Faculty Bibliography

PURPOSE: To investigate the effect on optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) thickness measurements of varying the standard 3.4-mm-diameter circle location. METHODS: The optic nerve head (ONH) region of 17 eyes of 17 healthy subjects was imaged with high-speed, ultrahigh-resolution OCT (hsUHR-OCT; 501 x 180 axial scans covering a 6 x 6-mm area; scan time, 3.84 seconds) for a comprehensive sampling. This method allows for systematic simulation of the variable circle placement effect. RNFL thickness was measured on this three-dimensional dataset by using a custom-designed software program. RNFL thickness was resampled along a 3.4-mm-diameter circle centered on the ONH, then along 3.4-mm circles shifted horizontally (x-shift), vertically (y-shift) and diagonally up to +/-500 microm (at 100-microm intervals). Linear mixed-effects models were used to determine RNFL thickness as a function of the scan circle shift. A model for the distance between the two thickest measurements along the RNFL thickness circular profile (peak distance) was also calculated. RESULTS: RNFL thickness tended to decrease with both positive and negative x- and y-shifts. The range of shifts that caused a decrease greater than the variability inherent to the commercial device was greater in both nasal and temporal quadrants than in the superior and inferior ones. The model for peak distance demonstrated that as the scan moves nasally, the RNFL peak distance increases, and as the circle moves temporally, the distance decreases. Vertical shifts had a minimal effect on peak distance. CONCLUSIONS: The location of the OCT scan circle affects RNFL thickness measurements. Accurate registration of OCT scans is essential for measurement reproducibility and longitudinal examination (ClinicalTrials.gov number, NCT00286637).

PURPOSE: To develop automated software for optic nerve head (ONH) quantitative assessment from stereoscopic disc photographs and to evaluate its performance in comparison with human expert assessment. METHODS: A fully automated system, including three-dimensional ONH modeling, disc margin detection, cup margin detection, and calculation of stereometric ONH parameters, was developed and tested. One eye each from 54 subjects (23 healthy, 17 suspected glaucoma, and 14 glaucoma) was enrolled. The majority opinion of three experts defined disc and cup margins on the disc photographs was used for comparison. Seven ONH parameters, disc area, rim area, rim volume, cup area, cup volume, cup-to-disc (C/D) area ratio, and vertical C/D ratio, were computed based on both machine- and expert-defined margins and compared between the methods. RESULTS: All automated ONH measurements showed good correlation with the expert defined margins (Pearson r = 0.90, disc area; 0.56, rim area; 0.78, rim volume; 0.88, cup area; 0.93, cup volume; 0.69, C/D area ratio; and 0.67, vertical C/D ratio; all P or= 0.21). The mean or median of automatically defined disc and cup areas was significantly higher than the subjective assessment (disc area P = 0.0001, t-test; cup area P = 0.036, Wilcoxon signed ranks test), although they had high correlation coefficients. The software failed to detect the disc margin for all the disc photographs with peripapillary atrophy. CONCLUSIONS: The automated ONH analysis method provides an objective and quantitative ONH evaluation using widely available stereo disc photographs.

AIMS: The purpose of this study was to compare the day-to-day reproducibility of optical coherence tomography (OCT; StratusOCT, Carl Zeiss Meditec, Dublin, CA) measurements of retinal nerve-fibre layer (RNFL) measurements at time points 1 year apart. METHODS: One eye in each of 11 healthy subjects was examined using the StratusOCT fast RNFL scan protocol. Three fast RNFL scans with signal strength > or =7 were obtained on each of 3 days within a month. This protocol was repeated after 12 months. A linear mixed effects model fitted to the nested data was used to compute the variance components. RESULTS: The square root of the variance component that was attributed to the differences between subjects was 7.17 microm in 2005 and 7.28 microm in 2006. The square roots of the variance component due to differences between days within a single subject were 1.95 microm and 1.50 microm, respectively, and for within day within a single subject were 2.51 microm and 2.55 microm, respectively. There were no statistically significant differences for any variance component between the two testing occasions. CONCLUSIONS: Measurement error variance remains similar from year to year. Day and scan variance component values obtained in a cohort study may be safely applied for prediction of long-term reproducibility.

AIMS: To assess performance of classifiers trained on Heidelberg Retina Tomograph 3 (HRT3) parameters for discriminating between healthy and glaucomatous eyes. METHODS: Classifiers were trained using HRT3 parameters from 60 healthy subjects and 140 glaucomatous subjects. The classifiers were trained on all 95 variables and smaller sets created with backward elimination. Seven types of classifiers, including Support Vector Machines with radial basis (SVM-radial), and Recursive Partitioning and Regression Trees (RPART), were trained on the parameters. The area under the ROC curve (AUC) was calculated for classifiers, individual parameters and HRT3 glaucoma probability scores (GPS). Classifier AUCs and leave-one-out accuracy were compared with the highest individual parameter and GPS AUCs and accuracies. RESULTS: The highest AUC and accuracy for an individual parameter were 0.848 and 0.79, for vertical cup/disc ratio (vC/D). For GPS, global GPS performed best with AUC 0.829 and accuracy 0.78. SVM-radial with all parameters showed significant improvement over global GPS and vC/D with AUC 0.916 and accuracy 0.85. RPART with all parameters provided significant improvement over global GPS with AUC 0.899 and significant improvement over global GPS and vC/D with accuracy 0.875. CONCLUSIONS: Machine learning classifiers of HRT3 data provide significant enhancement over current methods for detection of glaucoma.

PURPOSE: To test if improving optical coherence tomography (OCT) resolution and scanning speed improves the visualization of glaucomatous structural changes as compared with conventional OCT. DESIGN: Prospective observational case series. PARTICIPANTS: Healthy and glaucomatous subjects in various stages of disease. METHODS: Subjects were scanned at a single visit with commercially available OCT (StratusOCT) and high-speed ultrahigh-resolution (hsUHR) OCT. The prototype hsUHR OCT had an axial resolution of 3.4 mum (3 times higher than StratusOCT), with an A-scan rate of 24 000 hertz (60 times faster than StratusOCT). The fast scanning rate allowed the acquisition of novel scanning patterns such as raster scanning, which provided dense coverage of the retina and optic nerve head. MAIN OUTCOME MEASURES: Discrimination of retinal tissue layers and detailed visualization of retinal structures. RESULTS: High-speed UHR OCT provided a marked improvement in tissue visualization as compared with StratusOCT. This allowed the identification of numerous retinal layers, including the ganglion cell layer, which is specifically prone to glaucomatous damage. Fast scanning and the enhanced A-scan registration properties of hsUHR OCT provided maps of the macula and optic nerve head with unprecedented detail, including en face OCT fundus images and retinal nerve fiber layer thickness maps. CONCLUSION: High-speed UHR OCT improves visualization of the tissues relevant to the detection and management of glaucoma.

PURPOSE: To compare stereometric parameters and classification results from the Heidelberg Retina Tomograph version 2 (HRT2); HRT3; and HRT3 Glaucoma Probability Score (GPS), an automated method of obtaining optic nerve head analysis without the need for manual definition of disc margin. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: Five hundred four eyes from 281 consecutive subjects (glaucoma, glaucoma suspect, and healthy) evaluated in a glaucoma clinic. METHODS: All participants had HRT2 scanning of the optic nerve head. Inclusion criteria were scans with good centration and focus, even illumination, an overall quality score by HRT3 of acceptable or better, and standard deviation < 50 mum. A Bland-Altman analysis was used for the comparison of HRT2 and HRT3. From these results, calibration equations were determined to permit conversion of the measurements between devices. The agreement between HRT2 and HRT3 Moorfields regression analysis (MRA) and HRT3 GPS classification methods was measured using kappa statistics. MAIN OUTCOME MEASURES: Heidelberg Retina Tomograph version 2 and HRT3 stereometric parameters, MRA, and global GPS. RESULTS: There was a statistically significant difference between HRT2 and HRT3 global disc area, rim area, cup area, rim volume, cup volume, height variation contour, and retinal nerve fiber layer cross-sectional area stereometric parameters. All of those parameters were smaller using HRT3, due to a manufacturer-reported horizontal scaling error of 4% in HRT2 that was corrected in HRT3. kappas for agreement were 0.60 between classifications (within normal limits, borderline, and outside normal limits) of MRA by HRT2 and HRT3 and 0.47 between HRT3 MRA and GPS. CONCLUSIONS: The HRT3 generally provided smaller stereometric disc measurements than HRT2. There was no clear conversion between HRT3 and GPS parameters, as the 2 methods for measuring the stereometric parameters differ.

OBJECTIVE: To determine the correspondence between optic disc margins evaluated using disc photography (DP) and optical coherence tomography (OCT). METHODS: From May 1, 2005, through November 10, 2005, 17 healthy volunteers (17 eyes) had raster scans (180 frames, 501 samplings per frame) centered on the optic disc taken with stereo-optic DP and high-speed ultrahigh-resolution OCT (hsUHR-OCT). Two image outputs were derived from the hsUHR-OCT data set: an en face hsUHR-OCT fundus image and a set of 180 frames of cross-sectional images. Three ophthalmologists independently and in a masked, randomized fashion marked the disc margin on the DP, hsUHR-OCT fundus, and cross-sectional images using custom software. Disc size (area and horizontal and vertical diameters) and location of the geometric disc center were compared among the 3 types of images. RESULTS: The hsUHR-OCT fundus image definition showed a significantly smaller disc size than the DP definition (P <.001, mixed-effects analysis). The hsUHR-OCT cross-sectional image definition showed a significantly larger disc size than the DP definition (P <.001). The geometric disc center location was similar among the 3 types of images except for the y-coordinate, which was significantly smaller in the hsUHR-OCT fundus images than in the DP images. CONCLUSION: The optic disc margin as defined by hsUHR-OCT was significantly different than the margin defined by DP.

A scanning laser ophthalmoscopy (SLO) image, taken from optical coherence tomography (OCT), usually has lower global/local contrast and more noise compared to the traditional retinal photograph, which makes the vessel segmentation challenging work. A hybrid algorithm is proposed to efficiently solve these problems by fusing several designed methods, taking the advantages of each method and reducing the error measurements. The algorithm has several steps consisting of image preprocessing, thresholding probe and weighted fusing. Four different methods are first designed to transform the SLO image into feature response images by taking different combinations of matched filter, contrast enhancement and mathematical morphology operators. A thresholding probe algorithm is then applied on those response images to obtain four vessel maps. Weighted majority opinion is used to fuse these vessel maps and generate a final vessel map. The experimental results showed that the proposed hybrid algorithm could successfully segment the blood vessels on SLO images, by detecting the major and small vessels and suppressing the noises. The algorithm showed substantial potential in various clinical applications. The use of this method can be also extended to medical image registration based on blood vessel location.

PURPOSE: To demonstrate a new imaging method for high resolution spectral domain optical coherence tomography (SD-OCT) for small animal developmental imaging. METHODS: Wildtype zebrafish that were 24, 48, 72, and 120 h post fertilization (hpf) and nok gene mutant (48 hpf) embryos were imaged in vivo. Three additional embryos were imaged twice, once at 72 hpf and again at 120 hpf. Images of the developing eye, brain, heart, whole body, proximal yolk sac, distal yolk sac, and tail were acquired. Three-dimensional OCT data sets (501 x 180 axial scans) were obtained as well as oversampled frames (8,100 axial scans) and repeated line scans (180 repeated frames). Scan volumes ranged from 750 x 750 microm to 3 x 3 mm, each 1.8 mm thick. Three-dimensional data sets allowed construction of C-mode slabs of the embryo. RESULTS: SD-OCT provided ultra-high resolution visualization of the eye, brain, heart, ear, and spine of the developing embryo as early as 24 hpf, and allowed development to be documented in each of these organ systems in consecutive sessions. Repeated line scanning with averaging optimized the visualization of static and dynamic structures contained in SD-OCT images. Structural defects caused by a mutation in the nok gene were readily observed as impeded ocular development, and enlarged pericardial cavities. CONCLUSIONS: SD-OCT allowed noninvasive, in vivo, ultra-high resolution, high-speed imaging of zebrafish embryos in their native state. The ability to measure structural and functional features repeatedly on the same specimen, without the need to sacrifice, promises to be a powerful tool in small animal developmental imaging.