Multi-modal Anterior Eye Imager Combining Ultra-High Resolution OCT and Microvascular Imaging for Structural and Functional Evaluation of the Human Eye

Validation and optimization of smart eye camera as teleophthalmology device for the reduction of preventable and treatable blindness in Nigeria

BACKGROUND/OBJECTIVES

Limited resources and staffing hinders efforts to reduce preventable blindness, especially in low- to middle-income countries. The slit-lamp examination (SLE), which is essential for ophthalmology practices, is often unavailable in primary and secondary eye care facilities due to the high costs and lengthy training required for operation. We conducted a cross-sectional, multicentre study exploring the potential for a smart eye camera (SEC; a tele-ophthalmology handheld device developed by OUI Inc., Japan) to address the limitations of the SLE.

SUBJECT/METHODS

Ocular diagnoses, visual acuity assessments and examinations of the eyes were performed independently using both a conventional SLE and a SEC. Four independent assessors (blind to the study) reviewed the images captured by the SEC and the SLE as administered by separate investigators. All analyses were performed using R version 4.2.2 for macOS at a 5% level of statistical significance.

RESULTS

The results of the image quality analysis demonstrated that the number of higher-quality images was significantly higher (p < 0.05) for the images captured using the SEC device compared to the SLE machine. Remarkably, up to 96% accuracy of diagnosis was recorded with SEC. Evaluation of diagnostic accuracy rates derived from images obtained from both machines revealed a degree of divergence in assessments among evaluators, yielding a Fleiss's Kappa value of 0.092. The sensitivity analysis for the SEC device revealed a reasonably strong capacity to correctly identify true positive cases, with an average sensitivity score of 90%.

CONCLUSION

The results of this study indicate that SEC can effectively evaluate anterior segment lesions in ophthalmology.

Optical Coherence Tomography Angiography (OCTA) of the eye: A review on basic principles, advantages, disadvantages and device specifications

Optical Coherence Tomography Angiography (OCTA) is a relatively new imaging technique in ophthalmology for the visualization of the retinal microcirculation and other tissues of the human eye. This review paper aims to describe the basic definitions and principles of OCT and OCTA in the most straightforward possible language without complex mathematical and engineering analysis. This is done to help health professionals of various disciplines improve their understanding of OCTA and design further clinical research more efficiently. First, the basic technical principles of OCT and OCTA and related terminology are described. Then, a list of OCTA advantages and disadvantages, with a special reference to blood flow quantification limitations. Finally, an updated list of the basic hardware and software specifications of some of the commercially available OCTA devices is presented.

Portable boom-type ultrahigh-resolution OCT with an integrated imaging probe for supine position retinal imaging

To expand the clinical applications and improve the ease of use of ultrahigh-resolution optical coherence tomography (UHR-OCT), we developed a portable boom-type ophthalmic UHR-OCT operating in supine position that can be used for pediatric subjects, bedridden patients and perioperative conditions. By integrating the OCT sample arm probe with real-time iris display and automatic focusing electric lens for easy alignment, coupling the probe on a self-locking multi-directional manipulator to reduce motion artifacts and operator fatigue, and installing the OCT module on a moveable cart for system mobility, our customized portable boom-type UHR-OCT enables non-contact, high-resolution and high-stability retinal examinations to be performed on subjects in supine position. The spectral-domain UHR-OCT operates at a wavelength of 845 nm with 130 nm FWHM (full width at half maximum) bandwidth, achieving an axial resolution of ≈2.3µm in tissue with an A-line acquisition rate up to 128 kHz. A high-definition two-dimensional (2D) raster protocol was used for high-quality cross-sectional imaging while a cube volume three-dimensional (3D) scan was used for three-dimensional imaging and en-face reconstruction, resolving major layer structures of the retina. The feasibility of the system was demonstrated by performing supine position 2D/3D retinal imaging on healthy human subjects, sedated infants, and non-sedated awake neonates.

Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm

The quantification of blood flow velocity in the human conjunctiva is clinically essential for assessing microvascular hemodynamics. Since the conjunctival microvessel is imaged in several seconds, eye motion during image acquisition causes motion artifacts limiting the accuracy of image segmentation performance and measurement of the blood flow velocity. In this paper, we introduce a novel customized optical imaging system for human conjunctiva with deep learning-based segmentation and motion correction. The image segmentation process is performed by the Attention-UNet structure to achieve high-performance segmentation results in conjunctiva images with motion blur. Motion correction processes with two steps—registration and template matching—are used to correct for large displacements and fine movements. The image displacement values decrease to 4–7 μm during registration (first step) and less than 1 μm during template matching (second step). With the corrected images, the blood flow velocity is calculated for selected vessels considering temporal signal variances and vessel lengths. These methods for resolving motion artifacts contribute insights into studies quantifying the hemodynamics of the conjunctiva, as well as other tissues.