| Literature DB >> 36213634 |
Katherine Lun1,2, Yin Ci Sim3, Rachel Chong3,4, Damon Wong3,5,6,7, Bingyao Tan3,5,6, Rahat Husain3, Tin Aung2,3,4, Chelvin C A Sng2,3, Leopold Schmetterer3,4,5,6, Jacqueline Chua3,4.
Abstract
Introduction: There has been a growing interest in the role of vascular factors in glaucoma. Studies have looked at the characteristics of macular choriocapillaris in patients with glaucoma but with conflicting results. Our study aims to use swept-source optical coherence tomography angiography (SS-OCTA) to evaluate macular choriocapillaris metrics in normal participants and compare them with patients with early primary open-angle glaucoma (POAG) (mean deviation better than -6dB).Entities:
Keywords: choriocapillaris; choroid; glaucoma; primary open-angle glaucoma; swept-source optical coherence tomography angiography
Year: 2022 PMID: 36213634 PMCID: PMC9532514 DOI: 10.3389/fmed.2022.999167
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
FIGURE 1The framework of choriocapillaris OCTA image processing. Raw choriocapillaris OCTA image extracted from the OCTA machine (A) was binarized with a threshold of 1.5 standard deviation below the mean intensity of the image to segment flow deficits (B). Foveal avascular zone (FAZ) segmented from the raw superficial retinal plexus OCTA image was dilated by 800 μm (D) to generate a mask (E) that indicates the region to be analysed. The mask (E) was applied to the segmented flow deficits (B) to generate the final flow deficit image (C) where the density and size of flow deficits were computed.
Comparison of demographics, systemic, and ocular characteristics between normal control and primary open angle glaucoma patients.
| Normal control | Early POAG | ||
|
| 104 | 100 | |
| Age, years | 59.0 (11.5) | 62.0 (12.0) | 0.134 |
| Gender, Male | 51 (49.0) | 53 (53.0) | 0.572 |
| Ethnicity, Chinese | 91 (87.5) | 87 (87.0) | 0.287 |
| Diabetes | 0 (0) | 24 (24.0) |
|
| Hypertension | 2 (1.9) | 40 (40.0) |
|
| Systolic blood pressure, mmHg | 136.3 (18.6) | 129.9 (25.7) | 0.093 |
| Diastolic blood pressure, mmHg | 76.5 (14.6) | 74.8 (14.8) | 0.339 |
|
| 157 | 144 | |
| Intraocular pressure, mmHg | 17 (5) | 14 (4) |
|
| Axial length, mm | 24.11 (1.71) | 24.81 (2.17) |
|
| Visual field mean deviation (MD), dB | – | −2.40 (1.66) | – |
| Signal strength of scans | 9.15 ± 0.64 | 8.85 ± 0.93 |
|
Data are number (%), mean ± standard deviation (SD), or median (interquartile range), as appropriate.
*Test for differences between groups, based on one-way analysis of variance (ANOVA) for normally distributed continuous variables or Kruskal–Wallis equality-of-populations rank test for non-normally distributed continuous variables and with Chi-square tests or Fisher’s exact tests for categorical variables.
†1 represents poor scan quality while 10 represents high scan quality. dB, decibels; POAG, primary open angle glaucoma. Bold values denote statistical significance at the P < 0.05 level.
Multivariable linear regression modeling of the association between normal aging, primary open angle glaucoma and choriocapillaris flow deficits.
| Flow deficit density (%) | Average flow deficit size (μ m2) | |||||
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| Characteristic | β | 95% CI | * | β | 95% CI | * |
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| Age quintile, years | ||||||
| 42–52 ( | Reference | Reference | ||||
| 53–57 ( | 0.81 | 0.13 to 1.49 |
| 15.52 | −13.30 to 44.33 | 0.291 |
| 58–61 ( | 0.71 | 0.16 to 1.27 |
| 16.66 | −10.93 to 44.25 | 0.237 |
| 62–68 ( | 0.71 | 0.09 to 1.32 |
| 15.45 | −12.59 to 44.47 | 0.280 |
| 69–82 ( | 1.00 | 0.34 to 1.65 |
| 42.65 | 12.39 to 72.91 |
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| Normal ( | Reference | Reference | ||||
| Early POAG ( | 0.17 | −0.27 to 0.60 | 0.453 | −4.56 | −23.60 to 14.44 | 0.637 |
*Adjusted for diabetes, hypertension, intraocular pressure, axial length, and signal strength of scans. Bold values denote statistical significance at the P < 0.05 level. β, beta coefficient; CI, confidence interval; NA, not applicable; POAG, primary open angle glaucoma. Bold values denote statistical significance at the P < 0.05 level.
FIGURE 2Representative choriocapillaris OCTA 3 × 3 mm2 images (A,C,E,G) and their corresponding color-coded maps (B,D,F,H). The density and average size of choriocapillaris flow deficits (FD) in normal controls increases with age, where it is 8.4% and 260 μm2 in the 44-year-old subject (A,B), followed by 8.8% and 286 μm2 in the 61-year-old subject (C,D), and highest at 9.2% and 322 μm2 in the 71-year-old (E,F). Similar density and average size of choriocapillaris FD can be seen in a 72-year-old patient with mild primary open angle glaucoma (POAG; visual field mean deviation of −2.85 dB; G and H; 9.0% and 316 μm2) and a 71-year-old normal control (E,F; 9.2% and 322 μm2).
FIGURE 3Relationship between the choriocapillaris (A) flow deficit density (%) and (B) average flow deficit size (μm2) in normal controls (light grey bars) and patients with early primary open angle glaucoma (POAG; dark grey bars), stratified by age groups. Choriocapillaris flow deficit density was evidently higher in those aged 53 years and above (all P ≤ 0.024) whereas the average flow deficit size was significantly larger in those aged 69 years and above (P = 0.006) in both normal and glaucoma patients. There were no differences in the choriocapillaris characteristics between normal and glaucoma patients. Asterisks mark significant differences in reference to the youngest age group according to multivariable linear regression analysis with generalized estimating equations (GEE) adjusted for diabetes, hypertension, intraocular pressure, axial length, and signal strength of scans.