We have located links that may give you full text access.
Relationship of intercapillary area with visual acuity in diabetes mellitus: an optical coherence tomography angiography study.
British Journal of Ophthalmology 2018 June 5
AIM: To examine the correlation of best-corrected visual acuity (BCVA) with intercapillary area (ICA) measured from optical coherence tomography angiography (OCT-A) in patients with diabetes, and to compare the strength of associations between BCVA with ICA and other OCT-A metrics.
METHODS: A cross-sectional study involved 447 eyes from 299 patients with diabetes. All participants underwent OCT-A with a swept-source OCT (Triton DRI-OCT, Topcon, Tokyo, Japan). An automated customised MATLAB programme was used to quantify ICA (the mean of the 10 largest areas including foveal avascular zone (FAZ) area (ICA10_FAZ) and excluding FAZ area (ICA10_excFAZ)) and other OCT-A metrics (FAZ area, FAZ circularity and vessel density) from the macular OCT-A images. BCVA was measured using Snellen chart for the patients and then converted to logarithm of the minimum angle of resolution (logMAR) VA. We further defined 'good VA' as Snellen >0.7 and 'poor VA' as Snellen ≤0.7 as a binary VA outcome for logistic regression analysis.
RESULTS: In univariate regression analysis, increased ICA10_FAZ and ICA10_excFAZ were significantly correlated with logMAR (p values <0.05). In multivariate regression analysis, only the association between ICA10_FAZ and logMAR persisted (β=0.103, p=0.024). In multivariable logistic regression analysis, increased ICA10_FAZ (OR=1.300, 95% CI 1.076 to 1.679, p=0.044) and FAZ circularity (OR=1.285, 95% CI 1.031 to 1.603, p=0.026) showed significant associations with poor VA.
CONCLUSIONS: Increased ICA measured from OCT-A, describing enlargement of capillary rarefaction or closure at macular area, is independently associated with BCVA, suggesting that ICA is a potential marker to quantify retinal microvascular abnormalities relating to vision among individuals with diabetes.
METHODS: A cross-sectional study involved 447 eyes from 299 patients with diabetes. All participants underwent OCT-A with a swept-source OCT (Triton DRI-OCT, Topcon, Tokyo, Japan). An automated customised MATLAB programme was used to quantify ICA (the mean of the 10 largest areas including foveal avascular zone (FAZ) area (ICA10_FAZ) and excluding FAZ area (ICA10_excFAZ)) and other OCT-A metrics (FAZ area, FAZ circularity and vessel density) from the macular OCT-A images. BCVA was measured using Snellen chart for the patients and then converted to logarithm of the minimum angle of resolution (logMAR) VA. We further defined 'good VA' as Snellen >0.7 and 'poor VA' as Snellen ≤0.7 as a binary VA outcome for logistic regression analysis.
RESULTS: In univariate regression analysis, increased ICA10_FAZ and ICA10_excFAZ were significantly correlated with logMAR (p values <0.05). In multivariate regression analysis, only the association between ICA10_FAZ and logMAR persisted (β=0.103, p=0.024). In multivariable logistic regression analysis, increased ICA10_FAZ (OR=1.300, 95% CI 1.076 to 1.679, p=0.044) and FAZ circularity (OR=1.285, 95% CI 1.031 to 1.603, p=0.026) showed significant associations with poor VA.
CONCLUSIONS: Increased ICA measured from OCT-A, describing enlargement of capillary rarefaction or closure at macular area, is independently associated with BCVA, suggesting that ICA is a potential marker to quantify retinal microvascular abnormalities relating to vision among individuals with diabetes.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app