3D Spectral-domain Optical Coherence Tomography Research Articles

Disc Hemorrhages Are Associated With Localized Three-Dimensional Neuroretinal Rim Thickness Progression in Open-Angle Glaucoma

• PURPOSE:To evaluate the relationship between the occurrence of optic disc hemorrhages (DH) and glaucoma progression as determined by multiple glaucoma testing modalities.• DESIGN:Prospective cohort study.• METHODS:A longitudinal study was undertaken of 124 open-angle glaucoma patients who had yearly disc photography, visual fields (VFs), spectral-domain optical coherence tomography (SD-OCT), retinal nerve fiber layer (RNFL) thickness scans, and optic nerve volume scans (Spectralis), all performed on the same day over a 5-year period. The minimum distance band (MDB) thickness, a 3-dimensional (3D) neuroretinal rim parameter, was calculated from optic nerve volume scans. Patients were classified as glaucoma progressors or glaucoma nonprogressors using event-based analysis.• RESULTS:Of 124 open-angle glaucoma patients, 19 (15.3%) had 1 or more DHs on yearly disc photographs. Presence of a DH was associated with localized 3D neuroretinal rim thickness progression (superior MDB progression; odds ratio: 3.96; P = .04) but not with global or inferior MDB progression (P = .14 and .81, respectively), DP progression (P = .08), VF progression (P = .45), or RNFL global, inferior, or superior progression (P = .17, .26, and .76, respectively). In the majority of patients with MDB progression (14/17 or 82%), the progression was noted before or concurrently with the first instance of DH.• CONCLUSIONS:Glaucoma progression detected by high-density 3D SD-OCT neuroretinal rim measurements preceded DH occurrence in the majority of patients. These findings support the hypothesis that DHs are indicators of ongoing glaucoma progression rather than discrete events that cause subsequent progression.

Glaucoma Detection from Raw SD-OCT Volumes: A Novel Approach Focused on Spatial Dependencies

Background and objective:Glaucoma is the leading cause of blindness worldwide. Many studies based on fundus image and optical coherence tomography (OCT) imaging have been developed in the literature to help ophthalmologists through artificial-intelligence techniques. Currently, 3D spectral-domain optical coherence tomography (SD-OCT) samples have become more important since they could enclose promising information for glaucoma detection.To analyse the hidden knowledge of the 3D scans for glaucoma detection, we have proposed, for the first time, a deep-learning methodology based on leveraging the spatial dependencies of the features extracted from the B-scans.Methods:The experiments were performed on a database composed of 176 healthy and 144 glaucomatous SD-OCT volumes centred on the optic nerve head (ONH). The proposed methodology consists of two well-differentiated training stages: a slide-level feature extractor and a volume-based predictive model. The slide-level discriminator is characterised by two new, residual and attention, convolutional modules which are combined via skip-connections with other fine-tuned architectures. Regarding the second stage, we first carried out a data-volume conditioning before extracting the features from the slides of the SD-OCT volumes. Then, Long Short-Term Memory (LSTM) networks were used to combine the recurrent dependencies embedded in the latent space to provide a holistic feature vector, which was generated by the proposed sequential-weighting module (SWM).Results:The feature extractor reports AUC values higher than 0.93 both in the primary and external test sets. Otherwise, the proposed end-to-end system based on a combination of CNN and LSTM networks achieves an AUC of 0.8847 in the prediction stage, which outperforms other state-of-the-art approaches intended for glaucoma detection. Additionally, Class Activation Maps (CAMs) were computed to highlight the most interesting regions per B-scan when discerning between healthy and glaucomatous eyes from raw SD-OCT volumes.Conclusions:The proposed model is able to extract the features from the B-scans of the volumes and combine the information of the latent space to perform a volume-level glaucoma prediction. Our model, which combines residual and attention blocks with a sequential weighting module to refine the LSTM outputs, surpass the results achieved from current state-of-the-art methods focused on 3D deep-learning architectures.

Automated Quantification of Hyperreflective Foci in SD-OCT With Diabetic Retinopathy.

The presence of hyperreflective foci (HFs) is related to retinal disease progression, and the quantity has proven to be a prognostic factor of visual and anatomical outcome in various retinal diseases. However, lack of efficient quantitative tools for evaluating the HFs has deprived ophthalmologist of assessing the volume of HFs. For this reason, we propose an automated quantification algorithm to segment and quantify HFs in spectral domain optical coherence tomography (SD-OCT). The proposed algorithm consists of two parallel processes namely: region of interest (ROI) generation and HFs estimation. To generate the ROI, we use morphological reconstruction to obtain the reconstructed image and histogram constructed for data distributions and clustering. In parallel, we estimate the HFs by extracting the extremal regions from the connected regions obtained from a component tree. Finally, both the ROI and the HFs estimation process are merged to obtain the segmented HFs. The proposed algorithm was tested on 40 3D SD-OCT volumes from 40 patients diagnosed with non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR), and diabetic macular edema (DME). The average dice similarity coefficient (DSC) and correlation coefficient (r) are 69.70%, 0.99 for NPDR, 70.31%, 0.99 for PDR, and 71.30%, 0.99 for DME, respectively. The proposed algorithm can provide ophthalmologist with good HFs quantitative information, such as volume, size, and location of the HFs.

Segmentation Guided Registration for 3D Spectral-Domain Optical Coherence Tomography Images

Medical image registration can be used for combining information from multiple imaging modalities, monitoring changes in size, shape or image intensity over time intervals. However, the development of such technique can be challenging for 3D spectral-domain optical coherence tomography (SD-OCT) imaging, because SD-OCT image is inherently noisy and its high resolution leads to high complexity of non-rigid registration. In this paper, a new segmentation guided approach is reported for registration of retinal OCT data. The proposed method models the 3D registration as a two-stage registration including x-y direction registration and z direction registration. In x-y direction registration, the vessel maps of OCT projection images between the template and the subject are registered to find out x-y direction displacement. The multi-scale vessel enhancement filter and morphological thinning methods are used to extract the vessel maps from the projection image of 3D OCT scans. And then x-y direction displacement is estimated by matching Speeded-Up Robust Features of the vessel maps. In z direction registration, using the tissue map instead of the original intensity image, A-scans are aligned to get the local displacements in z direction. The proposed method was evaluated on 45 longitudinal retinal OCT scans from 15 subjects. Experimental results show that the proposed method is accurate and very efficient.

Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging.

The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues.

Parameters of ocular fundus on spectral-domain optical coherence tomography for glaucoma diagnosis.

In this review, we summarize the progression of several parameters assessed by spectral-domain optical coherence tomography (SD-OCT) in recent years for the detection of glaucoma. Monitoring the progression of defects in the retinal nerve fiber layer (RNFL) thickness is essential. Imaging and analysis of retinal ganglion cells (RGCs) and inner plexiform layer (IPL), respectively, have been of great importance. Optic nerve head (ONH) topography obtained from 3D SD-OCT images is another crucial step. Other important assessments involve locating the Bruch's membrane opening (BMO), estimating the optic disc size and rim area, and measuring the lamina cribrosa displacement. Still other parameters found in the past three years for glaucoma diagnosis comprise central retinal artery resistive index, optic disc perfusion in optical coherence tomography angiography (OCTA) study, peripapillary choroidal thickness, and choroidal area in SD-OCT. Recently, several more ocular fundus parameters have been found, and compared with the earlier parameters to judge the accuracy of diagnosis. While a few of these parameters have been widely used in clinical practice, a fair number are still in the experimental stage.

A Framework for Classification and Segmentation of Branch Retinal Artery Occlusion in SD-OCT.

Branch retinal artery occlusion (BRAO) is an ocular emergency, which could lead to blindness. Quantitative analysis of the BRAO region in the retina is necessary for the assessment of the severity of retinal ischemia. In this paper, a fully automatic framework was proposed to segment BRAO regions based on 3D spectral-domain optical coherence tomography (SD-OCT) images. To the best of our knowledge, this is the first automatic 3D BRAO segmentation framework. First, the input 3D image is automatically classified into BRAO of acute phase and BRAO of chronic phase or normal retina using an AdaBoost classifier based on combining local structural, intensity, textural features with our new feature distribution analyzing strategy. Then, BRAO regions of acute phase and chronic phase are segmented separately. A thickness model is built to segment BRAO in the chronic phase. While for segmenting BRAO in the acute phase, a two-step segmentation strategy is performed: rough initialization and refine segmentation. The proposed method was tested on SD-OCT images of 35 patients (12 BRAO acute phase, 11 BRAO chronic phase, and 12 normal eyes) using the leave-one-out strategy. The classification accuracy for BRAO acute phase, BRAO chronic phase, and normal retina were 100%, 90.9%, and 91.7%, respectively. The overall true positive volume fraction (TPVF) and false positive volume fraction (FPVF) for the acute phase were 91.1% and 5.5% and for the chronic phase were 92.7% and 8.4%, respectively.

High-low reflectivity enhancement based retinal vessel projection for SD-OCT images.

The retinal vessel visualization from spectral-domain optical coherence tomography (SD-OCT) images is important for ocular disease diagnosis and multimodal retinal image processing. The purpose is to display the retinal vessel in a single projection image from 3D SD-OCT images by using the light absorption and shadow characteristics of the retinal vessel. The authors present a novel retinal vessel projection method for SD-OCT images, which utilizes the light absorption and shadow characteristics of the retinal vessel, called high-low reflectivity enhancement (HLRE) method. The reflectivity of the retinal vessel increases between the internal limiting membrane and inner nuclear layer-outer plexiform layer (INL-OPL) layers because of the light absorption, and the reflectivity below the retinal vessel decreases because of the influence of the retinal vessel shadow. A retinal vessel mask image generated based on the reflectivity characteristics of the retinal vessel is used to enhance the subvolume projection image restricted between the INL-OPL and Bruch's membrane layers. Experimental results with 22 SD-OCT cubes from 12 patients and 10 normal persons demonstrate that the authors' method is more effective in displaying the retinal vessel than the summed-voxel projection and other five region restriction based projection methods. The average of the mean difference between the retinal vessel and background regions based on their HLRE method is 0.1921. The proposed HLRE method was more effective for the visualization of the retinal vessels than the state-of-art methods because it provides higher contrast and distinction.

Three-dimensional segmentation of retinal cysts from spectral-domain optical coherence tomography images by the use of three-dimensional curvelet based K-SVD

This paper presents a new three-dimensional curvelet transform based dictionary learning for automatic segmentation of intraretinal cysts, most relevant prognostic biomarker in neovascular age-related macular degeneration, from 3D spectral-domain optical coherence tomography (SD-OCT) images. In particular, we focus on the Spectralis SD-OCT (Heidelberg Engineering, Heidelberg, Germany) system, and show the applicability of our algorithm in the segmentation of these features. For this purpose, we use recursive Gaussian filter and approximate the corrupted pixels from its surrounding, then in order to enhance the cystoid dark space regions and future noise suppression we introduce a new scheme in dictionary learning and take curvelet transform of filtered image then denoise and modify each noisy coefficients matrix in each scale with predefined initial 3D sparse dictionary. Dark pixels between retinal pigment epithelium and nerve fiber layer that were extracted with graph theory are considered as cystoid spaces. The average dice coefficient for the segmentation of cystoid regions in whole 3D volume and with-in central 3 mm diameter on the MICCAI 2015 OPTIMA Cyst Segmentation Challenge dataset were found to be 0.65 and 0.77, respectively.

Restricted Summed-Area Projection for Geographic Atrophy Visualization in SD-OCT Images.

To enhance the rapid assessment of geographic atrophy (GA) across the macula in a single projection image generated from three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) scans by introducing a novel restricted summed-area projection (RSAP) technique. We describe a novel en face GA visualization technique, the RSAP, by restricting the axial projection of SD-OCT images to the regions beneath the Bruch's membrane (BM) boundary and also considering the choroidal vasculature's influence on GA visualization. The technique analyzes the intensity distribution beneath the retinal pigment epithelium (RPE) layer to fit a cross-sectional surface in the sub-RPE region. The area is taken as the primary GA projection. A median filter is then adopted to smooth the generated GA projection image. The RSAP technique was evaluated in 99 3D SD-OCT data sets from 27 eyes of 21 patients presenting with advanced nonexudative age-related macular degeneration and GA. We used the mean difference between GA and background regions and GA separability metric to measure GA contrast and distinction in the generated images, respectively. We compared our results with two existing GA projection techniques, the summed-voxel projection (SVP) and Sub-RPE Slab techniques. Comparative results demonstrate that the RSAP technique is more effective in displaying GA than the SVP and Sub-RPE Slab. The average of the mean difference between GA and background regions and the GA separability based on SVP, Sub-RPE Slab, and RSAP were 0.129/0.880, 0.238/0.919, and 0.276/0.938, respectively. The RSAP technique was more effective for GA visualization than the conventional SVP and Sub-RPE Slab techniques. Our technique decreases choroidal vasculature influence on GA projection images by analyzing the intensity distribution characteristics in sub-RPE regions. The generated GA projection image with the RSAP technique has improved contrast and distinction. Our method for automated generation of GA projection images from SD-OCT images may improve the visualization of the macular abnormalities and the management of GA.

A joint estimation detection of Glaucoma progression in 3D spectral domain optical coherence tomography optic nerve head images.

Glaucoma is an ocular disease characterized by distinctive changes in the optic nerve head (ONH) and visual field. Glaucoma can strike without symptoms and causes blindness if it remains without treatment. Therefore, early disease detection is important so that treatment can be initiated and blindness prevented. In this context, important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, an essential element for glaucoma detection and monitoring. 3D spectral domain optical coherence tomography (SD-OCT), an optical imaging technique, has been commonly used to discriminate glaucomatous from healthy subjects. In this paper, we present a new framework for detection of glaucoma progression using 3D SD-OCT images. In contrast to previous works that the retinal nerve fiber layer (RNFL) thickness measurement provided by commercially available spectral-domain optical coherence tomograph, we consider the whole 3D volume for change detection. To integrate a priori knowledge and in particular the spatial voxel dependency in the change detection map, we propose the use of the Markov Random Field to handle a such dependency. To accommodate the presence of false positive detection, the estimated change detection map is then used to classify a 3D SDOCT image into the "non-progressing" and "progressing" glaucoma classes, based on a fuzzy logic classifier. We compared the diagnostic performance of the proposed framework to existing methods of progression detection.

Comparative study of macular ganglion cell complex thickness measured by spectral-domain optical coherence tomography in healthy eyes, eyes with preperimetric glaucoma, and eyes with early glaucoma

To evaluate the diagnostic accuracy of Topcon 3D spectral-domain optical coherence tomography (SD-OCT) for measuring the macular inner retinal layers and the circumpapillary retinal nerve fiber layer (cpRNFL) in order to detect preperimetric glaucoma. Two hundred four eyes, including 64 healthy eyes, 68 eyes with preperimetric glaucoma, and 72 eyes with early glaucoma were analyzed. Patients had a comprehensive ocular examination including visual field testing and SD-OCT imaging (3D OCT-2000; Topcon Corporation, Tokyo, Japan) in the macular and peripapillary regions. OCT macular scans were segmented into the macular nerve fiber layer (mNFL), ganglion cell layer with the inner plexiform layer (GCIP), and ganglion cell complex (GCC) (composed of the mNFL and GCIP). Ability to discriminate preperimetric glaucoma was assessed using the area under the receiver operating curve for all macular parameters and the cpRNFL. The median visual field MD was -0.78 ± 1.19 dB for the healthy group, -1.02 ± 1.29 dB for the preperimetric glaucoma group, and -3.08 ± 1.61 dB for the early glaucoma group. There were significant differences between the preperimetric and healthy groups for GCIP and GCC and for almost all cpRNFL thickness parameters (P < 0.05), except for the mNFL and cpRNFL (nasal, 3, 4, 8, 9, and 10 o'clock sectors). The comparisons among the AUCs of the cpRNFL parameters (0.772), the GCIP parameters (0.727) and the GCC parameters (0.720) showed no significant differences in their abilities to detect preperimetric glaucoma. The capacity of Topcon 3D-OCT macular intraretinal parameters (GCIP and GCC measurements, not mNFL measurements) to diagnose preperimetric glaucoma is similar to that of the cpRNFL.

3D spectral domain OCT in spontaneous retinal pigment epithelial tear

IntroductionNeovascular age-related macular degeneration is character-ized by the presence of the choroidal neovascularizationmembrane (CNVM) and is associated with pigment epithe-lial detachment (PED) [1]. RPE tears are a serious compli-cation that can follow PED [2–6]. Fibrovascular contractionof choroidal neovascular membranes, mechanical forcesfrom vitreomacular traction, or interruption of tight junc-tions due to anti-VEGF therapy are the most probablecauses [5]. The RPE tear creates an area where photorecep-tors have no RPE support. If the fovea lies within the RPE-denuded area, a marked decrease in visual acuity is ob-served, often accompanied by eccentric fixation [7].Materials and methodsTheauthorsconfirmadherencetothetenetsoftheDeclarationof Helsinki. After taking a written informed consent, spectraldomain optical coherence tomography (SD-OCT) [Cirrushigh-definition OCT (Carl Zeiss Meditec Inc.), CA, USA]was performed in two cases of spontaneous retinal pigmentepithelium (RPE) tear in neovascular age-related maculardegeneration (AMD). 3D SD-OCT has been used for the firsttime for documenting an RPE tear in neovascular AMD.Case report 1—A 57-year-old female presented at ourtertiary center with the chief complaint of gradual progres-sive diminution of vision in both eyes since 5 years withrecent diminution of vision in the left eye since 10 days.Vision in the right eye was 20/60 and that in the left eye wasfinger counting 5 m. On slit lamp biomicroscopic examina-tion, the anteriorsegment was found to be unremarkable.Onfundus examination, the right eye showed retinal pigmentepithelial alteration in the macula. The left eye showed alarge crescentric RPE tear in the macular area with barechoroid above and rolled-up RPE below (Fig. 1). Fluores-cein angiography showed a crescent-shaped area ofhyperfluorescence corresponding to a bare choroid with anarea of hypofluorescencebelow itcorrespondingto reflectedRPE (Fig. 2).On advanced visualization of the macula, SD-OCTof theright eye revealed retinal pigment epithelial detachment. Ahyperreflective area of RPE with loss in its continuity waspresent at the edge of PED in the left eye (Fig. 3). The areaof the tear showed greater reflectivity and thickness ascompared to the rest of the RPE and extended in thesubretinal space. 3D SD-OCT precisely showed the RPEtear with hyperreflective dusting present around it (Fig. 4).Follow-up visit after 2 months showed marked changeson SD-OCT. Thickness of the hyperreflective RPE in-creased markedly with loss of its integrity (Fig. 5). Thesub-RPE space was obliterated with both hyperreflectiveand moderately reflective material representing the choroi-dal neovascular membrane (Fig. 5). Advanced visualizationof the area of bare choroid guided by scanning laser oph-thalmology exquisitely showed the presence of CNVM withthe absence of RPE (Fig. 6). 3D SD-OCT showed a signif-icant increase in hyperreflective dusting surrounding thearea of the tear (Fig. 7).Casereport2—A78-year-oldmalepresentedwithgraduallyprogressive diminution in both eyes for 7 years. Vision in the

Automated Segmentation of the Choroid from Clinical SD-OCT

We developed and evaluated a fully automated 3-dimensional (3D) method for segmentation of the choroidal vessels, and quantification of choroidal vasculature thickness and choriocapillaris-equivalent thickness of the macula, and evaluated repeat variability in normal subjects using standard clinically available spectral domain optical coherence tomography (SD-OCT). A total of 24 normal subjects was imaged twice, using clinically available, 3D SD-OCT. A novel, fully-automated 3D method was used to segment and visualize the choroidal vasculature in macular scans. Local choroidal vasculature and choriocapillaris-equivalent thicknesses were determined. Reproducibility on repeat imaging was analyzed using overlapping rates, Dice coefficient, and root mean square coefficient of variation (CV) of choroidal vasculature and choriocapillaris-equivalent thicknesses. For the 6 × 6 mm(2) macula-centered region as depicted by the SD-OCT, average choroidal vasculature thickness in normal subjects was 172.1 μm (95% confidence interval [CI] 163.7-180.5 μm) and average choriocapillaris-equivalent thickness was 23.1 μm (95% CI 20.0-26.2 μm). Overlapping rates were 0.79 ± 0.07 and 0.75 ± 0.06, Dice coefficient was 0.78 ± 0.08, CV of choroidal vasculature thickness was 8.0% (95% CI 6.3%-9.4%), and of choriocapillaris-equivalent thickness was 27.9% (95% CI 21.0%-33.3%). Fully automated 3D segmentation and quantitative analysis of the choroidal vasculature and choriocapillaris-equivalent thickness demonstrated excellent reproducibility in repeat scans (CV 8.0%) and good reproducibility of choriocapillaris-equivalent thickness (CV 27.9%). Our method has the potential to improve the diagnosis and management of patients with eye diseases in which the choroid is affected.

Automated Assessment of Drusen Using Three-Dimensional Spectral-Domain Optical Coherence Tomography

To compare automated assessment of macular drusen delineated by the authors' originally developed algorithm on three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) with the assessment by certified graders on color fundus photographs in nonneovascular age-related macular degeneration (AMD). Automated assessment of macular drusen was performed using raster scan by 3D OCT scans in 18 eyes with nonneovascular AMD with at least one large druse (≥125 μm) and predominantly soft indistinct drusen. Drusen was defined as the regions that have the distance between the retinal pigment epithelium and calculated Bruch's membrane lines > predefined threshold distances. The agreement was assessed on maximum drusen size and drusen area within grid between 3D SD-OCT and color fundus photographs, and false-negative and false-positive drusen at each threshold distance. There was agreement or agreement within one step in all eyes in maximum drusen size, and 15 (83.3%) of the eyes in the drusen area, except 6 pixels, regardless of threshold distances. However, the number of eyes with exact agreement in the drusen area increased when the threshold distances were smaller than 4 pixels. In the three cases with disagreement in the drusen area, false-negative drusen on 3D SD-OCT were characterized by being small in area and height. Automated assessment of drusen parameters based on the authors' algorithm on 3D SD-OCT, which was limited by the poor detection ability of small drusen, showed good agreement with the assessment by certified graders on color fundus photography in these subjects.

Three-dimensional spectral domain optical coherence tomography of retina in choroidal metastasis due to breast and lung carcinoma

Intraocular metastasis is now considered the most common malignancy of the eye [1]. The frequency of choroidal metastasis in patients with cancer is estimated to be approximately 2 to 7 % [2, 3]. While any portion of the eye can be involved by metastatic disease, the most common tissue involved is the highly vascular choroid [1–3]. There seems to be no predilection for metastasis to preferentially affect the right or left eye [3]. In each affected eye, more than one metastasis may be noted [4]. Most choroidal metastases occur posterior to the equator of the fundus, in the macular or paramacular regions. The common primary sites of cancer are the breast, lung, and gastrointestinal tract [2, 3]. Diagnosis of ocular metastases is based primarily on clinical findings supplemented by imaging studies. Spectral domain optical coherence tomography (SD-OCT) clearly outlines the changes in the retinal architecture due to the underlying choroidal mass. 3D SD-OCT feature of retina following choroidal metastasis due to uterine endometrial carcinoma has been reported by Saxena et al. [5]. 3D SD-OCT in choroidal metastasis due to breast and lung carcinoma is being reported for the first time.

Three dimensional spectral domain optical coherence tomography features of retinal–choroidal anastomosis

To correlate the three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) features of retinal-choroidal anastomosis (RCA) to conventional angiography. This is a retrospective chart review of consecutive patients diagnosed with RCA who underwent 3D SD-OCT between July 2007 and June 2010. Main outcome measures were the diagnostic capabilities of 3D SD-OCT, and the correlation between 3D findings and the features distinguished by conventional angiography. Eighteen eyes of 18 patients [five males, 13 females, mean age 79.5 ± 19.4years (range, 70-93years)] were included in the analysis. In eyes (n = 3) showing a focal staining on angiography, 3D OCT revealed a slight convex prominence of the inner retinal surface in correspondence of a small dome-shaped retinal pigment epithelium (RPE) elevation (which represented the early RCA). In eyes (n = 7) showing a "hot spot" without pigment epithelium detachment (PED) on angiography, 3D OCT revealed a convex prominence of the inner retinal surface in correspondence with a well-demarcated prominence of RPE with steep margins (which represented the RCA). In eyes (n = 8) showing a "hot spot" with PED on angiography, 3D OCT revealed a convex prominence of the inner retinal surface in correspondence with a convex RPE prominence with a peak at the top. 3D SD-OCT provides a map of the retina and RPE, allowing a realistic visualization of the different pathological features in the disease development, and may be able to provide clinically relevant information to complement angiography in the diagnosis of RCA.

3D Spectral Domain Optical Coherence Tomography Findings in Choroidal Tumors

To report the optical coherence tomographic features differentiating choroidal nevus from choroidal melanoma by 3D spectral-domain optical coherence tomography (SD-OCT) and OCT characteristics of other choroidal tumors. A total of 67 consecutive eyes with choroidal tumors including choroidal nevus (25 eyes), indeterminate choroidal melanocytic lesion (11 eyes), malignant melanoma (23 eyes), metastasis (4 eyes), hemangioma (2 eyes), and osteoma (2 eyes) were imaged with 3D SD-OCT (OCT-1000; Topcon Inc., Paramus, NJ). The images were analyzed for the presence or absence of SD-OCT findings such as retinal pigment epithelium (RPE)/choriocapillaris reflectivity, RPE irregularity, drusen, sub-RPE fluid, RPE thickness, subretinal deposit, subretinal fluid, intraretinal edema, retinal thickness, and photoreceptor inner and outer segment junction (IS/OS). Visualization of the choroidal tumor and its intrinsic reflectivity OCT features were also assessed. When compared with nevus, subretinal deposit, subretinal fluid, and intraretinal edema were detected significantly more frequently in the eyes with malignant melanoma (p<0.001). SD-OCT visualization of the tumor was limited only to the anterior aspect. Choroidal nevus, indeterminate lesions, melanoma, and metastatic lesions had variable intrinsic reflectivity pattern. Intrinsic features of hemangioma included choroidal hollowness whereas osteoma demonstrated high intrinsic reflectivity. SD-OCT provides useful information to observe and document the retinal and RPE changes secondary to choroidal tumors that help differentiate choroidal nevus from malignant melanoma. Improvements in the current OCT systems are needed to better characterize intrinsic features of choroidal tumors.