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16 pages, 2359 KiB  
Article
Using Ensemble OCT-Derived Features beyond Intensity Features for Enhanced Stargardt Atrophy Prediction with Deep Learning
by Zubin Mishra, Ziyuan Wang, SriniVas R. Sadda and Zhihong Hu
Appl. Sci. 2023, 13(14), 8555; https://doi.org/10.3390/app13148555 - 24 Jul 2023
Cited by 2 | Viewed by 1137
Abstract
Stargardt disease is the most common form of juvenile-onset macular dystrophy. Spectral-domain optical coherence tomography (SD-OCT) imaging provides an opportunity to directly measure changes to retinal layers due to Stargardt atrophy. Generally, atrophy segmentation and prediction can be conducted using mean intensity feature [...] Read more.
Stargardt disease is the most common form of juvenile-onset macular dystrophy. Spectral-domain optical coherence tomography (SD-OCT) imaging provides an opportunity to directly measure changes to retinal layers due to Stargardt atrophy. Generally, atrophy segmentation and prediction can be conducted using mean intensity feature maps generated from the relevant retinal layers. In this paper, we report an approach using advanced OCT-derived features to augment and enhance data beyond the commonly used mean intensity features for enhanced prediction of Stargardt atrophy with an ensemble deep learning neural network. With all the relevant retinal layers, this neural network architecture achieves a median Dice coefficient of 0.830 for six-month predictions and 0.828 for twelve-month predictions, showing a significant improvement over a neural network using only mean intensity, which achieved Dice coefficients of 0.744 and 0.762 for six-month and twelve-month predictions, respectively. When using feature maps generated from different layers of the retina, significant differences in performance were observed. This study shows promising results for using multiple OCT-derived features beyond intensity for assessing the prognosis of Stargardt disease and quantifying the rate of progression. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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Figure 1

Figure 1
<p>FAF and manual ground-truth registration. The baseline OCT en face mean intensity map shows vessel features that were used to register the shown six-month and twelve-month FAF images and ground truths.</p>
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<p>Architecture of a single U-Net in the ensemble neural network. Each solid horizontal arrow represents a set of a convolutional, a batch normalization, and a ReLU layer; each solid down arrow represents a max pooling layer; each up arrow represents a max unpooling layer; and each dashed horizontal arrow represents concatenation. The numbers in each box represent the dimensions of the data in that layer (height × width × number of channels).</p>
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<p>Architecture of the ensemble neural network. Each component U-Net takes in a single feature map as input. The outputs of all the U-Nets are combined through a maximum function, and probability maps are produced using a softmax function.</p>
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<p>Overview of the approach to predicting the region of atrophy in Stargardt patients. Orange boxes represent inputs, blue boxes represent processing and training, and yellow boxes represent output.</p>
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<p>Examples of ELM-IRPE feature maps, resultant six-month atrophy prediction, and comparison to the corresponding six-month FAF and ground truth for a relatively mild (<b>top</b>), a relatively moderate (<b>middle</b>), and a relatively severe (<b>bottom</b>) case of atrophy.</p>
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<p>A comparison of six-month and twelve-month predictions to a baseline feature map (gray-level entropy). The blue and red lines indicate the breadth of the six-month and twelve-month predictions, respectively. They indicate an increase in predicted area and where that increase in area corresponds on the baseline feature maps.</p>
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<p>Examples of two of the commonly encountered segmentation errors in this study. In both (<b>A</b>) and (<b>B</b>), the predicted atrophy fills the hole in the ground truth. In (<b>B</b>), the predicted atrophy does not include the satellite areas of atrophy in the ground truth.</p>
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12 pages, 1831 KiB  
Article
Optical Coherence Tomography: Focus on the Pathology of Macula in Scleritis Patients
by Lilla Smeller, Edit Toth-Molnar and Nicolette Sohar
J. Clin. Med. 2023, 12(14), 4825; https://doi.org/10.3390/jcm12144825 - 21 Jul 2023
Viewed by 988
Abstract
Optical coherence tomography (OCT) is a non-invasive imaging technique for high-resolution, cross-sectional tissue imaging of the eye. During the past two and a half decades, OCT has become an essential tool in ophthalmology. It is a painless method for examining details of ocular [...] Read more.
Optical coherence tomography (OCT) is a non-invasive imaging technique for high-resolution, cross-sectional tissue imaging of the eye. During the past two and a half decades, OCT has become an essential tool in ophthalmology. It is a painless method for examining details of ocular structures in vivo with high resolution that has revolutionized patient care following and treating scleritis patients. Methods: Twenty-four patients diagnosed with scleritis were selected for this study. All of the patients went through basic ophthalmological examinations, such as visual acuity testing (VA), intraocular pressure measurement (IOP), slit lamp examination, ophthalmoscopic examination, and OCT. OCT examinations were taken by SD-OCT Spectralis OCT system (Heidelberg Engineering, Heidelberg, Germany). Results: Twenty-seven eyes of 24 patients (7 males and 17 females) were included in this study, who were diagnosed with scleritis. OCT examinations showed epiretinal membrane (ERM) in three patients (12%), cystoid macular edema (CME) (three cases, 12%), diffuse macular edema (DME) (one case, 4%), and serous retinal detachment (SRD) (one case, 4%). Conclusions: OCT proved to be a valuable, non-invasive method for detecting macular pathology in patients with scleritis. Despite the best treatment regimen applied, macular involvement resulting in reduced visual acuity (VA) can develop, which we could detect with OCT since macular edema (ME) is the leading cause of decreased vision due to the damaged outer blood–retina barrier (BRB) in inflammation. OCT investigation is a highly important method for early detection of ocular complications in scleritis in order to prevent blindness. Full article
(This article belongs to the Topic Biomarker Development and Application)
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Figure 1

Figure 1
<p>Anterior segment picture of diffuse scleritis of the temporal part of the left eye.</p>
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<p>OCT of the right eye of a 28-year-old woman showing CME with loss of the foveal depression and intra-retinal cysts in the outer and inner nuclear layer of the retina. OCT scale: 512 × 496, high-speed mode, 20°.</p>
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<p>On this OCT image: DME is characterized by the disturbance of the layered retinal structure or low reflective areas looking similar to a sponge. The complication of corticosteroid therapy is cataract formation which can explain the quality of the image. OCT scale: 512 × 496, high-speed mode, 20°.</p>
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<p>OCT image from left eye: In SRD, fluid accumulates in the subretinal space between the sensory retina and the retinal pigment epithelium. OCT scale: 512 × 496, high-speed mode, 20°.</p>
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<p>OCT image of the epiretinal membrane (ERM): a reflective layer on the top of the internal limiting membrane (ILM) of a 28-year-old patient. The ERM is attached to the retinal surface of the left eye. OCT scale: 512 × 496, high-speed mode, 20°.</p>
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23 pages, 16441 KiB  
Review
Pearls and Pitfalls of Adaptive Optics Ophthalmoscopy in Inherited Retinal Diseases
by Helia Ashourizadeh, Maryam Fakhri, Kiana Hassanpour, Ali Masoudi, Sattar Jalali, Danial Roshandel and Fred K. Chen
Diagnostics 2023, 13(14), 2413; https://doi.org/10.3390/diagnostics13142413 - 19 Jul 2023
Cited by 1 | Viewed by 1582
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Advances in the Diagnosis of Retinal Diseases)
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Figure 1
<p>Schematic view of the adaptive optics retinal camera. The aberrated wavefront exits the eye (<b>A</b>), and the aberrations are corrected by a deformable mirror (<b>B</b>). The resultant image is divided by a beam splitter (<b>C</b>) and equally received by a wavefront sensor (<b>D</b>) measures the residual aberrations of the image corrected by the deformable mirror. Aberrometry data are analyzed by computer software (<b>E</b>), which adjusts the deformable mirror, and this loop (B &gt; C &gt; D &gt; E &gt; B) continues working until the least amount of aberration is detected by the wavefront sensor, when the final image will be captured and recorded by the retinal camera (<b>F</b>).</p>
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<p>Comparison of the magnified infrared reflectance (IR) image taken by SLO camera (<b>A</b>,<b>B</b>,<b>D</b>,<b>E</b>) with AO image taken by rtx1 AO camera (<b>C</b>,<b>F</b>). Red arrows in F show the internal and external boundaries of the vessels wall. Red (<b>A</b>) and yellow (<b>D</b>) boxes represent the magnified area shown in panels (<b>B</b>,<b>C</b>) and (<b>E</b>,<b>F</b>), respectively.</p>
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<p>Examples of montage created from different AO image acquisition sequences. Overlapping images were taken to cover the central 3° from the fovea using 4 image acquisitions (<b>A</b>), the central 6° using 12 (<b>B</b>) or 16 (<b>C</b>) image acquisitions, and the extended imaging along the horizontal and vertical meridians (up to 9°) using 20 image acquisitions (<b>D</b>). Green dots represent the foveal center.</p>
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<p>AO imaging using rtx1 device (<b>A</b>). The region of interest (yellow square in panel (<b>A</b>)) was used for automated cone detection (<b>B</b>) and segmentation (<b>C</b>) by AODetect software. Cone mosaic parameters are shown in (<b>D</b>). The analysis was performed at superior 2° (<b>2S</b>) from the fovea. White squares in panels (<b>B</b>,<b>C</b>) represent the analysis area.</p>
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<p>The internal and external vessel wall boundaries are marked automatically by the AODetect software (<b>A</b>) and adjusted manually if required. The boundaries are determined based on the peak signals (<b>B</b>) and measurements, including lumen diameter, total diameter, wall thicknesses, wall cross-sectional area (WCSA), and wall-to-lumen ration (WLR), which are provided in microns (<b>C</b>).</p>
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<p>Cone mosaic changes in RP. Automated detection of cones (red dots) with manual adjustment (green dots) shows normal cone mosaic with an eccentricity-dependent decline in cone density and an increase in cone spacing (<b>top row</b>) in a healthy subject. Patients may reveal mild perifoveal mosaic alteration (<b>second row</b>), parafoveal and perifoveal alteration (<b>third row</b>), and severe parafoveal and perifoveal alteration (<b>bottom row</b>). T = temporal; RP = retinitis pigmentosa.</p>
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<p>Cone density map in a 28 y/o healthy control (<b>A</b>) and different stages of RP (<b>B</b>–<b>E</b>). Note the increased cone visibility at the fovea in patients with RP (most prominent in <b>B</b>), a phenomenon that has been reported in these patients.</p>
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<p>Examples of AOFIO. Normal cone mosaic detectable in the entire imaging field in a normal healthy retina (<b>A</b>). Foveal cones are undetectable within the central 1–2° (<b>B</b>). Image quality might be affected by visually significant cataract (<b>C</b>,<b>D</b>), cystoid macular oedema (<b>E</b>), or high astigmatism (<b>F</b>).</p>
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11 pages, 1830 KiB  
Communication
The Disorganization of Retinal Inner Layers Is Correlated to Müller Cells Impairment in Diabetic Macular Edema: An Imaging and Omics Study
by Edoardo Midena, Tommaso Torresin, Stefano Schiavon, Luca Danieli, Chiara Polo, Elisabetta Pilotto, Giulia Midena and Luisa Frizziero
Int. J. Mol. Sci. 2023, 24(11), 9607; https://doi.org/10.3390/ijms24119607 - 1 Jun 2023
Cited by 7 | Viewed by 2427
Abstract
The disorganization of retinal inner layers (DRIL) is an optical coherence tomography (OCT) biomarker strictly associated with visual outcomes in patients with diabetic macular edema (DME) whose pathophysiology is still unclear. The aim of this study was to characterize in vivo, using retinal [...] Read more.
The disorganization of retinal inner layers (DRIL) is an optical coherence tomography (OCT) biomarker strictly associated with visual outcomes in patients with diabetic macular edema (DME) whose pathophysiology is still unclear. The aim of this study was to characterize in vivo, using retinal imaging and liquid biopsy, DRIL in eyes with DME. This was an observational cross-sectional study. Patients affected by center-involved DME were enrolled. All patients underwent spectral domain optical coherence tomography (SD-OCT) and proteomic analysis of aqueous humor (AH). The presence of DRIL at OCT was analyzed by two masked retinal experts. Fifty-seven biochemical biomarkers were analyzed from AH samples. Nineteen eyes of nineteen DME patients were enrolled. DRIL was present in 10 patients (52.63%). No statistically significant difference was found between DME eyes with and without DRIL, considering the AH concentration of all the analyzed biomarkers except for glial fibrillary acidic protein (GFAP), a biomarker of Müller cells dysfunction (p = 0.02). In conclusion, DRIL, in DME eyes, seems to strictly depend on a major dysfunction of Müller cells, explaining its role not only as imaging biomarker, but also as visual function Müller cells-related parameter. Full article
(This article belongs to the Special Issue The Role of Inflammation in Diabetic Retinopathy)
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<p>Detection of disorganization of retinal inner layers (DRIL) on optical coherence tomography (OCT). OCT scans obtained using Spectralis HRA + OCT (Heidelberg Engineering, Heidelberg, Germany) of (<b>a</b>) a patient with DME with DRIL and (<b>b</b>) a patient with DME without DRIL. Red and yellow arrows show the boundary between the ganglion cell—inner plexiform layer complex and inner nuclear layer (INL), and between the INL and outer plexiform layer, respectively, within the central 1000 μm. The boundaries are (<b>a</b>) not distinguishable in the first scan and (<b>b</b>) completely distinguishable in the second one.</p>
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16 pages, 596 KiB  
Article
Relationship between Diabetic Nephropathy and Development of Diabetic Macular Edema in Addition to Diabetic Retinopathy
by Yukihisa Suzuki and Motohiro Kiyosawa
Biomedicines 2023, 11(5), 1502; https://doi.org/10.3390/biomedicines11051502 - 22 May 2023
Cited by 8 | Viewed by 2477
Abstract
This study aimed to examine the relationship between diabetic retinopathy (DR) and systemic factors. We evaluated 261 patients (143 men, 118 women, aged 70.1 ± 10.1 years) with type 2 diabetes. All participants underwent a fundus examination, fundus photography using spectral domain optical [...] Read more.
This study aimed to examine the relationship between diabetic retinopathy (DR) and systemic factors. We evaluated 261 patients (143 men, 118 women, aged 70.1 ± 10.1 years) with type 2 diabetes. All participants underwent a fundus examination, fundus photography using spectral domain optical coherence tomography (SD-OCT), and blood tests. For glycated hemoglobin (HbA1c) levels, the average and highest values in the past were used. We observed DR in 127 (70 men and 57 women) of 261 patients. Logistic regression analyses revealed a significant correlation between DR development and the duration of diabetes (OR = 2.40; 95% CI: 1.50), average HbA1c level (OR = 5.57; 95% CI: 1.27, 24.4), highest HbA1c level (OR = 2.46; 95% CI: 1.12, 5.38), and grade of diabetic nephropathy (DN) (OR = 6.23; 95% CI: 2.70, 14.4). Regression analyses revealed a significant correlation between the severity of DR and duration of diabetes (t = –6.66; 95% CI: 0.21, 0.39), average HbA1c level (t = 2.59; 95% CI: 0.14, 1.02), and severity of DN (t = 6.10; 95% CI: 0.49, 0.97). Logistic regression analyses revealed a significant correlation between diabetic macular edema (DME) development and DN grade (OR = 2.22; 95% CI: 1.33, 3.69). DN grade correlates with the development of DR and DME, and decreased renal function predicts the onset of DR. Full article
(This article belongs to the Special Issue Molecular Research and Recent Advances in Diabetic Retinopathy)
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Graphical abstract

Graphical abstract
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<p>Flow chart of patient enrollment.</p>
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28 pages, 4872 KiB  
Review
Review of Retinal Imaging Modalities for Hydroxychloroquine Retinopathy
by Kai Xiong Cheong, Charles Jit Teng Ong, Priya R Chandrasekaran, Jinzhi Zhao, Kelvin Yi Chong Teo and Ranjana Mathur
Diagnostics 2023, 13(10), 1752; https://doi.org/10.3390/diagnostics13101752 - 16 May 2023
Cited by 2 | Viewed by 2642
Abstract
This review provides an overview of conventional and novel retinal imaging modalities for hydroxychloroquine (HCQ) retinopathy. HCQ retinopathy is a form of toxic retinopathy resulting from HCQ use for a variety of autoimmune diseases, such as rheumatoid arthritis and systemic lupus erythematosus. Each [...] Read more.
This review provides an overview of conventional and novel retinal imaging modalities for hydroxychloroquine (HCQ) retinopathy. HCQ retinopathy is a form of toxic retinopathy resulting from HCQ use for a variety of autoimmune diseases, such as rheumatoid arthritis and systemic lupus erythematosus. Each imaging modality detects a different aspect of HCQ retinopathy and shows a unique complement of structural changes. Conventionally, spectral-domain optical coherence tomography (SD-OCT), which shows loss or attenuation of the outer retina and/or retinal pigment epithelium–Bruch’s membrane complex, and fundus autofluorescence (FAF), which shows parafoveal or pericentral abnormalities, are used to assess HCQ retinopathy. Additionally, several variations of OCT (retinal and choroidal thickness measurements, choroidal vascularity index, widefield OCT, en face imaging, minimum intensity analysis, and artificial intelligence techniques) and FAF techniques (quantitative FAF, near-infrared FAF, fluorescence lifetime imaging ophthalmoscopy, and widefield FAF) have been applied to assess HCQ retinopathy. Other novel retinal imaging techniques that are being studied for early detection of HCQ retinopathy include OCT angiography, multicolour imaging, adaptive optics, and retromode imaging, although further testing is required for validation. Full article
(This article belongs to the Section Biomedical Optics)
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<p>SD-OCT showing evident loss of the photoreceptors and outer retina in the parafoveal region, which causes the inner retinal layers to be displaced downwards around the fovea as the fovea is spared.</p>
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<p>SD-OCT of an Asian patient showing similar outer retinal changes, including ellipsoid zone effacement, in the pericentral region.</p>
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<p>FAF showing parafoveal hyperautofluorescence corresponding to the changes in <a href="#diagnostics-13-01752-f001" class="html-fig">Figure 1</a>.</p>
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<p>FAF showing pericentral hyperautofluorescence corresponding to the changes in <a href="#diagnostics-13-01752-f002" class="html-fig">Figure 2</a>.</p>
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<p>Optos ultra-widefield FAF (<b>a</b>,<b>b</b>) and Heidelberg FAF (<b>c</b>,<b>d</b>) scans demonstrating a more eccentric pericentral hyperautofluorescent ring corresponding to photoreceptor atrophy, sparing the fovea. SD-OCT displays bilateral and severe inner segment EZ loss in the temporal perifovea (<b>e</b>,<b>f</b>), which highlights the need for widefield retinal imaging [<a href="#B88-diagnostics-13-01752" class="html-bibr">88</a>]. [Reprinted from work by Corradetti et al. Source: Corradetti, G.; Violanti, S.; Au, A.; Sarraf, D. Wide field retinal imaging and the detection of drug associated retinal toxicity. <span class="html-italic">Int. J. Retin. Vitr.</span> <b>2019</b>, <span class="html-italic">5</span> (Suppl. S1), 26. <a href="https://doi.org/10.1186/s40942-019-0172-0" target="_blank">https://doi.org/10.1186/s40942-019-0172-0</a>. Distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY) (<a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a>)].</p>
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<p>En face OCT in HCQ retinopathy demonstrates a smooth surface in the central area (inside the dashed line) on the areas with intact photoreceptors. In contrast, more granular reflectivity (outside the line) is noted in the pericentral area with retinal degenerative changes. The area with intact photoreceptors can be calculated and used as a quantitative measure of photoreceptor damage. The progression of photoreceptor damage is represented as a constricted ring at follow-up (10 months later). The quantitative measure of the area with intact photoreceptors decreased from 6.06 mm<sup>2</sup> at baseline to 5.28 mm<sup>2</sup> at the follow-up visit [<a href="#B28-diagnostics-13-01752" class="html-bibr">28</a>]. [Reprinted from work by Yusuf et al. Source: Yusuf, I.H.; Charbel Issa, P.; Ahn, S.J. Novel Imaging Techniques for Hydroxychloroquine Retinopathy. <span class="html-italic">Front. Med.</span> <b>2022</b>, <span class="html-italic">9</span>, 1026934. <a href="https://doi.org/10.3389/fmed.2022.1026934" target="_blank">https://doi.org/10.3389/fmed.2022.1026934</a>. Distributed under the terms of the Creative Commons Attribution 4.0 In-ternational License (CC BY) (<a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a>)].</p>
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<p>SW-AF (<b>A</b>) and NIR-AF (<b>B</b>) scans demonstrating normal patterns of autofluorescence centrally surrounded by a ring of hyperautofluorescence, which is surrounded by a region or ring of hypoautofluorescence in a bull's-eye pattern. Perimetry demonstrating a ring scotoma (<b>C</b>). On the SD-OCT (<b>D</b>) scan, the outer retina is significantly disrupted in a parafoveal manner, including loss of the EZ and IZ bands, with conservation of the fovea (“flying saucer”) [<a href="#B58-diagnostics-13-01752" class="html-bibr">58</a>]. [Reprinted from work by Jauregui et al. Source: Jauregui, R.; Parmann, R.; Nuzbrokh, Y.; Tsang, S.H.; Sparrow, J.R. Spectral-Domain Optical Coherence Tomography Is More Sensitive for Hydroxychloro-quine-Related Structural Abnormalities Than Short-Wavelength and Near-Infrared Autofluorescence. <span class="html-italic">Transl. Vis. Sci. Technol.</span> <b>2020</b>, <span class="html-italic">9</span>, 8. <a href="https://doi.org/10.1167/tvst.9.9.8" target="_blank">https://doi.org/10.1167/tvst.9.9.8</a>. Distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. (<a href="https://creativecommons.org/licenses/by-nc-nd/4.0/" target="_blank">https://creativecommons.org/licenses/by-nc-nd/4.0/</a>)].</p>
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<p>Ultra-widefield FAF in parafoveal and pericentral HCQ retinopathy. The images are placed in order of increasing severity and retinal damage based on the extent of hyper- and hypoautofluorescence, from temporal or inferior patchy hyperautofluorescence (arrowheads) to extensive hypoautofluorescence [<a href="#B28-diagnostics-13-01752" class="html-bibr">28</a>]. [Reprinted from work by Yusuf et al. Source: Yusuf, I.H.; Charbel Issa, P.; Ahn, S. J. Novel imaging techniques for hydroxychloroquine retinopathy. <span class="html-italic">Front. Med.</span> <b>2022</b>, <span class="html-italic">9</span>, 1026934. <a href="https://doi.org/10.3389/fmed.2022.1026934" target="_blank">https://doi.org/10.3389/fmed.2022.1026934</a>. Distributed under the terms of the Creative Commons Attribution 4.0 In-ternational License (CC BY) (<a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a>)].</p>
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<p>Choriocapillaris analysis using the Phansalkar local thresholding method in a patient’s eye with HCQ retinopathy. Flow deficit (FD) quantification (<b>A</b>–<b>D</b>) suggests that the choriocapillaris is involved in HCQ retinopathy [<a href="#B126-diagnostics-13-01752" class="html-bibr">126</a>]. [Reprinted from work by Halouani et al. Source: Halouani, S.; Le, H. M.; Cohen, S. Y.; Terkmane, N.; Herda, N.; Souied, E. H.; Miere, A. Choriocapillaris Flow Deficits Quantification in Hydroxychloroquine Retinopathy Using Swept-Source Optical Coherence Tomography Angiography. <span class="html-italic">J. Pers. Med.</span> <b>2022</b>, <span class="html-italic">12</span>, 1445. <a href="https://doi.org/10.3390/jpm12091445" target="_blank">https://doi.org/10.3390/jpm12091445</a>. Distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY) (<a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a>)].</p>
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<p>Colour fundus photography of the right and left eyes showing arcuate zone of hypopigmentation (white arrow heads) superior, temporal, and inferior to fovea (<b>a</b>,<b>b</b>). Multicolour imaging of the right and left eyes showing rings of darker hue around fovea (white arrow heads) corresponding to the arcuate hypopigmentation seen on colour fundus photography and extending beyond (<b>c</b>,<b>d</b>). Multicolour imaging image of the left eye of a normal individual showing the deep pink fovea centre surrounded by a greenish hue that is missing in the eye with HCQ retinopathy (<b>e</b>) [<a href="#B137-diagnostics-13-01752" class="html-bibr">137</a>]. [Reprinted from work by Saurabh et al. Source: Saurabh, K.; Roy, R.; Thomas, N.R.; Chowdhury, M. Multimodal Imaging Characteristics of Hydroxychloroquine Retinopathy. <span class="html-italic">Indian J. Ophthalmol.</span> <b>2018</b>, <span class="html-italic">66</span>, 324–327. <a href="https://doi.org/10.4103/ijo.IJO_787_17" target="_blank">https://doi.org/10.4103/ijo.IJO_787_17</a>. Distributed under the terms of the Creative Commons Attribu-tion-NonCommercial-ShareAlike 3.0 License (CC BY-NC-SA 3.0) (<a href="https://creativecommons.org/licenses/by-nc-sa/3.0/" target="_blank">https://creativecommons.org/licenses/by-nc-sa/3.0/</a>)].</p>
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<p>AO scanning laser ophthalmoscope (AO-SLO) montage of the left eye (<b>A</b>) matched with the corresponding red-free image. Magnified AO-SLO images are also shown (<b>B</b>,<b>C</b>). (<b>B</b>) shows the area indicated by the white box on the montage and it demonstrates disruptions in the cone mosaic, where cones are missing or lost. The cones are also asymmetrical in shape and size with variable brightness. (<b>C</b>) shows an age-matched normal retina in the same location without the structural changes seen in (<b>B</b>) [<a href="#B142-diagnostics-13-01752" class="html-bibr">142</a>]. [Reprinted from work by Bae et al. Source: Bae, E. J.; Kim, K. R.; Tsang, S. H.; Park, S. P.; Chang, S. Retinal damage in chloroquine maculopathy, revealed by high resolution imaging: a case report utilizing adaptive optics scanning laser ophthalmoscopy. <span class="html-italic">Korean J. Ophthalmol.</span> <b>2014</b>, <span class="html-italic">28</span>, 100–107. <a href="https://doi.org/10.3341/kjo.2014.28.1.100" target="_blank">https://doi.org/10.3341/kjo.2014.28.1.100</a>. Distributed under the terms of the Creative Commons Attribu-tion-NonCommercial 3.0 Unported License (CC BY-NC 3.0) (<a href="http://creativecommons.org/licenses/by-nc/3.0/" target="_blank">http://creativecommons.org/licenses/by-nc/3.0/</a>)].</p>
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10 pages, 8304 KiB  
Article
High-Precision Optical Coherence Tomography Navigated Laser Retinopexy for Retinal Breaks
by Simon Salzmann, Philip Wakili, Sami Al-Nawaiseh, Boris Považay, Christoph Meier and Christian Burri
Life 2023, 13(5), 1145; https://doi.org/10.3390/life13051145 - 9 May 2023
Viewed by 1737
Abstract
The prevalent cause of retinal detachment is a full-thickness retinal break and the ingress of fluid into the subretinal space. To prevent progression of the detachment, laser photocoagulation (LPC) lesions are placed around the break in clinical practice to seal the tissue. Unlike [...] Read more.
The prevalent cause of retinal detachment is a full-thickness retinal break and the ingress of fluid into the subretinal space. To prevent progression of the detachment, laser photocoagulation (LPC) lesions are placed around the break in clinical practice to seal the tissue. Unlike the usual application under indirect ophthalmoscopy, we developed a semi-automatic treatment planning software based on a sequence of optical coherence tomography (OCT) scans to perform navigated LPC treatment. The depth information allows demarcation of the border where the neurosensory retina is still attached to the retinal pigment epithelium (RPE), which is critical for prevention of detachment progression. To evaluate the method, artificially provoked retinal breaks were treated in seven ex-vivo porcine eyes. Treatment outcome was assessed by fundus photography and OCT imaging. The automatically applied lesions surrounding each detachment (4.4–39.6 mm2) could be identified as highly scattering coagulation regions in color fundus photography and OCT. Between the planned and applied pattern, a mean offset of 68 µm (SD ± 16.5 µm) and a mean lesion spacing error of 5 µm (SD ± 10 µm) was achieved. The results demonstrate the potential of navigated OCT-guided laser retinopexy to improve overall treatment accuracy, efficiency, and safety. Full article
(This article belongs to the Section Medical Research)
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<p>Schematic representation of the workflow for optical coherence tomography (OCT)-based semi-automatic treatment of retinal breaks. The first step (1) is to acquire an OCT volume scan (C-scan or radial scan) covering the retinal break and adjacent detached areas. Subsequently, (2) the OCT data are imported into a treatment planning software, where the user encircles the retinal detachment (RD) (still attached neurosensory retina (NSR) to the retinal pigment epithelium (RPE)) by investigating the OCT B-scans. Based on the demarcation, an optimal treatment area is calculated (3) and finally applied (4).</p>
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<p>Example of the proposed method of an optimized elliptical treatment region and uniformly placed treatment points around a retinal break. The position of the active spectral domain (SD)-OCT scan (red line) in the confocal scanning laser ophthalmoscope (cSLO) fundus image (<b>a</b>) is movable according to the acquired B-scans (red arrow) and corresponds to the SD-OCT B-scan shown (<b>b</b>). The two green retinal detachment marker lines in the B-scan are moved by the user (green arrows) to mark the visible outer boundary of the detached NSR from the RPE. The six pairs of markers in the fundus image represent the marked detachment boundary of the annotated B-scans. Based on these markings, an enclosing ellipse with minimum area is fitted to optimally surround the break and adjacent RD (inner ellipse). Together with a similar but enlarged second ellipse (outer ellipse), the treatment region is defined. This region is also visualized in each B-scan (purple lines). In the example shown, three rows of evenly spaced treatment points have been placed within the treatment region.</p>
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<p>Example of initial situation (<b>a</b>), treatment planning (<b>b</b>) and outcome (<b>c</b>). While the cSLO image showed only the full-thickness retinal defect, SD-OCT based treatment planning revealed a large area of detached NSR in the upper quarter of the image. Based on the precisely determined detachment boundary, a minimum elliptical treatment area (violet ellipses) is calculated. Uniformly distributed treatment points (violet crosses) are subsequently positioned in this area and the LPC is applied accordingly.</p>
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<p>Example 1: treatment outcome in ex-vivo porcine eye with artificially induced retinal break (area of retinal break and adjacent RD: 25.2 mm<sup>2</sup>). Fundus photographs before (<b>a</b>) and after (<b>b</b>) treatment, infrared scanning laser ophthalmoscope images before (<b>c</b>) and after (<b>d</b>) treatment with the corresponding SD-OCT B-scans (<b>e</b>,<b>f</b>). A total of 200 lesions were applied in three rows with a radial and tangential (point to point) distance of 200 µm and 300 µm, respectively. The LPC treatment time was 4:19 min. The effect of LPC treatment is visible in (<b>b</b>,<b>d</b>) as spots of whitened tissue and in (<b>f</b>) as ruptures in the retina at the treatment sites (red).</p>
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<p>Example 2: treatment outcome in ex-vivo porcine eye with artificially induced retinal break (area of retinal break and adjacent RD: 15.4 mm<sup>2</sup>). Fundus photographs before (<b>a</b>) and after (<b>b</b>) treatment, infrared scanning laser ophthalmoscope images before (<b>c</b>) and after (<b>d</b>) treatment with the corresponding SD-OCT B-scans (<b>e</b>,<b>f</b>). A total of 153 lesions were applied in three rows with a radial and tangential (point to point) distance of 200 µm and 300 µm, respectively. The LPC treatment time was 2:11 min. The effect of LPC treatment is visible in (<b>b</b>,<b>d</b>) as spots of whitened tissue and in (<b>f</b>) as ruptures in the retina at the treatment sites (red).</p>
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19 pages, 5025 KiB  
Article
A Novel Intraretinal Layer Semantic Segmentation Method of Fundus OCT Images Based on the TransUNet Network Model
by Zhijun Gao, Zhiming Wang and Yi Li
Photonics 2023, 10(4), 438; https://doi.org/10.3390/photonics10040438 - 12 Apr 2023
Cited by 7 | Viewed by 1872
Abstract
Optical coherence tomography (OCT) is used to obtain retinal images and stratify them to obtain the thickness of each intraretinal layer, which plays an important role in the clinical diagnosis of many ophthalmic diseases. In order to overcome the difficulties of layer segmentation [...] Read more.
Optical coherence tomography (OCT) is used to obtain retinal images and stratify them to obtain the thickness of each intraretinal layer, which plays an important role in the clinical diagnosis of many ophthalmic diseases. In order to overcome the difficulties of layer segmentation caused by uneven distribution of retinal pixels, fuzzy boundaries, unclear texture, and irregular lesion structure, a novel lightweight TransUNet deep network model was proposed for automatic semantic segmentation of intraretinal layers in OCT images. First, ResLinear-Transformer was introduced into TransUNet to replace Transformer in TransUNet, which can enhance the receptive field and improve the local segmentation effect. Second, Dense Block was used as the decoder of TransUNet, which can strengthen feature reuse through dense connections, reduce feature parameter learning, and improve network computing efficiency. Finally, the proposed method was compared with the state-of-the-art on the public SD-OCT dataset of diabetic macular edema (DME) patients released by Duke University and POne dataset. The proposed method not only improves the overall semantic segmentation accuracy of retinal layer segmentation, but also reduces the amount of computation, achieves better effect on the intraretinal layer segmentation, and can better assist ophthalmologists in clinical diagnosis of patients. Full article
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<p>Fundus OCT intraretinal layer segmentation.</p>
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<p>Framework Overview: (<b>a</b>) Transformer layer framework; (<b>b</b>) TransUNet architecture.</p>
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<p>Flowchart of the proposed method.</p>
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<p>Improved Transformer structure diagram: (<b>a</b>) RL-Transformer structure; (<b>b</b>) ResMLP structure.</p>
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<p>Five-layer dense block.</p>
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<p>Error bar curves of different methods: (<b>a</b>) Expert 1 as the golden annotation; (<b>b</b>) Expert 2 as the golden annotation.</p>
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<p>Comparison of ROC curves of the segmentation results of the proposed method and other methods at each layer: (<b>a</b>) NFL layer; (<b>b</b>) GCL-IPL layer; (<b>c</b>) INL layer; (<b>d</b>) OPL layer; (<b>e</b>) ONL-ISM layer; (<b>f</b>) ISE layer; (<b>g</b>) OS-RPE layer.</p>
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<p>Qualitative comparison of OCT image segmentation: (<b>a</b>) The original OCT image; (<b>b</b>) annotation with Expert 1; (<b>c</b>) annotation with Expert 2; (<b>d</b>) U-Net prediction; (<b>e</b>) ReLayNet prediction; (<b>f</b>) Swin-Unet prediction; (<b>g</b>) TransUNet prediction; (<b>h</b>) the proposed method prediction.</p>
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<p>Comparison of ablation experiments: (<b>a</b>) The original image; (<b>b</b>) Expert 1 annotation; (<b>c</b>) Baseline 1; (<b>d</b>) Baseline 2; (<b>e</b>) Baseline 3; (<b>f</b>) the proposed method.</p>
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<p>Comparison of different models: (<b>a</b>) Comparison of the number of parameters; (<b>b</b>) comparison of the amount of calculation.</p>
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<p>Qualitative comparison of OCT image segmentation: (<b>a</b>) original OCT image; (<b>b</b>) marked with Expert 1; (<b>c</b>) annotate with Expert 2; (<b>d</b>) U-Net prediction; (<b>e</b>) ReLayNet prediction; (<b>f</b>) TransUNet prediction; (<b>g</b>) the proposed method prediction.</p>
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13 pages, 3649 KiB  
Article
Retinal Nerve Fiber Layer Imaging with Two Different Spectral Domain Optical Coherence Tomographs: Normative Data for Romanian Children
by Iulia-Andrada Nemeș-Drăgan, Ana-Maria Drăgan, Mădălina Claudia Hapca and Mara Oaida
Diagnostics 2023, 13(8), 1377; https://doi.org/10.3390/diagnostics13081377 - 10 Apr 2023
Cited by 1 | Viewed by 1453
Abstract
The purpose of this study is to analyze and compare pediatric normative data for the retinal nerve fiber layer of Romanian children using two different spectral domain optical coherence tomographs. Due to different scanning speeds and axial and transverse resolution, the results of [...] Read more.
The purpose of this study is to analyze and compare pediatric normative data for the retinal nerve fiber layer of Romanian children using two different spectral domain optical coherence tomographs. Due to different scanning speeds and axial and transverse resolution, the results of the measurements of scans cannot be transposed. A total of 140 healthy children aged 4 to 18 were enrolled in the study. Overall, 140 eyes were scanned with a Spectralis SD-OCT (Heidelberg Technology), and the other 140 eyes were imaged with a Copernicus REVO SOCT (Optopol Technology (Zawiercie, Poland)). The mean global RNFL thickness and average RNFL thickness for the four quadrants were measured and compared. The average peripapillary RNFL thickness measured with the Spectralis was 104.03 ± 11.42 (range 81 to 126 µm), while the one measured with the Revo 80 was 127.05 ± 15.6 (range 111.43–158.28). The RNFL thickness measurements taken with the Spectralis in the superior, inferior, nasal, and temporal quadrants were 132 ±19.1, 133.5 ± 21.77, 74 ± 16.48, and 73 ± 11.95 µm, respectively, while those taken with the Revo 80 were 144.44 ± 9.25, 144.86 ±23.12, 96.49 ± 19.41, and 77 ± 11.4 µm, respectively. Multivariate analysis showed that the average RNFL thickness was not influenced by gender or eye laterality and was negatively correlated with age when we used the Spectralis device. This study provides normative data for SD-OCT peripapillary RNFL in healthy Romanian children for two different tomographs. These data help the clinician evaluate and interpret the results of optical coherence tomography for a child, taking into consideration all the technical and individual parameters. Full article
(This article belongs to the Special Issue Diagnosis, Treatment and Management of Eye Diseases)
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<p>(<b>a</b>) Spectralis SD-OCT scans of retinal nerve fiber layer thickness map. (<b>b</b>) SOCT Copernicus REVO NFL thickness profile. [Personal database].</p>
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<p>Clustered bar chart displaying the differences between mean values of global and sectorial RNFL in Spectralis and Revo80.</p>
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<p>Bland–Altman chart of Spectralis and Revo80 measurements for Global RNFL, where ◦ is difference, <b><span style="color:red">--</span></b> mean, and <b><span style="color:#538135">--</span></b> lower and upper 95% limit values.</p>
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<p>Scatterplot of global RNFL (<b>A</b>) and superior sector RNFL (<b>B</b>) thickness as a function of age of the subjects on Spectralis measurements.</p>
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13 pages, 5291 KiB  
Article
Thickness Measurement of Self-Lubricating Fabric Liner of Inner Ring of Sliding Bearings Using Spectral-Domain Optical Coherence Tomography
by Yaosen Deng, Shuncong Zhong, Jiewen Lin, Qiukun Zhang, Walter Nsengiyumva, Shuying Cheng, Yi Huang and Zhixiong Chen
Coatings 2023, 13(4), 708; https://doi.org/10.3390/coatings13040708 - 31 Mar 2023
Cited by 4 | Viewed by 1957
Abstract
This study presents a novel and highly accurate method of measuring the geometric thickness of the self-lubricating fabric liner of bearings by combining the optical coherence tomography (OCT) technology and the Hanning-windowed energy centrobaric method (HnWECM). The geometric thickness of wear-resistant coating material [...] Read more.
This study presents a novel and highly accurate method of measuring the geometric thickness of the self-lubricating fabric liner of bearings by combining the optical coherence tomography (OCT) technology and the Hanning-windowed energy centrobaric method (HnWECM). The geometric thickness of wear-resistant coating material is one of the important indicators for evaluating its wear, and the measurement of its geometric thickness is of great significance for preventing coating failure. To address the issue of significant measurement errors caused by using the refractive index of the sample instead of the group refractive index to calculate the material’s geometrical thickness in previous OCT research and applications, our proposed method can accurately measure the geometrical thickness of materials without the influence of the refractive index of the material. Moreover, this method exhibits the advantages of non-contact and high precision, since it utilizes an SD-OCT system, making it a novel method for extracting the physical parameters of composite materials. The geometric thickness of the peeled-off liner obtained from our method is compared with the thickness measured by the spiral micrometer to evaluate its accuracy. The experimental results indicate that the thickness measured by the spiral micrometer was 172 μm, while the maximum difference in the data obtained by our method was 171.261 μm. This suggests that the difference between the two methods is less than 0.430%, which verifies the accuracy and validity of our method. Additionally, the obtained geometric thickness and the optical thickness of the peeled-off liner are used to evaluate the group refractive index of this material. The inside geometrical structure of the self-lubricating fabric liner on the end face and inner ring of the sliding bearing is imaged with this group refractive index. The measurement of the inner ring liner of the sliding bearing proves the flexibility of the fiber-optic OCT and provides a non-contact, nondestructive testing method for measuring the geometric thickness and internal geometric structure of composite materials. Full article
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<p>Schematic diagram of the SD-OCT. SLD: superluminescent diode; MS: mating sleeve; FC: fiber coupler (50:50); BL: bearing liner; PB: probe beam; RB: reference beam; G: grating; C: collimator; M: mirror; L: lens; FSG: fused silica glass; S: sample; RB: reference beam; PB: probe beam.</p>
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<p>The stepwise flowchart for the measurement of the group refractivity index and the geometric thickness of the peeled-off self-lubricating fabric liner.</p>
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<p>Inspection schematic diagram: (<b>a</b>) the interferometric signal and FFT result of FSG2; (<b>b</b>) the interferometric signal and FFT result of FSG2 after inserting the liner into the probe beam; (<b>c</b>) the surface and inner layer of the liner.</p>
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<p>Geometric thickness and group refractivity measurement for the peeled-off self-lubricating fabric liner (<b>a</b>) the photo of experimental system; (<b>b</b>) the peeled-off self-lubricating fabric liner; (<b>c</b>) the tomography before inserting the liner into the probe beam; (<b>d</b>) the tomography after inserting the liner into the probe beam; (<b>e</b>) the tomography of the peeled-off self-lubricating fabric liner.</p>
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<p>The line chart of geometric thickness data at different detection tracks of the peeled-off self-lubricating fabric liner.</p>
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<p>The air refractivity–wavelength relationship curve at 773.314 torrs (103.1 kPa) and 25 °C.</p>
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<p>The tomographic image of the end face of the sliding bearing’s liner: (<b>a</b>) schematic diagram of bearing detection track; (<b>b</b>) schematic diagram of inner structure of liner; (<b>c</b>) the tomographic image.</p>
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<p>The tomographic image of the inner diameter liner: (<b>a</b>) the photo of the experimental system; (<b>b</b>,<b>c</b>) the diagram of the sliding bearing; (<b>d</b>) the tomographic image of the inner ring liner; (<b>e</b>) the partially enlarged view of (<b>d</b>); (<b>f</b>) the 1-D figure of the dotted line in (<b>e</b>).</p>
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12 pages, 622 KiB  
Article
Pyridostigmine Bromide Pills and Pesticides Exposure as Risk Factors for Eye Disease in Gulf War Veterans
by Lauren E. Truax, Jaxon J. Huang, Katherine Jensen, Elyana V. T. Locatelli, Kimberly Cabrera, Haley O. Peterson, Noah K. Cohen, Simran Mangwani-Mordani, Andrew Jensen, Raquel Goldhardt and Anat Galor
J. Clin. Med. 2023, 12(6), 2407; https://doi.org/10.3390/jcm12062407 - 21 Mar 2023
Viewed by 3180
Abstract
To examine associations between the pyridostigmine bromide (PB) pill and/or pesticide exposure during the 1990–1991 Gulf War (GW) and eye findings years after deployment. A cross-sectional study of South Florida veterans who were deployed on active duty during the GW Era (GWE). Information [...] Read more.
To examine associations between the pyridostigmine bromide (PB) pill and/or pesticide exposure during the 1990–1991 Gulf War (GW) and eye findings years after deployment. A cross-sectional study of South Florida veterans who were deployed on active duty during the GW Era (GWE). Information on GW exposures and ocular surface symptoms were collected via standardized questionnaires and an ocular surface examination was performed. Participants underwent spectral domain–ocular coherence tomography (SD-OCT) imaging that included retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), and macular maps. We examined for differences in eye findings between individuals exposed versus not exposed to PB pills or pesticides during service. A total of 40.7% (n = 44) of individuals reported exposure to PB pills and 41.7% (n = 45) to pesticides; additionally, 24 reported exposure to both in the GW arena. Demographics were comparable across groups. Individuals exposed to PB pills reported higher dry eye (DE) symptoms scores (the 5-Item Dry Eye Questionnaire, DEQ-5: 9.3 ± 5.3 vs. 7.3 ± 4.7, p = 0.04) and more intense ocular pain (average over the last week: 2.4 ± 2.6 vs. 1.5 ± 1.8, p = 0.03; Neuropathic Pain Symptom Inventory modified for the Eye (NPSI-E): 18.2 ± 20.0 vs. 10.8 ± 13.8, p = 0.03) compared to their non-exposed counterparts. DE signs were comparable between the groups. Individuals exposed to PB pills also had thicker OCT measurements, with the largest difference in the outer temporal segment of the macula (268.5 ± 22.2 μm vs. 260.6 ± 14.5 μm, p = 0.03) compared to non-exposed individuals. These differences remained significant when examined in multivariable models that included demographics and deployment history. Individuals exposed to pesticides had higher neuropathic ocular pain scores (NPSI-E: 17.1 ± 21.1 vs. 11.6 ± 12.9, p = 0.049), but this difference did not remain significant in a multivariable model. Individuals exposed to PB pills during the GWE reported more severe ocular surface symptoms and had thicker OCT measures years after deployment compared to their non-exposed counterparts. Full article
(This article belongs to the Collection Ocular Manifestations of Systemic Diseases)
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<p>Visual summary of the possible effects of PB pills and pesticides on the cornea and retina.</p>
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13 pages, 5304 KiB  
Article
Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD
by Gagan Kalra, Hasan Cetin, Jon Whitney, Sari Yordi, Yavuz Cakir, Conor McConville, Victoria Whitmore, Michelle Bonnay, Jamie L. Reese, Sunil K. Srivastava and Justis P. Ehlers
Diagnostics 2023, 13(6), 1178; https://doi.org/10.3390/diagnostics13061178 - 20 Mar 2023
Cited by 4 | Viewed by 2324
Abstract
Background: The development and testing of a deep learning (DL)-based approach for detection and measurement of regions of Ellipsoid Zone (EZ) At-Risk to study progression in nonexudative age-related macular degeneration (AMD). Methods: Used in DL model training and testing were 341 subjects with [...] Read more.
Background: The development and testing of a deep learning (DL)-based approach for detection and measurement of regions of Ellipsoid Zone (EZ) At-Risk to study progression in nonexudative age-related macular degeneration (AMD). Methods: Used in DL model training and testing were 341 subjects with nonexudative AMD with or without geographic atrophy (GA). An independent dataset of 120 subjects were used for testing model performance for prediction of GA progression. Accuracy, specificity, sensitivity, and intraclass correlation coefficient (ICC) for DL-based EZ At-Risk percentage area measurement was calculated. Random forest-based feature ranking of EZ At-Risk was compared to previously validated quantitative OCT-based biomarkers. Results: The model achieved a detection accuracy of 99% (sensitivity = 99%; specificity = 100%) for EZ At-Risk. Automatic EZ At-Risk measurement achieved an accuracy of 90% (sensitivity = 90%; specificity = 84%) and the ICC compared to ground truth was high (0.83). In the independent dataset, higher baseline mean EZ At-Risk correlated with higher progression to GA at year 5 (p < 0.001). EZ At-Risk was a top ranked feature in the random forest assessment for GA prediction. Conclusions: This report describes a novel high performance DL-based model for the detection and measurement of EZ At-Risk. This biomarker showed promising results in predicting progression in nonexudative AMD patients. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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<p>Flowchart of the data workflow during model training, validation, testing, and analysis. Independent random forest analysis was based on longitudinal dataset over a 5-year follow-up. The fully trained model was utilized in the DL-based measurement of percentage area of <span class="html-italic">EZ At-Risk</span>, which was subsequently tested in the random forest based predictive analysis of AMD progression. SD-OCT: spectral domain optical coherence tomography; DL: deep learning; EZ: ellipsoid zone; ROC: receiver operator curve.</p>
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<p>OCT B-scan showing multi-layer segmentation. From top to bottom: ONL (green line); EZ (red line); RPE (orange line); BM (pink line). Regions of GA (red overlay); regions of <span class="html-italic">EZ At-Risk</span> (blue overlay). OCT: optical coherence tomography; ONL: outer nuclear layer; EZ: ellipsoid zone; RPE: retinal pigment epithelium; BM: Bruchs membrane; GA: geographic atrophy.</p>
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<p>Output of the DL-based <span class="html-italic">EZ At-Risk</span> detection and segmentation model. (<b>A</b>,<b>E</b>) raw OCT B-scan; (<b>B</b>,<b>F</b>) OCT B-scan with ground truth <span class="html-italic">EZ At-Risk</span> mask overlay (green); (<b>C</b>,<b>G</b>) OCT B-scan with true positive DL output overlay (blue), false negative DL output overlay (green), false positive DL output overlay (orange); (<b>D</b>,<b>H</b>) DL gray scale output. DL: deep learning; EZ: ellipsoid zone; OCT: optical coherence tomography.</p>
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<p>ROC illustration of the DL-based <span class="html-italic">EZ At-Risk</span> segmentation model at the individual SD-OCT B-scan level with accuracy, sensitivity, and specificity. ROC: receiver operator curve; DL: deep learning: EZ: ellipsoid zone; SD-OCT: spectral domain optical coherence tomography.</p>
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<p>A case example of GA progression on en face OCT from (<b>A</b>) baseline scan to (<b>B</b>) 5-year follow-up scan (GA area labeled in green). (<b>C</b>) en face compilation of DL grayscale output of <span class="html-italic">EZ At-Risk</span> measurement on baseline OCT. (<b>D</b>) overlay of baseline DL output and year 5 follow-up GA ground truth showcasing the prediction potential of baseline <span class="html-italic">EZ At-Risk</span> measurement where green region indicates successful prediction of GA at year 5, red indicates false positive GA prediction for year 5, and yellow indicates false negative GA prediction at year 5. GA: geographic atrophy; OCT: optical coherence tomography; DL: deep learning; EZ: ellipsoid zone.</p>
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<p>ROC illustration of the random forest model for prediction of sfGA using quantitative OCT-biomarkers including <span class="html-italic">EZ At-Risk</span>. Ten-fold cross validation was performed, and mean ROC results are represented by the blue solid line while random chance is represented by the red dashed line. ROC: receiver operator curve; sfGA: sub-foveal geographic atrophy; OCT: optical coherence tomography; EZ: ellipsoid zone.</p>
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8 pages, 1013 KiB  
Brief Report
Optical Coherence Tomography Angiography in Macular Holes Autologous Retinal Transplant
by Virgilio Morales-Canton, Daniela Meizner-Grezemkovsky, Pablo Baquero-Ospina, Nicolás Crim and Lihteh Wu
J. Clin. Med. 2023, 12(6), 2350; https://doi.org/10.3390/jcm12062350 - 17 Mar 2023
Cited by 1 | Viewed by 1181
Abstract
In this paper, we compare the post-operative macular microvascular parameters (vascular density and foveal avascular zone) in eyes with refractory macular hole (MH) that underwent pars plana vitrectomy and autologous retinal transplant (ART) with the fellow unoperated eye. We conducted a retrospective case [...] Read more.
In this paper, we compare the post-operative macular microvascular parameters (vascular density and foveal avascular zone) in eyes with refractory macular hole (MH) that underwent pars plana vitrectomy and autologous retinal transplant (ART) with the fellow unoperated eye. We conducted a retrospective case control study of six consecutive patients who underwent pars plana vitrectomy and ART with at least six months of post-operative follow-up. Pre-operatively, all eyes underwent SD-OCT (Spectral Domain Optical Coherence Tomography) examination. Post-operative OCT-A analyses included vascular density (VD) and the foveal avascular zone (FAZ) area. Six patients with a mean age of 63.7 ± 14.3 years were included. The mean follow-up was 24 months (range 6–30 months). The pre-operative BCVA (best-corrected visual acuity) was 0.99 ± 0.46 logMAR and 1.02 ± 0.23 logMAR at the last post-operative visit (p = 1.00). The mean MH diameter was 966 ± 620 µm. VD in the MH group was 28.1 ± 7.3% compared to 20.2 ± 2.9% in the fellow eyes group (p < 0.05). The mean post-operative FAZ area in the MH group was 109.8 ± 114.6 mm2 compared to 41.5 ± 10.4 mm2 in the control group (p < 0.05). In all six eyes, MH closure was obtained. The post-operative visual acuity did not improve after ART. Eyes with a closed MH showed a bigger FAZ with a higher VD compared to the fellow healthy eye. Full article
(This article belongs to the Section Ophthalmology)
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<p>Retinal graft is displaced using ILM (Internal Limiting Membrane) forceps.</p>
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<p>SD-OCT of pre-op and post-op (6 months) MH and ART. OCT-A density map. <b>Case 1</b> (<b>A</b>–<b>C</b>): (<b>A</b>) Left eye pre-operative macular SD OCT with MH and intraretinal cyst (Spectralis, Heidelberg Engineering, Heidelberg, Germany). (<b>B</b>) Post-operative macular SD-OCT with central ART, presence of some intraretinal cyst. (<b>C</b>) Density map (Topcon, Triton, Topcon Healthcare). <b>Case 2</b> (<b>D</b>–<b>F</b>): (<b>D</b>) Right eye pre-operative macular SD OCT (Spectralis, Heidelberg Engineering, Heidelberg, Germany). (<b>E</b>) Post-operative macular SD-OCT with central ART. (<b>F</b>) Density map (Topcon, Triton, Topcon Healthcare). <b>Case 3</b> (<b>G</b>–<b>I</b>): (<b>G</b>) Left eye pre-operative macular SD OCT MH with intraretinal cyst (Spectralis, Heidelberg Engineering, Heidelberg, Germany). (<b>H</b>) Post-operative macular SD-OCT with ART. (<b>I</b>) Density map (Topcon, Triton, Topcon Healthcare). <b>Case 4</b> (<b>J</b>–<b>L</b>): (<b>J</b>) Right eye pre-operative macular OCT (Cirrus HD-OCT 4000, Zeiss) 1154 um. (<b>K</b>) Post-operative macular SD-OCT with ART. (<b>L</b>) Density map (Topcon, Triton, Topcon Healthcare). <b>Case 5</b> (<b>M–O</b>): (<b>M</b>) Left eye pre-operative macular SD OCT, subretinal fluid (Spectralis, Heidelberg Engineering, Heidelberg, Germany). (<b>N</b>) Post-operative macular SD-OCT with ART. (<b>O</b>) Density map (Topcon, Triton, Topcon Healthcare). <b>Case 6</b> (<b>P</b>–<b>R</b>): (<b>P</b>) Left eye pre-operative macular SD OCT and intraretinal cyst (Spectralis, Heidelberg Engineering, Heidelberg, Germany). (<b>Q</b>) Post-operative macular SD-OCT with ART and intraretinal cyst. (<b>R</b>) Density map (Topcon, Triton, Topcon Healthcare). MLD (minimum lineal dimension), FAZ (foveal avascular zone), MH (macular hole).</p>
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11 pages, 14597 KiB  
Case Report
Purtscher-like Retinopathy in a Patient with Systemic Sclerosis: A Case Report and Narrative Review
by Barbara Pieklarz, Ewa Gińdzieńska-Sieśkiewicz, Izabela Zawadzka, Magdalena Bagrowska, Joanna Daniluk, Joanna Konopińska, Otylia Kowal-Bielecka and Diana Anna Dmuchowska
Biomedicines 2023, 11(3), 839; https://doi.org/10.3390/biomedicines11030839 - 10 Mar 2023
Cited by 3 | Viewed by 2050
Abstract
Purtscher-like retinopathy (PLR) is an uncommon occlusive microangiopathy associated with various systemic conditions. We report a case of PLR related to severe progressive systemic sclerosis (SSc), an autoimmune disease characterized by widespread angiopathy and fibrosis, in a 44-year-old Caucasian male diagnosed with early [...] Read more.
Purtscher-like retinopathy (PLR) is an uncommon occlusive microangiopathy associated with various systemic conditions. We report a case of PLR related to severe progressive systemic sclerosis (SSc), an autoimmune disease characterized by widespread angiopathy and fibrosis, in a 44-year-old Caucasian male diagnosed with early diffuse cutaneous systemic sclerosis (dSSc). Upon ophthalmological examination, pathognomonic fundoscopy abnormalities were found. Spectral domain optical coherence tomography (SD-OCT), angio-OCT, and visual field results are documented at initial diagnosis and follow-up visits. The detailed ophthalmological assessment is juxtaposed with rheumatological evaluation and treatment. Current literature on probable pathophysiological mechanisms is reviewed in accordance with the described case. The PLR seems to be connected to severe SSc-related angiopathy initiated by capillary endothelial damage, with ultimate arteriolar precapillary occlusion in the inner retinal layer. Although this is not routinely recommended, we suggest that ophthalmological examinations may be advantageous in patients with SSc, as serious eye pathology may be present despite the lack of symptoms reported by the patient. Patients with PLR require a differential diagnosis and regular follow-up. Proper treatment of the underlying disease may have beneficial effects on the natural course of PLR. Full article
(This article belongs to the Special Issue Pathogenesis and Treatment of Autoimmune and Inflammatory Diseases)
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<p>Painful ulcers and skin thickening of both hands.</p>
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<p>Nailfold capillaroscopy demonstrating severe microangiopathy.</p>
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<p>(<b>A</b>). Fundoscopy of RE and LE at diagnosis: cotton-wool spots and Purtscher flecken. (<b>B</b>). Fundoscopy of RE and LE showing reduced cotton-wool spots at 1 month follow-up.</p>
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<p>SD-OCT: hyperreflectivity in retinal nerve fiber layer corresponding to cotton-wool spots in (<b>A</b>) RE and (<b>B</b>) LE; (<b>C</b>) macular cystoid spaces in RE.</p>
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<p>(<b>A</b>). Initial OCT thickness mapping of RE and LE. (<b>B</b>). OCT thickness mapping of RE and LE 4 weeks later, showing reduction. (<b>C</b>). OCT thickness mapping of RE and LE 6 months later showing further reduction. (<b>D</b>). OCT thickness mapping of RE and LE around 12 month follow-up, showing stabilization.</p>
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<p>Fluorescein angiography of (<b>A</b>) RE and (<b>B</b>) LE reflecting vascular wall enhancement, vein dilatation, and capillary occlusion, as well as slight leakage within macula and optic disc in RE.</p>
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<p>OCT-A of RE reflecting local deficiency within superficial and deep capillary plexus and choriocapillaris. (<b>A</b>–<b>C</b>) Macular area and (<b>D</b>–<b>F</b>) peripapillary area: (<b>A</b>,<b>D</b>) superficial plexus, (<b>B</b>,<b>E</b>) deep plexus, (<b>C</b>,<b>F</b>) choriocapillaris.</p>
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<p>(<b>A</b>). Visual field test (30-2) of RE and LE. (<b>B</b>). Visual field test (30-2) of RE and LE 4 weeks later. (<b>C</b>). Visual field test (30-2) of RE and LE at 12 month follow-up.</p>
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14 pages, 4248 KiB  
Article
Long-Term Evaluation of Retinal Morphology and Function in Rosa26-Cas9 Knock-In Mice
by Kabhilan Mohan, Sushil Kumar Dubey, Kyungsik Jung, Rashmi Dubey, Qing Jun Wang, Subhash Prajapati, Jacob Roney, Jennifer Abney and Mark Ellsworth Kleinman
Int. J. Mol. Sci. 2023, 24(6), 5186; https://doi.org/10.3390/ijms24065186 - 8 Mar 2023
Cited by 1 | Viewed by 2056
Abstract
The CRISPR/Cas9 system is a robust, efficient, and cost-effective gene editing tool widely adopted in translational studies of ocular diseases. However, in vivo CRISPR-based editing in animal models poses challenges such as the efficient delivery of the CRISPR components in viral vectors with [...] Read more.
The CRISPR/Cas9 system is a robust, efficient, and cost-effective gene editing tool widely adopted in translational studies of ocular diseases. However, in vivo CRISPR-based editing in animal models poses challenges such as the efficient delivery of the CRISPR components in viral vectors with limited packaging capacity and a Cas9-associated immune response. Using a germline Cas9-expressing mouse model would help to overcome these limitations. Here, we evaluated the long-term effects of SpCas9 expression on retinal morphology and function using Rosa26-Cas9 knock-in mice. We observed abundant SpCas9 expression in the RPE and retina of Rosa26-Cas9 mice using the real-time polymerase chain reaction (RT-PCR), Western blotting, and immunostaining. SD-OCT imaging and histological analysis of the RPE, retinal layers, and vasculature showed no apparent structural abnormalities in adult and aged Cas9 mice. Full-field electroretinogram of adult and aged Cas9 mice showed no long-term functional changes in the retinal tissues because of constitutive Cas9 expression. The current study showed that both the retina and RPE maintain their phenotypic and functional features in Cas9 knock-in mice, establishing this as an ideal animal model for developing therapeutics for retinal diseases. Full article
(This article belongs to the Special Issue Retinal Degeneration—From Genetics to Therapy)
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Graphical abstract

Graphical abstract
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<p>Evaluation of SpCas9 expression in RPE/choroid and retina of WT and Cas9 mice. (<b>A</b>) qPCR analysis of RPE/choroid and retinal tissues reveal abundant Cas9 expression in the adult and aged Cas9 mice (n = 5–6 per group; *** <span class="html-italic">p</span> &lt; 0.001). Statistical significance was determined by Mann–Whitney U test; error bars depict SEM. (<b>B</b>) Representative Western blots show Cas9 expression in RPE/choroid and neural retina of adult and aged Cas9 mice. β-actin served as the loading control. (<b>C</b>) Relative expression of Cas9 in RPE/choroid and retina of adult and aged Cas9 mice with respect to the beta-actin, Rpe65 (RPE/choroid), and Rho; Prph2 (retina) was determined by qPCR (n = 5–6 per group, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, ns, no significance). All qPCR data were normalized to GAPDH and error bars were represented as SEM. (<b>D</b>) Fluorescence images of retinal flat mounts from adult (left) and aged (right) mice showing Cas9-EGFP expression only in Cas9 mice (scale bars, 2000 μm). (<b>E</b>) Representative fluorescence images of retinal cross sections of adult (left) and aged (right) mice showing widespread Cas9 expression across different retinal layers. Representative WT mice retinal cross sections exhibit mild autofluorescence (scale bars, 50 μm). (<b>F</b>) Representative immunofluorescence images of the retina from WT and Cas9 mice showing ubiquitous Cas9 expression across retinal layers in adult and aged Cas9 mice. Adult and aged WT and isotype controls stained negative for anti-SpCas9 antibody. GCL, ganglion cell layer; IPL, inner plexiform layer; INL, inner nuclear layer; OPL, outer plexiform layer; ONL, outer nuclear layer; PRL, photoreceptor layer, RPE; retinal pigment epithelium. Hoechst staining (Hoechst 33342, blue) in both WT and Cas9 mice represent intact nuclei of retina. Scale bar: 25 μm.</p>
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<p>Phenotypic comparison between wildtype and Cas9 mouse eyes. (<b>A</b>,<b>E</b>) Representative fundus photographs of adult Cas9 mice (<b>E</b>) appear to be normal and healthy and comparable to those of the adult WT mice (<b>A</b>). (<b>B</b>,<b>F</b>) Representative fundus photographs of aged Cas9 mice (<b>F</b>) show normal fundus and are comparable to those of the similarly aged WT mice (<b>B</b>). (<b>C</b>,<b>G</b>) Fluorescein angiography of fundus showed no vascular defects in aged Cas9 and WT mice. (<b>D</b>,<b>H</b>) Fundus autofluorescence imaging showed absence of autofluorescence in both aged Cas9 and WT mice. (<b>I</b>,<b>J</b>) RPE morphology was visualized by immunostaining for ZO-1 (red) on <span class="html-italic">R</span>PE/choroid flat mounts of adult and aged WT mice. (<b>K</b>,<b>L</b>) RPE of adult Cas9 mice and age-matched controls showed typical hexagon pattern with ZO-1 staining (red) and nuclear-localized signal from EGFP (green).White arrowheads in images from the inset in K and L indicate nuclear-localized EGFP. Scale bar: 100 μm.</p>
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<p>Comparison of WT and Cas9 mice retinal structure using SD-OCT imaging and histostaining. (<b>A</b>–<b>C</b>) Representative SD-OCT images from WT and Cas9 mice reveal normal retinal layers with no indication of retinal thinning or degeneration. (<b>D</b>) No statistically significant differences were observed in total retinal thickness between WT and Cas9 mice (<span class="html-italic">p</span> = 0.53, ns, no significance, Mann–Whitney test). (<b>E</b>–<b>G</b>) H&amp;E staining showed all the major retinal layers and RPE/choroid to be intact in both WT and Cas9 mice. The retinal layers of the Cas9 mice were well aligned with the WT mice retinal layers represented by GCL, ganglion cell layer; IPL, inner plexiform layer; INL, inner nuclear layer; OPL, outer plexiform layer; ONL, outer nuclear layer; PRL, photoreceptor layer, RPE; retinal pigment epithelium. Scale bar: 50 μm.</p>
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<p>ERG analysis of retina function in Cas9 mice (<b>A</b>) Representative waveforms from ERGs of adult WT and Cas9 mice. (<b>B</b>,<b>C</b>) Scotopic a- and b-wave amplitudes, respectively, of adult and aged WT and Cas9 mice as a function of light intensity. Error bars represent SD (n = 6–8 per group). The a-wave and b-wave amplitudes at different flash intensities did not show any statistically significant (Mann–Whitney test; <span class="html-italic">p</span>-value &lt; 0.01 considered significant) differences between age-matched WT (black) and Cas9 mice (red).</p>
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