Idiopathic Intracranial Hypertension with Normal Cerebrospinal Fluid Pressure

This is a Letter to the Editor and does not have an abstract

Correction of Retinal Nerve Fiber Layer Thickness Measurement on Spectral-Domain Optical Coherence Tomographic Images Using U-net Architecture

Purpose: In this study, an algorithm based on deep learning was presented to reduce the retinal nerve fiber layer (RNFL) segmentation errors in spectral domain optical coherence tomography (SD-OCT) scans using ophthalmologists’ manual segmentation as a reference standard. Methods: In this study, we developed an image segmentation network based on deep learning to automatically identify the RNFL thickness from B-scans obtained with SD-OCT. The scans were collected from Farabi Eye Hospital (500 B-scans were used for training, while 50 were used for testing). To remove the speckle noise from the images, preprocessing was applied before training, and postprocessing was performed to fill any discontinuities that might exist. Afterward, output masks were analyzed for their average thickness. Finally, the calculation of mean absolute error between predicted and ground truth RNFL thickness was performed. Results: Based on the testing database, SD-OCT segmentation had an average dice similarity coefficient of 0.91, and thickness estimation had a mean absolute error of 2.23 ± 2.1 μm. As compared to conventional OCT software algorithms, deep learning predictions were better correlated with the best available estimate during the test period (r2 = 0.99 vs r2 = 0.88, respectively; P < 0.001). Conclusion: Our experimental results demonstrate effective and precise segmentation of the RNFL layer with the coefficient of 0.91 and reliable thickness prediction with MAE 2.23 ± 2.1 μm in SD-OCT B-scans. Performance is comparable with human annotation of the RNFL layer and other algorithms according to the correlation coefficient of 0.99 and 0.88, respectively, while artifacts and errors are evident

Lamina Cribrosa and Choroid Features and Their Relationship to Stage of Pseudoexfoliation Glaucoma.

PurposeTo better understand the relationship of lamina cribrosa (LC) and choroid features to the severity of pseudoexfoliation glaucoma (PXG).MethodsIn this cross-sectional study, 137 eyes of 122 subjects (47 eyes with moderate/advanced PXG [mean deviation (MD), -15.0 ± 7.7 dB], 34 eyes with mild PXG [MD, -2.7 ± 1.5 dB], 32 aged-matched pseudoexfoliation syndrome [PXS] eyes, and 24 aged-matched control eyes) were investigated. Optic discs, LC thickness, and anterior LC depth (ALD; midsuperior, center, and midinferior) as well as peripapillary choroidal thickness were determined. Linear mixed modeling was used to adjust for age, sex, and axial length.ResultsA progressive decrease in LC thickness was found when comparing controls (271.9 ± 61.3 μm), PXS (212.6 ± 51.5 μm), mild PXG (180.8 ± 24.6 μm), and moderate/advance PXG (138.9 ± 37.5 μm) (P < 0.001). ALD was greater (P < 0.001) in moderate/advance glaucoma (306.7 ± 105.3 μm) and mild PXG (209.5 ± 79.7 μm) compared with PXS (155 ± 86.7 μm) and healthy controls (149.2 ± 103 μm). Although eyes with moderate/advance PXG had the thinnest choroid (117.2 ± 36.6 μm), choroidal thickness was comparable in mild PXG, PXS, and controls (150.0 ± 46.1, 159.7 ± 65.5, and 157.5 ± 51.1 μm, respectively; P = 0.002). Worse MD was the only factor associated with thinner LC (β = 2.344, P < 0.001) and choroid (β = 1.717, P = 0.009 μm) in PXG eyes. Higher IOP (β = 4.305, P = 0.013) and worse MD (β = -6.390, P < 0.001) were associated with deeper ALD in PXG.ConclusionsIn pseudoexfoliation, LC thinning is an early sign, and there is progressive thinning with advancing glaucoma. Choroidal thinning is observable only with moderate/advanced glaucoma. In PXG eyes, LC thickness, depth, and peripapillary choroidal thickness are associated with glaucoma severity

Parapapillary choroidal microvascular density in acute primary angle-closure and primary open-angle glaucoma: an optical coherence tomography angiography study

Back ground/aims To determine whether parapapillary choroidal microvasculature (PPCMv) density, measured by optical coherence tomography angiography, differed between acute primary angle-closure (APAC), primary open-angle glaucoma (POAG) and controls.Methods This is a prospective, cross-sectional, observational study. Data from 149 eyes from two academic referral centres were analysed. Automated PPCMv density was calculated in inner and outer annuli around the optic nerve region in addition to the peripapillary superficial vasculature, using customised software. A generalised estimating equation was used to compare vessel densities among groups, adjusted for confounders.Results Data from 40 eyes with APAC, 65 eyes with POAG and 44 eyes in healthy controls were gathered and analysed. Global radial peripapillary capillary densities were reduced in eyes with APAC and POAG compared with controls (p=0.027 and 0.136, respectively). Mean outer annular PPCMv density in the POAG group was lower vs the APAC group by 3.6% (95% CI 0.6% to 6.5%) (p=0.018) in the multivariable model adjusted for confounders. The mean difference in inner and outer superior PPCMv between the POAG and APAC groups was 5.9% and 4.4% (95% CI 1.9% to 9.9% and 1.0% to 7.7%, respectively; both p<0.010). Furthermore, POAG and APAC groups both had significantly lower PPCMv compared with controls (both, p<0.001).Conclusions While superficial peripapillary vessels were affected to similar degrees in POAG and APAC, PPCMv drop-out was greater with POAG versus APAC, suggesting that choroidal vessel density may be affected to a lesser extent following an acute increase in intraocular pressure before glaucoma develops

Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs.

BACKGROUND: Nonophthalmologist physicians do not confidently perform direct ophthalmoscopy. The use of artificial intelligence to detect papilledema and other optic-disk abnormalities from fundus photographs has not been well studied. METHODS: We trained, validated, and externally tested a deep-learning system to classify optic disks as being normal or having papilledema or other abnormalities from 15,846 retrospectively collected ocular fundus photographs that had been obtained with pharmacologic pupillary dilation and various digital cameras in persons from multiple ethnic populations. Of these photographs, 14,341 from 19 sites in 11 countries were used for training and validation, and 1505 photographs from 5 other sites were used for external testing. Performance at classifying the optic-disk appearance was evaluated by calculating the area under the receiver-operating-characteristic curve (AUC), sensitivity, and specificity, as compared with a reference standard of clinical diagnoses by neuro-ophthalmologists. RESULTS: The training and validation data sets from 6779 patients included 14,341 photographs: 9156 of normal disks, 2148 of disks with papilledema, and 3037 of disks with other abnormalities. The percentage classified as being normal ranged across sites from 9.8 to 100%; the percentage classified as having papilledema ranged across sites from zero to 59.5%. In the validation set, the system discriminated disks with papilledema from normal disks and disks with nonpapilledema abnormalities with an AUC of 0.99 (95% confidence interval [CI], 0.98 to 0.99) and normal from abnormal disks with an AUC of 0.99 (95% CI, 0.99 to 0.99). In the external-testing data set of 1505 photographs, the system had an AUC for the detection of papilledema of 0.96 (95% CI, 0.95 to 0.97), a sensitivity of 96.4% (95% CI, 93.9 to 98.3), and a specificity of 84.7% (95% CI, 82.3 to 87.1). CONCLUSIONS: A deep-learning system using fundus photographs with pharmacologically dilated pupils differentiated among optic disks with papilledema, normal disks, and disks with nonpapilledema abnormalities. (Funded by the Singapore National Medical Research Council and the SingHealth Duke-NUS Ophthalmology and Visual Sciences Academic Clinical Program.)

Acute Comitant Esotropia in a Child with a Cerebellar Tumor

Acute comitant esotropia is generally thought to be benign and further neurological investigationis not warranted

Susac's Syndrome in a 27-Year Old Female: The First Case Report in Iran

Susac's syndrome is an extremely rare neurological disorder with involving three systems: encephalopathy, branchretinal artery occlusion, and hearing loss

Associations of refractive amblyopia in a population of Iranian children

Background: To determine the factors associated with amblyopia in a referral clinical population. Methods: In this cross-sectional study, 164 subjects who were referred to an amblyopia clinic were enrolled and divided into two groups: refractive amblyopia group and refractive non-amblyopia group. Visual acuity, refractive measurements, and information on birth parameter and delivery mode were compared between both groups. Results: We included 164 children (91 children in the non-amblyopic group and 73 children in the amblyopic group) aged 5–10 years. 50.6% of children with amblyopia had anisometropia, defined as a difference among eyes in spherical equivalent of 1.00 D or more. The regression analysis revealed that amblyopia was strongly associated with hyperopia ≥2.00 D (odds ratio, 10.0; 95% CI, 3.27–30.58), anisometropia ≥1.00 D (odds ratio, 7.78; 95% CI, 3.64–16.61), astigmatism ≥1.00 D (odds ratio, 5.23; 95% CI, 2.48–11.02), and myopia ≥−2 D (odds ratio, 6.96; 95% CI, 1.9–25.28). There were also significant associations of amblyopia with low birth weight (≤2500 g), preterm birth (≤37 weeks), and dystocia (all P < 0.001). Conclusion: Prematurity, low birth weight, and dystocia as well as refractive errors were associated with amblyopia in our select patient population