Adaptive Optics Retinal Imaging Research Articles

Adaptive optics retinal imaging in patients with usher syndrome

PurposeTo determine the structure of the cone photoreceptor mosaic in the macula in eyes with retinitis pigmentosa related to Usher syndrome using adaptive optics fundus (AO) imaging and to correlate these findings with those of the standard clinical diagnostics.MethodsTen patients with a genetically confirmed retinitis pigmentosa in Usher syndrome due to biallelic variants in MYO7A or USH2A were enrolled in the study. All patients underwent a complete ophthalmological examination including best corrected visual acuity (BCVA), spectral-domain optical coherence tomography (SD-OCT) with fundus autofluorescence photography (FAF), full-field (ffERG) and multifocal electroretinography (mfERG) and Adaptive Optics Flood Illuminated Ophthalmoscopy (AO, rtx1™, Imagine Eyes, Orsay, France). The cone density was assessed centrally and at each 0.5 degree horizontally and vertically from 1–4 degree of eccentricity.ResultsIn the AO images, photoreceptor cell death was visualized as a disruption of the cone mosaic and low cone density. In the early stage of the disease, cones were still visible in the fovea, whereas outside the fovea a loss of cones was recognizable by blurry, dark patches. The blurry patches corresponded to the parafoveal hypofluorescent ring in the FAF images and the beginning loss of the IS/OS line and external limiting membrane in the SD-OCT images. FfERGs were non-recordable in 7 patients and reduced in 3. The mfERG was reduced in all patients and correlated significantly (p <0.001) with the cone density. The kinetic visual field area, measured with III4e and I4e, did not correlate with the cone density.ConclusionThe structure of the photoreceptors in Usher syndrome patients were detectable by AO fundus imaging. The approach of using high-resolution technique to assess the photoreceptor structure complements the established clinical examinations and allows a more sensitive monitoring of early stages of retinitis pigmentosa in Usher syndrome.

Adaptive Optics Retinal Imaging in RDH12-Associated Early Onset Severe Retinal Dystrophy.

RDH12 is among the most common genes found in individuals with early-onset severe retinal (EOSRD). Adaptive optics scanning light ophthalmoscopy (AOSLO) enables resolution of individual rod and cone photoreceptors in the retina. This study presents the first AOSLO imaging of individuals with RDH12-associated EOSRD. Case series of patients who attended Moorfields Eye Hospital (London, UK). Spectral-domain optical coherence tomography, near-infrared reflectance (NIR), and blue autofluorescence imaging were analyzed. En face image sequences of photoreceptors were recorded using either of two AOSLO modalities. Cross-sectional analysis was undertaken for seven patients and longitudinal analysis for one patient. Nine eyes from eight patients are presented in this case series. The mean age at the time of the assessment was 11.2 ± 6.5years of age (range 7-29). A subfoveal continuous ellipsoid zone (EZ) line was present in eight eyes. Posterior pole AOSLO revealed patches of cone mosaics. Average cone densities at regions of interest 0.5° to the fovea ranged from 12,620 to 23,660 cells/mm2, whereas intercell spacing ranged from 7.0 to 9.7µm. This study demonstrates that AOSLO can provide useful high-quality images in patients with EOSRD, even during childhood, with nystagmus, and early macular atrophy. Cones at the posterior pole can appear as scattered islands or, possibly later in life, as a single subfoveal conglomerate. Detailed image analysis suggests that retinal pigment epithelial stress and dysfunction may be the initial step toward degeneration, with NIR being a useful tool to assess retinal well-being in RDH12-associated EOSRD.

Semi-supervised generative adversarial learning for denoising adaptive optics retinal images.

This study presents denoiseGAN, a novel semi-supervised generative adversarial network, for denoising adaptive optics (AO) retinal images. By leveraging both synthetic and real-world data, denoiseGAN effectively addresses various noise sources, including blur, motion artifacts, and electronic noise, commonly found in AO retinal imaging. Experimental results demonstrate that denoiseGAN outperforms traditional image denoising methods and the state-of-the-art conditional GAN model, preserving retinal cell structures and enhancing image contrast. Moreover, denoiseGAN aids downstream analysis, improving cell segmentation accuracy. Its 30% faster computational efficiency makes it a potential choice for real-time AO image processing in ophthalmology research and clinical practice.

Substrip-based registration and automatic montaging of adaptive optics retinal images.

Precise registration and montage are critical for high-resolution adaptive optics retinal image analysis but are challenged by rapid eye movement. We present a substrip-based method to improve image registration and facilitate the automatic montaging of adaptive optics scanning laser ophthalmoscopy (AOSLO). The program first batches the consecutive images into groups based on a translation threshold and selects an image with minimal distortion within each group as the reference. Within each group, the software divides each image into multiple strips and calculates the Normalized Cross-Correlation with the reference frame using two substrips at both ends of the whole strip to estimate the strip translation, producing a registered image. Then, the software aligns the registered images of all groups also using a substrip based registration, thereby generating a montage with cell-for-cell precision in the overlapping areas of adjacent frames. The algorithm was evaluated with AOSLO images acquired in human subjects with normal macular health and patients with age-related macular degeneration (AMD). Images with a motion amplitude of up to 448 pixels in the fast scanner direction over a frame of 512 × 512 pixels can be precisely registered. Automatic montage spanning up to 22.6 degrees on the retina was achieved on a cell-to-cell precision with a low misplacement rate of 0.07% (11/16,501 frames) in normal eyes and 0.51% (149/29,051 frames) in eyes with AMD. Substrip based registration significantly improved AOSLO registration accuracy.

Pregnancy induces retinal microvascular changes indicating cardio-metabolic stress

We performed longitudinal examinations of the arterial retinal microvasculature using Adaptive Optics Retinal Imaging in a 30-year-old healthy woman with twin pregnancy from the 23rd week of gestation (wog) to three days postpartum. Two blinded graders recorded the average wall-to-lumen ratio (WLR) of the examined retinal artery. There was a significant increase in the mean WLR over the course of pregnancy followed by a decreasing WLR from the 37th wog. The demonstrated changes in WLR may be an expression of vascular remodeling and adaptation to volume load which indicates that pregnancy can be viewed as a cardiovascular stress test.

Mapping the human parafoveal vascular network to understand flow variability in capillaries.

Capillary flow is known to be non-homogenous between vessels and variable over time, for reasons that are poorly understood. The local properties of individual vessels have been shown to have limited explanatory power in this regard. This exploratory study investigates the association of network-level properties such as vessel depth, branch order, and distance from the feeding arteriole with capillary flow. Detailed network connectivity analysis was undertaken in 3 healthy young subjects using flood-illuminated adaptive optics retinal imaging, with axial depth of vessels determined via optical coherence tomography angiography. Forty-one out of 70 vessels studied were of terminal capillary type, i.e. fed from an arterial junction and drained by a venous junction. Approximately half of vessel junctions were amenable to fitting with a model of relative branch diameters, with only a few adhering to Murray's Law. A key parameter of the model (the junction exponent) was found to be inversely related to the average velocity (r = -0.59, p = 0.015) and trough velocity (r = -0.67, p = 0.004) in downstream vessels. Aspects of cellular flow, such as the minimum velocity, were also moderately correlated (r = 0.46, p = 0.009) with distance to the upstream feeding arteriole. Overall, this study shows that capillary network topology contributes significantly to the flow variability in retinal capillaries in human eyes. Understanding the heterogeneity in capillary flow is an important first step before pathological flow states can be properly understood. These results show that flow within capillary vessels is not affected by vessel depths but significantly influenced by the upstream feeder distance as well as the downstream vessel junction exponents, but there remains much to be uncovered regarding healthy capillary flow.

Pearls and Pitfalls of Adaptive Optics Ophthalmoscopy in Inherited Retinal Diseases.

Adaptive optics (AO) retinal imaging enables individual photoreceptors to be visualized in the clinical setting. AO imaging can be a powerful clinical tool for detecting photoreceptor degeneration at a cellular level that might be overlooked through conventional structural assessments, such as spectral-domain optical coherence tomography (SD-OCT). Therefore, AO imaging has gained significant interest in the study of photoreceptor degeneration, one of the most common causes of inherited blindness. Growing evidence supports that AO imaging may be useful for diagnosing early-stage retinal dystrophy before it becomes apparent on fundus examination or conventional retinal imaging. In addition, serial AO imaging may detect structural disease progression in early-stage disease over a shorter period compared to SD-OCT. Although AO imaging is gaining popularity as a structural endpoint in clinical trials, the results should be interpreted with caution due to several pitfalls, including the lack of standardized imaging and image analysis protocols, frequent ocular comorbidities that affect image quality, and significant interindividual variation of normal values. Herein, we summarize the current state-of-the-art AO imaging and review its potential applications, limitations, and pitfalls in patients with inherited retinal diseases.

High-resolution structural and functional retinal imaging in the awake behaving mouse

The laboratory mouse has provided tremendous insight to the underpinnings of mammalian central nervous system physiology. In recent years, it has become possible to image single neurons, glia and vascular cells in vivo by using head-fixed preparations combined with cranial windows to study local networks of activity in the living brain. Such approaches have also succeeded without the use of general anesthesia providing insights to the natural behaviors of the central nervous system. However, the same has not yet been developed for the eye, which is constantly in motion. Here we characterize a novel head-fixed preparation that enables high-resolution adaptive optics retinal imaging at the single-cell level in awake-behaving mice. We reveal three new functional attributes of the normal eye that are overlooked by anesthesia: 1) High-frequency, low-amplitude eye motion of the mouse that is only present in the awake state 2) Single-cell blood flow in the mouse retina is reduced under anesthesia and 3) Mouse retinae thicken in response to ketamine/xylazine anesthesia. Here we show key benefits of the awake-behaving preparation that enables study of retinal physiology without anesthesia to study the normal retinal physiology in the mouse.

Precise in vivo adaptive optics imaging of retinal vessels

Adaptive optics (AO) provides new, unique opportunities for in vivo visualization of retinal vasculature. AO retinal vessel imaging can be utilized as a component of multimodal imaging tools to complement conventional diagnostic imaging modalities. Non-invasive and highly promising AO imaging of fundus structures allows the qualitative and quantitative assessment of early signs of retinal vascular remodeling associated with age, arterial hypertension, diabetes mellitus and other disorders.

Unique Haplotypes in OPN1LW as a Common Cause of High Myopia With or Without Protanopia: A Potential Window Into Myopic Mechanism.

Specific haplotypes (LVAVA, LIVVA, and LIAVA) formed by five polymorphisms (p.L153M, p.V171I, p.A174V, p.I178V, and p.S180A in exon 3 of OPN1LW) that cause partial or complete exon skipping have been reported as unique genetic causes of high myopia with or without colorblindness. This study aimed to identify the contribution of OPN1LW to early-onset high myopia (eoHM) and the molecular basis underlying eoHM with or without colorblindness. Comparative analysis of exome sequencing data was conducted for 1226 families with eoHM and 9304 families with other eye conditions. OPN1LW variants detected by targeted or whole exome sequencing were confirmed by long-range amplification and Sanger sequencing, together with segregation analysis. The clinical data were thoroughly analyzed. Unique haplotypes and truncation variants in OPN1LW were detected exclusively in 68 of 1226 families with eoHM but in none of the 9304 families with other visual diseases (P = 1.63 × 10-63). Four classes of variants were identified: haplotypes causing partial splicing defects in OPN1LW (LVAVA or LIVVA in 31 families), LVAVA in OPN1LW-OPN1MW hybrid gene (in 3 families), LIAVA in OPN1LW (in 29 families), and truncations in OPN1LW (in 5 families). The first class causes partial loss of red photopigments, whereas the latter three result in complete loss of red photopigments. This is different from the replacement of red with green owing to unequal re-arrangement causing red-green colorblindness alone. Of the 68 families, 42 affected male patients (31 families) with the first class of variants (LVAVA or LIVVA in OPN1LW) had eoHM alone, whereas 37 male patients with the latter 3 classes had eoHM with protanopia. Adaptive optics retinal imaging demonstrated reduced cone regularity and density in men with eoHM caused by OPN1LW variants compared to those patients with eoHM and without OPN1LW variants. Based on the 68 families with unique variants in OPN1LW, our study provides firm evidence that the two different phenotypes (eoHM with or without colorblindness) are caused by two different classes of variants (partial splicing-effect haplotypes or complete splicing-effect haplotypes/truncation variants, respectively). The contribution of OPN1LW to eoHM (isolated and syndromic) was characterized by OPN1LW variants found in 5.5% (68/1226) of the eoHM families, making it the second most common cause of monogenic eoHM alone (2.4%) and a frequent cause of syndromic monogenic eoHM with colorblindness. Such haplotypes, in which each individual variant alone is considered a benign polymorphism, are potential candidates for other hereditary diseases with causes of missing genetic defects.

Mercury intoxication and ophthalmic involvement: An update review.

Human intoxication after mercury exposure is a rare condition that can cause severe damage to the central nervous, respiratory, cardiovascular, renal, gastrointestinal, skin, and visual systems and represents a major public health concern. Ophthalmic involvement includes impaired function of the extraocular muscles and the eyelids, as well as structural changes in the ocular surface, lens, retina, and optic nerve causing a potential irreversible damage to the visual system. Although, there are many pathways for poisoning depending on the mercury form, it has been suggested that tissue distribution does not differ in experimental animals when administered as mercury vapor, organic mercury, or inorganic mercury. Additionally, visual function alterations regarding central visual acuity, color discrimination, contrast sensitivity, visual field and electroretinogram responses have also been described widely. Nevertheless, there is still controversy about whether visual manifestations occur secondary to brain damage or as a direct affectation, and which ocular structure is primarily affected. Despite the use of some imaging techniques such as in vivo confocal microscopy of the cornea, optical coherence tomography (OCT) of the retina and optic nerve, and functional tests such as electroretinography has helped to solve in part this debate, further studies incorporating other imaging modalities such as autofluorescence, OCT angiography or adaptive optics retinal imaging are needed. This review aims to summarize the published structural and functional alterations found in the visual system of patients suffering from mercury intoxication.

Evolution of adaptive optics retinal imaging [Invited

This review describes the progress that has been achieved since adaptive optics (AO) was incorporated into the ophthalmoscope a quarter of a century ago, transforming our ability to image the retina at a cellular spatial scale inside the living eye. The review starts with a comprehensive tabulation of AO papers in the field and then describes the technological advances that have occurred, notably through combining AO with other imaging modalities including confocal, fluorescence, phase contrast, and optical coherence tomography. These advances have made possible many scientific discoveries from the first maps of the topography of the trichromatic cone mosaic to exquisitely sensitive measures of optical and structural changes in photoreceptors in response to light. The future evolution of this technology is poised to offer an increasing array of tools to measure and monitor in vivo retinal structure and function with improved resolution and control.

Comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects.

This work presents a novel fully automated method for retinal analysis in images acquired with a flood illuminated adaptive optics retinal camera (AO-FIO). The proposed processing pipeline consists of several steps: First, we register single AO-FIO images in a montage image capturing a larger retinal area. The registration is performed by combination of phase correlation and the scale-invariant feature transform method. A set of 200 AO-FIO images from 10 healthy subjects (10 images from left eye and 10 images from right eye) is processed into 20 montage images and mutually aligned according to the automatically detected fovea center. As a second step, the photoreceptors in the montage images are detected using a method based on regional maxima localization, where the detector parameters were determined with Bayesian optimization according to manually labeled photoreceptors by three evaluators. The detection assessment, based on Dice coefficient, ranges from 0.72 to 0.8. In the next step, the corresponding density maps are generated for each of the montage images. As a final step, representative averaged photoreceptor density maps are created for the left and right eye and thus enabling comprehensive analysis across the montage images and a straightforward comparison with available histological data and other published studies. Our proposed method and software thus enable us to generate AO-based photoreceptor density maps for all measured locations fully automatically, and thus it is suitable for large studies, as those are in pressing need for automated approaches. In addition, the application MATADOR (MATlab ADaptive Optics Retinal Image Analysis) that implements the described pipeline and the dataset with photoreceptor labels are made publicly available.

New approaches in the detection and management of diabetic retinopathy in the near future

Diabetes mellitus (DM), a group of metabolic diseases characterized by hyperglycemia, is a major public health problem worldwide. In recent years, the incidence and prevalence of DM has been increasing as a global epidemic. Diabetic retinopathy (DR) is the most common complication of DM and remains the major cause of preventable blindness among working-age people in most developed countries and it has a significant socioeconomic impact and source of morbidity. DR, which has long been recognized as a microvascular disease, has been demonstrated by laboratory and clinical evidence that inflammation and retinal neurodegeneration may also contribute to diabetic retinal damage in the early stages of DR. New diagnostic and treatment modalities in DR management is promising. Further elucidation of the underlying molecular mechanisms may provide new medical approaches for the development of novel therapeutic modalities. Nowadays, novel diagnostic devices such as ultrawide field fundus fluorescein angiography, optic coherence tomography angiography and adaptive optics retinal imaging have improved the detection of DR earlier, faster and more accurately. Subthreshold micropulse laser and other laser photocoagulation applications may be an alternative to conventional retinal photocoagulation with lower complications for DR treatment. In recent years, artificial intelligence, machine learning, and deep learning based diagnosis and treatment applications are developing. In addition, in recent years, unmanned automated-based diagnostic and treatment methods and newly developed intravitreal drugs and implants can offer more diagnostic and treatment options with promising results. This review provides an overview of novel diagnostic and treatment approaches for preventing the progression of diabetic retinopathy.

Adaptive Optics Imaging of Inherited Retinal Disease.

The human retina is amenable to direct, noninvasive visualization using a wide array of imaging modalities. In the ∼140 years since the publication of the first image of the living human retina, there has been a continued evolution of retinal imaging technology. Advances in image acquisition and processing speed now allow real-time visualization of retinal structure, which has revolutionized the diagnosis and management of eye disease. Enormous advances have come in image resolution, with adaptive optics (AO)-based systems capable of imaging the retina with single-cell resolution. In addition, newer functional imaging techniques provide the ability to assess function with exquisite spatial and temporal resolution. These imaging advances have had an especially profound impact on the field of inherited retinal disease research. Here we will review some of the advances and applications of AO retinal imaging in patients with inherited retinal disease.

Challenges in Age-Related Macular Degeneration: From Risk Factors to Novel Diagnostics and Prevention Strategies.

Age-related macular degeneration (AMD) is a chronic multifactorial eye disease representing the primary cause of vision loss in people aged 60 years and older. The etiopathogenesis of the disease remains uncertain, with several risk factors contributing to its onset and progression, such as genotype, aging, hypertension, smoking, overweight, and low dietary intake of carotenoids. Since the aging populations of the industrialized world are increasing rapidly, the impact of AMD in the socio-economical life-developed countries is expected to increase dramatically in the next years. In this context, the benefits of prevention and early disease detection for prompt and effective treatment can be enormous to reduce the social and economic burden of AMD. Nutritional and lifestyle changes, including dietary intake of xanthophyll pigments, such as lutein and zeaxanthin, no smoking, and regular exercise, are known to protect from risk of AMD progression from early to advanced disease stages. In this review, we present the clinical outcomes of a pilot study on trans-scleral iontophoresis delivery of lutein in patients with AMD. Topical delivery of lutein directly to the macula may provide a more efficient method for enriching the macular pigment and for achieving greater patient compliance to therapy than oral administration and thus enhancing prevention strategies. Modern diagnostic methodologies shall address the major problem of accurately detecting the risk of transition from intermediate AMD to advanced AMD stages. Adaptive optics retinal imaging and resonance Raman spectroscopy are two highly promising technologies for the objective assessment of patients with AMD. In this review, we present some of their clinical applications for collecting quantitative measurements of retinal cellular changes and macular content of xanthophyll pigments, respectively. In conclusion, there is great expectation that technological advancements in AMD management will deliver improved screening, therapeutic prevention, and diagnostic systems in the coming decade through a pro-active strategy of “treatment for prevention” that will aim to reduce the global burden of vision loss caused by AMD in the elderly.

Longitudinal chromatic aberration compensation method for dual-wavelength retinal imaging adaptive optics systems

The predecessor of China Optics was China Optics and Applied Optics Digest, which was founded in 1985. At that time, it was the only retrieval journal in the field of optics in China. At the end of 2008, China Optics and Applied Optics Digest was renamed

ATF6 is essential for human cone photoreceptor development

Endoplasmic reticulum (ER) stress and Unfolded Protein Response (UPR) signaling promote the pathology of many human diseases. Loss-of-function variants of the UPR regulator Activating Transcription Factor 6 (ATF6) cause severe congenital vision loss diseases such as achromatopsia by unclear pathomechanisms. To investigate this, we generated retinal organoids from achromatopsia patient induced pluripotent stem cells carrying ATF6 disease variants and from gene-edited ATF6 null hESCs. We found that achromatopsia patient and ATF6 null retinal organoids failed to form cone structures concomitant with loss of cone phototransduction gene expression, while rod photoreceptors developed normally. Adaptive optics retinal imaging of achromatopsia patients carrying ATF6 variants also showed absence of cone inner/outer segment structures but preserved rod structures, mirroring the defect in cone formation observed in our retinal organoids. These results establish that ATF6 is essential for human cone development. Interestingly, we find that a selective small molecule ATF6 signaling agonist restores the transcriptional activity of some ATF6 disease-causing variants and stimulates cone growth and gene expression in patient retinal organoids carrying these variants. These findings support that pharmacologic targeting of the ATF6 pathway can promote human cone development and should be further explored for blinding retinal diseases.

Active Cell Appearance Model Induced Generative Adversarial Networks for Annotation-Efficient Cell Segmentation and Identification on Adaptive Optics Retinal Images.

Data annotation is a fundamental precursor for establishing large training sets to effectively apply deep learning methods to medical image analysis. For cell segmentation, obtaining high quality annotations is an expensive process that usually requires manual grading by experts. This work introduces an approach to efficiently generate annotated images, called "A-GANs", created by combining an active cell appearance model (ACAM) with conditional generative adversarial networks (C-GANs). ACAM is a statistical model that captures a realistic range of cell characteristics and is used to ensure that the image statistics of generated cells are guided by real data. C-GANs utilize cell contours generated by ACAM to produce cells that match input contours. By pairing ACAM-generated contours with A-GANs-based generated images, high quality annotated images can be efficiently generated. Experimental results on adaptive optics (AO) retinal images showed that A-GANs robustly synthesize realistic, artificial images whose cell distributions are exquisitely specified by ACAM. The cell segmentation performance using as few as 64 manually-annotated real AO images combined with 248 artificially-generated images from A-GANs was similar to the case of using 248 manually-annotated real images alone (Dice coefficients of 88% for both). Finally, application to rare diseases in which images exhibit never-seen characteristics demonstrated improvements in cell segmentation without the need for incorporating manual annotations from these new retinal images. Overall, A-GANs introduce a methodology for generating high quality annotated data that statistically captures the characteristics of any desired dataset and can be used to more efficiently train deep-learning-based medical image analysis applications.

Automated Iterative Label Transfer Improves Segmentation of Noisy Cells in Adaptive Optics Retinal Images.

High quality data labeling is essential for improving the accuracy of deep learning applications in medical imaging. However, noisy images are not only under-represented in training datasets, but also, labeling of noisy data is low quality. Unfortunately, noisy images with poor quality labels are exacerbated by traditional data augmentation strategies. Real world images contain noise and can lead to unexpected drops in algorithm performance. In this paper, we present a non-traditional, purposeful data augmentation method to specifically transfer high quality automated labels into noisy image regions for incorporation into the training dataset. The overall approach is based on the use of paired images of the same cells in which variable image noise results in cell segmentation failures. Iteratively updating the cell segmentation model with accurate labels of noisy image areas resulted in an improvement in Dice coefficient from 77% to 86%. This was achieved by adding only 3.4% more cells to the training dataset, showing that local label transfer through graph matching is an effective augmentation strategy to improve segmentation.