The crystalline lens and cornea comprise the eye’s optical system for focusing light in human vision. The changes in biomechanical properties of the lens and cornea are closely associated with common diseases, including presbyopia and cataract. Currently, most in vivo elasticity studies of the anterior eye focus on the measurement of the cornea, while lens measurement remains challenging. To better understand the anterior segment of the eye, we developed an optical coherence elastography system utilizing acoustic radiation force excitation to simultaneously assess the elasticities of the crystalline lens and the cornea in vivo. A swept light source was integrated into the system to provide an enhanced imaging range that covers both the lens and the cornea. Additionally, the oblique imaging approach combined with orthogonal excitation also improved the image quality. The system was tested through first ex vivo and then in vivo experiments using a rabbit model. The elasticities of corneal and lens tissue in an excised normal whole-globe and a cold cataract model were measured to reveal that cataractous lenses have a higher Young’s modulus. Simultaneous in vivo elasticity measurements of the lens and cornea were performed in a rabbit model to demonstrate the correlations between elasticity and intraocular pressure and between elasticity and age. To the best of our knowledge, we demonstrated the first in vivo elasticity of imaging of both the lens and cornea using acoustic radiation force-optical coherence elastography, thereby providing a potential powerful clinical tool to advance ophthalmic research in disorders affecting the lens and the cornea.

We report on a real-time acoustic radiation force optical coherence elastography (ARF-OCE) system to map the relative elasticity of corneal tissue. A modulated ARF is used as excitation to vibrate the cornea, while OCE serves as detection of tissue response. To show feasibility of detecting mechanical contrast using this method, we performed tissue-equivalent agarose phantom studies with inclusions of a different stiffness. We obtained 3-D elastograms of a healthy cornea and a highly cross-linked cornea. Finally, we induced a stiffness change on a small portion of a cornea and observed the differences in displacement.

Purpose: We used acoustic radiation force optical coherence elastography (ARF-OCE) to map out the elasticity of retinal layers in healthy and diseased in vivo rabbit models for the first time. Methods: A healthy rabbit eye was proptosed and imaged using ARF-OCE, by measuring the tissue deformation after an acoustic force is applied. A diseased retinal inflammation model was used to observe the contrast before and after disease formation. Retinal histologic analysis was performed to identify layers of the retina corresponding with the optical images. Results: The general trend of the retinal layer elasticity is increasing stiffness from the ganglion side to the photoreceptor side, with the stiffest layer being the sclera. In a healthy rabbit model, the mechanical properties varied from 3 to 16 kPa for the five layers that were identified via optical imaging and histology (3.09 ± 0.46, 3.82 ± 0.88, 4.53 ± 0.74, 6.59 ± 2.27, 16.11 ± 5.13 kPa). In the diseased model, we have induced optical damage in a live rabbit and observed a change in the stiffness trend in its retina. Conclusions: High sensitivity elasticity maps can be obtained using the ARF-OCE system to differentiate different retinal layers. Subtle changes in the mechanical properties during the onset of diseases, such as retinal degeneration, can be measured and aid in early clinical diagnosis. This study validates our imaging system for the characterization of retinal elasticity for the detection of retinal diseases in vivo.

Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly (over the age of 60 years) in western countries. In the early stages of the disease, structural changes may be subtle and cannot be detected. Recently it has been postulated that the mechanical properties of the retina may change with the onset of AMD. In this manuscript, we present a novel, non-invasive means that utilizes synchronized acoustic radiation force optical coherence elastography (ARF-OCE) to measure and estimate the elasticity of cadaver porcine retina. Both regions near the optic nerve and in the peripheral retina were studied. An acoustic force is exerted on the tissue for excitation and the resulting tissue vibrations, often in the nanometer scale, are detected with high-resolution optical methods. Segmentation has been performed to isolate individual layers and the Young’s modulus has been estimated for each. The results have been successfully compared and mapped to corresponding histological results using H&E staining. Finally, 64 elastograms of the retina were analyzed, as well as the elastic properties, with stiffness ranging from 1.3 to 25.9 kPa in the ganglion to the photoreceptor sides respectively. ARF-OCE allows for the elasticity mapping of anatomical retinal layers. This imaging approach needs further evaluation but has the potential to allow physicians to gain a better understanding of the elasticity of retinal layers in retinal diseases such as AMD.

Automatic and accurate optical coherence tomography (OCT) image classification is of great significance to computer-assisted diagnosis of retinal disease. In this study, we propose a hybrid ConvNet-Transformer network (HCTNet) and verify the feasibility of a Transformer-based method for retinal OCT image classification. The HCTNet first utilizes a low-level feature extraction module based on the residual dense block to generate low-level features for facilitating the network training. Then, two parallel branches of the Transformer and the ConvNet are designed to exploit the global and local context of the OCT images. Finally, a feature fusion module based on an adaptive re-weighting mechanism is employed to combine the extracted global and local features for predicting the category of OCT images in the testing datasets. The HCTNet combines the advantage of the convolutional neural network in extracting local features and the advantage of the vision Transformer in establishing long-range dependencies. A verification on two public retinal OCT datasets shows that our HCTNet method achieves an overall accuracy of 91.56% and 86.18%, respectively, outperforming the pure ViT and several ConvNet-based classification methods.

We report on a novel acoustic radiation force orthogonal excitation optical coherence elastography (ARFOE-OCE) technique for imaging shear wave and quantifying shear modulus under orthogonal acoustic radiation force (ARF) excitation using the optical coherence tomography (OCT) Doppler variance method. The ARF perpendicular to the OCT beam is produced by a remote ultrasonic transducer. A shear wave induced by ARF excitation propagates parallel to the OCT beam. The OCT Doppler variance method, which is sensitive to the transverse vibration, is used to measure the ARF-induced vibration. For analysis of the shear modulus, the Doppler variance method is utilized to visualize shear wave propagation instead of Doppler OCT method, and the propagation velocity of the shear wave is measured at different depths of one location with the M scan. In order to quantify shear modulus beyond the OCT imaging depth, we move ARF to a deeper layer at a known step and measure the time delay of the shear wave propagating to the same OCT imaging depth. We also quantitatively map the shear modulus of a cross-section in a tissue-equivalent phantom after employing the B scan.