Akram Belghith

Optical Coherence Tomography Angiography Vessel Density in Healthy, Glaucoma Suspect, and Glaucoma Eyes

Purpose The purpose of this study was to compare retinal nerve fiber layer (RNFL) thickness and optical coherence tomography angiography (OCT-A) retinal vasculature measurements in healthy, glaucoma suspect, and glaucoma patients. Methods Two hundred sixty-one eyes of 164 healthy, glaucoma suspect, and open-angle glaucoma (OAG) participants from the Diagnostic Innovations in Glaucoma Study with good quality OCT-A images were included. Retinal vasculature information was summarized as a vessel density map and as vessel density (%), which is the proportion of flowing vessel area over the total area evaluated. Two vessel density measurements extracted from the RNFL were analyzed: (1) circumpapillary vessel density (cpVD) measured in a 750-μm-wide elliptical annulus around the disc and (2) whole image vessel density (wiVD) measured over the entire image. Areas under the receiver operating characteristic curves (AUROC) were used to evaluate diagnostic accuracy. Results Age-adjusted mean vessel density was significantly lower in OAG eyes compared with glaucoma suspects and healthy eyes. (cpVD: 55.1 ± 7%, 60.3 ± 5%, and 64.2 ± 3%, respectively; P < 0.001; and wiVD: 46.2 ± 6%, 51.3 ± 5%, and 56.6 ± 3%, respectively; P < 0.001). For differentiating between glaucoma and healthy eyes, the age-adjusted AUROC was highest for wiVD (0.94), followed by RNFL thickness (0.92) and cpVD (0.83). The AUROCs for differentiating between healthy and glaucoma suspect eyes were highest for wiVD (0.70), followed by cpVD (0.65) and RNFL thickness (0.65). Conclusions Optical coherence tomography angiography vessel density had similar diagnostic accuracy to RNFL thickness measurements for differentiating between healthy and glaucoma eyes. These results suggest that OCT-A measurements reflect damage to tissues relevant to the pathophysiology of OAG.

Structural Change Can Be Detected in Advanced-Glaucoma Eyes.

Purpose To compare spectral-domain optical coherence tomography (SD-OCT) standard structural measures and a new three-dimensional (3D) volume optic nerve head (ONH) change detection method for detecting change over time in severely advanced-glaucoma (open-angle glaucoma [OAG]) patients. Methods Thirty-five eyes of 35 patients with very advanced glaucoma (defined as a visual field mean deviation < −21 dB) and 46 eyes of 30 healthy subjects to estimate aging changes were included. Circumpapillary retinal fiber layer thickness (cpRNFL), minimum rim width (MRW), and macular retinal ganglion cell–inner plexiform layer (GCIPL) thicknesses were measured using the San Diego Automated Layer Segmentation Algorithm (SALSA). Progression was defined as structural loss faster than 95th percentile of healthy eyes. Three-dimensional volume ONH change was estimated using the Bayesian-kernel detection scheme (BKDS), which does not require extensive retinal layer segmentation. Results The number of progressing glaucoma eyes identified was highest for 3D volume BKDS (13, 37%), followed by GCPIL (11, 31%), cpRNFL (4, 11%), and MRW (2, 6%). In advanced-OAG eyes, only the mean rate of GCIPL change reached statistical significance, −0.18 μm/y (P = 0.02); the mean rates of cpRNFL and MRW change were not statistically different from zero. In healthy eyes, the mean rates of cpRNFL, MRW, and GCIPL change were significantly different from zero. (all P < 0.001). Conclusions Ganglion cell–inner plexiform layer and 3D volume BKDS show promise for identifying change in severely advanced glaucoma. These results suggest that structural change can be detected in very advanced disease. Longer follow-up is needed to determine whether changes identified are false positives or true progression.

Does the Location of Bruch's Membrane Opening Change Over Time? Longitudinal Analysis Using San Diego Automated Layer Segmentation Algorithm (SALSA)

Purpose We determined if the Bruchs membrane opening (BMO) location changes over time in healthy eyes and eyes with progressing glaucoma, and validated an automated segmentation algorithm for identifying the BMO in Cirrus high-definition coherence tomography (HD-OCT) images. Methods We followed 95 eyes (35 progressing glaucoma and 60 healthy) for an average of 3.7 ± 1.1 years. A stable group of 50 eyes had repeated tests over a short period. In each B-scan of the stable group, the BMO points were delineated manually and automatically to assess the reproducibility of both segmentation methods. Moreover, the BMO location variation over time was assessed longitudinally on the aligned images in 3D space point by point in x, y, and z directions. Results Mean visual field mean deviation at baseline of the progressing glaucoma group was −7.7 dB. Mixed-effects models revealed small nonsignificant changes in BMO location over time for all directions in healthy eyes (the smallest P value was 0.39) and in the progressing glaucoma eyes (the smallest P value was 0.30). In the stable group, the overall intervisit–intraclass correlation coefficient (ICC) and coefficient of variation (CV) were 98.4% and 2.1%, respectively, for the manual segmentation and 98.1% and 1.9%, respectively, for the automated algorithm Conclusions Bruchs membrane opening location was stable in normal and progressing glaucoma eyes with follow-up between 3 and 4 years indicating that it can be used as reference point in monitoring glaucoma progression. The BMO location estimation with Cirrus HD-OCT using manual and automated segmentation showed excellent reproducibility.

A hierarchical framework for estimating neuroretinal rim area using 3D spectral domain optical coherence tomography (SD-OCT) optic nerve head (ONH) images of healthy and glaucoma eyes

Glaucoma is a chronic neurodegenerative disease characterized by loss of retinal ganglion cells, resulting in distinctive changes in the optic nerve head (ONH) and retinal nerve fiber layer (RNFL). Important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, a crucial step in diagnosing and monitoring glaucoma. 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 approach for locating the Bruchs membrane opening BMO and then estimating the optic disc size and rim area of 3D Spectralis SD-OCT images. To deal with the overlapping of the Bruchs membrane BM layer and the border tissue of Elschnig due to the poor image resolution, we propose the use of image deconvolution approach to separate these layers. To estimate the optic disc size and rim area, we propose the use of a new regression method based on the artificial neural network principal component analysis (ANN-PCA), which allows us to model irregularity in the BMO estimation due to scan shifts and/or poor image quality. The diagnostic accuracy of rim area, and rim to disc area ratio is compared to the diagnostic accuracy of global RNFL thickness measurements provided by two commercially available SD-OCT devices using receiver operating characteristic curve analyses.

Automated segmentation of anterior lamina cribrosa surface: How the lamina cribrosa responds to intraocular pressure change in glaucoma eyes?

The lamina cribrosa is a sieve-like structure where retinal ganglion cell axons and central retinal vessels exit from the eye through the scleral canal. The lamina cribrosa has been known to play an essential role in the physiopathology of glaucoma and has been investigated as a potential location to identify early glaucomatous damage. Many researchers have been studying how the lamina cribrosa responds to intraocular pressure change, leading to axonal insults. Recently, 3D spectral domain optical coherence tomography (SD-OCT) Enhanced depth imaging (EDI), an optical imaging technique, has been proposed to improve OCT imaging of deeper retinal structures such as the choroid and the lamina cribrosa. However, the shadowing from vasculature and other reflective structures make the segmentation of the anterior lamina cribrosa surface difficult. In this paper, we present a new approach for the segmentation of the anterior lamina cribrosa surface. To deal with the complexity of the surface segmentation, we propose the use of a shape-constrained surface evolution method where the surface is refined iteratively using a non-local Markov random field based segmentation. The estimation of the model parameter is addressed using a Metropolis-Hastings algorithm. Our experiments showed a significant correlation between change in the intraocular pressure level and change in the position of the lamina cribrosa over time.

Reproducibility of Optical Coherence Tomography Angiography Macular and Optic Nerve Head Vascular Density in Glaucoma and Healthy Eyes

Purpose: Optical coherence tomography angiography (OCT-A) is a noninvasive technology that allows visualization of retinal blood vessels. It is important to determine reproducibility of measurements as low precision can impair its diagnostic capabilities. The purpose of this study is to determine intravisit and intervisit reproducibility of optic nerve head (ONH) and macular vessel density measurements with OCT-A. Patients and Methods: Fifteen healthy volunteers and 14 glaucoma patients completed 2 OCT-A (AngioVue; Optovue Inc.) scanning sessions on each of 2 separate days to assess intravisit and intervisit reproducibility. A series of ONH and macula scans were acquired at each session. Vessel density (%), the proportion of vessel area over the total measurement area was calculated. Reproducibility was summarized using coefficients of variation (CV) and intraclass correlation coefficients calculated from variance component models. Results: In healthy eyes, the CV of intravisit and intervisit global vessel density measures ranged from 1.8% to 3.2% in ONH scans and 2.5% to 9.0% in macular scans. In glaucoma eyes, the CV of intravisit and intervisit global vessel density measures ranged from 2.3% to 4.1% in ONH scans and 3.2% to 7.9% in macular scans. CVs were lower for global than sectorial measures. Global OCT-A ONH intraclass correlation measurements for the retinal nerve fiber layer in healthy eyes were lower (range: 0.65 to 0.85) than in glaucoma eyes (range: 0.89 to 0.94). Scan size did not make large differences in measurement CVs. Conclusions: Reproducibility of OCT-A ONH and macula vessel density measurements is good. Moreover, glaucoma patients have sparser vessel density with poorer reproducibility than healthy subjects.

Learning from healthy and stable eyes

UNLABELLED Glaucoma is a chronic neurodegenerative disease characterized by loss of retinal ganglion cells, resulting in distinctive changes in the optic nerve head (ONH) and retinal nerve fiber layer. Important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, a crucial step in diagnosing and monitoring glaucoma. Three dimensional (3D) spectral domain optical coherence tomography (SD-OCT), an optical imaging technique, is now the standard of care for diagnosing and monitoring progression of numerous eye diseases. METHOD This paper aims to detect changes in multi-temporal 3D SD-OCT ONH images using a hierarchical fully Bayesian framework and then to differentiate between changes reflecting random variations or true changes due to glaucoma progression. To this end, we propose the use of kernel-based support vector data description (SVDD) classifier. SVDD is a well-known one-class classifier that allows us to map the data into a high-dimensional feature space where a hypersphere encloses most patterns belonging to the target class. RESULTS The proposed glaucoma progression detection scheme using the whole 3D SD-OCT images detected glaucoma progression in a significant number of cases showing progression by conventional methods (78%), with high specificity in normal and non-progressing eyes (93% and 94% respectively). CONCLUSION The use of the dependency measurement in the SVDD framework increased the robustness of the proposed change-detection scheme with comparison to the classical support vector machine and SVDD methods. The validation using clinical data of the proposed approach has shown that the use of only healthy and non-progressing eyes to train the algorithm led to a high diagnostic accuracy for detecting glaucoma progression compared to other methods.

A sustained intravitreal drug delivery system with remote real time monitoring capability

UNLABELLED Many chorioretinal diseases are chronic and need sustained drug delivery systems to keep therapeutic drug level at the disease site. Many intravitreal drug delivery systems under developing do not have mechanism incorporated for a non-invasive monitoring of drug release. The current study prepared rugate porous silicon (pSi) particles by electrochemical etching with the current frequency (K value) of 2.17 and 2.45. Two model drugs (rapamycin and dexamethasone) and two drug-loading strategies were tested for the feasibility to monitor drug release from the pSi particles through a color fundus camera. The pSi particles (k=2.45) with infiltration loading of rapamycin demonstrated progressively more violet color reflection which was negatively associated with the rapamycin released into the vitreous (r=-0.4, p<0.001, pairwise). In contrast, pSi with K value of 2.17 demonstrated progressive color change toward green and a weak association between rapamycin released into vitreous and green color abundance was identified (r=-0.23, p=0.002, pairwise). Dexamethasone was covalently loaded on to the fully oxidized pSi particles that appeared in vitreous as yellow color and fading over time. The yellow color decrease over time was strongly associated with the dexamethasone detected from the vitreous samples (r=0.7, p<0.0001, pairwise). These results suggest that engineered porous silicon particles may be used as a self-reporting drug delivery system for a non-invasive real time remote monitoring. STATEMENT OF SIGNIFICANCE The current study, for the first time, demonstrated proof of concept that engineered porous silicon photonic crystal may deliver therapeutics in a controlled fashion while at the same time might offer a noninvasive remote monitoring of its payload release in a living eye. Porous silicon photonic crystal changes color which is in association with its payload release into vitreous. With further optimization, the color change may be harnessed to inform eye care professionals of real time drug concentration in the eye and allow them to make informed decision to re-dose the patients.

Luminosity and contrast normalization in color retinal images based on standard reference image

Color retinal images are used manually or automatically for diagnosis and monitoring progression of a retinal diseases. Color retinal images have large luminosity and contrast variability within and across images due to the large natural variations in retinal pigmentation and complex imaging setups. The quality of retinal images may affect the performance of automatic screening tools therefore different normalization methods are developed to uniform data before applying any further analysis or processing. In this paper we propose a new reliable method to remove non-uniform illumination in retinal images and improve their contrast based on contrast of the reference image. The non-uniform illumination is removed by normalizing luminance image using local mean and standard deviation. Then the contrast is enhanced by shifting histograms of uniform illuminated retinal image toward histograms of the reference image to have similar histogram peaks. This process improve the contrast without changing inter correlation of pixels in different color channels. In compliance with the way humans perceive color, the uniform color space of LUV is used for normalization. The proposed method is widely tested on large dataset of retinal images with present of different pathologies such as Exudate, Lesion, Hemorrhages and Cotton-Wool and in different illumination conditions and imaging setups. Results shows that proposed method successfully equalize illumination and enhances contrast of retinal images without adding any extra artifacts.

Macular Ganglion Cell Inner Plexiform Layer Thickness in Glaucomatous Eyes with Localized Retinal Nerve Fiber Layer Defects.

Purpose To investigate macular ganglion cell–inner plexiform layer (mGCIPL) thickness in glaucomatous eyes with visible localized retinal nerve fiber layer (RNFL) defects on stereophotographs. Methods 112 healthy and 149 glaucomatous eyes from the Diagnostic Innovations in Glaucoma Study (DIGS) and the African Descent and Glaucoma Evaluation Study (ADAGES) subjects had standard automated perimetry (SAP), optical coherence tomography (OCT) imaging of the macula and optic nerve head, and stereoscopic optic disc photography. Masked observers identified localized RNFL defects by grading of stereophotographs. Result 47 eyes had visible localized RNFL defects on stereophotographs. Eyes with visible localized RNFL defects had significantly thinner mGCIPL thickness compared to healthy eyes (68.3 ± 11.4 μm versus 79.2 ± 6.6 μm respectively, P<0.001) and similar mGCIPL thickness to glaucomatous eyes without localized RNFL defects (68.6 ± 11.2 μm, P = 1.000). The average mGCIPL thickness in eyes with RNFL defects was 14% less than similarly aged healthy controls. For 29 eyes with a visible RNFL defect in just one hemiretina (superior or inferior) mGCIPL was thinnest in the same hemiretina in 26 eyes (90%). Eyes with inferior-temporal RNFL defects also had significantly thinner inferior-temporal mGCIPL (P<0.001) and inferior mGCIPL (P = 0.030) compared to glaucomatous eyes without a visible RNFL defect. Conclusion The current study indicates that presence of a localized RNFL defect is likely to indicate significant macular damage, particularly in the region of the macular that topographically corresponds to the location of the RNFL defect.