The EXPLORE Study - The Use of Binocular OCT Imaging for the Assessment of Ocular Disease

Eye Diseases Clinical Trial

Official title: A Prospective Single-Site Non-Interventional Exploratory Study Using a Prototype Binocular Optical Coherence Tomography System for Imaging of Ocular Disease

Status Completed

Clinical Trial Summary

Optical coherence tomography (OCT) is an imaging modality, first described in 1991, that provides cross-sectional images of the eye in a non-invasive manner. OCT is analogous to ultrasonography but measures the "echoes" of light waves rather than sound and, as a result, generates extremely high-resolution images (~5 μm axial resolution). Although OCT has already proven revolutionary in ophthalmology, current OCT systems are large, expensive, and require skilled personnel for image acquisition and interpretation. Furthermore, current OCT systems are limited to examination of specific regions of single eyes - for example, separate devices are typically required for anterior segment (e.g., cornea) versus posterior segment (e.g., retina) imaging. A new form of OCT imaging has recently been developed - so-called "binocular" optical coherence tomography (OCT) (Envision Diagnostics, Inc., California).1,2 Binocular OCT addresses many of the short-comings of conventional OCT devices.

Binocular OCT extends the application of OCT devices beyond that of simple, cross- sectional imaging to a diverse array of diagnostic tests. The binocular design also removes the need for additional personnel to perform testing (i.e., the device can be self-operated in an automated manner), and allows for novel testing to be performed that is not possible with monocular imaging. In particular, binocular OCT devices have the potential to perform automated, quantitative pupillary measurements - an entirely novel application for this imaging modality, plus also adds a number of unique capabilities. In particular, binocular OCT removes the need for additional personnel to acquire the images by enabling patients to align the optical axes of the instrument with the optical axes of their own eyes. The system also employs recently developed "swept-source" lasers as its light source, allowing it to see deeper into the eye than conventional OCT systems. Finally, binocular OCT systems allow image capture from both eyes at the same time. This "simultaneous" ocular imaging extends the range of diagnostic testing possible, allowing for features such as pupillometry and ocular motility.

The greatly increased range of imaging for these lasers enables the entire depth of eye tissue to be captured in just a few sequences of images - so- called "whole eye" OCT or "OCT ophthalmoscopy".

In this study, the investigators aim to explore the unique imaging features of the binocular OCT to describe novel features across a range of diseases. The repeatability of quantifying various parameters in the images acquired using the system will be assessed.

Clinical Trial Description

Imaging of the retina using OCT is the commonest ophthalmic imaging procedure worldwide - in 2011, it is estimated that more than 20 million retinal OCT images were obtained, more than the sum of all other ophthalmic imaging procedures combined).4 OCT is also used to image the anterior segment, particularly to measure corneal thickness, in glaucoma to measure the irido-corneal angle, 5 and more recently to measure cells in ocular inflammatory conditions. In addition, vitreous imaging may be useful to measure cells in the posterior chamber.

Most OCT systems are dedicated to retinal imaging or anterior segment imaging. Some commercial retinal scanners are capable of switching between anterior and posterior imaging modes with additional optical attachments, however anterior segment imaging performance is typically suboptimal in these instruments. A key feature of the Binocular OCT is that it can perform 'whole-eye' OCT imaging spanning from the eyelids to the posterior pole in a single instrument without the requirement of additional attachments, and in an automated way.

This study will determine whether the instrument can be used for patients with different eye diseases. The investigators anticipate recruiting approximately 100 participants with anterior eye conditions such as keratoconus, acute anterior uveitis, and pigment dispersion syndrome, in addition to approximately 100 participants with posterior segment eye conditions such as diabetic retinopathy, age-related macular degeneration, and glaucoma.

As this device can image many structures of the eye and with a greater depth range than most commercial OCT devices, it may be possible to visualise features not previously imaged with other devices such as vitreous imaging, or imaging of cells in the ocular inflammatory conditions. In this study, the prototype binocular OCT system will be used to describe novel features across a range of ocular diseases. Qualitative analyses of raw binocular OCT images will be performed (including assessments of retinal pathological features, corneal and anterior chamber morphology, lens status, iris dynamics, and ocular inflammatory cells). These parameters will be correlated with findings from other non-invasive ocular imaging previously obtained during routine clinical care. Although raw OCT images can be useful for diagnosis, quantitative data from the images are useful to monitor eye disease. Commercial OCT devices have built-in software packages to analyse OCT images to provide the clinician with parameters for detecting and monitoring eye disease. Quantitative analysis of binocular OCT images will be performed using MATLAB (The MathWorks, Inc., Natick, Massachusetts, United States).

In addition, the ability to combine structural and functional assessments in the same instrument may permit better examinations of ophthalmic disease compared to separate clinical tests. This study will also permit future studies to be correctly powered. ;

Related Conditions & MeSH terms

• Eye Diseases
• Eye Infections
• Eye Inflammation
• Inflammation

• NCT number: NCT03553017
• Study type: Observational
• Source: University College, London
• Status: Completed
• Start date: May 22, 2018
• Completion date: March 1, 2020