 0.001 
  Temporal sector 40.54±8.30 33.36±8.04 21.29±8.50 <0.001 0.127 <0.001 0.001 
Macular SCP VD, % 
 Total area 28.86±3.13 28.37±3.18 22.37±3.25 <0.001 1.000 <0.001 <0.001 
 Parafovea VD 47.41±1.50 46.88±2.29 44.75±2.86 <0.001 1.000 0.001 0.007 
  Superior sector 48.78±2.43 48.64±3.08 45.67±2.74 <0.001 1.000 0.001 0.001 
  Inferior sector 48.63±1.97 46.15±4.35 44.33±3.79 <0.001 0.078 <0.001 0.303 
  Nasal sector 45.25±2.07 45.30±2.84 45.53±2.24 0.825    
  Temporal sector 46.96±2.17 47.41±2.66 43.46±6.52 0.004 1.000 0.024 0.009 
Macular DCP VD, % 32.37±2.11  30.67±2.17 0.008    

APAC, acute primary angle closure; PACG, primary angle closure glaucoma; IOP, intraocular pressure; OCT, optical coherence tomography; cpRNFL, circumpapillary retinal nerve fiber layer; GCC, ganglion cell complex; ONH, optic nerve head; OCTA, optical coherence tomography angiography; VD, vessel density; SCP, superficial capillary plexus; DCP, deep capillary plexus; BCVA, best-corrected visual acuity.

p value <0.05 was of statistical significance.

1p value: comparisons between control and APAC group.

2p value: comparisons between control and PACG group.

3p value: comparisons between APAC and PACG groups.

In the APAC eyes, Table 2 showed the AUC and sensitivity of VD parameters at a fixed specificity. There was no significant difference in the AUC between RPC and ONH VD in peripapillary area. But RPC had a higher AUC (0.845) than ONH AUC (0.761) in the total optic area (p = 0.039). In PACG, it had similar AUC in the total optic area and every sector of peripapillary area of ONH and RPC (p > 0.05) (Table 3). Compared with the healthy group, there was no significant difference in AUC in the total optic area (0.998) and cpRNFL thickness (0.998). It also had similar AUC in the superficial macular area (0.796) and GCC thickness (0.977), but the superficial layer had the greater AUC (0.912) than the deep layer AUC (0.714), p = 0.01.

Table 2.

Area under ROC curve (AUC) for the OCTA parameters in optic disc area of APAC eye

VariablesAUCStandard error95% CIp value
ONH OCTA parameter, % 
 Total area 0.761 0.074 0.609–0.877 <0.001 
 Peripapillary VD 0.880 0.054 0.747–0.958 <0.001 
  Superior sector 0.890 0.054 0.785–0.996 <0.001 
  Inferior sector 0.872 0.058 0.737–0.953 <0.001 
RPC OCTA parameter, % 
 Total area 0.845 0.065 0.718–0.972 <0.001 
 Peripapillary VD 0.879 0.055 0.745–0.958 <0.001 
  Superior sector 0.841 0.061 0.699–0.934 <0.001 
  Inferior sector 0.824 0.064 0.680–0.922 <0.001 
VariablesAUCStandard error95% CIp value
ONH OCTA parameter, % 
 Total area 0.761 0.074 0.609–0.877 <0.001 
 Peripapillary VD 0.880 0.054 0.747–0.958 <0.001 
  Superior sector 0.890 0.054 0.785–0.996 <0.001 
  Inferior sector 0.872 0.058 0.737–0.953 <0.001 
RPC OCTA parameter, % 
 Total area 0.845 0.065 0.718–0.972 <0.001 
 Peripapillary VD 0.879 0.055 0.745–0.958 <0.001 
  Superior sector 0.841 0.061 0.699–0.934 <0.001 
  Inferior sector 0.824 0.064 0.680–0.922 <0.001 

APAC, acute primary angle closure; OCTA, optical coherence tomography angiography; VD, vessel density; RPC, radial peripapillary capillary; GCC, ganglion cell complex.

p value <0.05 was of statistical significance.

Table 3.

Area under ROC curve (AUC) for the OCTA parameters of PACG eye

VariablesAUCStandard error95% CIp value
ONH OCTA parameter, % 
 Total area 0.998 0.002 0.924–1.0 <0.001 
 Peripapillary VD 0.973 0.024 0.881–0.999 <0.001 
  Superior sector 0.944 0.039 0.839–0.990 <0.001 
  Inferior sector 0.941 0.035 0.835–0.988 <0.001 
  Nasal sector 0.843 0.058 0.711–0.931 <0.001 
  Temporal sector 0.938 0.033 0.830–0.987 <0.001 
RPC OCTA parameter, % 
 Total area 0.968 0.032 0.873–0.997 <0.001 
 Peripapillary VD 0.949 0.035 0.846–0.992 <0.001 
  Superior sector 0.934 0.036 0.825–0.985 <0.001 
  Inferior sector 0.880 0.056 0.756–0.956 <0.001 
  Nasal sector 0.803 0.064 0.665–0.903 <0.001 
  Temporal sector 0.92 0.040 0.816–0.982 <0.001 
Macular SCP VD, % 0.912 0.0400 0.796–0.974 <0.001 
Macular DCP VD, % 0.714 0.0754 0.567–0.834 <0.001 
cpRNFL thickness, μm 0.998 0.002 0.924–1.0 <0.001 
GCC thickness, μm 0.977 0.017 0.888–0.999 <0.001 
VariablesAUCStandard error95% CIp value
ONH OCTA parameter, % 
 Total area 0.998 0.002 0.924–1.0 <0.001 
 Peripapillary VD 0.973 0.024 0.881–0.999 <0.001 
  Superior sector 0.944 0.039 0.839–0.990 <0.001 
  Inferior sector 0.941 0.035 0.835–0.988 <0.001 
  Nasal sector 0.843 0.058 0.711–0.931 <0.001 
  Temporal sector 0.938 0.033 0.830–0.987 <0.001 
RPC OCTA parameter, % 
 Total area 0.968 0.032 0.873–0.997 <0.001 
 Peripapillary VD 0.949 0.035 0.846–0.992 <0.001 
  Superior sector 0.934 0.036 0.825–0.985 <0.001 
  Inferior sector 0.880 0.056 0.756–0.956 <0.001 
  Nasal sector 0.803 0.064 0.665–0.903 <0.001 
  Temporal sector 0.92 0.040 0.816–0.982 <0.001 
Macular SCP VD, % 0.912 0.0400 0.796–0.974 <0.001 
Macular DCP VD, % 0.714 0.0754 0.567–0.834 <0.001 
cpRNFL thickness, μm 0.998 0.002 0.924–1.0 <0.001 
GCC thickness, μm 0.977 0.017 0.888–0.999 <0.001 

PACG, primary angle closure glaucoma; ONH, optic nerve head; OCTA, optical coherence tomography angiography; VD, vessel density; SCP, superficial capillary plexus; DCP, deep capillary plexus; RPC, radial peripapillary capillary.

p value <0.05 was of statistical significance.

In this study, compared with the macular region, vascular perfusion in the optic disc region was more susceptible while IOP increased. In the APAC eye, there was a perfusion defect in the optic disc region and an increase in RNFL thickness. Meanwhile, glaucoma preferentially affected perfusion in RPC layer more than ONH layer. In PACG, glaucoma preferentially affected VD in the macular superficial layer more than deep layer and choriocapillaris. RPC and ONH papillary VD, macular superficial VD detected glaucoma with high accuracy and could be valuable in diagnose of glaucoma. And this study is the first one that focuses on RPC network in the PACG eye. The VD parameters of ONH and RPC have similar diagnosis ability as cpRNFL thickness.

OCTA is a novel and noninvasive blood flow imaging technique, which can quantitatively analyze vessel perfusion by related software [13]. In the POAG and PACG eye, many studies detected the optic disc area and macular vessel perfusion defect compared with healthy eye [4, 5]. Previously, Zhu et al. [14] found that the parafovea region VD of the well-controlled group was not significantly different from VD in not well-controlled group. But in the peripapillary region, the well-controlled group has greater vascular perfusion compared with the not-well-controlled group. Furthermore, Rao et al. [15] also found that the VD in the peripapillary region in PACG eyes decreased more than the parafovea region (14% vs. 6%). In this study, it shown that the PACG eye had a greater decrease percentage of VD in the total optic disc area of ONH layer (13.85%) than the total macula SCP (6.49%). The previous studies had similar findings. Our results shown that the APAC group had lower VD in total optic disc area of ONH and RPC layer, peripapillary areas of ONH and RPC layer compared with the healthy eye, but there was no significant difference between the APAC group and the control group in macular SCP. It was agreed that peripapillary VD had a greater ability of diagnosis compare with parafovea VD in glaucoma, and the peripapillary VD had similar diagnosis ability with cpRNFL in glaucoma. Therefore, whatever IOP increased slowly or rapidly, compared with the macular area, the optic disc area vascular perfusion was more valuable for the diagnosis of glaucoma. This phenomenon was not fully understood. The macular region and the optic disc region had different sources of vascular perfusion. Retinal artery was the only supply vessel for the macular area, the optic disc was supplied by the retinal and ciliary arteries. It was found that choroidal vascular perfusion was a more sensitive defect to high IOP, and the retinal macular network had a higher tolerance for high IOP compared with the choroidal vascular network [16]. The difference in vascular supply maybe the reason, but more evidence is still needed to explain the phenomenon.

In this study, the APAC group had thicker cpRNFL, superior sector of cpRNFL than the control group. Compared with the control group, the APAC group had lower VD in total optic disc area, peripapillary areas, superior, inferior sector of peripapillary areas in ONH and RPC layer. Wang et al. [17] observed a significant ONH vascular perfusion defect in the APAC eyes from 2 to 120 after APAC episode, even if the structure parameter were not a significant difference compared with the control group. Moghimi et al. [9] found that the ONH vascular perfusion defect over 6 weeks after the attack, they observed ONH VD decrease at 1 week after the attack, the thickness of RNFL initially increased and then subsequently decreased. These studies all showed that the ONH vascular perfusion defect happened earlier than RNFL loss [18]. In this study, we presented a similar result, but they did not investigate RPC. Previous study had shown that RPC played an important role in glaucoma pathogenesis [19]. We found that the changes in VD between ONH and RPC were no significant difference after the attack. But the AUC of the total RPC VD was higher than the AUC of the total ONH VD. It still needs more studies to find the reason.

Aghsaei et al. [20] observed that the eye with optic disc edema had decreased peripapillary vascular density around optic disc compared with the healthy eye. It is possible that the edema of the RNFL causes the blockage of the capillaries, which in turn causes ischemia. In this study, we also observed that the APAC group had thicker cpRNFL, lower VD of peripapillary in ONH and RPC compared with the healthy eye.

This study demonstrated that the PACG eye had significantly lower vascular perfusion than the control group in every sector of the optic area and macular area (except the nasal sector of parafoveal). RPC exists in the superficial layer around the optic disc and is proportional to the thickness of RNFL, RPC may be the main vascular network for nourishes RNFL [21]. Previous studies had shown that the POAG eye had RPC perfusion defect compared with the healthy eye, and there was a direct correlation between RPC perfusion and RNFL thickness [22, 23]. This study is the first one that focuses on RPC network in the PACG eye. We observed that the PACG eye optic area VD in RPC and ONH was significantly decreased compared with the healthy eye. The VD parameters of ONH and RPC have a similar diagnosis ability as cpRNFL thickness. Alnawaiseh et al. [24] demonstrated that RPC has the most significant difference between the POAG eye and the healthy eye compared with the ONH vessel parameters and macular vessel parameters, and RPC had the highest ability for discriminating between the PAOG eye and the control eye. However, there was no significant difference in diagnosis ability between the ONH vessel parameters and the RPC vessel parameters in this study. A possible reason is the distinct pathogenesis between POAG and PACG. In PACG, elevated intraocular pressure secondary to angle closure is considered the main mechanism. But in POAG, vascular perfusion abnormalities and lower systolic/diastolic blood pressure are also considered risk factors for open-angle glaucoma [25].

The total optic disc region VD (include ONH and RPC) has a similar diagnostic ability compared with the RNFL measurement in this study. Similar to our results, Rao et al. [26] detected that the OCTA VD parameters had a good diagnostic ability, there was no significant difference in diagnostic accuracy between the OCTA peripapillary VD parameters and RNFL thickness in both POAG and PACG.

In this study, the diagnostic accuracy of macular superficial VD was higher than the macular DCP VD, and total macular SCP VD has similar diagnostic accuracy as GCC thickness. Hana et al. [27] demonstrated that the macular SCP VD had higher diagnostic accuracy than the macular DCP VD in POAG. These findings indicated that the superficial perfusion in the macula had a more severe defect than the deeper vascular network in glaucomatous eye.

There are some limitations in this study. First of all, due to the cross-sectional design, we could not evaluate the value of retina vascular perfusion measurements in the progression of glaucoma. Second, the condition of the APAC eye before the attack was unclear. It was an assumption that the APAC eye before the attack has similar vascular perfusion and retinal structural measurements as the healthy eye. Due to long-term repeated subclinical elevation IOP, the vascular perfusion and RNFL thickness maybe already defected before the attack. Mild corneal edema may affect the quality of the OCTA measurement in the APAC eye. Third, this study had a relatively small sample size. Fourth, the subjects in the PACG and APAC groups had different medication histories, but medications on the retinal perfusion are not fully understood. Fifth, this study lacked the VF results of the control group, but statistically significant visual acuity abnormalities required 20–50% nerve loss [28]. The OCT structure measurement and the examination by a clinical expert could be used to identify whether it is healthy. At the last, ONH parameters were not collected in this study and will be analyzed in our further study to demonstrate the correlations between optic nerve and RNFL and vessel perfusion density in APAC and PACG.

In summary, elevated IOP preferentially affects vascular perfusion in the optic disc region more than the macular region. In the APAC eye, there was a perfusion defect in the optic disc region and an increase in RNFL thickness. In this study, the OCTA vascular parameters have similar performance to the OCT structural parameters for glaucoma diagnosis in PACG.

The authors thank all of the technicians and clinical research collaborators of the clinical research center at JSIEC.

The study protocol was approved and reviewed by the Ethics Committee of Joint Shantou International Eye Center (JSIEC) of Shantou University and the Chinese University of Hong Kong (Shantou City, China) and was conducted in accordance with Good Clinical Practice within the tenets of the Declaration of Helsinki. Written informed consent to participate in the study was obtained from participants before being enrolled in the study and prior to any measurements being taken. Ethical approval number: EC20200609(6)-P19 and EC20190612(3)-P14.

The authors have no conflicts of interest to declare.

This study was supported by Science and Technology Project of Shantou City, Guangdong, China (2019-85 and 2020-58).

Chukai Huang participated in the design of the study and critically revised the article. Chao Li, Li Tan, and Xing Xu analyzed and interpreted the data. Chao Li and Li Tan wrote the article and contributed equally to the work. Chao Li, Li Tan, and Shirong Chen collected the data. All authors read and approved the final manuscript.

Additional Information

Chao Li and Li Tan contributed equally to this work presented here and should therefore be regarded as equivalent authors.

The author confirms that all relevant data are included in the article. Data are not publicly available due to ethical reasons. Further inquiries can be directed to the corresponding author.

1.
Tham
Y
,
Li
X
,
Wong
T
,
Quigley
H
,
Aung
T
,
Cheng
C
.
Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis
.
Ophthalmology
.
2014
;
121
(
11
):
2081
90
.
2.
Nongpiur
M
,
Ku
J
,
Aung
T
.
Angle closure glaucoma: a mechanistic review
.
Curr Opin Ophthalmol
.
2011
;
22
(
2
):
96
101
.
3.
Shin
J
,
Sung
K
,
Lee
J
,
Kwon
J
,
Seong
M
.
Optical coherence tomography angiography vessel density mapping at various retinal layers in healthy and normal tension glaucoma eyes
.
Graefes Arch Clin Exp Ophthalmol
.
2017
;
255
(
6
):
1193
202
.
4.
Rao
H
,
Pradhan
Z
,
Weinreb
R
,
Reddy
H
,
Riyazuddin
M
,
Dasari
S
.
Regional comparisons of optical coherence tomography angiography vessel density in primary open-angle glaucoma
.
Am J Ophthalmol
.
2016
;
171
:
75
83
.
5.
Wang
X
,
Jiang
C
,
Ko
T
,
Kong
X
,
Yu
X
,
Min
W
.
Correlation between optic disc perfusion and glaucomatous severity in patients with open-angle glaucoma: an optical coherence tomography angiography study
.
Graefes Arch Clin Exp Ophthalmol
.
2015
;
253
(
9
):
1557
64
.
6.
Alterman
M
,
Henkind
P
.
Radial peripapillary capillaries of the retina. II. Possible role in Bjerrum scotoma
.
Br J Ophthalmol
.
1968
;
52
(
1
):
26
31
.
7.
Gazzard
G
,
Foster
P
,
Devereux
J
,
Oen
F
,
Chew
P
,
Khaw
P
.
Intraocular pressure and visual field loss in primary angle closure and primary open angle glaucomas
.
Br J Ophthalmol
.
2003
;
87
(
6
):
720
5
.
8.
Ko
Y
,
Liu
C
,
Hsu
W
,
Cheng
C
,
Kuang
T
,
Chou
P
.
Determinants and characteristics of angle-closure disease in an elderly Chinese population
.
Ophthalmic Epidemiol
.
2015
;
22
(
2
):
109
15
.
9.
Moghimi
S
,
SafiZadeh
M
,
Fard
M
,
Motamed-Gorji
N
,
Khatibi
N
,
Chen
R
.
Changes in optic nerve head vessel density after acute primary angle closure episode
.
Invest Ophthalmol Vis Sci
.
2019
;
60
(
2
):
552
8
.
10.
Triolo
G
,
Rabiolo
A
,
Shemonski
N
,
Fard
A
,
Di Matteo
F
,
Sacconi
R
.
Optical coherence tomography angiography macular and peripapillary vessel perfusion density in healthy subjects, glaucoma suspects, and glaucoma patients
.
Invest Ophthalmol Vis Sci
.
2017
;
58
(
13
):
5713
22
.
11.
Battaglia Parodi
M
,
Cicinelli
M
,
Rabiolo
A
,
Pierro
L
,
Bolognesi
G
,
Bandello
F
.
Vascular abnormalities in patients with Stargardt disease assessed with optical coherence tomography angiography
.
Br J Ophthalmol
.
2017
;
101
(
6
):
780
5
.
12.
Mansoori
T
,
Gamalapati
J
,
Sivaswamy
J
,
Balakrishna
N
.
Optical coherence tomography angiography measured capillary density in the normal and glaucoma eyes
.
Saudi J Ophthalmol
.
2018
;
32
(
4
):
295
302
.
13.
Rao
HL
,
Pradhan
ZS
,
Suh
MH
,
Moghimi
S
,
Mansouri
K
,
Weinreb
RN
.
Optical coherence tomography angiography in glaucoma
.
J Glaucoma
.
2020
;
29
(
4
):
312
21
.
14.
Zhu
L
,
Zong
Y
,
Yu
J
,
Jiang
C
,
He
Y
,
Jia
Y
.
Reduced retinal vessel density in primary angle closure glaucoma: a quantitative study using optical coherence tomography angiography
.
J Glaucoma
.
2018
;
27
(
4
):
322
7
.
15.
Rao
H
,
Pradhan
Z
,
Weinreb
R
,
Riyazuddin
M
,
Dasari
S
,
Venugopal
J
.
Vessel density and structural measurements of optical coherence tomography in primary angle closure and primary angle closure glaucoma
.
Am J Ophthalmol
.
2017
;
177
:
106
15
.
16.
Scimeca
H
.
Optic disc changes in glaucoma
.
Int Ophthalmol Clin
.
1979
;
19
(
1
):
127
54
.
17.
Wang
X
,
Jiang
C
,
Kong
X
,
Yu
X
,
Sun
X
.
Peripapillary retinal vessel density in eyes with acute primary angle closure: an optical coherence tomography angiography study
.
Graefes Arch Clin Exp Ophthalmol
.
2017
;
255
(
5
):
1013
8
.
18.
Wang
X
,
Chen
J
,
Kong
X
,
Sun
X
.
Quantification of retinal microvascular density using optic coherence tomography angiography in primary angle closure disease
.
Curr Eye Res
.
2021
;
46
(
7
):
1018
24
.
19.
Fan
X
,
Xu
H
,
Zhai
R
,
Sheng
Q
,
Kong
X
.
Retinal microcirculatory responses to hyperoxia in primary open-angle glaucoma using optical coherence tomography angiography
.
Invest Ophthalmol Vis Sci
.
2021
;
62
(
14
):
4
.
20.
Rougier
M
,
Le Goff
M
,
Korobelnik
J
.
Optical coherence tomography angiography at the acute phase of optic disc edema
.
Eye Vis
.
2018
;
5
:
15
.
21.
Suh
M
,
Kim
S
,
Park
K
,
Kim
S
,
Kim
T
,
Hwang
S
.
Comparison of the correlations between optic disc rim area and retinal nerve fiber layer thickness in glaucoma and nonarteritic anterior ischemic optic neuropathy
.
Am J Ophthalmol
.
2011
;
151
(
2
):
277
86.e1
.
22.
Mastropasqua
R
,
Agnifili
L
,
Borrelli
E
,
Fasanella
V
,
Brescia
L
,
Di Antonio
L
.
Optical coherence tomography angiography of the peripapillary retina in normal-tension glaucoma and chronic nonarteritic anterior ischemic optic neuropathy
.
Curr Eye Res
.
2018
;
43
(
6
):
778
84
.
23.
Nelson
A
,
Chu
Z
,
Burkemper
B
,
Chang
B
,
Xu
B
,
Wang
R
.
Clinical utility of triplicate en face image averaging for optical coherence tomography angiography in glaucoma and glaucoma suspects
.
J Glaucoma
.
2020
;
29
(
9
):
823
30
.
24.
Alnawaiseh
M
,
Lahme
L
,
Müller
V
,
Rosentreter
A
,
Eter
N
.
Correlation of flow density, as measured using optical coherence tomography angiography, with structural and functional parameters in glaucoma patients
.
Graefes Arch Clin Exp Ophthalmol
.
2018
;
256
(
3
):
589
97
.
25.
Bonomi
L
,
Marchini
G
,
Marraffa
M
,
Bernardi
P
,
Morbio
R
,
Varotto
A
.
Vascular risk factors for primary open angle glaucoma: the Egna-Neumarkt Study
.
Ophthalmology
.
2000
;
107
(
7
):
1287
93
.
26.
Rao
H
,
Kadambi
S
,
Weinreb
R
,
Puttaiah
N
,
Pradhan
Z
,
Rao
D
.
Diagnostic ability of peripapillary vessel density measurements of optical coherence tomography angiography in primary open-angle and angle-closure glaucoma
.
Br J Ophthalmol
.
2017
;
101
(
8
):
1066
70
.
27.
Takusagawa
H
,
Liu
L
,
Ma
K
,
Jia
Y
,
Gao
S
,
Zhang
M
.
Projection-resolved optical coherence tomography angiography of macular retinal circulation in glaucoma
.
Ophthalmology
.
2017
;
124
(
11
):
1589
99
.
28.
Harwerth
R
,
Wheat
J
,
Fredette
M
,
Anderson
D
.
Linking structure and function in glaucoma
.
Prog Retin Eye Res
.
2010
;
29
(
4
):
249
71
.