Faculty Bibliography

AIM: To describe the appearance of the non-exudative forms of age related macular degeneration (AMD) as imaged by ultrahigh resolution optical coherence tomography (UHR-OCT). METHODS: A UHR-OCT ophthalmic imaging system, which utilises a femtosecond laser light source capable of approximately 3 mum axial resolution, was employed to obtain retinal cross sectional images of patients with non-exudative AMD. Observational studies of the resulting retinal images were performed. RESULTS: 52 eyes of 42 patients with the clinical diagnosis of non-exudative AMD were imaged using the UHR-OCT system. 47 of the 52 (90%) eyes had the clinical diagnosis of drusen and/or retinal pigment epithelial (RPE) changes. In these patients, three patterns of drusen were apparent on UHR-OCT: (1) distinct RPE excrescences, (2) a saw toothed pattern of the RPE, and (3) nodular drusen. On UHR-OCT, three eyes (6%) with a clinical diagnosis of non-exudative AMD had evidence of fluid under the retina or RPE. Two of these three patients had findings suspicious for subclinical choroidal neovascularisation on UHR-OCT. CONCLUSION: With the increased resolution of UHR-OCT compared to standard OCT, the involvement of the outer retinal layers are more clearly defined. UHR-OCT may allow for the detection of early exudative changes not visible clinically or by angiography.

Any complete theory of human stereopsis must model not only how the correspondences between locations in the two views are determined and the depths are recovered from their disparity, but also how the ambiguity arising from such factors as noise, periodicity, and large regions of constant intensity are resolved and missing data are interpolated. In investigating this process of recovering surface structure from sparse disparity information, using stereo pairs with sparse identifiable features, we made an observation that contradicts all extant models. It suggests the inadequacy of retinotopic representation in modeling surface perception in this stage. We also suggest a possible alternative theory, which is a minimization of the modulus of Gaussian curvature.

PURPOSE: Machine-learning classifiers are trained computerized systems with the ability to detect the relationship between multiple input parameters and a diagnosis. The present study investigated whether the use of machine-learning classifiers improves optical coherence tomography (OCT) glaucoma detection. METHODS: Forty-seven patients with glaucoma (47 eyes) and 42 healthy subjects (42 eyes) were included in this cross-sectional study. Of the glaucoma patients, 27 had early disease (visual field mean deviation [MD] > or = -6 dB) and 20 had advanced glaucoma (MD < -6 dB). Machine-learning classifiers were trained to discriminate between glaucomatous and healthy eyes using parameters derived from OCT output. The classifiers were trained with all 38 parameters as well as with only 8 parameters that correlated best with the visual field MD. Five classifiers were tested: linear discriminant analysis, support vector machine, recursive partitioning and regression tree, generalized linear model, and generalized additive model. For the last two classifiers, a backward feature selection was used to find the minimal number of parameters that resulted in the best and most simple prediction. The cross-validated receiver operating characteristic (ROC) curve and accuracies were calculated. RESULTS: The largest area under the ROC curve (AROC) for glaucoma detection was achieved with the support vector machine using eight parameters (0.981). The sensitivity at 80% and 95% specificity was 97.9% and 92.5%, respectively. This classifier also performed best when judged by cross-validated accuracy (0.966). The best classification between early glaucoma and advanced glaucoma was obtained with the generalized additive model using only three parameters (AROC = 0.854). CONCLUSIONS: Automated machine classifiers of OCT data might be useful for enhancing the utility of this technology for detecting glaucomatous abnormality.

OBJECTIVE: To compare ultrahigh-resolution optical coherence tomography (UHR OCT) with standard-resolution OCT for imaging macular diseases, develop baselines for interpreting OCT images, and identify situations where UHR OCT can provide additional information on disease morphology. DESIGN: Cross-sectional study. PARTICIPANTS: One thousand two eyes of 555 patients with different macular diseases including macular hole, macular edema, central serous chorioretinopathy, age-related macular degeneration (AMD), choroidal neovascularization, epiretinal membrane, retinal pigment epithelium (RPE) detachment, and retinitis pigmentosa. METHODS: A UHR ophthalmic OCT system that achieves 3-microm axial image resolution was developed for imaging in the ophthalmology clinic. Comparative studies were performed with both UHR OCT and standard 10-microm-resolution OCT. Standard scanning protocols of 6 radial 6-mm scans through the fovea were obtained with both systems. Ultrahigh-resolution OCT and standard-resolution OCT images were correlated with standard ophthalmic examination techniques (dilated ophthalmoscopy, fluorescein angiography, indocyanine green angiograms) to assess morphological information contained in the images. MAIN OUTCOME MEASURES: Ultrahigh-resolution and standard-resolution OCT images of macular pathologies. RESULTS: Correlations of UHR OCT images, standard-resolution images, fundus examination, and/or fluorescein angiography were demonstrated in full-thickness macular hole, central serous chorioretinopathy, macular edema, AMD, RPE detachment, epiretinal membrane, vitreal macular traction, and retinitis pigmentosa. Ultrahigh-resolution OCT and standard-resolution OCT exhibited comparable performance in differentiating thicker retinal layers, such as the retinal nerve fiber, inner and outer plexiform, and inner and outer nuclear. Ultrahigh-resolution OCT had improved performance differentiating finer structures or structures with lower contrast, such as the ganglion cell layer and external limiting membrane. Ultrahigh-resolution OCT confirmed the interpretation of features, such as the boundary between the photoreceptor inner and outer segments, which is also visible in standard-resolution OCT. The improved resolution of UHR OCT is especially advantageous in assessing photoreceptor morphology. CONCLUSIONS: Ultrahigh-resolution OCT enhances the visualization of intraretinal architectural morphology relative to standard-resolution OCT. Ultrahigh-resolution OCT images can provide a baseline for defining the interpretation of standard-resolution images, thus enhancing the clinical utility of standard OCT imaging. In addition, UHR OCT can provide additional information on macular disease morphology that promises to improve understanding of disease progression and management.

An upgraded optical coherence tomography system with integrated retinal tracker (TOCT) was developed. The upgraded system uses improved components to extend the tracking bandwidth, fully integrates the tracking hardware into the optical head of the clinical OCT system, and operates from a single software platform. The system was able to achieve transverse scan registration with sub-pixel accuracy (~10 microm). We demonstrate several advanced scan sequences with the TOCT, including composite scans averaged (co-added) from multiple B-scans taken consecutively and several hours apart, en face images collected by summing the A-scans of circular, line, and raster scans, and three-dimensional (3D) retinal maps of the fovea and optic disc. The new system achieves highly accurate OCT scan registration yielding composite images with significantly improved spatial resolution, increased signal-to-noise ratio, and reduced speckle while maintaining well-defined boundaries and sharp fine structure compared to single scans. Precise re-registration of multiple scans over separate imaging sessions demonstrates TOCT utility for longitudinal studies. En face images and 3D data cubes generated from these data reveal high fidelity image registration with tracking, despite scan durations of more than one minute.

PURPOSE: To develop a software algorithm to perform automated segmentation of retinal layer structures on linear macular optical coherence tomography (StratusOCT; Carl Zeiss Meditec, Inc., Dublin, CA) scan images and to test its performance in discriminating normal from glaucomatous eyes in comparison with conventional circumpapillary nerve fiber layer (cpNFL) thickness measurement. METHODS: Four layer structures within the retina were defined: the macular nerve fiber layer (mNFL), the inner retinal complex (IRC; retinal ganglion cell [RGC] layer + inner plexiform and nuclear layers), outer plexiform layer (OPL), and outer retinal complex (ORC; outer nuclear layer + photoreceptor layer). Normal and glaucomatous eyes underwent fast macular map and fast NFL OCT scans. Linear macular images were analyzed using the developed algorithm, and the results were compared with the cpNFL thickness measurement. RESULTS: Forty-seven subjects (23 normal and 24 with glaucoma) were analyzed. mNFL, cpNFL, IRC, and the total retinal thicknesses were significantly greater in normal than in glaucomatous eyes (P < or = 0.0002; Wilcoxon), whereas OPL thickness did not show a significant difference (P = 0.46). ORC thickness was significantly greater in glaucomatous than normal eyes (P = 0.035). Areas under the receiver operator characteristic curve (AROCs) for discriminating normal from glaucomatous eyes were highest with mNFL + IRC (0.97) and lowest with OPL (0.56). AROCs for OPL and ORC were significantly smaller than those for mNFL, IRC, mNFL+IRC, and cpNFL (P < or = 0.01). AROCs for IRC, mNFL + IRC, and cpNFL were significantly larger than for retinal thickness (P < or = 0.049). Among the best-performing parameters (mNFL, IRC, mNFL + IRC, and cpNFL) there was no significant difference in AROCs (P > or = 0.15). CONCLUSIONS: The newly developed macular segmentation algorithm described herein demonstrated its ability to quantify objectively the glaucomatous damage to RGCs and NFL and to discriminate between glaucomatous and normal eyes. Further algorithm refinement and improvements in resolution and image quality may yield a more powerful methodology for clinical glaucoma evaluation.

OBJECTIVES: To longitudinally evaluate optical coherence tomography (OCT) peripapillary retinal nerve fiber layer thickness measurements and to compare these measurements across time with clinical status and automated perimetry. METHODS: Retrospective evaluation of 64 eyes (37 patients) of glaucoma suspects or patients with glaucoma participating in a prospective longitudinal study. All participants underwent comprehensive clinical assessment, visual field (VF) testing, and OCT every 6 months. Field progression was defined as a reproducible decline of at least 2 dB in VF mean deviation from baseline. Progression of OCT was defined as reproducible mean retinal nerve fiber layer thinning of at least 20 mum. RESULTS: Each patient had a median of 5 usable OCT scans at median follow-up of 4.7 years. The difference in the linear regression slopes of retinal nerve fiber layer thickness between glaucoma suspects and patients with glaucoma was nonsignificant for all variables; however, Kaplan-Meier survival curve analysis demonstrated a higher progression rate by OCT vs VF. Sixty-six percent of eyes were stable throughout follow-up, whereas 22% progressed by OCT alone, 9% by VF mean deviation alone, and 3% by VF and OCT. CONCLUSIONS: A greater likelihood of glaucomatous progression was identified by OCT vs automated perimetry. This might reflect OCT hypersensitivity or true damage identified by OCT before detection by conventional methods.

An active, hardware-based retinal tracker is integrated with a clinical optical coherence tomography (OCT) system to investigate the effects of stabilization on acquisition of high-resolution retinal sections. The prototype retinal tracker locks onto common fundus features, detects transverse eye motion via changes in feature reflectance, and positions the OCT diagnostic beam to fixed coordinates on the retina with mirrors driven by a feedback control loop. The system is tested in a full clinical protocol on subjects with normal and glaucomatous eyes. Experimental analysis software is developed to coalign and coadd multiple fundus and OCT images and to extract quantitative information on the location of structures in the images. Tracking is highly accurate and reproducible on all but one subject, resulting in the ability to scan the same retinal location continually over long periods of time. The results show qualitative improvement in 97% of coadded OCT scans and a reduction in the variance of the position of the optic disc cup edge to less than 1 pixel (< 60 microm). The tracking system can be easily configured for use in research on ultra-high-resolution OCT systems for advanced image modalities. For example, tracking will enable very high density 3-D scans of the retina, which are susceptible to eye motion artifacts even for new high-speed systems.