Optical Coherence Tomography Fundus Images Research Articles

Improved predictive diagnosis of diabetic macular edema based on hybrid models: An observational study

Diabetic Macular Edema (DME) is the most common sight-threatening complication of type 2 diabetes. Optical Coherence Tomography (OCT) is the most useful imaging technique to diagnose, follow up, and evaluate treatments for DME. However, OCT exam and devices are expensive and unavailable in all clinics in low- and middle-income countries. Our primary goal was therefore to develop an alternative method to OCT for DME diagnosis by introducing spectral information derived from spontaneous electroretinogram (ERG) signals as a single input or combined with fundus that is much more widespread. Baseline ERGs were recorded in 233 patients and transformed into scalograms and spectrograms via Wavelet and Fourier transforms, respectively. Using transfer learning, distinct Convolutional Neural Networks (CNN) were trained as classifiers for DME using OCT, scalogram, spectrogram, and eye fundus images. Input data were randomly split into training and test sets with a proportion of 80 %–20 %, respectively. The top performers for each input type were selected, OpticNet-71 for OCT, DenseNet-201 for eye fundus, and non-evoked ERG-derived scalograms, to generate a combined model by assigning different weights for each of the selected models. Model validation was performed using a dataset alien to the training phase of the models. None of the models powered by mock ERG-derived input performed well. In contrast, hybrid models showed better results, in particular, the model powered by eye fundus combined with mock ERG-derived information with a 91 % AUC and 86 % F1-score, and the model powered by OCT and mock ERG-derived scalogram images with a 93 % AUC and 89 % F1-score. These data show that the spontaneous ERG-derived input adds predictive value to the fundus- and OCT-based models to diagnose DME, except for the sensitivity of the OCT model which remains the same. The inclusion of mock ERG signals, which have recently been shown to take only 5 min to record in daylight conditions, therefore represents a potential improvement over existing OCT-based models, as well as a reliable and cost-effective alternative when combined with the fundus, especially in underserved areas, to predict DME.

Retinal sensitivity and fundus autofluorescence in adult-onset foveomacular vitelliform dystrophy

The present study aimed to compare retinal sensitivity (RS) at each stage and to evaluate the relationship between RS and fundus autofluorescence (FAF) pattern in adult-onset foveomacular vitelliform dystrophy (AOFVD). We retrospectively reviewed 17 eyes of 13 patients with AOFVD. In addition to best-corrected visual acuity (VA), RS within the affected lesion and optical coherence tomography (OCT) measurements were carried out in each participant. All the examined eyes were classified into 4 stages and 3 FAF patterns. RS was superimposed on OCT fundus image and RS within the affected lesion was calculated in each eye. The relationships between visual functions (VA and RS within the affected lesion) and stages and also FAF patterns were analyzed using the linear mixed model. As a result, RS within the affected lesion was significantly associated with FAF pattern, but not with stage. In contrast, VA was correlated with neither stages nor FAF patterns. Our current result suggested that RS within the affected lesion was related to FAF patterns but this was not the case with VA in eyes with AOFVD, demonstrating the usefulness of measuring RS, not only VA, to comprehend the disease status in AOFVD.

Mstnet: method for glaucoma grading based on multimodal feature fusion of spatial relations

Objective. The objective of this study is to develop an efficient multimodal learning framework for the classification of glaucoma. Glaucoma is a group of eye diseases that can result in vision loss and blindness, often due to delayed detection and treatment. Fundus images and optical coherence tomography (OCT) images have proven valuable for the diagnosis and management of glaucoma. However, current models that combine features from both modalities often lack efficient spatial relationship modeling. Approach. In this study, we propose an innovative approach to address the classification of glaucoma. We focus on leveraging the features of OCT volumes and harness the capabilities of transformer models to capture long-range spatial relationships. To achieve this, we introduce a 3D transformer model to extract features from OCT volumes, enhancing the model’s effectiveness. Additionally, we employ downsampling techniques to enhance model efficiency. We then utilize the spatial feature relationships between OCT volumes and fundus images to fuse the features extracted from both sources. Main results. Our proposed framework has yielded remarkable results, particularly in terms of glaucoma grading performance. We conducted our experiments using the GAMMA dataset, and our approach outperformed traditional feature fusion methods. By effectively modeling spatial relationships and combining OCT volume and fundus map features, our framework achieved outstanding classification results. Significance. This research is of significant importance in the field of glaucoma diagnosis and management. Efficient and accurate glaucoma classification is essential for timely intervention and prevention of vision loss. Our proposed approach, which integrates 3D transformer models, offers a novel way to extract and fuse features from OCT volumes and fundus images, ultimately enhancing the effectiveness of glaucoma classification. This work has the potential to contribute to improved patient care, particularly in the early detection and treatment of glaucoma, thereby reducing the risk of vision impairment and blindness.

Quantitative Detection and Follow-Up of Intracranial Hypertension in Craniosynostosis: An Optical Coherence Tomography Study.

In patients with craniosynostosis, the authors evaluated the diagnostic accuracy of fundoscopy and optical coherence tomography (OCT) to detect intracranial hypertension (ICH), the time course of retinal thickness after treatment of ICH, and the relationship between high hyperopia (HH) and fundoscopy/OCT scan findings. Patients with syndromic, multisuture, unicoronal, unilambdoid, or sagittal synostosis visiting the authors' national center were included in this longitudinal cohort study and formed a consecutive series. Retinal layers on OCT, OCT fundus images, and fundoscopy results were evaluated. ICH was scored according to presence of abnormal intracranial pressures, hydrocephalus, progressive cerebellar tonsillar herniation or fingerprinting, and growth arrest. Diagnostic accuracy of OCT, fundoscopy, and fundus image; the time course of retinal thickness after ICH; and interference of HH were analyzed using linear mixed models. A total of 577 OCT scans in 307 patients were included. ICH was found in 7.2%. Combining total retinal thickness (TRT), OCT fundus imaging and fundoscopy resulted in a sensitivity of 76% and 81% specificity to detect signs of ICH. TRT was increased in patients who had had signs of ICH versus patients who had never had signs of ICH (β +44.9 µm in patients who had had ICH [95% CI, 9.0 to 80.8]; P = 0.01). TRT decreased to normal in the years after surgery (β -3.6 µm/yr [95% CI, -7.2 to -0.05]; P = 0.047). There were greater odds of having increased TRT in patients with HH (OR, 2.9 [95% CI, 1.1 to 7.6]; P = 0.03). The correlation among TRT, OCT fundus image, fundoscopy, and particularly the combination of these measures with intracranial pressure surrogate markers is fair. Increased TRT in the presence of a clinical suspicion of ICH warrants further screening. Diagnostic, III.

A novel vessel segmentation algorithm for pathological en-face images based on matched filter

The vascular information in fundus images can provide important basis for detection and prediction of retina-related diseases. However, the presence of lesions such as Coroidal Neovascularization can seriously interfere with normal vascular areas in optical coherence tomography (OCT) fundus images. In this paper, a novel method is proposed for detecting blood vessels in pathological OCT fundus images. First of all, an automatic localization and filling method is used in preprocessing step to reduce pathological interference. Afterwards, in terms of vessel extraction, a pore ablation method based on capillary bundle model is applied. The ablation method processes the image after matched filter feature extraction, which can eliminate the interference caused by diseased blood vessels to a great extent. At the end of the proposed method, morphological operations are used to obtain the main vascular features. Experimental results on the dataset show that the proposed method achieves 0.88 ± 0.03, 0.79 ± 0.05, 0.66 ± 0.04, results in DICE, PRECISION and TPR, respectively. Effective extraction of vascular information from OCT fundus images is of great significance for the diagnosis and treatment of retinal related diseases.

Difference between before and after Compensating for Cyclotorsion by Optical Coherence Tomography Guided Progression Analysis

Purpose: This study evaluated the difference in parameters before and after the application of optical coherence tomography (OCT) Guided Progression Analysis (GPA) to compensate for cyclotorsion during image acquisition.Methods: Among glaucomatous eyes with ≥4 OCT tests, eyes with correction for cyclotorsion in GPA printouts defined as rotated OCT fundus images were included. The degree of cyclotorsion (i.e., the degree of fundus image rotation), direction of cyclotorsion (incyclotorsion or excyclotorsion), difference in optic nerve head (ONH) parameters, and retinal nerve fiber layer (RNFL) thickness before and after correction were analyzed.Results: Correction for cyclotorsion was seen in 33 of the 401 eyes (12.2%). Incyclotorsion was observed in 16 eyes (48.5%) and excyclotorsion in 17 (51.5%). The mean degree of cyclotorsion was 5.5 ± 2.3 degrees. The ONH parameters were unchanged after correcting for cyclotorsion. The mean overall, inferior, and superior quadrant RNFL thicknesses were 73.6 ± 14.8, 79.3 ± 26.3, and 90.1 ± 24.7 μm before correction and 73.6 ± 14.9, 79.6 ± 26.6, 89.7 ± 24.8 μm afterwards (p > 0.05). The difference in RNFL thickness after correction ranged from 0 to 6 μm.Conclusions: The difference in RNFL thickness before and after cyclotorsion correction by GPA was not large. GPA did not correct the ONH parameters induced by cyclotorsion. Regarding this, GPA algorithm improvements may be needed.

Predicting Visual Acuity in Patients Treated for AMD.

The leading diagnostic tool in modern ophthalmology, Optical Coherence Tomography (OCT), is not yet able to establish the evolution of retinal diseases. Our task is to forecast the progression of retinal diseases by means of machine learning technologies. The aim is to help the ophthalmologist to determine when early treatment is needed in order to prevent severe vision impairment or even blindness. The acquired data are made up of sequences of visits from multiple patients with age-related macular degeneration (AMD), which, if not treated at the appropriate time, may result in irreversible blindness. The dataset contains 94 patients with AMD and there are 161 eyes included with more than one medical examination. We used various techniques from machine learning (linear regression, gradient boosting, random forest and extremely randomised trees, bidirectional recurrent neural network, LSTM network, GRU network) to handle technical challenges such as how to learn from small-sized time series, how to handle different time intervals between visits, and how to learn from different numbers of visits for each patient (1–5 visits). For predicting the visual acuity, we performed several experiments with different features. First, by considering only previous measured visual acuity, the best accuracy of 0.96 was obtained based on a linear regression. Second, by considering numerical OCT features such as previous thickness and volume values in all retinal zones, the LSTM network reached the highest score (). Third, by considering the fundus scan images represented as embeddings obtained from the convolutional autoencoder, the accuracy was increased for all algorithms. The best forecasting results for visual acuity depend on the number of visits and features used for predictions, i.e., 0.99 for LSTM based on three visits (monthly resampled series) based on numerical OCT values, fundus images, and previous visual acuities.

Macular and Optic Disc Parameters in Children with Amblyopic and Nonamblyopic Eyes under Optical Coherence Tomography Fundus Images.

The aim of this study was to investigate the characteristics of macular and optic disc parameters in children with amblyopic and nonamblyopic eyes, using fundus images under optical coherence tomography (OCT). 36 patients with anisometropic amblyopia were selected in the experimental group, and another 36 healthy volunteers were selected in the control group, OCT examinations were performed in all groups, and the mean diopter, mean corrected visual acuity (CVA), mean axial length, mean optic disc retinal nerve fiber layer (RNFL) thickness, and mean macular fovea thickness were recorded in the two groups. The results found that the average diopter of the patients in the control group and the experimental group was +2.30 ± 2.54 D and +5.51 ± 1.76 D, respectively. The average CVA was 0.86 ± 0.07 and 0.22 ± 0.16, respectively; the average eye axial length was 22.41 ± 1.20 mm and 21.11 ± 0.78 mm, respectively. As P < 0.05, the differences were statistically significant in the three indicators between the two groups. There was no significant difference between the two groups in the average thickness of the RNFL of the optic disc and the average thickness of the central fovea of macula (P > 0.05). There was some correlation among CVA, diopter, eye axial length, RNFL thickness, and average thickness of macular fovea, but the correlation was not significant. It was suggested that there were certain differences in the macular and optic disc parameters between amblyopic and nonamblyopic children, but the difference is little. Thereout, a certain objective basis was provided for the early detection and treatment of amblyopia.

Retinal fundus image superresolution generated by optical coherence tomography based on a realistic mixed attention GAN.

Optical coherence tomography (OCT) is widely used to diagnose retinal diseases. However, due to the limited resolution of OCT imaging systems, the quality of fundus images displayed is not satisfactory, which hinders the diagnosis of patients by ophthalmologists. This is an inevitable problem of OCT imaging systems, but few people have given attention to it. We attempt to solve this problem through deep learning methods. In this paper, we propose a single-image superresolution (SISR) model that is based on a generative adversarial network (GAN) for restoring low-resolution (LR) OCT fundus images to high-resolution (HR) counterparts. To obtain more realistic images, we craft the training data set by obtaining the real blur kernels of the LR images instead of using the bicubic interpolation kernel. The baseline of our generator is similar to that of an enhanced superresolution generative adversarial network (ESRGAN), but we creatively propose a mixed attention block (MAB). In contrast to other superresolution (SR) tasks, to adapt to the characteristics of OCT imaging systems, our network can reconstruct LR images with different upscaling factors in the height and widthdirections. The results of qualitative and quantitative experiments prove that our model is capable of reconstructing retinal fundus images clearly andaccurately. We propose a new GAN model for enhancing the quality of displayed OCT retinal fundus images and achieve state-of-the-artresults.

The Weiss Ring, a Major Confounding Factor For Measurements of Peripapillary Retinal Nerve Fiber Layer Thickness: Short title: The Impact of the Weiss Ring On RNFL Thickness Measurements

To identify how the Weiss ring affects the measurement of mean and sectoral peripapillary retinal nerve fiber layer (pRNFL) thicknesses. Retrospective, cross-sectional study. Subjects were divided into two groups: controls (control group) and subjects in which a Weiss ring was visible on optical coherence tomography fundus images (WR group). Mean and sectoral pRNFL thicknesses were compared between the two groups. A total of 205 eyes were enrolled: 131 eyes in the control group and 74 eyes in the WR group. The mean pRNFL thicknesses of the control group and WR group were 97.2 ± 6.7µm and 94.6 ± 10.8 µm, respectively (P=.042). In sectoral thickness, the inferior sector of the WR group was 112.1 ± 23.2 µm, which was significantly thinner than that of the control group (125.5 ± 13.3 µm; P < .001). The Weiss ring was located in 10 eyes (13.5%) in the superior sector, 7 eyes (9.5%) in the temporal sector, 40 eyes (54.1%) in the inferior sector, and 17 eyes (23.0%) in the nasal sector. In analyses of reproducibility, the coefficient of variation and intraclass coefficient of the inferior sector measurement were 10.90% and 0.409, respectively, indicating low reliability of the measurement. Eyes with a Weiss ring showed thinner mean and inferior pRNFL thicknesses than normal controls, which would be a measurement error caused by the Weiss ring. This could be a major confounding factor for analyses of pRNFL changes, especially in glaucoma patients.

Iterative registration for multi‐modality retinal fundus photographs using directional vessel skeleton

This paper proposes an automated registration method for multi-modality retinal fundus photographs based on the directional vessel skeleton. The main purpose is to register two retinal fundus photographs with different modalities of the same scanning region, which can provide multi-modality information for clinicians to diagnose retinal diseases or to make a treatment decision. The directional vessel skeleton of each fundus image is first detected by bias field correction and Gabor filter. The final registered fundus photographs are then obtained by the iterative affine registration between the detected directional vessel skeletons of two photographs. In this work, four kinds of fundus photographs in the macular regions of the patient with diseases, consisting of 20 optical coherence tomography fundus images, 20 colour fundus photographs, 20 fluorescein fundus angiography images and 20 indocyanine green angiography images, are utilised to quantitatively evaluate the proposed method. The root-mean-square errors show an advantageous performance in both registration success rate and accuracy.

Determination and correction of aberrations in full field optical coherence tomography using phase gradient autofocus by maximizing the likelihood function.

A method for numerical estimation and correction of aberrations of the eye in fundus imaging with optical coherence tomography (OCT) is presented. Aberrations are determined statistically by using the estimate based on likelihood function maximization. The method can be considered as an extension of the phase gradient autofocusing algorithm in synthetic aperture radar imaging to 2D optical aberration correction. The efficacy of the proposed method has been demonstrated in OCT fundus imaging with 6λ aberrations. After correction, single photoreceptors were resolved. It is also shown that wave front distortions with high spatial frequencies can be determined and corrected.

Local comparison of cup to disc ratio in right and left eyes based on fusion of color fundus images and OCT B-scans

Symmetry analysis of Optical Coherence Tomography (OCT) images in right and left eyes can lead to introduction of new biomarkers for early detection of eye diseases. In this study, we investigate the symmetry between two eyes by calculating local cup to disc ratio (CDR) from each B-scan based on fusion of fundus images and OCT B-scans. For this purpose, in the first phase, the OCT data of Optic Nerve Head (ONH) in right and left eyes are aligned by finding the equivalent B-scans of both eyes based on the fovea-ONH axes. Since the fovea-ONH axes in OCT data are not available, at first, left and right fundus images are aligned according to their automatically detected fovea-ONH axes. Then, OCT data are registered to corresponding fundus images based on maximum similarity between en-face OCT data and fundus image in each eye. This two-stage alignment procedure depends on 1) the blood vessels, automatically extracted by Hessian analysis of directional curvelet sub-bands, and 2) the disc contour of ONH in fundus images, detected by Distance Regularized Level Set Evolution (DRLSE) algorithm. In the second phase, in order to calculate the local CDRs, the disc and cup boundaries are extracted from the aligned B-scans in left and right eyes. The disc boundary is limited by Bruch-Membrane opening, and the cup boundary is defined by retinal layer border. Therefore, Inner Limiting Membrane (ILM) and Retinal Pigment Epithelium (RPE) layers are extracted using ridgelet transform to find the disc-edge point and cup-edge point in each B-scan. Finally, the ratio of summed areas of cups to summed areas of discs is calculated in corresponding local regions to find the local CDRs. Using this method, we can also introduce a new index called local volumetric CDR (VCDR) by dividing the volume of cup in a specific region to the corresponding volume of disc extracted from OCT images of ONH. Forty healthy OCT datasets of size 650 × 512 × 128 (acquired from Topcon 3D OCT-1000) and corresponding 1536 × 1612 fundus images were used in this study. In addition to point-by-point comparison of CDRs in equivalent B-scans of aligned OCTs, the CDRs in upper, middle and lower regions were calculated and the maximum symmetry is observed in middle region. In addition, using local VCDR, the symmetry of 3D OCTs of both eyes is analyzed in 24 volumetric sectors.

Prevalence of choroidal nevus and retinal pigment epithelial alterations in vitiligo patients.

To investigate ocular manifestations in patients with vitiligo by multimodal imaging, including optical coherence tomography (OCT), color fundus photography, and fundus autofluorescence (FAF). In this prospective, observational clinical study, vitiligo patients underwent ophthalmologic and dermatologic clinical assessment and imaging by spectral-domain OCT, FAF, and color fundus imaging. Ocular echography was performed as indicated. Statistical analysis was performed using paired T test and Pearson correlation. A total of 61 eyes of 31 vitiligo patients were examined. Ocular findings consisted of choroidal nevi (n = 10, 32%), of which four (40%) were bilateral; two patients (6.5%) had a prominent choroidal pattern, two (6.5%) had hypopigmentary retinal pigment epithelium (RPE) lesions, and one (3.2%) had peripapillary atrophy of the RPE. Choroidal nevi were demonstrated only in eyes of patients with generalized vitiligo and were more common with upper body involvement (p = 0.02) and more prevalent in women (p = 0.02). Hypopigmentary lesions were detected in two patients and demonstrated on OCT as RPE atrophy and as photoreceptor/RPE changes. In this case series, vitiligo patients had a higher rate of choroidal nevi than previously reported. The hypopigmentary vitiliginous fundus lesions were depicted on OCT as photoreceptor and RPE atrophy. These findings may suggest the advisability of regular ocular monitoring for vitiligo patients.

Analysis of changes in serum levels of endothelin-1 in patients with retinal vein occlusion

Aim. To analyze the level of endothelin-1 in blood serum in patients with retinal venous occlusions. Metods. 60 patients with macular edema due to retinal vein occlusion (RVO) were included in the study. 19 patients were diagnosed with central retinal vein occlusion, 9 of them had non-ischemic type and 10 had ischemic type of central retinal vein occlusion. 41 patients had branch retinal vein occlusion, 23 of them had non-ischemic type and 18 had ischemic type of occlusion. Patients underwent fluorescein angiography and optical coherence tomography fundus imaging. Before intravitreal injection of ranibizumab, the level of endothelin-1 in the blood serum was determined. Analysis was performed in patients’ subgroups depending on the localization of occlusion, type of occlusion, disease relapse, presence of optic disc swelling. &#x0D; Results. Differences in the systemic level of endothelin-1, depending on the localization of occlusion, presence of ischemic type and relapse, the disease was not detected (p ≥0.05). With the development of optic disc swelling, a statistically significant increase in the level of endothelin-1 was noted in peripheral blood: 38.73 fmol/ml in patients with optic disc swelling and 27.65 fmol/ml in patients without it (p=0.018). &#x0D; Conclusion. In patients with optic disc swelling a statistically significant increase of endothelin-1 in blood was revealed.

The Development of a Cat Model of Retinal Detachment and Re-attachment.

We present an optimized surgical technique for feline retinal detachment which allows for natural re-attachment, reduces retinal scarring and vitreal bands, and allows central placement of the detachment in close proximity to the optic nerve. This enables imaging via Optical Coherence Tomography (OCT) and multifocal electroretinography (mfERG) analysis. Ideal detachment conditions involve a lensectomy followed by a three-port pars plana vitrectomy. A 16-20% retinal detachment is induced by injecting 8% C3F8 gas into the subretinal space in the central retina with a 42G cannula. The retinal detachment resolves approximately 6 weeks post-surgery. Imaging is enhanced by using a 7.5 and 20 diopter lens for OCT and mfERG fundus imaging, respectively, to compensate for the removed lens.

Retinal Laser Lesion Visibility in Simultaneous Ultra-High Axial Resolution Optical Coherence Tomography

Ex vivo porcine retina laser lesions applied with varying laser power (20 mW–2 W, 10 ms pulse, 196 lesions) are manually evaluated by microscopic and optical coherence tomography (OCT) visibility, as well as in histological sections immediately after the deposition of the laser energy. An optical coherence tomography system with 1.78 $\mu\hbox{m}$ axial resolution specifically developed to image thin retinal layers simultaneously to laser therapy is presented, and visibility thresholds of the laser lesions in OCT data and fundus imaging are compared. Optical coherence tomography scans are compared with histological sections to estimate the resolving power for small optical changes in the retinal layers, and real-time time-lapse scans during laser application are shown and analyzed quantitatively. Ultrahigh-resolution OCT inspection features a lesion visibility threshold 40–50 mW (17% reduction) lower than for visual inspection. With the new measurement system, 42% of the lesions that were invisible using state-of-the-art ophthalmoscopic methods could be detected.

Vascular network of the human macula from OCT

AbstractPurpose To compute the vascular network of the human macula from spectral‐domain optical coherence tomography (OCT) to an extent similar to that of color fundus photography (CFP).Methods Macular cube protocol scans of 512x128x1024 and 200x200x1024 voxels of 20 eyes from 13 type 2 diabetic patients and 10 eyes from 10 healthy volunteers were collected from the Cirrus HD‐OCT (Carl Zeiss Meditec, Dublin, CA, USA) database. Additionally, CFPs and fluorescein angiograms (FAs) from the patients' eyes were gathered from the imaging database. Three distinct fundus references were computed from the OCT volumes after proper preprocessing. An additional OCT fundus image (OCTref) is computed as the principal component of these 3 OCT fundus references. The visible vascular network was manually segmented on CFP, FA and OCTref for comparison. Finally, a support vector machine (SVM) pattern classification algorithm was used to classify each pixel of the OCTref image into the vessel or non‐vessel classes from a set of 14 features computed from the OCT fundus references.Results Over 67% (67.8(7.2)%, average(SD)) of the vascular network manually segmented from the FA was manually segmented from the CFP, while this percentage raises to 69.2(8.9)% for OCT. In this way, the OCTref allows to compute an extended vascular network as compared to the CFP (102.8(14.4)%). When comparing the automatic versus the manual vascular segmentation, a specificity of 99.4(0.2)% and a sensitivity of 83.9(4.0)% were obtained. Overall, the accuracy of the automatic classification is of 98.0(0.4)%.Conclusion The proposed algorithm allows for the segmentation of the vascular network from OCT scans of the ocular fundus to a level similar to that of color fundus photography.

Advanced retinal pigment epithelium analysis by SD-OCT to monitor dry AMD progression

This article provides a short overview of developments in optical coherence tomography (OCT) technology and highlights the advantages of spectral domain OCT, which allows for high-speed, high-resolution imaging of retinal structures. Established clinical applications to diagnose and monitor macular diseases are summarized and the rapidly evolving role of OCT technology in this field is described. Recent clinical studies show that spectral domain OCT permits volumetric measurement of drusen and might be used for quantitative assessment of drusen progression. Furthermore, spectral domain OCT fundus images can be used to evaluate atrophic lesions of geographic atrophy. A new retinal pigment epithelium analysis tool is presented that should allow for automated, quantitative assessment of drusen and atrophic lesions and could potentially provide more objective and easier classification of age-related macular degeneration.

Photoreceptor Layer Map Using Spectral-Domain Optical Coherence Tomography

To develop a novel method for analysis of the photoreceptor layer map (PLM) generated using spectral-domain optical coherence tomography (OCT). OCT scans were obtained from 20 eyes, 10 with macular holes (MH) and 10 with central serous chorioretinopathy (CSC) using the Macular Cube (512 x 128) protocol of the Cirrus HD-OCT (Carl Zeiss). The scanned data were processed using embedded tools of the advanced visualization. A partial thickness OCT fundus image of the photoreceptor layer was generated by setting the region of interest to a 50-microm thick layer that was parallel and adjacent to the retinal pigment epithelium. The resulting image depicted the photoreceptor layer as a map of the reflectivity in OCT. The PLM was compared with fundus photography, auto-fluorescence, tomography, and retinal thickness map. The signal from the photoreceptor layer of every OCT scan in each case was demonstrated as a single image of PLM in a fundus photograph fashion. In PLM images, detachment of the sensory retina is depicted as a hypo-reflective area, which represents the base of MH and serous detachment in CSC. Relative hypo-reflectivity, which was also noted at closed MH and at recently reattached retina in CSC, was associated with reduced signal from the junction between the inner and outer segments of photoreceptors in OCT images. Using PLM, changes in the area of detachment and reflectivity of the photoreceptor layer could be efficiently monitored. The photoreceptor layer can be analyzed as a map using spectral-domain OCT. In the treatment of both MH and CSC, PLM may provide new pathological information about the photoreceptor layer to expand our understanding of these diseases.