A survey and comparative study on the instruments for glaucoma detection

Rapid tear screening of diabetic retinopathy by a detachable surface acoustic wave enabled immunosensor

BACKGROUND

Diabetic retinopathy (DR), a chronic and progressive microvascular complication of diabetes mellitus, substantially threatens vision and is a leading cause of blindness among working-age individuals worldwide. Traditional diagnostic methods, such as ophthalmoscopy and fluorescein angiography are nonquantitative, invasive, and time consuming. Analysis of protein biomarkers in tear fluid offers noninvasive insights into ocular and systemic health, aiding in early DR detection. This study introduces a surface acoustic wave (SAW) microchip that rapidly enhances fluorescence in bead-based immunoassays for the sensitive and noninvasive DR detection from human tear samples.

RESULTS

The device facilitated particle mixing for immunoassay formation and particle concentration in the droplet, resulting in an enhanced immunofluorescence signal. This detachable SAW microchip allows the disposal of the cover glass after every use, thereby improving the reusability of the interdigital transducer and minimizing potential cross-contamination. A preliminary clinical test was conducted on a cohort of 10 volunteers, including DR patients and healthy individuals. The results demonstrated strong agreement with ELISA studies, validating the high accuracy rate of the SAW microchip.

SIGNIFICANCE

This comprehensive study offers significant insights into the potential application of a novel SAW microchip for the early detection of DR in individuals with diabetes. By utilizing protein biomarkers found in tear fluid, the device facilitates noninvasive, rapid, and sensitive detection, potentially revolutionizing DR diagnostics and improving patient outcomes through timely intervention and management of this vision-threatening condition.

Classification of Glaucoma Stages Using Image Empirical Mode Decomposition from Fundus Images

One of the most prevalent causes of visual loss and blindness is glaucoma. Conventionally, instrument-based tools are employed for glaucoma screening. However, they are inefficient, time-consuming, and manual. Hence, computerized methodologies are needed for fast and accurate diagnosis of glaucoma. Therefore, we proposed a Computer-Aided Diagnosis (CAD) method for the classification of glaucoma stages using Image Empirical Mode decomposition (IEMD). In this study, IEMD is applied to decompose the preprocessed fundus photographs into different Intrinsic Mode Functions (IMFs) to capture the pixel variations. Then, the significant texture-based descriptors have been computed from the IMFs. A dimensionality reduction approach called Principal Component Analysis (PCA) has been employed to pick the robust descriptors from the retrieved feature set. We used the Analysis of Variance (ANOVA) test for feature ranking. Finally, the LS-SVM classifier has been employed to classify glaucoma stages. The proposed CAD system achieved a classification accuracy of 94.45% for the binary classification on the RIM-ONE r12 database. Our approach demonstrated better glaucoma classification performance than the existing automated systems.

Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis

AIM

To compare the effectiveness of two well described machine learning modalities, ocular coherence tomography (OCT) and fundal photography, in terms of diagnostic accuracy in the screening and diagnosis of glaucoma.

METHODS

A systematic search of Embase and PubMed databases was undertaken up to 1^st of February 2019. Articles were identified alongside their reference lists and relevant studies were aggregated. A Meta-analysis of diagnostic accuracy in terms of area under the receiver operating curve (AUROC) was performed. For the studies which did not report an AUROC, reported sensitivity and specificity values were combined to create a summary ROC curve which was included in the Meta-analysis.

RESULTS

A total of 23 studies were deemed suitable for inclusion in the Meta-analysis. This included 10 papers from the OCT cohort and 13 from the fundal photos cohort. Random effects Meta-analysis gave a pooled AUROC of 0.957 (95%CI=0.917 to 0.997) for fundal photos and 0.923 (95%CI=0.889 to 0.957) for the OCT cohort. The slightly higher accuracy of fundal photos methods is likely attributable to the much larger database of images used to train the models (59 788 vs 1743).

CONCLUSION

No demonstrable difference is shown between the diagnostic accuracy of the two modalities. The ease of access and lower cost associated with fundal photo acquisition make that the more appealing option in terms of screening on a global scale, however further studies need to be undertaken, owing largely to the poor study quality associated with the fundal photography cohort.

Automated detection of glaucoma using optical coherence tomography angiogram images

Glaucoma is a malady that occurs due to the buildup of fluid pressure in the inner eye. Detection of glaucoma at an early stage is crucial as by 2040, 111.8 million people are expected to be afflicted with glaucoma globally. Feature extraction methods prove to be promising in the diagnosis of glaucoma. In this study, we have used optical coherence tomography angiogram (OCTA) images for automated glaucoma detection. Ocular sinister (OS) from the left eye while ocular dexter (OD) were obtained from right eye of subjects. We have used OS macular, OS disc, OD macular and OD disc images. In this work, local phase quantization (LPQ) technique was applied to extract the features. Information fusion and principal component analysis (PCA) are used to combine and reduce the features. Our method achieved the highest accuracy of 94.3% using LPQ coupled with PCA for right eye optic disc images with AdaBoost classifier. The proposed technique can aid clinicians in glaucoma detection at an early stage. The developed model is ready to be tested with more images before deploying for clinical application.

Distribution of Anterior Chamber Parameters in Normal Chinese Children and the Associated Factors

PURPOSE

To describe the distribution of anterior chamber depth (ACD), anterior chamber volume (ACV), and anterior chamber angle (ACA) and establish the associated factors in the pediatric population in Shanghai, China.

MATERIALS AND METHODS

In this cross-sectional study, children aged 6 to 18 years from 9 primary and middle schools in Shanghai were enrolled. The Pentacam Scheimpflug camera was used to measure anterior eye chamber parameters. The distribution of ACD, ACV, ACA, and their associations with age, sex, body mass index, cycloplegic refractive error, axial length, intraocular pressure, and other parameters were analyzed.

RESULTS

A total of 1321 children were included, with a mean age of 9.65±2.95 years. The mean ACA, ACD, and ACV values were 37.95±7.96 degrees, 3.22±0.23 mm and 194.89±28.95 mm, respectively, and were higher in boys than in girls. ACV and ACD had similar growth trend curves with age, whereas ACA was stable. Overall, 5% of the tested children had ACA values ≤24.91 degrees. Greater ACV, deeper ACD, shorter pupil diameter, shorter axial length, and thinner apex corneal thickness were the independent factors associated with wider ACA (R=13.0%, P<0.001).

CONCLUSIONS

As one of diagnostic indicators of angle closure, ACA was stable with age. The results of this study should improve the current understanding of the distribution of anterior chamber parameters and the main factors affecting their variation.

Characterization of Corneal Biomechanical Properties and Determination of Natural Intraocular Pressure Using CID-GAT

Purpose

The intraocular pressure (IOP) measured using Goldmann Applanation Tonometry (GAT) is confounded by individual corneal properties. We investigated a modified method that removes the confoundment by incorporating corneal properties into the Imbert-Fick's law is investigated.

Method

Porcine eyes were pressurized between 10 and 40 mm Hg using a manometer. The eyes were indented using a flat cylindrical indenter. A modified corneal indentation device (CID) procedure was used to obtain the corneal moduli E_qs. The calculated IOP_NC from the Imbert-Fick's Law using the corneal moduli E_qs was compared to the natural IOP_N, measured using pressure sensor inserted into the eye.

Results

Test results showed that IOP-dependent corneal modulus E_qs is a primary confounding factor in IOP calculation. The average elastic modulus E_qs is 0.173 ± 0.018 MPa at 20 mm Hg, and increases with IOP at a linear rate of 0.0066 MPa per mm Hg (r = 0.997, P < 0.001). Incorporation of individual E_qs into IOP_NC calculation showed that IOP_NC are in good agreement with reference IOP_N (slope = 0.999, r = 0.939, P < 0.001).

Conclusions

The IOP-dependent corneal modulus E_qs is a primary confounding factor in IOP calculation. A modified CID-GAT procedure to obtain natural cornea-independent IOP_NC is developed and verified in this study. The CID-GAT IOP modification may be used in place of conventional GAT when the confounding effects in eyes with atypical cornea (e.g., laser-assisted in situ keratomileusis [LASIK] thinned) are significant.

Translational Relevance

Confoundment from corneal properties results in IOP measurement errors. The study showed that the CID-GAT method can significantly reduce the confounding corneal errors.

Computer-aided diagnosis of glaucoma using fundus images: A review

BACKGROUND AND OBJECTIVES

Glaucoma is an eye condition which leads to permanent blindness when the disease progresses to an advanced stage. It occurs due to inappropriate intraocular pressure within the eye, resulting in damage to the optic nerve. Glaucoma does not exhibit any symptoms in its nascent stage and thus, it is important to diagnose early to prevent blindness. Fundus photography is widely used by ophthalmologists to assist in diagnosis of glaucoma and is cost-effective.

METHODS

The morphological features of the disc that is characteristic of glaucoma are clearly seen in the fundus images. However, manual inspection of the acquired fundus images may be prone to inter-observer variation. Therefore, a computer-aided detection (CAD) system is proposed to make an accurate, reliable and fast diagnosis of glaucoma based on the optic nerve features of fundus imaging. In this paper, we reviewed existing techniques to automatically diagnose glaucoma.

RESULTS

The use of CAD is very effective in the diagnosis of glaucoma and can assist the clinicians to alleviate their workload significantly. We have also discussed the advantages of employing state-of-art techniques, including deep learning (DL), when developing the automated system. The DL methods are effective in glaucoma diagnosis.

CONCLUSIONS

Novel DL algorithms with big data availability are required to develop a reliable CAD system. Such techniques can be employed to diagnose other eye diseases accurately.

Mean curvature and texture constrained composite weighted random walk algorithm for optic disc segmentation towards glaucoma screening

Accurate optic disc (OD) segmentation is an important step in obtaining cup-to-disc ratio-based glaucoma screening using fundus imaging. It is a challenging task because of the subtle OD boundary, blood vessel occlusion and intensity inhomogeneity. In this Letter, the authors propose an improved version of the random walk algorithm for OD segmentation to tackle such challenges. The algorithm incorporates the mean curvature and Gabor texture energy features to define the new composite weight function to compute the edge weights. Unlike the deformable model-based OD segmentation techniques, the proposed algorithm remains unaffected by curve initialisation and local energy minima problem. The effectiveness of the proposed method is verified with DRIVE, DIARETDB1, DRISHTI-GS and MESSIDOR database images using the performance measures such as mean absolute distance, overlapping ratio, dice coefficient, sensitivity, specificity and precision. The obtained OD segmentation results and quantitative performance measures show robustness and superiority of the proposed algorithm in handling the complex challenges in OD segmentation.

Tonometers-which one should I use?

Although several factors are known to play a role in the development and progression of glaucoma, intraocular pressure (IOP) remains the only modifiable risk factor. Medical and surgical treatments for glaucoma both aim to reduce IOP to minimize disease progression. Tonometry is therefore an essential element of the ophthalmological exam. There are several types of tonometers available currently. These range from well-established instruments that have been in clinical use for decades to new devices, which are the result of recent technological advances. The various instruments have advantages and disadvantages that affect their suitability for a given setting, purpose, and patient population. In this review, we aim to describe the most commonly available tonometers today along with their advantages, disadvantages, and applicability.

Adaptive optics optical coherence tomography in glaucoma

Since the introduction of commercial optical coherence tomography (OCT) systems, the ophthalmic imaging modality has rapidly expanded and it has since changed the paradigm of visualization of the retina and revolutionized the management and diagnosis of neuro-retinal diseases, including glaucoma. OCT remains a dynamic and evolving imaging modality, growing from time-domain OCT to the improved spectral-domain OCT, adapting novel image analysis and processing methods, and onto the newer swept-source OCT and the implementation of adaptive optics (AO) into OCT. The incorporation of AO into ophthalmic imaging modalities has enhanced OCT by improving image resolution and quality, particularly in the posterior segment of the eye. Although OCT previously captured in-vivo cross-sectional images with unparalleled high resolution in the axial direction, monochromatic aberrations of the eye limit transverse or lateral resolution to about 15-20 μm and reduce overall image quality. In pairing AO technology with OCT, it is now possible to obtain diffraction-limited resolution images of the optic nerve head and retina in three-dimensions, increasing resolution down to a theoretical 3 μm3. It is now possible to visualize discrete structures within the posterior eye, such as photoreceptors, retinal nerve fiber layer bundles, the lamina cribrosa, and other structures relevant to glaucoma. Despite its limitations and barriers to widespread commercialization, the expanding role of AO in OCT is propelling this technology into clinical trials and onto becoming an invaluable modality in the clinician's arsenal.

Course of serum autoantibodies in patients after acute angle-closure glaucoma attack

BACKGROUND

The aim of our investigation was to analyze the autoantibody -reactivities of patients after acute angle-closure glaucoma (AACG) by means of a protein microarray approach to identify intraocular pressure(IOP)-dependent antibodies.

METHODS

Collected sera from different study time points (AACG n = 6, 0, 2, 4 and 12 weeks) and control group (CTRL n = 11, 0 and 12 weeks) were analyzed. Protein-microarrays were incubated with sera, and occurring immunoreactivities were visualized with fluorescence labeled secondary antibodies. To detect changes, spot intensities were digitized and compared with statistical techniques.

RESULTS

Three autoantibodies with significant level-alteration in the time course of the survey could be identified. Immunoreactivities to heat shock 27-kDa protein (HSP27), tubulin-tyrosine ligase-like protein 12 (TTLL12), and neuron-specific enolase (NSE) show an increasing linear trend from week 0 up to week 12 with a positive correlation coefficient (P ≤ 0.05, r ≥ 0.4). In the CTRL- group, no significant alterations could be detected in corresponding autoantibody-level. Analysis of variance revealed significant changes of antibody-level between certain time points (anti-HSP27 antibody [week 0 vs. 2], anti-TTLL12 antibody [week 0 vs. 12], and anti-NSE antibody [week 4 vs. 12] [P ≤ 0.05, respectively]) in AACG group.

CONCLUSIONS

With this autoantibodies profiling approach, we were able to detect autoimmune reactivities in sera of patients without former indication for glaucomatous damage after rise of IOP due to AACG attack. After further validation in subsequent studies, this autoantibodies could give further insights into the pathogenesis of glaucoma and could possibly help to understand the effect of IOP on glaucomatous optic neuropathy.

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images

Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM).

Individual-specific tonometry on porcine eyes

Intraocular pressure (IOP) monitoring is important in the diagnosis and management of glaucoma. The measurement of IOP is affected by corneal properties, but the effect of corneal stiffness on IOP measurement is unaccounted for in pressure measurement instruments such as the Goldmann Applanation Tonometer (GAT). A new instrumented non-invasive indentation tonometry that can measure IOPIST, a corneal stiffness-corrected intraocular pressure is developed. The inter-individual corneal variations of 12 porcine eyes ex vivo were independently characterized; and their true intraocular pressure, IOPT's, were set using a manometer before indentation using the new indentation tonometry. Analyses of the load-displacement data showed that porcine corneal stiffness varied more than five times from 0.045 to 0.253N/mm. Analysis showed that, without individual stiffness correction, inter-individual variation of IOPGAT can vary up to 8mmHg from IOPT at 15mmHg; the error becomes larger at high IOPT. In comparison when corneal stiffness is accounted for, IOPIST has a significantly smaller error of 1.82±1.70mmHg for IOPT between 12 and 40mmHg than IOPGAT. The results showed that the new tonometry successfully accounted for inter-individual variations in IOP measurement.

Adaptive optics retinal imaging--clinical opportunities and challenges

The array of therapeutic options available to clinicians for treating retinal disease is expanding. With these advances comes the need for better understanding of the etiology of these diseases on a cellular level as well as improved non-invasive tools for identifying the best candidates for given therapies and monitoring the efficacy of those therapies. While spectral domain optical coherence tomography offers a widely available tool for clinicians to assay the living retina, it suffers from poor lateral resolution due to the eye's monochromatic aberrations. Ophthalmic adaptive optics (AO) is a technique to compensate for the eye's aberrations and provide nearly diffraction-limited resolution. The result is the ability to visualize the living retina with cellular resolution. While AO is unquestionably a powerful research tool, many clinicians remain undecided on the clinical potential of AO imaging - putting many at a crossroads with respect to adoption of this technology. This review will briefly summarize the current state of AO retinal imaging, discuss current as well as future clinical applications of AO retinal imaging, and finally provide some discussion of research needs to facilitate more widespread clinical use.

Optical properties of retinal tissue and the potential of adaptive optics to visualize retinal ganglion cells in vivo

Many efforts have been made to improve the diagnostic tools used to identify and to estimate the progress of ganglion cell and nerve fibre degeneration in glaucoma. Imaging by optical coherence tomography and measurements of the dimensions of the optic nerve head and the nerve fibre layer in central retinal areas is currently used to estimate the grade of pathological changes. The visualization and quantification of ganglion cells and nerve fibres directly in patients would dramatically improve glaucoma diagnostics. We have investigated the optical properties of cellular structures of retinal tissue in order to establish a means of visualizing and quantifying ganglion cells in the living retina without staining. We have characterized the optical properties of retinal tissue in several species including humans. Nerve fibres, blood vessels, ganglion cells and their cell processes have been visualized at high image resolution by means of the reflection mode of a confocal laser scanning microscope. The potential of adaptive optics in current imaging systems and the possibilities of imaging single ganglion cells non-invasively in patients are discussed.

Adaptive optics technology for high-resolution retinal imaging

Adaptive optics (AO) is a technology used to improve the performance of optical systems by reducing the effects of optical aberrations. The direct visualization of the photoreceptor cells, capillaries and nerve fiber bundles represents the major benefit of adding AO to retinal imaging. Adaptive optics is opening a new frontier for clinical research in ophthalmology, providing new information on the early pathological changes of the retinal microstructures in various retinal diseases. We have reviewed AO technology for retinal imaging, providing information on the core components of an AO retinal camera. The most commonly used wavefront sensing and correcting elements are discussed. Furthermore, we discuss current applications of AO imaging to a population of healthy adults and to the most frequent causes of blindness, including diabetic retinopathy, age-related macular degeneration and glaucoma. We conclude our work with a discussion on future clinical prospects for AO retinal imaging.