• Users Online: 333
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 22  |  Issue : 1  |  Page : 42-48

Optical coherence tomography angiography features in diabetic patients with unexplained visual loss


1 Department of Ophthalmology, Faculty of Medicine, Ain Shams University, Egypt
2 New Cairo Hospital, Cairo, Egypt

Date of Submission26-May-2020
Date of Decision23-Jul-2020
Date of Acceptance07-Sep-2020
Date of Web Publication24-Mar-2021

Correspondence Address:
MBBCh Enas I Abdallah Ibrahiem
New Cairo Hospital, 44, 5th Local, 3rd Settlement, New Cairo 11865
Egypt
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/DJO.DJO_46_20

Rights and Permissions
  Abstract 

Background Diabetic macular ischemia (DMI) has a known effect on visual loss in diabetics. Optical coherence tomography angiography (OCTA) allows identification of the vascular abnormalities of diabetic maculopathy.
Aim This study aimed to detect the quantitative and qualitative OCTA features of foveal and macular areas in diabetic patients with unexplained visual loss.
Settings and design This was a cross-sectional study.
Patients and methods This cross-sectional study enrolled 15 diabetic patients with unexplained visual loss. They underwent comprehensive ophthalmological assessment, including measurement of best-corrected visual acuity (BCVA) converted to LogMAR for statistical analysis and macular OCTA imaging (AngioVue OCTA). Quantitative data analyzed were foveal avascular zone (FAZ) area, FAZ perimeter, and acircularity index (AI). Vessel density (VD) parameters included full-retinal VD in a 300-µm circle around the FAZ (FD-300) plus foveal and parafoveal VD in superficial and deep capillary plexuses.
Results A positive significant correlation was found between LogMAR BCVA and FAZ area (r=0.701, P=0.004), FAZ perimeter (r=0.732, P=0.002), and AI (r=0.540, P=0.038). However, there was no significant correlation between BCVA and either FD-300 (P=0.144), or superficial and deep parafoveal VD (P=0.187 and 0.764, respectively), or superficial and deep foveal VD (P=0.34 and 0.187, respectively). In addition, DMI grade showed a significant positive correlation with LogMAR BCVA (P=0.011).
Conclusion FAZ parameters (perimeter, area, and AI) measured by OCTA macula can precisely depict DMI in diabetic patients with unexplained visual loss and are closely correlated to BCVA. It is recommended to perform OCTA macula for those patients before making treatment decisions.

Keywords: diabetic macular ischemia, foveal avascular zone, optical coherence tomography angiography, unexplained visual loss


How to cite this article:
Ebeid WM, Salman AG, Abdallah Ibrahiem EI, Abozeid NH. Optical coherence tomography angiography features in diabetic patients with unexplained visual loss. Delta J Ophthalmol 2021;22:42-8

How to cite this URL:
Ebeid WM, Salman AG, Abdallah Ibrahiem EI, Abozeid NH. Optical coherence tomography angiography features in diabetic patients with unexplained visual loss. Delta J Ophthalmol [serial online] 2021 [cited 2022 Aug 18];22:42-8. Available from: http://www.djo.eg.net/text.asp?2021/22/1/42/311889


  Introduction Top


Diabetes mellitus is a chronic disorder that causes multiorgan ischemic changes. Early detection of its first signs in the diabetic eye plays a pivotal role in the management of this significant public health issue [1].

Diabetic macular ischemia (DMI) is regarded as an important cause of visual impairment in diabetic patients, owing to the devastating and irreversible visual loss it can cause [2].

For decades, fundus fluorescein angiography (FFA) has been the gold standard to understand, diagnose, and treat retinal disorders. DMI can be identified in FFA by two basic parameters: first, enlarged foveal avascular zone (FAZ) area, and second, by the pattern of macular capillaries that has many irregularities and spacing, indicating that there is some degree of intervening capillary loss [3]. However, being an invasive procedure, it has several limitations including adverse drug reactions. Hence, other noninvasive tests that can be repeated during the course of the disease are required [4].

Optical coherence tomography angiography (OCTA) has been recently introduced as a novel noninvasive depth-resolved imaging technique of retinal and choroidal vasculature alternative to FFA. It can provide images with higher details regarding macular status. So, it can be considered the new recent imaging technique for diagnosis of DMI, providing an alternative imaging technique to FFA for this purpose [5].

OCTA can be used to quantify numerous parameters useful in the diagnosis and follow-up of patients with DMI. These include FAZ metrics such as FAZ area, FAZ perimeter, acircularity index (AI), and foveal microcirculation parameters [6].

This study aimed to detect the quantitative and qualitative OCTA parameters of macular area as FAZ area, perimeter, AI, and vessel density (VD) in both superficial and deep retinal layers in diabetic patients with unexplained visual loss.


  Patients and methods Top


This cross-sectional study was conducted on 15 diabetic patients with unexplained visual loss. The study was performed in accordance with the tents of the Declaration of Helsinki and upon approval of the Ethical Committee of the Faculty of Medicine, Ain Shams University. A written informed consent was obtained from all patients to participate in the study and for publication of the results of the study.

Inclusion criteria were as follows: patients with type I or type II diabetes mellitus with no clinically apparent diabetic retinopathy nor diabetic maculopathy having unexplained loss of visual acuity (VA) with best-corrected visual acuity (BCVA) less than 6/9. Exclusion criteria were significant media opacities interfering with images’ signal strength and myopia greater than −6.00 D for the possibility of erroneous FAZ area measurements (magnification errors). In addition, patients with any subfoveal hard exudates, vitreoretinal interface abnormalities, known glaucoma or uveitis, any optic nerve diseases, or retinal diseases were also excluded.

All patients underwent a comprehensive ophthalmological assessment including measurement of BCVA using Landolt’s broken ring chart converted to LogMAR for statistical analysis and OCTA imaging.

AngioVue OCTA system (RTVue-XR Avanti; Optovue Inc., Fremont, California, USA) running on software, version 2016.2.0 with Dual Trac was employed. This device has an A-scan rate of 70 000 scans per second. Each B-scan was composed of 304×304 A-scans, with axial resolution of 5 μm. Pupils were dilated by cycloplegic eye drops before scanning to more than or equal to 6-mm diameter. During imaging, the patient was instructed to fixate on an internal fixation target.

The macular area was scanned in 3×3 mm scans from the center of the fovea. The retina was automatically segmented into four slabs (superficial and deep retinal layers, outer retina, and choroid) with simple en‐face visualization of the corresponding vascular supply for each layer.

The software was used to automatically identify the borders of the FAZ, where it is acknowledged on the angioflow system as the central area void of any vasculature.

The study analyzed the new quantitative OCTA data in foveal and macular areas. FAZ metrics that were used to quantify the FAZ abnormalities included FAZ area and FAZ perimeter (defined as the length of the outer outline border of the FAZ which reflects the irregularity of this area), in addition to the AI, which was defined as the ratio of the measured perimeter of the FAZ to the perimeter of a circle that has equal area to the measured FAZ area ([Figure 1]).
Figure 1 Automated foveal avascular zone (FAZ) parameters.

Click here to view


The VD parameters used in this study were FD-300 (VD of the full retina not only superficial and deep capillary plexuses in a width of 300 µm around the FAZ), superficial and deep foveal capillary plexuses and superficial and deep parafoveal capillary plexuses ([Figure 2] and [Figure 3]). In addition, the macular thickness was calculated in both foveal and parafoveal areas ([Figure 2]).
Figure 2 Automated parafoveal and foveal density in the superficial plexus and automated foveal and parafoveal retinal thickness by optical coherence tomography angiography.

Click here to view
Figure 3 Automated parafoveal and foveal density in the deep plexus by optical coherence tomography angiography.

Click here to view


DMI was qualitatively evaluated according to the apparent distortion of the outer FAZ outline that appeared on OCTA images. The DMI was classified as follows: grade 0: normal FAZ outline (absence of disturbances), grade 1: questionable (not smoothly round or oval with no clear pathology), grade 2: mild (less than half the original circumference destroyed), grade 3: moderate (more than half the original circumference destroyed), grade 4: severe (capillary outline completely destroyed), and up to grade 8: ungradable (unable to grade) [7].

Statistical analysis

Data were analyzed using the Statistical Package of Social Science (SPSS) program for Windows (standard version 24.0; IBM Corp., Armonk, New York, USA). The normality of data was first tested with the Shapiro test. Qualitative data were described using number and percent. Association between categorical variables was tested using a Monte Carlo test when expected cell count was less than 5. Continuous variables were presented as mean±SD. Analysis of variance test was used to compare more than two groups (parametric), whereas the Kruskal–Wallis test was used to compare more than two medians (nonparametric). Spearman correlation was used to correlate continuous variables.

For all the aforementioned statistical tests done, the threshold of significance was fixed at 5% level (P value). The results were considered significant when the P value was equal to or less than 5% (P≤0.05).


  Results Top


A total of 15 patients were included in this study; six patients were males and nine were females. Age ranged from 39 to 85 years (mean=58.53±13.84 years). Four of the patients were diagnosed as having diabetes type I, whereas 11 of them were diagnosed as having diabetes type II. The mean duration of diabetes was 13.93±3.23 years. The mean intraocular pressure (IOP) was 16.53±2.45 mmHg, and the median BCVA (LogMAR) was 0.4.

The FAZ area was 0.331±0.12 mm2. The FAZ perimeter was 2.35±0.55 mm, and the AI was 1.19±0.13, with a VD in FD-300 being 43.34±6.55% ([Table 1]).
Table 1 Foveal avascular zone, vessel density, and retinal thickness parameters

Click here to view


The VD data were computed at the level of the superficial and deep capillary plexuses for both the foveal (superficial=20.43±4.49% and deep=26.60±5.68%) and parafoveal areas (superficial=43.12±5.01% and deep=46.39±4.97%). Moreover, foveal and parafoveal retinal thickness were calculated (283.20±53.21 and 331.73±38.34 μm, respectively, [Table 1]).

All patients had some degree of DMI. Seven patients demonstrated a mild DMI grade 2, whereas six demonstrated a moderate DMI grade 3 and 2 demonstrated severe DMI grade 4.

There was a significant correlation between LogMAR BCVA and many variables. Age of the patients showed a significant positive correlation with BCVA (P=0.001). A significant positive correlation was also found between LogMAR BCVA and FAZ area (P=0.004), FAZ perimeter (P=0.002), and AI (P=0.038). Additionally, DMI was positively correlated with BCVA (P=0.011). However, there was no significant correlation between BCVA and the other variables studied including foveal and parafoveal VD and retinal thickness ([Table 2]).
Table 2 Correlation between best-corrected visual acuity (LogMAR) and other variables

Click here to view


The patients were categorized into three groups according to their DMI grade. Different variables were compared between these groups. Age, sex, type of diabetes, duration of diabetes, and IOP did not differ significantly between the different grades of DMI. Nevertheless, BCVA LogMAR showed a significant difference among the three groups (P=0.04), with the worse the BCVA, the higher the DMI grade ([Table 3]).
Table 3 The relation between diabetic macular ischemia and studied variables

Click here to view



  Discussion Top


In this study, sex, type and duration of diabetes, and IOP did not correlate with BCVA (LogMAR), nor did they differ among different DMI grades. Thus, we could exclude the role of these parameters or its contributing causative effects on BCVA decrease. On the contrary, there was a positive significant correlation between age and BCVA, which means that the increasing age may be associated with more visual loss. In accordance, Tan et al. [8] have reported that the increase in age was a risk factor for decrease of vision associated with the decreased VD in diabetics.

Moreover, the current study demonstrated a positive significant correlation between LogMAR BCVA and different FAZ parameters (area, perimeter, and acicularity index), which means that the unexplained decrease of VA was commonly associated with enlarged FAZ metrics. In accordance with this, Freiberg et al. [9] and Balaratnasingam et al. [10] have demonstrated that FAZ dimensions obtained by OCTA correlated with vision in diabetic cases. On the contrary, Safi et al. [11] did not report such findings. They excluded any significant relation between FAZ metrics and BCVA (LogMAR). However, in their study, they depended on FAZ area only to evaluate the FAZ, unlike the current study, which confirmed the results by measuring perimeter and AI for more detailed evaluation of the FAZ.

The descriptive data of VD were calculated in this study for the purpose of establishing a relationship between VD and the unexplained decrease in BCVA. Nevertheless, we could not detect any significant correlation between BCVA and any of the following variables of VD: VD of FD-300, superficial and deep foveal capillary plexuses, and superficial and deep parafoveal capillary plexuses. Similarly, Dupas et al. [12] and Hwang et al. [13] reported that the decreases of VD in the foveal and parafoveal plexuses were not associated with the decrease of vision. In contrast to the current study, Samara et al. [14] and Balaratnasingam et al. [10] have shown a correlation between BCVA and VD at the parafoveal region, involving both superficial and deep capillary plexuses. This can be explained by using different software with different motion and projection artifacts correction algorithm, which could affect the quantitative measurements of VD.

In the present study, there was no significant correlation between LogMAR BCVA and macular thickness in both foveal and parafoveal areas. In contrast, a study by Goebel and Kretzchmar-Gross [15] denoted some correlation between retinal thickness and VA. Nevertheless, this was established in diabetic patients with no macular ischemia, so it could not be compared with the patients in the present study who had evident macular ischemia.

All diabetic patients, in the current study, with unexplained visual loss were found to have some degree of DMI. There was a significant difference in BCVA among cases with different DMI grades, indicating more pronounced visual loss associated with higher DMI grades. Similarly, a study by Sim et al. [16] demonstrated a strong association between DMI and decrease of VA independent of age, sex, and diabetic retinopathy stage. In addition, Usman [17] have reported that the decrease in BCVA can be considered the most important sequelae of DMI. In contrast, no correlation between DMI and VA was detected by some studies, such as that of Jonas et al. [18].

The limitations of this study include the small sample size and the cross-sectional nature. In addition, the noninvasive OCTA was only performed for the patients rather than the invasive FFA. Future longitudinal studies comparing the two modalities are warranted and could help in confirming the current results.


  Conclusion Top


The current study demonstrated the significant correlation between FAZ parameters (area, perimeter, and AI) measured by AngioVue OCTA and BCVA in diabetic patients with unexplained decrease of vision. In addition, we elucidated that DMI by itself, independent of any other factors, can worsen the VA. Hence, it is recommended to perform OCTA macula for any diabetic patient with unexplained visual loss to precisely depict macular ischemia, which is crucial before making treatment decisions. It is also recommended to give special attention to the FAZ parameters rather than the VD measurements on interpreting OCTA in such cases, for the sake of documenting the presence of DMI. OCTA is currently enhancing our understanding of the role of the retinal microvasculature in the pathogenesis of DMI.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Geiss LS, Wang J, Cheng YJ, Thompson TJ, Barker L, Li Y et al. Prevalence and incidence trends for diagnosed diabetes among adults aged 20 to 79 years, United States, 1980-2012. JAMA 2014; 312:1218–1226.  Back to cited text no. 1
    
2.
Sim DA, Keane PA, Zarranz VJ, Fung S, Powner MB, Platteau E et al. The effects of macular ischemia on visual acuity in diabetic retinopathy. Investig Ophthalmol Vis Sci 2013; 54:2353–2360.  Back to cited text no. 2
    
3.
Salz DA, Witkin AJ. Imaging in diabetic retinopathy. Middle East Afr J Ophthalmol 2015; 22:145.  Back to cited text no. 3
[PUBMED]  [Full text]  
4.
Jayadev C, Jain N, Sachdev S, Mohan A, Yadav NK. Utility of noninvasive imaging modalities in a retina practice. Indian J Ophthalmol 2016; 64:940.  Back to cited text no. 4
[PUBMED]  [Full text]  
5.
Garcia JM, Lima TT, Louzada RN, Rassi AT, Isaac DL, Avila M. Diabetic macular ischemia diagnosis: comparison between optical coherence tomography angiography and fluorescein angiography. J Ophthalmol 2016; 2016:3989310.  Back to cited text no. 5
    
6.
Liu L, Gao J, Bao W, Hu C, Xu Y, Zhao B et al. Analysis of foveal microvascular abnormalities in diabetic retinopathy using optical coherence tomography angiography with projection artifact removal. J Ophthalmol 2018; 2018:3926745.  Back to cited text no. 6
    
7.
Early Treatment Diabetic Retinopathy Study Research Group. Classification of diabetic retinopathy from fluorescein angiograms: ETDRS report number 11. Ophthalmology 1991; 98:807–822.  Back to cited text no. 7
    
8.
Tan F, Chen Q, Zhuang X, Wu C, Qian Y, Wang Y et al. Associated risk factors in the early stage of diabetic retinopathy. Eye Vis 2019; 6:23.  Back to cited text no. 8
    
9.
Freiberg FJ, Pfau M, Wons J, Wirth MA, Becker MD, Michels S. Optical coherence tomography angiography of the foveal avascular zone in diabetic retinopathy. Graefes Arch Clin Exp Ophthalmol 2016; 254:1051–1058.  Back to cited text no. 9
    
10.
Balaratnasingam C, Inoue M, Ahn S, McCann J, Dhrami-Gavazi E, Yannuzzi LA et al. Visual acuity is correlated with the area of the foveal avascular zone in diabetic retinopathy and retinal vein occlusion. Ophthalmology 2016; 123:2352–2367.  Back to cited text no. 10
    
11.
Safi H, Anvari P, Naseri D, Shenazandi H, Kazemi P, Farsi P et al. Quantitative analysis of optical coherence tomography angiography metrics in diabetic retinopathy. Ther Adv Ophthalmol 2020; 12:2515841419897459.  Back to cited text no. 11
    
12.
Dupas B, Minvielle W, Bonnin S, Couturier A, Erginay A, Massin P et al. Association between vessel density and visual acuity in patients with diabetic retinopathy and poorly controlled type 1 diabetes. JAMA Ophthalmol 2018; 136:721–728.  Back to cited text no. 12
    
13.
Hwang TS, Gao SS, Liu L, Lauer AK, Bailey ST, Flaxel CJ et al. Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy. JAMA Ophthalmol 2016; 134:367–373.  Back to cited text no. 13
    
14.
Samara WA, Shahlaee A, Adam MK, Khan MA, Chiang A, Maguire JI et al. Quantification of diabetic macular ischemia using optical coherence tomography angiography and its relationship with visual acuity. Ophthalmology 2017; 124:235–244.  Back to cited text no. 14
    
15.
Goebel W, Kretzchmar-Gross T. Retinal thickness in diabetic retinopathy: a study using optical coherence tomography (OCT). Retina 2002; 22:759–767.  Back to cited text no. 15
    
16.
Sim DA, Keane PA, Zarranz-Ventura J, Bunce CV, Fruttiger M, Patel PJ et al. Predictive factors for the progression of diabetic macular ischemia. Am J Ophthalmol 2013; 156:684–692.  Back to cited text no. 16
    
17.
Usman M. An overview of our current understanding of diabetic macular ischemia (DMI). Cureus 2018; 10:e3064.  Back to cited text no. 17
    
18.
Jonas JB, Martus P, Degenring RF, Kreissig I, Akkoyun I. Predictive factors for visual acuity after intravitreal triamcinolone treatment for diabetic macular oedema. Arch Ophthalmol 2005; 123:1338–1343.  Back to cited text no. 18
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Patients and methods
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed474    
    Printed8    
    Emailed0    
    PDF Downloaded70    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]