Thinner subfoveal choroidal thickness in eyes with ocular ischemic syndrome than in unaffected contralateral eyes

Aim. To analyze the subfoveal choroid thickness and choroidal volume in unilateral ocular ischemic syndrome (OIS).Methods. A retrospective review was conducted for all patients with unilateral OIS from October 2010 through June 2014. The subfoveal choroidal thickness (SFChT) and choroidal volume of both eyes were compared.Results. 19 unilateral OIS patients were included in this study. The mean SFChT of OIS eyes was significantly lower than that of fellow eyes (OIS eyes: 208.89 ± 82.62 μm and fellow eyes: 265.31 ± 82.77 μm,P<0.001). The choroidal volume of OIS eyes was significantly smaller than that of fellow eyes (OIS eyes: 0.16 ± 0.05 mm3and fellow eyes: 0.21 ± 0.05 mm3,P<0.001).Conclusion. The choroidal thickness and volume of OIS eyes were smaller than those of unaffected fellow eyes. Decreased choroidal circulation caused by carotid artery stenosis might affect the discordance of choroidal thickness and choroidal volume.

Download Full-text

Evaluating the effectiveness of fructose‑1,6‑diphosphate in treating of ocular ischemic syndrome

European Science Review ◽

10.29013/esr-16-1.2-83-87 ◽

2016 ◽

pp. 83-87

Author(s):

D. Makhkamova

Keyword(s):

Ocular Ischemic Syndrome ◽

Ischemic Syndrome

Download Full-text

Clinical features of ocular ischemic syndrome in atherosclerotic lesions of the internal carotid artery

Practical medicine ◽

10.32000/2072-1757-2018-16-5-173-178 ◽

2018 ◽

Vol 16 (5) ◽

pp. 173-178

Author(s):

V. V. Tuzlaev ◽

◽

V. V. Egorov ◽

I. Z. Kravchenko ◽

G. P. Smoliakova ◽

...

Keyword(s):

Carotid Artery ◽

Internal Carotid Artery ◽

Clinical Features ◽

Internal Carotid ◽

Ocular Ischemic Syndrome ◽

Atherosclerotic Lesions ◽

Ischemic Syndrome

Download Full-text

Subfoveal choroidal thickness and peripapillary retinal nerve fiber layer thickness in young obese males

European Journal of Ophthalmology ◽

10.1177/1120672120982899 ◽

2020 ◽

pp. 112067212098289

Author(s):

Ceylan Uslu Dogan ◽

Damla Culha

Keyword(s):

Nerve Fiber ◽

Retinal Nerve Fiber Layer ◽

Choroidal Thickness ◽

Obese Group ◽

Fiber Layer ◽

Subfoveal Choroidal Thickness ◽

Young Males ◽

Rnfl Thickness ◽

Patient Groups ◽

Temporal Quadrant

Objective: Regarding the effect of obesity on subfoveal choroidal thickness (CT) and peripapillary retinal nerve fiber layer (RNFL) thickness, controversial results have been reported in different patient groups. This study aimed to evaluate the effect of obesity on these parameters among young male subjects in comparison with age-matched non-obese healthy males. Methods: This prospective, cross-sectional study included both eyes of 50 obese young males and 50 healthy non-obese young males. The obese and the non-obese groups included subjects with a BMI of ⩾30 and ⩽25 kg/m², respectively. Subfoveal choroidal thickness and RNFL analyses were conducted by spectral domain optical coherence tomography (SD-OCT). Results: Subfoveal choroidal thickness (321.0 ± 46.7 vs 338.4±35.3, p = 0.002) and RNFL thickness at temporal quadrant (73.4 ± 9.9 vs 76.4 ± 9.3, p = 0.008) was significantly lower in the obese group when compared to the non-obese group. The groups did not differ regarding peripapillary RNFL thickness at other quadrants (superior, inferior, or nasal) or regarding mean peripapillary RNFL thickness. Conclusion: Findings of this study demonstrated a negative correlation of obesity with subfoveal choroidal thickness and temporal quadrant peripapillary RNFL thickness. Larger studies on different patient groups with longer-term follow-up are warranted to better elucidate the ophthalmological effects of obesity.

Download Full-text

Automatic Segmentation of Choroid Layer Using Deep Learning on Spectral Domain Optical Coherence Tomography

Applied Sciences ◽

10.3390/app11125488 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5488

Author(s):

Wei Ping Hsia ◽

Siu Lun Tse ◽

Chia Jen Chang ◽

Yu Len Huang

Keyword(s):

Optical Coherence Tomography ◽

Deep Learning ◽

Choroidal Thickness ◽

Automatic Segmentation ◽

Average Error ◽

Good Prediction ◽

Optical Coherence ◽

Learning Method ◽

Subfoveal Choroidal Thickness ◽

Fully Connected

The purpose of this article is to evaluate the accuracy of the optical coherence tomography (OCT) measurement of choroidal thickness in healthy eyes using a deep-learning method with the Mask R-CNN model. Thirty EDI-OCT of thirty patients were enrolled. A mask region-based convolutional neural network (Mask R-CNN) model composed of deep residual network (ResNet) and feature pyramid networks (FPNs) with standard convolution and fully connected heads for mask and box prediction, respectively, was used to automatically depict the choroid layer. The average choroidal thickness and subfoveal choroidal thickness were measured. The results of this study showed that ResNet 50 layers deep (R50) model and ResNet 101 layers deep (R101). R101 U R50 (OR model) demonstrated the best accuracy with an average error of 4.85 pixels and 4.86 pixels, respectively. The R101 ∩ R50 (AND model) took the least time with an average execution time of 4.6 s. Mask-RCNN models showed a good prediction rate of choroidal layer with accuracy rates of 90% and 89.9% for average choroidal thickness and average subfoveal choroidal thickness, respectively. In conclusion, the deep-learning method using the Mask-RCNN model provides a faster and accurate measurement of choroidal thickness. Comparing with manual delineation, it provides better effectiveness, which is feasible for clinical application and larger scale of research on choroid.

Download Full-text