Optic Disc Vessels Research Articles

Automated Diagnosis of Age Related Macular degeneration from fundus image

Retinal image analysis paves the way for easy diagnosis of retinal pathologies and acts as a first aid tool for ophthalmologist. In this paper a novel approach has been proposed for the automated diagnosis of age related macular degeneration (AMD) from fundus image. A landmark called Drusen, in fundus image whose detection and its location identification play the crucial to detect and grade AMD. In pre-processing step optic disk and blood vessels are detected and removed. By applying log Gabor filter to the pre-processed image energy has been computed. Gray level co-occurrence matrix has been calculated for the image and after applying fuzzy entropy thresholding technique, two discriminative features auto correlation and contrast features have been chosen. Classification is done by using a total of three feature vector using k-nearest neighbour, Support Vector Machine, Random forest classifier. Highest sensitivity is obtained in the case of Random forest classifier. SVM with RBF kernel also does better classification next to random forest.

Obtaining optic disc center and pixel region by automatic thresholding methods on morphologically processed fundus images

Development of automatic retinal disease diagnosis systems based on retinal image computer analysis can provide remarkably quicker screening programs for early detection. Such systems are mainly focused on the detection of the earliest ophthalmic signs of illness and require previous identification of fundal landmark features such as optic disc (OD), fovea or blood vessels. A methodology for accurate center-position location and OD retinal region segmentation on digital fundus images is presented in this paper. The methodology performs a set of iterative opening–closing morphological operations on the original retinography intensity channel to produce a bright region-enhanced image. Taking blood vessel confluence at the OD into account, a 2-step automatic thresholding procedure is then applied to obtain a reduced region of interest, where the center and the OD pixel region are finally obtained by performing the circular Hough transform on a set of OD boundary candidates generated through the application of the Prewitt edge detector. The methodology was evaluated on 1200 and 1748 fundus images from the publicly available MESSIDOR and MESSIDOR-2 databases, acquired from diabetic patients and thus being clinical cases of interest within the framework of automated diagnosis of retinal diseases associated to diabetes mellitus. This methodology proved highly accurate in OD-center location: average Euclidean distance between the methodology-provided and actual OD-center position was 6.08, 9.22 and 9.72 pixels for retinas of 910, 1380 and 1455 pixels in size, respectively. On the other hand, OD segmentation evaluation was performed in terms of Jaccard and Dice coefficients, as well as the mean average distance between estimated and actual OD boundaries. Comparison with the results reported by other reviewed OD segmentation methodologies shows our proposal renders better overall performance. Its effectiveness and robustness make this proposed automated OD location and segmentation method a suitable tool to be integrated into a complete prescreening system for early diagnosis of retinal diseases.

Optic nerve and retinal features in uveitis associated with juvenile systemic granulomatous disease (Blau syndrome).

To determine whether patients with juvenile systemic granulomatous disease (JSGD) (Blau syndrome) and uveitis have a characteristic ocular phenotype. Clinical and imaging data were collected retrospectively from patients attending the Regional Combined Paediatric Rheumatology and Ocular Inflammatory Service, Bristol Eye Hospital. General demographic information, laterality of the uveitis, age at onset, anatomical classification and course of the uveitis, clinical phenotype and specific NOD2 mutation were recorded for each patient. Seventeen eyes from nine patients (five males; four females) were included in the study. Mean age at the disease onset was 15 months, range 1-84 months. Eight patients had bilateral uveitis. Anterior uveitis was present in five eyes, intermediate uveitis in two eyes, and there were 10 eyes with panuveitis, manifesting as multifocal choroiditis. Appearance of optic disc included indistinct disc margins in six eyes, optic nerve head pallor in six eyes, optic disc vessel sheathing in four eyes, and there was peripapillary hypo/hyperpigmentation in 13 eyes accompanied with characteristic peripapillary nodular excrescences. Among NOD2 mutations, the p.R334W was the most commonly detected (n: four cases), and three patients carried novel variants, the p.E338D and p.D390V variants in one patient, and the p.H520Y and p.Q809K variants in two different patients. Chronic bilateral panuveitis and a nodular peripapillary appearance in childhood onset uveitis are characteristic features of JSGD, which support the need for an appropriate genetic NOD2 analysis.

A SEQUENTIAL LEARNING METHOD FOR DETECTION AND CLASSIFICATION OF EXUDATES IN RETINAL IMAGES TO ASSESS DIABETIC RETINOPATHY

One of the greatest concerns to the personnel in the current health care sector is the severe progression of diabetes. People can often have diabetes and be completely unaware as the symptoms seem harmless when they are seen on their own. Diabetic retinopathy (DR) is an eye disease that is associated with long-standing diabetes. Retinopathy can occur with all types of diabetes and can lead to blindness if left untreated. The conventional method followed by ophthalmologists is the regular testing of the retina. As this method takes time and energy of the ophthalmologists, a new feature-based automated technique for classification and detection of exudates in color fundus image is proposed in this paper. This method reduces the work of the professionals while examining every fundus image rather than only on abnormal image. The exudates are detected from the color fundus image by applying a few pre-processing techniques that remove the optic disk and similar blood vessels using morphological operations. The pre-processed image was then applied for feature extraction and these features were utilized for classification purpose. In this paper, a novel classification technique such as self-adaptive resource allocation network (SRAN) and meta-cognitive neural network (McNN) classifier is employed for classification of images as exudates, their severity and nonexudates. SRAN classifier makes use of self-adaptive thresholds to choose the appropriate training samples and removes the redundant samples to prevent over-training. These selected samples are availed to improve the classification performance. McNN classifier employs human-like meta-cognition to regulate the sequential learning process. The meta-cognitive component controls the learning process in the cognitive component by deciding what-to-learn, when-to-learn and how-to-learn. It is therefore evident that the implementation of human meta-cognitive learning principle improves efficient learning.

C-reactive protein and chitinase 3-like protein 1 as biomarkers of spatial redistribution of retinal blood vessels on digital retinal photography in patients with diabetic retinopathy.

The aim of the study was to investigate the correlation between the levels of C-reactive protein (CRP) and chitinase 3-like protein 1 (YKL-40) in blood samples with morpohometric parameters of retinal blood vessels in patients with diabetic retinopathy. Blood laboratory examination of 90 patients included the measurement of glycemia, HbA1C, total cholesterol, LDL-C, HDL-C, triglycerides and CRP. Levels of YKL-40 were detected and measured in serum by ELISA (Micro VueYKL-40 EIA Kit, Quidel Corporation, San Diego, USA). YKL-40 correlated positively with diameter and negatively with number of retinal blood vessels. The average number of the blood vessels per retinal zone was significantly higher in the group of patients with mild non-proliferative diabetic retinopathy than in the group with severe form in the optic disc and all five retinal zones. The average outer diameter of the evaluated retinal zones and optic disc vessels was significantly higher in the group with severe compared to the group with mild diabetic retinopathy. Morphological analysis of the retinal vessels on digital fundus photography and correlation with YKL-40 may be valuable for the follow-up of diabetic retinopathy.

MASK IMAGE GENERATION FOR SEGMENTING RETINAL FUNDUS IMAGE FEATURES INTO ISNT QUADRANTS USING ARRAY CENTROID METHOD

Retinal fundus image processing paves the way for diagnosis of many eye disorders. The fundus image features such as optic disc, optic cup, optic rim and blood vessels help to analyse the pathological condition of eye. The analysis involves calculation of ocular parameters such as Rim to Disc Ratio (RDR) and Inferior Superior Nasal Temporal (ISNT) Ratio and verification of ISNT Rule. For this analysis the fundus image features have to be segmented into ISNT quadrants. This paper presents a novel approach towards mask image generation for segmenting fundus image feature into ISNT quadrants using array centroid method. The existing method uses a predefined mask image which is not accurate and the proposed array centroid method overcomes the limitations of existing method. The method involves centroid calculation, array initialization; mask image generation and, mask- feature image multiplication. The proposed method is applied to the fundus images collected from a reputed eye hospital.

CRITICAL EVALUATION OF THE USABILITY OF AUGMENTED REALITY OPHTHALMOSCOPY FOR THE TRAINING OF INEXPERIENCED EXAMINERS

To measure the value of augmented reality technology usage to teach the medical students performing binocular indirect ophthalmoscopy. Thirty-seven medical students were randomly assigned to the training of binocular indirect ophthalmoscopy either in the conventional way or with augmented reality ophthalmoscopy (ARO). For testing student's skills, they had to examine a real person using a conventional ophthalmoscopy system and draw the optic disk. They also had to fill out a questionnaire. Subjective and objective evaluations were performed. Thirty-seven students were randomly assigned to two groups. Eighteen students were trained with conventional ophthalmoscopy and 19 students with ARO. The questionnaires showed no differences. Performing an objective analysis, the median ophthalmoscopy training score for the conventional ophthalmoscopy group was 1.2 (range, 0.67-2) and showed a significant difference (P < 0.0033) to the ARO group (median 2; range, 0.67-2). The study provides evidence that a single ARO training is efficient to improve ophthalmoscopy skills. As the objective analysis showed, the ARO group had a significantly superior performance. Our study also indicates that subjective evaluation of the fundus drawings without systematic analysis is prone to errors.

A60: Optic Nerve and Retinal Features in Uveitis Associated With Juvenile Systemic Granulomatous Disease (Blau Syndrome)

Background/Purpose:Juvenile systemic granulomatous disease (JSGD), also known as Blau syndrome, is a dominantly‐inherited autoinflammatory disorder associated with gain‐of‐function mutations in the NOD2 gene. The aim of this study was to determine whether patients with JSGD and uveitis have a specific ocular phenotype.Methods:Clinical and imaging data were collected retrospectively from patients attending the Regional Combined Paediatric Rheumatology and Ocular Inflammatory Service, Bristol Eye Hospital. General demographic information, laterality of the uveitis, age at onset, anatomical classification and course of the uveitis, clinical phenotype, and specific NOD2 mutation were recorded for each patient. All data were recorded in a database designed in Microsoft® Access®. Statistical analysis was performed using SPSS 20.0 (Cary, NC).Results:Seventeen eyes from 9 patients (5 males; 4 females) were included in the study. Mean age at the disease onset was 15 months; range 1–84 months. Eight patients had bilateral uveitis. Anterior uveitis was present in five eyes, intermediate uveitis in 2 eyes and there were 10 eyes with panuveitis, manifesting as multifocal choroiditis. Appearance of optic disc included indistinct disc margins in 6 eyes, optic nerve head palor in 6 eyes and optic disc vessels sheathing in 4 eyes. Fundal appearance included peripapillary hypo/hyperpigmention in 13 eyes accompanied with characteristic peripapillary nodular excrescences. Among NOD2 mutations, the p.R334W was the most commonly detected (n: 4 cases) and three patients carried novel variants, the p.E338D and p.D390V variants in one patient, and the p.H520Y and p.Q809K variants in two different patients.Conclusion:Chronic bilateral panuveitis and a nodular peripapillary appearance in childhood onset uveitis are characteristic features of JSGD, which support the need for an appropriate genetic NOD2 analysis.

Early detection and classification of microaneurysms in retinal fundus images using sequential learning methods

Diabetic retinopathy is the most common diabetic eye disease and causes blindness if not treated on time. Microaneurysms are one of the first clinical signs of diabetic retinopathy and appear as small red dots on fundus images. The incidence of blindness can be reduced by detecting microaneurysms at an earlier stage. In this paper, a new method is proposed for detection of microaneurysms from the colour fundus retinal images to assist the eye care specialist to examine large populations of patient. The microaneurysms are detected from the colour fundus image by applying the pre-processing techniques in order to remove the optic disc and similar blood vessels using morphological operations. The pre-processed image was then used for feature extraction, and these features were used for the purpose of classification. The classifiers used are support vector machine, Meta-cognitive Neural Network (McNN) and Self-adaptive Resource Allocation Network (SRAN), and their performances are compared and presented.

Bio-medical imaging: Localization of main structures in retinal fundus images

Retinal fundus images have three main structures, the optic disk, fovea and blood vessels. By examining fundus images, an ophthalmologist can diagnose various clinical disorders of the eye and the body, typically indicated by changes in the diameter, area, branching angles and tortuosity of the three ma in retinal structures. Knowledge of the optic disk position is an important diagnostic index fo r many diseases related to the retina. In this paper, localization of optic disc is discussed. Optic disk detection is based on morphological operationsand smoothing filters. Blood vessels are extracted using the green component of a colour retinal image with the help of a median filter. Maximum intensity values are validated with blood vessels to localize the optic disk location. The proposed method has shown significant improvements in results.

Segmentation on the Key Structures of the Fundus Digital Image

Fundus abnormalities were usually diagnosed by clinical ophthalmologists using the equipment like ophthalmoscope, which was influenced by complex method, subjective fault and low efficiency. Fortunately, fundus can be shown in the key structures of the fundus digital image. Hence, it is necessary to develop a computer-aided fundus image processing system as a tool to assist in the diagnosis diseases. Algorithms were proposed including the pre-processing such as contrast enhancement and spatial filtering, binaryzation, morphology, boundary extraction and skeleton extraction. This paper preliminary summarized the key technologies of segmentation on the structures of optic cup, optic disc and blood vessel. Experiments were performed in MATLAB. Automatic algorithms were evaluated to be able to detect the key structures of the fundus digital image. It is expected to be applied in computer-aided fundus image processing system.

INTRAVITREAL BEVACIZUMAB IN THE TREATMENT OF DIABETIC OCULAR NEOVASCULARIZATION

To evaluate the efficacy of intravitreal bevacizumab for treating diabetic retinal and/or iris neovascularization. Consecutive, prospective, interventional case series study of 60 eyes with diabetic retinal and/or iris neovascularization. Patients had a complete ocular examination before receiving 1.25 mg (0.05 mL) of intravitreal bevacizumab. Abnormal new vessels elsewhere in the retina, optic disk, or iris were graded by size and associated hemorrhage or glaucoma. Patients had complete postinjection ophthalmic evaluations with regrading of the abnormal new vessels at 3 months and 6 months. The main outcome measures included clinical partial or total regression of abnormal new vessels, changes in visual acuity, and complications related to the intravitreal injections. Twenty-six patients (47.3%) were men (mean age, 59 years). Abnormal new vessel regression at 6 months occurred in 65% of new vessels of the iris (P = 0.001), 45% of new vessels of the optic disk (P = 0.009), and 43% of new vessels elsewhere (P = 0.008). The visual acuity improved in 20% of eyes, which was not significant (P = 0.235); the visual acuity deteriorated in 23% of eyes (P = 0.163). No systemic or ocular side effects developed except for postinjection hypotony in one eye. Intravitreal bevacizumab is a well-tolerated medication that causes regression of abnormal diabetic neovascularization. New vessels of the iris responded more than new vessels of the optic disk and new vessels elsewhere.

Vessels Extraction from Retinal Images

The main cause of eye diseases in the working human is Diabetic retinopathy. Eye disease can be prevented if detects early. The extraction of blood vessels from retinal images is an essential and challenging task in medical diagnosis and analysis. This paper describes the effective and efficient extraction of blood vessels from retinal image by using Kirsch's templates. The Kirsch's edge operators detect the edges using eight filters, generated by the compass rotation mechanism. The method is used to automatic detection of landmark features of the fundus, such as the optic disc, fovea and blood vessels. I. Introduction The extraction of Retinal blood vessel is an essential step for the diagnosis of various eye diseases. Retinal images of humans play a crucial role in the detection and diagnosis of several eye diseases for the oculists (1-2). Color retinal images are used in mass screen systemic diseases such as Diabetic Retinopathy (DR). The risk of the Diabetic Retinopa-thy increases with age and small eye blood vessels damaged the due to this disease. The information about blood vessels, such as length, width, diameter and branching pattern, can help to diagnose the symptom of diseases (3-4). The oculists may examine retinal images and give the diagnostic results by searching the possible anomalies like diabetic retinopathy, glaucoma and retinal artery occlusion. With the help of computer aided diagnosis (CAD), the success rate of the treatment of these diseases may increase significantly. If the retinopathy detects in early stage (5-6), the probability of visual loss resulting from diabetic retinopathy can be prevented. The filtering based method which is used for the effective extraction the blood vessels of retinal images are described in (7-8). In the past various techniques are used to extract the blood vessels from retinal images. One technique not only finds the blood vessels that originate from a set of primary starting point but also finds all branches off of the primary vessels. The second method use Matched Filter (MF) for the extraction of blood vessels. This method will respond not only to vessels but also to non-vessel edges (9). The third method is the novel hybrid automatic approach for the extraction of retinal image vessels which reduce the weak edges and noise, and finally results the blood vessels extraction. In this paper a method is proposed which uses the Kirsch's templates for the extraction of the blood vessels from retinal images. The rest of paper is organized into 5 Sections. The Kirsch's edge operators are described in Section 2. Section 3 explains proposed method for the extraction of blood vessels from retinal images. Section 4 shows the results and discussion and finally, the conclusion is given in Section 5.

Sweet's syndrome with panuveitis resembling Behçet's disease

Sweet's syndrome (SS) is a skin disorder clinically characterized by fever, neutrophilia, and painful edematous plaques that occasionally causes posterior uveitis. We present two cases of SS with panuveitis resembling Behçet's disease (BD). Two patients with panuveitis associated with SS. The patient in case 1 was a 57-year-old Japanese man who developed acute severe iritis with hypopyon in the left eye. Fluorescein angiography (FA) performed 1 month after treatment showed findings observed in posterior uveitis: dye leakage from the optic disc and a petaloid pattern of hyperfluorescence in the macular region. The patient in case 2 was a 64-year-old Japanese man who complained of blurred vision in his left eye. Faint flare and occasional cells were present in the left anterior chamber, 2+ cells in the anterior vitreous, and 2+ vitreous opacification in the left eye. FA demonstrated dye leakage from the optic disc and peripheral capillary vessels in both eyes. Both patients were diagnosed as having SS on the basis of fever, neutrophilia, elevated C-reactive protein, and skin biopsy results of neutrophilic infiltration without vasculitis. Differentiation of SS from BD based on the ocular manifestations is difficult. Ophthalmologists should bear in mind that SS can exhibit panuveitis resembling BD.

SEGMENTING THE EYE FUNDUS IMAGES FOR IDENTIFICATION OF BLOOD VESSELS

Retinal (eye fundus) images are widely used for diagnostic purposes by ophthalmologists. The normal features of eye fundus images include the optic nerve disc, fovea and blood vessels. Algorithms for identifying blood vessels in the eye fundus image generally fall into two classes: extraction of vessel information and segmentation of vessel pixels. Algorithms of the first group start on known vessel point and trace the vasculature structure in the image. Algorithms of the second group perform a binary classification (vessel or non-vessel, i.e. background) in accordance of some threshold. We focus here on the binarization [4] methods that adapt the threshold value on each pixel to the global/local image characteristics. Global binarization methods [5] try to find a single threshold value for the whole image. Local binarization methods [3] compute thresholds individually for each pixel using information from the local neighborhood of the pixel. In this paper, we modify and improve the Sauvola local binarization method [3] by extending its abilities to be applied for eye fundus pictures analysis. This method has been adopted for automatic detection of blood vessels in retinal images. We suggest automatic parameter selection for Sauvola method. Our modification allows determine/extract the blood vessels almost independently of the brightness of the picture.

Optic perineuritis secondary to tuberculosis: A rare case presentation

A 58-year-old Malay lady, presented with gradual loss of vision in the right eye for 1 month duration. It was associated with right sided headache, nausea and vomiting. Patient had a history of contact with tuberculosis patient. On examination, visual acuity in right eye was no perception of light with presence of relative afferent pupillary defect. The left eye visual acuity was 6.0/7.5. There was a total restriction of extraocular movement in all direction (frozen eye) in the right eye. Both anterior segments were unremarkable. Fundoscopy in both eyes showed normal appearance of optic disc and retinal vessels. Other cranial nerves were normal. Lungs were clear and had no lymphadenopathy. Chest radiograph was normal. Erythrocyte sedimentation rate was elevated by 35 mm/h and Mantoux test was positive (20 mm). MRI of brain and orbit demonstrated thickening and irregularity of the right optic nerve on axial view with doughnut sign on coronal view. Patient was diagnosed to have optic perineuritis secondary to tuberculosis. She was treated with anti-TB drugs. Systemic corticosteroid was commenced after 2 weeks. The visual acuity was improved to hand motion after 1 month with almost complete resolution of extraocular movement.

Optical coherence tomography and fundus autofluorescence imaging study of chorioretinal atrophy involving the macula in Alagille syndrome

We report the first case in the literature of chorioretinal atrophy involving the macula in an 11-year-old girl with Alagille syndrome, as examined by optical coherence tomography, and fundus autofluorescence imaging. Funduscopy revealed diffuse choroidal hypopigmentation with increased visibility of the choroidal vessels and symmetric, well circumscribed macular discoloration. Anomalous oblique configuration of the optic disc and peripapillary tortuous vessels were also detected. Optical coherence tomography demonstrated decreased retinal thickness, especially the outer retinal layer, and the photoreceptor inner segment/outer segment junctions were irregular and discontinued, corresponding to macular discoloration. Fundus autofluorescence imaging clearly defined hypofluorescent areas in the peripapillary regions that extended along the macula and had a sleep mask appearance. We suggest that transient hypovitaminosis due to Alagille syndrome early in life might contribute to the retinal degeneration seen in this case.

Detecting optic disc on asians by multiscale gaussian filtering.

The optic disc (OD) is an important anatomical feature in retinal images, and its detection is vital for developing automated screening programs. Currently, there is no algorithm designed to automatically detect the OD in fundus images captured from Asians which are larger and have thicker vessels compared to Caucasians. In this paper, we propose such a method to complement current algorithms using two steps: OD vessel candidate detection and OD vessel candidate matching. The first step is achieved with multiscale Gaussian filtering, scale production, and double thresholding to initially extract the vessels' directional map of various thicknesses. The map is then thinned before another threshold is applied to remove pixels with low intensities. This result forms the OD vessel candidates. In the second step, a Vessels' Directional Matched Filter (VDMF) of various dimensions is applied to the candidates to be matched, and the pixel with the smallest difference designated the OD center. We tested the proposed method on a new database consisting of 402 images from a diabetic retinopathy (DR) screening programme consisting of Asians. The OD center was successfully detected with an accuracy of 99.25% (399/402).

Therapeutic Dosing of Fingolimod (FTY720) Prevents Cell Infiltration, Rapidly Suppresses Ocular Inflammation, and Maintains the Blood-Ocular Barrier

Fingolimod (FTY720) is an FDA-approved therapeutic drug with efficacy demonstrated in experimental models of multiple sclerosis and in phase III human multiple sclerosis trials. Fingolimod prevents T-cell migration to inflammatory sites by decreasing expression of the sphingosine-1 phosphate receptor normally required for egress from secondary lymphoid tissue. As a preclinical model of human uveitis, experimental autoimmune uveoretinitis permits assessment of immunotherapeutic efficacy. Murine experimental autoimmune uveoretinitis is induced by activation of retinal antigen-specific CD4(+) T cells that infiltrate the eye. High-dose fingolimod treatment administered before disease onset reduces ocular infiltration within hours of administration and suppresses clinicopathologic expression of experimental autoimmune uveoretinitis. In the present investigation of the efficacy of fingolimod treatment for established disease, single-dose treatment was effective and immunosuppressive ability was maintained through a dose range, demonstrating significant and rapid reduction in CD4(+) cell infiltration at clinically relevant therapeutic doses of fingolimod. A repeated-treatment regimen using a dose similar to that in current multiple sclerosis patient protocols significantly reduced infiltration within 24 hours of administration; importantly, repeated doses did not compromise the vascular integrity of the blood-ocular barrier. On withdrawal of fingolimod, drug-induced remission was lost and recrudescence of clinical disease was observed. These results support a strong therapeutic potential for fingolimod as an acute rescue therapy for the treatment of ocular immune-mediated inflammation.

Changes in the retinal vessel diameter, retinal nerve fiver layer thickness, and optic disc after vitrectomy

AbstractPurpose To investigate the retinal vascular caliber, retinal nerve fiver layer thickness, and optic disc changes in patients after pars plana vitrectomy.Methods We examined 40 eyes in 40 patients who had undergone unilateral pars plana vitrectomy at before and 3 months, 6 months after operation. The diameters of central retinal arteries and veins were measured on retinal photographs. The central retinal arteriolar equivalent (CRAE) and central retinal venular equivalent (CRVE) were calculated using the revised Parr‐Hubbard formula. Retinal nerve fiver layer thickness was obtained using Stratus optical coherence tomography. Cup‐to‐disc vertical ratios of optic disc was evaluated using stereo optic disc photoResults There were no significant differences between both eyes before operation. Cup‐to‐disc vertical ratios of optic disc significantly increased for 3 months and 6 months post‐operatively (p&lt;0.01, p&lt;0.01) and there was significant difference between operation eye and fellow eye at the same period (p&lt;0.01, p&lt;0.01). The changes of CRAE and CRVE in operation eye were significantly larger than fellow eye at 6 months post‐operatively (p&lt;0.01, p&lt;0.01). The retinal nerve fiver layer thickness showed no significant changes.Conclusion Whereas no retinal nerve fiver layer thickness decrease was observed, vitrectomy induced changes in Cup‐to‐disc vertical ratios of optic disc and retinal vessel diameter for significant periods following surgery.