Clinical characteristics and surgical outcomes in patients with superior oblique muscle palsy: a retrospective study on 1057 patients.

BACKGROUND: To evaluate the clinical findings of patients with SOP who underwent surgery. METHODS: This historical cohort study was performed on 1057 SOP patients managed with surgery in Farabi Hospital, Iran, from 2011 to 2022. RESULTS: There were 990 (93.7%) patients with unilateral SOP with the mean age of 21.8 ± 14.8 years. Of these, 715 patients (72.2%) were diagnosed with congenital SOP, and 275 patients (27.8%) had acquired SOP (P < 0.001). In contrast, 67 (6.3%) patients were diagnosed with bilateral SOP, with the mean age of 19.4 ± 15.6 years. Among these, 18 cases exhibited the masked type. The mean angle of vertical deviation in primary position at far in unilateral and bilateral cases was 15.6 ± 8.3 and 13.3 ± 9.1 △, respectively (P < 0.001). In unilateral cases, abnormal head posture (AHP) was detected in 847 (85.5%) patients and 12 (1.2%) had paradoxical AHP. Amblyopia was found in 89 (9.9%) unilateral and 7 (10.3%) bilateral cases. Solitary inferior oblique myectomy, was the most common surgery in both unilateral (n = 756, 77.1%) and bilateral (n = 35, 52.2%) patients. The second surgery was performed for 84 (8.6%) unilateral and 33 (49.3%) bilateral cases (P < 0.001). The prevalence of amblyopia and the mean angle of horizontal deviation were significantly higher in patients who needed more than one surgery (all P < 0.05). CONCLUSION: Congenital SOP was more than twice as frequent as acquired SOP and about 90% of unilateral and 50% of bilateral cases were managed with one surgery. Amblyopia and significant horizontal deviation were the most important factors for reoperation. TRIAL REGISTRATION: The Institutional Review Board approval was obtained from the Tehran University of Medical Sciences (IR.TUMS.FNM.REC.1400.012) and this study adhered to the tenets of the Declaration of Helsinki and HIPAA.

Vessel Density Features of Optical Coherence Tomography Angiography for Classification of Optic Neuropathies Using Machine Learning.

BACKGROUND: To evaluate the classification performance of machine learning based on the 4 vessel density features of peripapillary optical coherence tomography angiography (OCT-A) for classifying healthy, nonarteritic anterior ischemic optic neuropathy (NAION), and optic neuritis (ON) eyes. METHODS: Forty-five eyes of 45 NAION patients, 32 eyes of 32 ON patients, and 76 eyes of 76 healthy individuals with optic nerve head OCT-A were included. Four vessel density features of OCT-A images were developed using a threshold-based segmentation method and were integrated in 3 models of machine learning classifiers. Classification performances of support vector machine (SVM), random forest, and Gaussian Naive Bayes (GNB) models were evaluated with the area under the receiver-operating-characteristic curve (AUC) and accuracy. RESULTS: We divided 121 images into a 70% training set and 30% test set. For ON-NAION classification, best results were achieved with 50% threshold, in which 3 classifiers (SVM, RF, and GNB) discriminated ON from NAION with an AUC of 1 and accuracy of 1. For ON-Normal classification, with 100% threshold, SVM and RF classifiers were able to discriminate normal from ON with AUCs of 1 and accuracies of 1. For NAION-normal classification, with 50% threshold, the SVM and RF classified the NAION from normal with AUC and accuracy of 1. CONCLUSIONS: ML based on the combined peripapillary vessel density features of total vessels and capillaries in the whole image and ring image could provide excellent performance for NAION and ON distinction.

Vessel Density Features of Optical Coherence Tomography Angiography for Classification of Glaucoma Using Machine Learning.

PRCIS: Machine learning (ML) based on the optical coherence tomography angiography vessel density features with different thresholds using a support vector machine (SVM) model provides excellent performance for glaucoma detection. BACKGROUND: To assess the classification performance of ML based on the 4 vessel density features of peripapillary optical coherence tomography angiography for glaucoma detection. METHODS: Images from 119 eyes of 119 glaucoma patients and 76 eyes of 76 healthy individuals were included. Four vessel density features of optical coherence tomography angiography images were developed using a threshold-based segmentation method and were integrated into 3 models of machine learning classifiers. Images were divided into 70% training set and 30% test set. Classification performances of SVM, random forest, and Gaussian Naive Bayes models were evaluated with the area under the receiver operating characteristic curve (AUC) and accuracy. RESULTS: Glaucoma eyes had lower vessel densities at different thresholds. For differentiating glaucoma eyes, the best results were achieved with 70% and 100% thresholds, in which SVM classifier discriminated glaucoma from healthy eyes with an AUC of 1 and accuracy of 1. After SVM, the random forest classifier with 100% thresholds showed an AUC of 0.993 and an accuracy of 0.994. Furthermore, the AUC of our ML performance (SVM) was 0.96 in a subgroup analysis of mild and moderate glaucoma eyes. CONCLUSIONS: ML based on the combined peripapillary vessel density features of total vessels and capillaries in the whole image and ring image could provide excellent performance for glaucoma detection.

Disagreement of Radial Peripapillary Capillary Density Among Four Optical Coherence Tomography Angiography Devices.

Purpose: This prospective study evaluated the agreement among four optical coherence tomography angiography (OCTA) devices in the assessment of radial peripapillary capillary (RPC) density. Methods: The study included 48 eyes of 48 subjects (14 healthy, 19 glaucomatous, and 15 non-glaucomatous optic neuropathy). Each participant was scanned using four OCTA devices in a random sequence: RTVue XR Avanti (RTVue), DRI OCT Triton (Triton), Revo NX 130 (Revo), and PLEX Elite 9000 (PlexE). All 6 × 6-mm grayscale OCTA images from each device were analyzed for RPC density using a customized algorithm. Agreement between each pair of devices was assessed using intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results: There was a poor correlation between devices in all comparisons (RTVue-Triton, ICC = 0.34; RTVue-Revo, ICC = 0.31; RTVue-PlexE, ICC = 0.28; Triton-Revo, ICC = 0.31; Triton-PlexE, ICC = 0.17; Revo-PlexE, ICC = 0.34). Significant proportional biases (P < 0.05) and wide limits of agreement with apparent constant biases were identified in all comparisons. The mean difference was greatest for the RTVue-Revo pair (-49.3%; 95% confidence interval [CI], -52.9 to -45.8) and smallest for the Triton-PlexE pair (-7.7%; 95% CI, -10.1 to -5.3). Conclusions: The RPC densities obtained from each device had poor inter-device agreement and significant biases and cannot be used interchangeably. Translational Relevance: RPC density obtained from different OCTA devices is not interchangeable; thus, the progression of optic neuropathy should be monitored using the same OCTA device.

Differentiating Glaucomatous Optic Neuropathy From Non-glaucomatous Optic Neuropathies Using Deep Learning Algorithms.

PURPOSE: A deep learning framework to differentiate glaucomatous optic disc changes due to glaucomatous optic neuropathy (GON) from non-glaucomatous optic disc changes due to non-glaucomatous optic neuropathies (NGONs). DESIGN: Cross-sectional study. METHOD: A deep-learning system was trained, validated, and externally tested to classify optic discs as normal, GON, or NGON, using 2183 digital color fundus photographs. A Single-Center data set of 1822 images (660 images of NGON, 676 images of GON, and 486 images of normal optic discs) was used for training and validation, whereas 361 photographs from 4 different data sets were used for external testing. Our algorithm removed the redundant information from the images using an optic disc segmentation (OD-SEG) network, after which we performed transfer learning with various pre-trained networks. Finally, we calculated sensitivity, specificity, F1-score, and precision to show the performance of the discrimination network in the validation and independent external data set. RESULTS: For classification, the algorithm with the best performance for the Single-Center data set was DenseNet121, with a sensitivity of 95.36%, precision of 95.35%, specificity of 92.19%, and F1 score of 95.40%. For the external validation data, the sensitivity and specificity of our network for differentiating GON from NGON were 85.53% and 89.02%, respectively. The glaucoma specialist who diagnosed those cases in masked fashion had a sensitivity of 71.05% and a specificity of 82.21%. CONCLUSIONS: The proposed algorithm for the differentiation of GON from NGON yields results that have a higher sensitivity than those of a glaucoma specialist, and its application for unseen data thus is extremely promising.

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.

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.

Hemi-central retinal artery occlusion following methanol toxicity.

Objective: To describe a patient with hemi-retinal artery occlusion following methanol toxicity. Methods: Observational case report. Results: We report a case presented with an acute altitudinal visual field loss in the right eye following consumption of illicit alcoholic drink. In fundus photography, a well demarcated superior hemi-retinal whitening with foveal sparing was noted. Careful inspection of the optic nerve head in the right eye revealed that there was no main trunk of the central retinal artery anterior to the lamina cribrosa. Two separately emerging superior and inferior arterial trunks were noted. In fundus fluorescein angiography, earlier dye filling in the territory of the superior arterial trunk compared to the inferior arterial trunk was evident. Conclusion: Hemi-central retinal occlusion may happen as an ocular consequence of methanol toxicity in patients with a proximal bifurcation of the central retinal artery.

Measurement of retinal nerve fiber layer thickness with a deep learning algorithm in ischemic optic neuropathy and optic neuritis.

This work aims at determining the ability of a deep learning (DL) algorithm to measure retinal nerve fiber layer (RNFL) thickness from optical coherence tomography (OCT) scans in anterior ischemic optic neuropathy (NAION) and demyelinating optic neuritis (ON). The training/validation dataset included 750 RNFL OCT B-scans. Performance of our algorithm was evaluated on 194 OCT B-scans from 70 healthy eyes, 82 scans from 28 NAION eyes, and 84 scans of 29 ON eyes. Results were compared to manual segmentation as a ground-truth and to RNFL calculations from the built-in instrument software. The Dice coefficient for the test images was 0.87. The mean average RNFL thickness using our U-Net was not different from the manually segmented best estimate and OCT machine data in control and ON eyes. In NAION eyes, while the mean average RNFL thickness using our U-Net algorithm was not different from the manual segmented value, the OCT machine data were different from the manual segmented values. In NAION eyes, the MAE of the average RNFL thickness was 1.18 ± 0.69 µm and 6.65 ± 5.37 µm in the U-Net algorithm segmentation and the conventional OCT machine data, respectively (P = 0.0001).

Clinical characteristics and surgical approach in Duane retraction syndrome: a study of 691 patients.

PURPOSE: To evaluate the clinical findings of different types of Duane retraction syndrome (DRS). STUDY DESIGN: Retrospective. METHODS: This study was performed on 691 patients with DRS who underwent surgery. Clinical examinations included laterality, abnormal head posture (AHP), corrected distance visual acuity (CDVA), refractive error, amblyopia, deviation, overshoots, and type of surgery. RESULTS: The mean age of patients with DRS was 16.7 ± 12.5 (range 1.0-73) years. The patients included 396 (57.3%) women and 295 (42.7%) men (P < 0.001). DRS type I, was observed in 429 (62.1%), II in 168 (24.3%), III in 88 (12.7%) and IV in 6 (0.9%) patients. Unilateral DRS was observed OS in 628 (90.9%) [471 (%78.9) and OD in 157 (21.1%) eyes (P < 0.001)]. O ther clinical findings were AHP (n = 522, 78.1%), overshoot (n = 236, 34.2%) and amblyopia (n = 118, 17.1%). The prevalence of overshoot in types I, II, and III was 17.5% (75/429), 60.7% (102/168) and 64.8% (57/88), respectively (P < 0.001). The prevalence of amblyopia was significantly lower in patients with AHP (80/522, 15.3%) compared to patients with normal head posture (38/169, 22.5%) (P = 0.023). The mean angle of deviation in the primary position (PP) at distance was 21.7 ± 11.5 △ for esotropic group and 17.8 ± 12.4 △ for exotropic group. Sixty-two (9.0%) patients required second surgery for resolving residual misalignment (1.1 surgeries for each patient). CONCLUSIONS: About two-thirds of DRS patients had AHP, one-third had overshoots, and one-sixth had amblyopia. The results show that different types of DRS are associated with different epidemiological and clinical characteristics.

Follow-up of Nonarteritic Anterior Ischemic Optic Neuropathy With Optical Coherence Tomography Angiography.

BACKGROUND: Peripapillary and macular microvasculature alterations after nonarteritic ischemic optic neuropathy (NAION) have been investigated in several studies. We aimed to explore the vascular changes from acute NAION (aNAION) to chronic NAION (cNAION). METHODS: This prospective observational study composed of 16 eyes with aNAION and 40 healthy age-matched controls. Eyes with NAION were followed up for more than 6 months after acute event. Optical coherence tomography angiography (OCTA) was used to evaluate peripapillary and macular vessel densities (VDs). The customized software was used for calculating deep retinal VD to attenuate the large superficial vessel projection effect. RESULT: The mean age of patients with NAION and controls was 56.13 ± 13.2 and 54.46 ± 15.5 years, respectively (P = 0.195). Radial peripapillary capillary density was significantly lower in both eyes with aNAION and eyes with cNAION than healthy eyes. Peripapillary capillary density decreased significantly from the acute to the chronic phase of NAION with values of 41.77 ± 4.05% and 34.35 ± 7.30%, respectively (P < 0.001). The mean superficial macular VD was 46.83 ± 3.47% in aNAION and 44.49 ± 4.50% in cNAION eyes with no significant difference between them (P = 0.252), but both were lower than control eyes. Deep macular VD was not affected in aNAION and cNAION eyes compared with control eyes. Correlation analysis in eyes with cNAION revealed that there were significant correlations between peripapillary nerve fiber layer and the capillary density (r = 0.772, P < 0.001) and between ganglion cell complex thickness and corresponding superficial macular VD. CONCLUSIONS: Although a decrease in peripapillary capillary density in aNAION eyes with active disc edema progressed when evaluated in the cNAION state, progressive VD loss was not observed in the macular area, suggesting a nonprogressive nature of macular vessel involvement in NAION.

Neuroprotective Effect of Intravitreal Single-Dose Lithium Chloride after Optic Nerve Injury in Rats.

OBJECTIVE: Lithium is an old drug to control bipolar disorder. Moreover, it presents neuroprotective effects and supports neuronal plasticity. The aim of this study was to evaluate neuroprotective effect of intravitreal lithium after optic nerve injury. METHODS: Three dosages of lithium chloride, including 2 pmol, 200 pmol, and 2 nmol, were injected intravitreally after rat optic nerve injury. Proteins expression were assessed by western blot. Nitric oxide (NO) metabolites were measured by Griess test. Visual evoked potential (VEP) and optical coherence tomography (OCT) measurement were performed after trauma induction, in addition to H & E and TUJ1 staining of ganglion cells. RESULTS: Western blot depicted lithium can significantly increase antiapoptotic Bcl-2 protein level and reduce p-ERK, Toll-like receptor 4 (TLR4) and proapoptotic proteins such as Bax level in retinal tissue and Griess test reflected that NO metabolites level decreased in lithium treated eyes (P < .05). While, OCT showed no significant changes (P = .36 and P = .43 comparing treated group with trauma) in retinal ganglion cell layer thickness after lithium injection, VEP P2 wave amplitude increased significantly (P < .01) in lithium-treated eyes and its latency reduced (P < .05 for N1 wave and P < .01 for P2 wave). Tuj1 antibody-labeled retinal ganglion cells analyzing showed that the number of retinal ganglion cells were significantly higher in lithium treated eyes compared to untreated eyes with optic nerve injury. CONCLUSION: It seems intravitreally lithium has optic nerve neuroprotective effects by various mechanisms like overexpression of antiapoptotic proteins, suppressing proinflammatory molecules and proapoptotic factors, and decreasing nitric oxide.

Automated Evaluation of Parapapillary Choroidal Microvasculature in Pseudoexfoliation Syndrome and Pseudoexfoliation Glaucoma.

OBJECTIVE: To determine whether parapapillary choroidal microvasculature (PPCMv) density as measured by optical coherence tomography angiography differs between pseudoexfoliation syndrome (PXS) and pseudoexfoliation glaucoma (PXG). DESIGN: Cross-sectional study. METHODS: One hundred ninety-two eyes of 120 subjects from 2 academic referral institutions were enrolled. Automated PPCMv density was calculated using custom Matlab software in inner and outer annuli around the optic nerve region in addition to peripapillary superficial vasculature. Linear modeling was used to compare vessel densities among groups. RESULTS: Data from 64 eyes with PXS, 84 eyes with PXG, and 44 eyes healthy control subjects were analyzed. The differences of visual field mean deviation and peripapillary retinal nerve fiber layer thickness among study groups were statistically significant with lower values in PXG eyes compared with the PXS and control groups. Peripapillary superficial retinal vessel densities were significantly reduced in patients with PXG compared with patients with PXS and normal control subjects (all P < .001) without a difference between PXS and control eyes. Customized outer annular PPCMv density in the PXG group with a value of 11.1% (SD 5.1%) was lower than that in PXS with a value of 13.2% (SD 5.3%; P = .001). Similarly, PXS values were lower than those of control eyes with a value of 18.6% (SD 5.1%; P < .001). CONCLUSION: A progressive decrease in outer PPCMv from the control group to those with PXS without glaucoma to those with PXS and glaucoma (PXG) showed deep peripapillary vasculopathy in pseudoexfoliation syndrome. Choroidal vessel density may be affected early in the course of pseudoexfoliation before glaucoma develops.

Optical coherence tomography angiography in glaucoma.

Assessment of the vasculature within the optic nerve, peripapillary superficial retina, macula, and peripapillary choroid can be determined in glaucoma using optical coherence tomography angiography (OCTA). Decreased perfusion within the pre-laminar layer of the optic nerve has been correlated with glaucoma severity. The peripapillary superficial retinal vessel density allows diagnosis and detection of glaucoma progression in a manner similar to the peripapillary retinal nerve fiber layer (RNFL) thickness. Furthermore, decreased peripapillary vessel density of the intact hemiretina or unaffected eye of glaucomatous eyes suggests that vascular changes can occur prior to detectable visual field damage. The accuracy for glaucoma detection of the macular ganglion cell (MGC) thickness compared to macular vessel density has differed among studies. Several studies have reported reduction of macular vessel density as well as its ganglion cell thickness. Results of studies evaluating the parapapillary choroid have shown a greater prevalence of choroidal microvasculature dropout in glaucomatous eyes with a parapapillary gamma zone, which is associated with central visual field defects or glaucoma progression. It remains unclear whether the reduced vessel density in glaucoma is a primary event or secondary to glaucomatous damage. Further studies are warranted to elucidate this question.

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.).

Effect of phenytoin on retinal ganglion cells in acute isolated optic neuritis.

OBJECTIVE: Phenytoin has been shown to reduce the peripapillary retinal nerve fiber layer (pRNFL) loss in optic neuritis (ON). We evaluated the effects of phenytoin on retinal ganglion layers and visual outcomes of newly diagnosed acute ON. METHODS: A randomized, placebo-controlled trial was conducted in a tertiary referral eye hospital and patients with the first episode of typical demyelinating ON, without any history of multiple sclerosis were randomly assigned to phenytoin or placebo. The thickness of ganglion cell-inner plexiform layer (GCIPL) measured by optical coherence tomography (OCT) was considered as the primary outcome. RESULTS: One patient in the phenytoin group developed severe cutaneous rashes that progressed to Stevens-Johnson syndrome (SJS)/toxic epidermal necrosis (TEN), and further allocation of patients to the phenytoin group was stopped, and finally fifteen participants were included in the phenytoin group. Fifty-one patients were enrolled to the placebo group, from which four were excluded. Both visual acuity and field were not significantly different between the control and phenytoin groups after 1 and 6 months. Mean 3- and 6-mm macular GCIPL thicknesses decreased after 6 months to 73.6 ± 14.1 and 57.9 ± 7.5 µm, respectively, in the phenytoin group and to 71.6 ± 15.7 and 55.6 ± 6.6 µm, respectively, in the placebo group with no significant differences between the two groups (P = 0.77 and P = 0.26, respectively, linear multilevel model). CONCLUSION: Phenytoin is not probably safe and effective as neuroprotection after acute ON. Further investigation with other sodium channel inhibitors could be considered.

Automated Evaluation of Parapapillary Choroidal Microvasculature in Ischemic Optic Neuropathy and Open Angle Glaucoma.

Purpose: To determine whether parapapillary choroidal microvasculature (PPCMv) density as measured by optical coherence tomography angiography differs between nonarteritic anterior ischemic optic neuropathy (NAION) and primary open angle glaucoma (POAG). Methods: Thirty-seven eyes with chronic NAION, 34 unaffected fellow eyes with NAION, 47 moderate and severe POAG eyes, and 54 healthy control subjects were evaluated. Automated PPCMv density was calculated using custom Matlab software in inner and outer annuli around the optic nerve region in addition to peripapillary superficial retinal vessels. Results: Linear models showed no difference in peripapillary retinal nerve fiber layer between NAION and POAG eyes. Mean peripapillary superficial small vessels in the NAION and POAG groups were 36.62 ± 7.1% and 39.72 ± 8.18% without a statistically difference between them (P = 0.16). Mean inner and outer annular region PPCMv densities in the NAION group were 26.55 ± 9.2% and 17.81 ± 6.9%, which were not different from unaffected fellow eyes and the control group. However, the POAG group had significantly reduced PPCMv density in both inner and outer annuli with values of 15.84 ± 6.5% and 12.80 ± 5.0%, respectively, compared with normal subjects (both P < 0.001). Inner and outer circle PPCMv densities were also significantly reduced in the POAG group compared with the NAION group. Conclusions: Reduced PPCMv density in POAG eyes shows that deep optic nerve head ocular blood flow may contribute to axonal damage in patients with glaucoma.

Optic canal size in idiopathic intracranial hypertension and asymmetric papilledema.

OBJECTIVE: Asymmetric papilledema (AP) is a rare condition in idiopathic intracranial hypertension (IIH). As the pathophysiology of papilledema developement in IIH remains unclear, the study of AP could clarify some etiologic aspects. We aimed to evaluate bony optic canal size in IIH patients with AP. PATIENTS AND METHODS: All IIH patients based on modified Dandy criteria in our referral tertiary eye hospital underwent neuro-opthalmologic exams and grading of papilledema according to modified Frisén scale. Very asymmetric papilledema (VAP) defined as a ≥2 grade difference between the two eyes. Clinical features, cerebrospinal fluid opening pressure (CSF OP), best corrected visual acuity, Humphery visual field, and brain magnetic resonance imaging (MRI) and MR venography was performed for all patients. Spiral orbital computed tomography (CT) scan which is the choice method for details of bony structures with axial, coronal and sagittal planes was done in patients with VAP. RESULT: 59 patients with IIH were diagnosed that 18.6% of them (n = 11) had VAP. There was no IIH patient with strictly unilateral Papilledema. Presenting symptoms and CSF OP was not significantly different between patients with symmetric and asymmetric papilledema. In patients with VAP, bony optic canal size was not statistically significant different in axial, coronal and sagittal plane when comparing the eye with higher grade edema to the fellow eye. CONCLUSION: Our study showed that bony optic canal size evaluated by orbital CT scan was not different in VAP in IIH patients. Finding the exact pathophysiology of AP need further studies.

Arteritic Anterior Ischaemic Optic Neuropathy with Unusual Systemic Manifestations.

An 84-year-old man presented with anterior ischaemic optic neuropathy with unusual histopathological findings for giant cell arteritis on temporal artery biopsy. Further systemic manifestations occurred three months later with lung nodules, renal dysfunction and sinusitis. A probable diagnosis of polyangiitis overlap syndrome was made and he was treated with steroids and an immunomodulator.