Taeyoon Son

SignificanceStimulus-evoked intrinsic optical signal (IOS) changes in retinal photoreceptors are critical for functional optoretinography (ORG). Optical coherence tomography (OCT), with its depth-resolved imaging capability, has been actively explored for IOS imaging of retinal photoreceptors. However, recent OCT studies have reported conflicting results regarding light-induced changes in the photoreceptor outer segments (OSs), with both elongation and shrinkage being observed. These discrepancies may stem from the difficulty in reliably identifying OS boundaries, particularly the inner segment/outer segment (IS/OS) junction and OS tip, as well as potential confusion with subretinal space dynamics. Gaining a better understanding of these light-induced OS changes is essential for accurate interpretation of ORG measurements and for optimizing IOS imaging systems to enhance sensitivity.AimWe aim to develop a method for the reliable identification of OS boundaries and to verify light-induced photoreceptor OS shrinkage and subretinal space expansion.ApproachWe employed a polarization-resolved full-field swept-source optical coherence tomography system capable of sequentially capturing parallel-polarization and cross-polarization OCT signals. The parallel-polarization mode is optimized to detect ballistically reflected photons from well-defined retinal boundaries, such as the IS/OS junction and the photoreceptor tips, whereas cross-polarization primarily captures multiply scattered photons. This differentiation enables parallel-polarization OCT to minimize the interference from scattered photons, enhancing the precision of OCT band quantification.ResultsParallel-polarization OCT revealed photoreceptor OS shrinkage and subretinal space expansion in light conditions compared with dark conditions. Moreover, the overall outer retinal length appeared to swell under light. These observations were consistently confirmed in four healthy adult human subjects.ConclusionsParallel-polarization OCT provides a reliable method for identifying the IS/OS junction and OS tip, confirming light-induced photoreceptor OS shrinkage and subretinal space expansion.

Retinopathy of prematurity (ROP) occurs in premature infants due to underdeveloped retinal vasculature at birth,¹ causing abnormal blood vessel growth at the boundary of partially vascularized and avascular retinal areas.^2,3 ROP is the leading preventable cause of childhood blindness worldwide.^4,5 The severity of ROP is classified into five stages, corresponding to mild to severe stages.⁶ Appropriate detection and accurate ROP diagnosis in premature infants is crucial to prevent irreversible vision loss and associated visual developmental complications such as astigmatism, myopia, glaucoma, cataracts, anisometropia, amblyopia, strabismus, and retinal detachment.^7,8

Ultrasound A-scan is an important tool for quantitative assessment of ocular lesions. However, its usability is limited by the difficulty of accurately localizing the ultrasound probe to a lesion of interest. In this study, a transparent LiNbO₃ single crystal ultrasound transducer was fabricated, and integrated with a widefield fundus camera to guide the ultrasound local position. The electrical impedance, phase spectrum, pulse-echo performance, and optical transmission spectrum of the ultrasound transducer were validated. The novel fundus camera-guided ultrasound probe was tested for in vivo measurement of rat eyes. Anterior and posterior segments of the rat eye could be unambiguously differentiated with the fundus photography-guided ultrasound measurement. A model eye was also used to verify the imaging performance of the prototype device in the human eye. The prototype shows the potential of being used in the clinic to accurately measure the thickness and echogenicity of ocular lesions in vivo.

Ultrasound A-scan is an important tool for quantitative assessment of ocular lesions. However, its usability is limited by difficulty to accurately localize the ultrasound probe to a lesion of interest. In this study, a transparent LiNbO3 single crystal ultrasound transducer was fabricated, and integrated with a widefield fundus camera to guide the ultrasound local position. The novel fundus camera guided ultrasound probe was validated for in vivo measurement of rat eyes. Anterior and posterior segments of the rat eye could be unambiguously differentiated with the fundus photography guided ultrasound measurement. A model eye was also used to verify the clinical potential of the prototype device.

Major retinopathies can differentially impact the arteries and veins. Traditional fundus photography provides limited resolution for visualizing retinal vascular details. Optical coherence tomography (OCT) can provide improved resolution for retinal imaging. However, it cannot discern capillary-level structures due to the limited image contrast. As a functional extension of OCT modality, optical coherence tomography angiography (OCTA) is a non-invasive, label-free method for enhanced contrast visualization of retinal vasculatures at the capillary level. Recently differential artery–vein (AV) analysis in OCTA has been demonstrated to improve the sensitivity for staging of retinopathies. Therefore, AV classification is an essential step for disease detection and diagnosis. However, current methods for AV classification in OCTA have employed multiple imagers, that is, fundus photography and OCT, and complex algorithms, thereby making it difficult for clinical deployment. On the contrary, deep learning (DL) algorithms may be able to reduce computational complexity and automate AV classification. In this article, we summarize traditional AV classification methods, recent DL methods for AV classification in OCTA, and discuss methods for interpretability in DL models.

Accurate image registration is essential for eye movement compensation in optical coherence tomography (OCT) and OCT angiography (OCTA). The spatial resolution of an OCT instrument is typically anisotropic, i.e., different resolutions in the lateral and axial dimensions. When OCT images have anisotropic pixel resolution, residual distortion (RD) and false translation (FT) were always observed after image registration for rotational movement. In this study, RD and FT were quantitively analyzed over different degrees of rotational movement and various lateral and axial pixel resolution ratio (RL/RA) values. The theoretical analysis confirmed that the RD and FT increase significantly with the rotation degree and RL/RA. An image resizing assisting registration (RAR) strategy was proposed for accurate image registration. The performance of direct registration (DR) and RAR for retinal OCT and OCTA images were quantitatively compared. Experimental results confirmed that unnormalized RL/RA causes RD and FT, RAR can effectively improve the performance of OCT and OCTA image registration and distortion compensation.

SPIE Digital Library Proceedings

Intrinsic optical signal (IOS) imaging of the retina, also termed as optoretinography (ORG), promises a noninvasive method for objective assessment of retinal function. By providing unparalleled capability to differentiate individual layers of the retina, functional optical coherence tomography (OCT) has been actively investigated for intrinsic signal ORG measurements. However, clinical deployment of functional OCT for quantitative ORG is still challenging due to the lack of a standardized imaging protocol and the complication of IOS sources and mechanisms. This article aims to summarize recent developments of functional OCT for ORG measurement, OCT intensity- and phase-based IOS processing. Technical challenges and perspectives of quantitative IOS analysis and ORG interpretations are discussed.

Chromatic dispersion is a common problem to degrade the system resolution in optical coherence tomography (OCT). This study is to develop a deep learning network for automated dispersion compensation (ADC-Net) in OCT. The ADC-Net is based on a redesigned UNet architecture which employs an encoder-decoder pipeline. The input section encompasses partially compensated OCT B-scans with individual retinal layers optimized. Corresponding output is a fully compensated OCT B-scans with all retinal layers optimized. Two numeric parameters, i.e., peak signal to noise ratio (PSNR) and structural similarity index metric computed at multiple scales (MS-SSIM), were used for objective assessment of the ADC-Net performance. Comparative analysis of training models, including single, three, five, seven and nine input channels were implemented. The five-input channels implementation was observed as the optimal mode for ADC-Net training to achieve robust dispersion compensation in OCT