Evaluating fingerprint-like patterns in the healthy Henle fiber layer using enface OCT imaging.

PURPOSE: Enface OCT may disclose a distinct "fingerprint-like' pattern within the HFL in various macular disorders. This study aims to investigate the frequency and characteristics of this pattern in healthy eyes and identify potential factors influencing its visibility. METHODS: Two, independent masked reading center graders evaluated for the presence and prominence of a fingerprint pattern in the Henle fiber layer (HFL) on enface OCT images from 33 healthy subjects (66 eyes). The prominence of the pattern was rated qualitatively using a 0-3 scale, with 3 indicating the strongest prominence. Tilt angles (relative to the normal/perpendicular at the center) of the retina were measured on horizontal and vertical B-scans, and the retinal curvature was assessed using ImageJ, in order to determine the impact of the incident light angle on the visibility and prominence of the fingerprint pattern. Inter-grader agreement using Cohen's kappa and the frequency and percentage of patterns in the entire enface image and in each quadrant were calculated and compared using the Friedman test with Dunn's post-test. A generalized estimating equation (GEE) was used to analyze the association between these metrics and fingerprint prominence. RESULTS: Substantial inter-grader agreement was observed (Cohen's kappa = 0.71) for assessing the prominence of the fingerprint pattern. Over 70% of eyes exhibited some evidence of the pattern (score ≥1). Significant difference in pattern prominence across quadrants was detected (p < 0.05), with lowest prominence in the temporal quadrant (p < 0.001 for pairwise comparisons against all other quadrants). The GEE analysis to account for the extent of the effect of scan tilt angle and RPE curvature was not able to predict the prominence of the fingerprint pattern, highlighting that angle of incidence (of the scanning laser light) alone could not explain the pattern. CONCLUSIONS: This study confirms that a fingerprint-like pattern within the HFL can also be observed in healthy eyes, challenging the notion that this finding is only manifest in the setting of disease. In addition, the lack of correlation with angle of incident light suggests that the pattern may be related to other intrinsic characteristics of the HFL.

Impact of 12-Month Angioscopic Thrombi and Yellow Plaque After Drug-Eluting Stent Implantation.

BACKGROUND: Coronary angioscopy (CAS) has 2 unique abilities: direct visualization of thrombi and plaque color. However, in the recent drug-eluting stent (DES) era, serial CAS findings after DES implantation have not been fully elucidated. We investigated the impact of CAS findings after implantation of a polymer-free biolimus A9-coated stent (PF-BCS) or durable polymer everolimus-eluting stent (DP-EES).Methods and Results: We investigated serial CAS and optical coherence tomography (OCT) findings at 1 and 12 months in 99 patients who underwent PF-BCS or DP-EES implantation. We evaluated factors correlated with angioscopic thrombi and yellow plaque, and the clinical impact of both thrombi and yellow plaque at 12 months (BTY). The BTY group included 17 (22%) patients. The incidence and grade of thrombi and yellow plaque decreased from 1 to 12 months. Although no patients had newly appearing thrombi at 12 months, 2 DP-EES patients had newly appearing yellow plaque at 12 months. Multivariable analysis revealed HbA1c, minimum stent area, and adequate strut coverage were significant factors correlated with 12-month angioscopic thrombi, and DP-EESs were significantly correlated with 12-month yellow plaque. However, BTY was not correlated with clinical events. CONCLUSIONS: The management of diabetes, stent area, and adequate stent coverage are important for intrastent thrombogenicity and polymer-free stents are useful for stabilizing plaque vulnerability.

Tuberculum meningioma with recovery of glaucoma-like visual field defects after chiasmal decompression: a case report.

BACKGROUND: To report a case of tuberculum meningioma with recovery of glaucoma-like visual field defects after chiasmal decompression. CASE PRESENTATION: A 39-year-old woman presenting with headache was found to have bilateral arcuate retinal nerve fiber layer (RNFL) thinning on optical coherence tomography (OCT) with a corresponding arcuate scotomas consistent with glaucomatous change. However a suprasellar tumor compressing the anterior chiasm from below was found on magnetic resonance imaging of the brain. After resection of the mass, which was diagnosed as meningothelial meningioma by the pathological examination, the glaucoma-like visual field defects resolved despite the RNFL thinning on the OCT showing no improvement. CONCLUSIONS: Chiasmal compression may mimic glaucoma and produce arcuate scotoma rather than temporal visual field loss. There is a possibility that the development of chiasmal compression somehow converted preperimetric glaucoma into a more advanced form accompanied by visual field defects and that the glaucoma reverted to the preperimetric state after chiasmal decompression.

Quantitative optical coherence tomography angiography assessments in the fellow eyes of those with central serous chorioretinopathy.

BACKGROUND: To analyze the vessel density (VD) of the retina and choriocapillaris (CC) layer and the structure of the foveal avascular zone (FAZ) in the fellow eyes of central serous chorioretinopathy (CSC) patients by using optical coherence tomography angiography (OCTA). METHODS: This was a case-control study. Unilateral CSC patients and age-matched healthy subjects were recruited from the Affiliated Eye Hospital of Wenzhou Medical University between July 2016 and July 2021. All eyes were divided into three groups: acute CSC (aCSC), chronic CSC (cCSC), and healthy controls. Both aCSC and cCSC were again divided into two subgroups: the affected eyes and the fellow eyes. In this study, all parameters of VD and FAZ were measured by self-software of OCTA. RESULTS: A total of 231 eyes of 137 subjects were included, with 47 aCSC patients, 47 cCSC patients, and 43 healthy controls. In the fellow eyes of CSC, the retinal VD was significantly lower (all P < 0.05), and the FAZ was significantly larger (all P < 0.05) in the cCSC group than in healthy controls, while no difference was detected in the CC layer. There was no significant difference between the aCSC group and healthy controls in all OCTA parameters. In the affected eyes of CSC, the superficial retinal vessel density (SRVD) was significantly higher (all P < 0.05) in healthy controls than in the aCSC and cCSC groups, while the deep retinal vessel density (DRVD) was significantly lower (all P < 0.05) and the FAZ was larger (all P < 0.05) in the cCSC group than in the aCSC group and healthy controls. A liner regression equation was established: Y (BCVA, best corrected visual acuity) = 3.692-0.036✱X1 (DRVD-Fovea)-0.031✱X2 (FD-300, vessel density around the 300 µm width of the FAZ), R2 = 0.427. CONCLUSION: Based on OCTA measurements, this study revealed that the retinal microvascular network was impaired even in the fellow eyes of those with cCSC, which should arouse attention to the observation of unilateral CSC.

91-month follow-up of solitary punctate chorioretinitis in a Chinese patient.

BACKGROUND: Solitary Punctate Chorioretinitis (SPC) is a recently identified form of punctate inner choroidopathy (PIC) characterized by a single lesion in the fovea of the macula. Previous studies with a maximum follow-up of 48 months were insufficient. Our review uncovered a case sustained for 91 months. CASE PRESENTATION: A 28-year-old young woman experienced with sudden visual loss in her right eye. Comprehensive examinations, including assessment of best-corrected visual acuity (BCVA), slit-lamp biomicroscopy, noncontact tonometry, fundus fluorescein angiography (FFA), fundus autofluorescence (FAF), optical coherence tomography angiography (OCTA), perimetry, and microperimetry, were conducted. Over 91 months, the lesion slightly enlarged, remained yellow-white and punctate, and stayed in the central macula of the posterior pole. OCT images depicted subsidence in the inner nuclear layer (INL), the outer plexiform layer (OPL), photoreceptor layer, and disruption of the external limiting membrane (ELM), ellipsoid zone, and retinal pigment epithelium (RPE)/Bruch's membrane complex. Retinal herniation, focal choroidal excavation (FCE), and abnormal vessels in the choriocapillaris were noted. At the slab of the choriocapillaris, OCTA demonstrated that the lesion resembled a linear vascular structure, distinct from the structure of normal choriocapillaris. This confirmed the lesion as an abnormal vascular formation. FAF revealed a punctate hypo-autofluorescence lesion and abnormal hyper-autofluorescence near the optic disc and macula. FFA demonstrated a punctate hyper-fluorescent lesion inferotemporal to the fovea. The vascular structure remained stable without fluid exudation on OCT images, hence anti-vascular endothelial growth factor (anti-VEGF) treatment was not administered. Visual acuity improved from counting fingers to 0.07 in 52 days, reached 0.6 after 15 months, remained at 0.6 from 56 to 80 months, and returned to 0.8 after 91 months, although accompanied by local scotomas. The lesion pattern slightly enlarged without scarring. CONCLUSIONS: Throughout long-term follow-up, we had long suspected the presence of choroidal neovascularization (CNV) and found the FCE in the last visit. Eventually, we concluded that SPC could potentially constitute a distinct subtype of PIC. The patient received no treatment, and vision recovered to 0.8. If CNV is suspected in SPC, anti-VEGF treatment may not be necessary without activity on OCT, but close monitoring is essential.

Dense Convolutional Neural Network-Based Deep Learning Pipeline for Pre-Identification of Circular Leaf Spot Disease of Diospyros kaki Leaves Using Optical Coherence Tomography.

Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading to substantial harvest reductions. Existing visual and destructive inspection methods suffer from subjectivity, limited accuracy, and considerable time consumption. This study presents an automated pre-identification method of the disease through a deep learning (DL) based pipeline integrated with optical coherence tomography (OCT), thereby addressing the highlighted issues with the existing methods. The investigation yielded promising outcomes by employing transfer learning with pre-trained DL models, specifically DenseNet-121 and VGG-16. The DenseNet-121 model excels in differentiating among three stages of CLS disease (healthy (H), apparently healthy (or healthy-infected (HI)), and infected (I)). The model achieved precision values of 0.7823 for class-H, 0.9005 for class-HI, and 0.7027 for class-I, supported by recall values of 0.8953 for class-HI and 0.8387 for class-I. Moreover, the performance of CLS detection was enhanced by a supplemental quality inspection model utilizing VGG-16, which attained an accuracy of 98.99% in discriminating between low-detail and high-detail images. Moreover, this study employed a combination of LAMP and A-scan for the dataset labeling process, significantly enhancing the accuracy of the models. Overall, this study underscores the potential of DL techniques integrated with OCT to enhance disease identification processes in agricultural settings, particularly in persimmon cultivation, by offering efficient and objective pre-identification of CLS and enabling early intervention and management strategies.

Thinner inner retinal layers are associated with lower cognitive performance, lower brain volume, and altered white matter network structure-The Maastricht Study.

INTRODUCTION: The retina may provide non-invasive, scalable biomarkers for monitoring cerebral neurodegeneration. METHODS: We used cross-sectional data from The Maastricht study (n = 3436; mean age 59.3 years; 48% men; and 21% with type 2 diabetes [the latter oversampled by design]). We evaluated associations of retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses with cognitive performance and magnetic resonance imaging indices (global grey and white matter volume, hippocampal volume, whole brain node degree, global efficiency, clustering coefficient, and local efficiency). RESULTS: After adjustment, lower thicknesses of most inner retinal layers were significantly associated with worse cognitive performance, lower grey and white matter volume, lower hippocampal volume, and worse brain white matter network structure assessed from lower whole brain node degree, lower global efficiency, higher clustering coefficient, and higher local efficiency. DISCUSSION: The retina may provide biomarkers that are informative of cerebral neurodegenerative changes in the pathobiology of dementia.

A new computer-aided diagnosis tool based on deep learning methods for automatic detection of retinal disorders from OCT images.

PURPOSE: Early detection of retinal disorders using optical coherence tomography (OCT) images can prevent vision loss. Since manual screening can be time-consuming, tedious, and fallible, we present a reliable computer-aided diagnosis (CAD) software based on deep learning. Also, we made efforts to increase the interpretability of the deep learning methods, overcome their vague and black box nature, and also understand their behavior in the diagnosis. METHODS: We propose a novel method to improve the interpretability of the used deep neural network by embedding the rich semantic information of abnormal areas based on the ophthalmologists' interpretations and medical descriptions in the OCT images. Finally, we trained the classification network on a small subset of the online publicly available University of California San Diego (UCSD) dataset with an overall of 29,800 OCT images. RESULTS: The experimental results on the 1000 test OCT images show that the proposed method achieves the overall precision, accuracy, sensitivity, and f1-score of 97.6%, 97.6%, 97.6%, and 97.59%, respectively. Also, the heat map images provide a clear region of interest which indicates that the interpretability of the proposed method is increased dramatically. CONCLUSION: The proposed software can help ophthalmologists in providing a second opinion to make a decision, and primitive automated diagnoses of retinal diseases and even it can be used as a screening tool, in eye clinics. Also, the improvement of the interpretability of the proposed method causes to increase in the model generalization, and therefore, it will work properly on a wide range of other OCT datasets.

Wide-Field Three-Dimensional Depth-Invariant Cellular-Resolution Imaging of the Human Retina.

Three-dimensional (3D) cellular-resolution imaging of the living human retina over a large field of view will bring a great impact in clinical ophthalmology, potentially finding new biomarkers for early diagnosis and improving the pathophysiological understanding of ocular diseases. While hardware-based and computational adaptive optics (AO) optical coherence tomography (OCT) have been developed to achieve cellular-resolution retinal imaging, these approaches support limited 3D imaging fields, and their high cost and intrinsic hardware complexity limit their practical utility. Here, this work demonstrates 3D depth-invariant cellular-resolution imaging of the living human retina over a 3 × 3 mm field of view using the first intrinsically phase-stable multi-MHz retinal swept-source OCT and novel computational defocus and aberration correction methods. Single-acquisition imaging of photoreceptor cells, retinal nerve fiber layer, and retinal capillaries is presented across unprecedented imaging fields. By providing wide-field 3D cellular-resolution imaging in the human retina using a standard point-scan architecture routinely used in the clinic, this platform proposes a strategy for expanded utilization of high-resolution retinal imaging in both research and clinical settings.

The effect of moderate-intensity aerobic exercise on non-proliferative diabetic retinopathy in type II diabetes mellitus patients: A clinical trial.

INTRODUCTION: Diabetic retinopathy (DR) is one of the most threatening complications of diabetes and a leading cause of visual loss in working-age population. Although exercise is beneficial in diabetes, previous studies have showed contradictory and inconclusive results on how it effects DR. In this study, we aimed to investigate the effect of moderate-intensity aerobic exercise on non-proliferative diabetic retinopathy. MATERIALS & METHODS: In this before-after clinical trial, 40 patients with diabetic retinopathy were enrolled by convenient sampling method in Shahid Labbafinejad Hospital in Tehran during 2021-2022. Before the intervention, central macular thickness (CMT, microns) measured by optical coherence tomography (OCT) and fasting blood sugar (FBS, mg/dl) were obtained. Then, patients took part in a 12-week moderate-intensity aerobic exercise (3 sessions per week, each session 45 min). Data were analyzed using SPSS version 26.0. RESULTS: Out of 40 examined patients, 21 (52.5 %) were male and 19 (47.5 %) were female. The mean age of the patients was 50.8 years. The mean rank of FBS (mg/dl) significantly decreased from 21.12 before the exercise to 8.75 after the exercise (p < 0.001). Also, the mean rank of CMT (microns) showed a significant decrease from 21.11 before the intervention to 16.20 after the exercise (p < 0.001). There was a significant positive correlation between patients' age and FBS (mg/dl) before (rho = 0.457, p = 0.003) and after (rho = 0.365, p = 0.021) the intervention. Also, a significant positive correlation was found between patients' age and CMT (microns) before (rho = 0.525, p = 0.001) and after (rho = 0.461, p = 0.003) moderate exercise. CONCLUSION: Moderate-intensity aerobic exercise leads to lower FBS (mg/dl) and CMT (microns) in patients with diabetic retinopathy, so it may be beneficial for diabetic patients to avoid sedentary lifestyle.

Cataract surgery in neovascular AMD: impact on visual acuity and disease activity.

BACKGROUND: Cataract and neovascular age-related macular degeneration (nAMD) often co-exist and both contribute to impaired vision. It has been debated whether cataract surgery can increase nAMD activity. The purpose of this retrospective study was to investigate the impact of cataract surgery on visual acuity, treatment intensity for nAMD and macular morphology in patients with on-going treatment for nAMD. METHODS: Data was obtained from the Swedish Macular Register, the Swedish National Cataract Register, optical coherence tomography (OCT) images and patient charts. All eyes were treated at the Department of Ophthalmology at the County Hospital of Västmanland, Västerås, Sweden. Follow-up was 6 months after surgery. The study was approved by the Swedish Ethical Review Authority. RESULTS: In total, 156 patients (168 eyes) were included. The mean age at cataract surgery was 82 (standard deviation, SD 6) years. Both distance and near visual acuity improved after surgery. Distance visual acuity increased from 59 (SD 12) to 66 (SD 15) letters ETDRS (P < 0.001). Proportion of eyes with normal near visual acuity increased from 12 to 41%. The anti-vascular endothelial growth factor (VEGF) treatment intensity remained unchanged: mean of 3.4 (SD 1.9) and 3.3 (SD 1.7) treatments were given 6 months pre- and postoperatively, respectively. The prevalence of intraretinal fluid (IRF) in the macula increased from 22 to 31% postoperatively, while subretinal fluid, fluid under the pigment epithelium (sub-RPE fluid) and central retinal thickness were unaltered. In eyes with new IRF, improvement in visual acuity and number of anti-VEGF treatments were similar to eyes without new IRF. CONCLUSION: Cataract surgery improved visual acuity in patients with on-going treatment for nAMD and did not affect anti-VEGF treatment intensity. Macular morphology remained unchanged. The slight increase in intraretinal fluid after surgery was not found to affect visual acuity or anti-VEGF treatment intensity. It is hypothesized that this might indicate that it represents degenerative intraretinal cystic fluid.

Comparison of the morphological characteristics of the choroidal sublayer between idiopathic macular holes and epiretinal membranes with automatic analysis.

PURPOSE: To compare the choroidal sublayer morphologic features between idiopathic macular hole (IMH) and idiopathic epiretinal membrane (iERM) on spectral-domain optical coherent tomography (SD-OCT) using an automatic segmentation model. METHODS: Thirty-three patients with idiopathic IMHs and 44 with iERMs who underwent vitrectomies were involved. The enhanced depth imaging mode of SD-OCT was used to obtain the B-scan image after single line scanning of the macular fovea. The choroidal sublayer automatic analysis model divides the choroidal into the choroidal large vessel layer, the middle vessel layer and the small vessel layer (LVCL, MVCL and SVCL, respectively) and calculates the choroidal thickness (overall, LVCL, MVCL and SVCL) and vascular index (overall, LVCL, MVCL and SVCL). The morphological characteristics of the choroidal sublayer in the ERM eyes and the IMH eyes were compared. RESULTS: The mean choroidal thickness in the macular centre of the IMH eyes was significantly thinner than that of the ERM eyes (206.35 ± 81.72 vs. 273.33 ± 82.31 µm; P < 0.001). The analysis of the choroidal sublayer showed that the MVCL and SVCL macular centres and 0.5-1.5 mm of the nasal and temporal macula were significantly thinner in the IMH eyes than in the ERM eyes (P < 0.05), and there was a difference in the macular centre of the LVCL between the two groups (P < 0.05). In contrast, the choroidal vascular index of the macular centre in the IMH eyes was significantly higher than that in iERM eyes (0.2480 ± 0.0536 vs. 0.2120 ± 0.0616; P < 0.05). There was no significant difference in the CVI of other parts of the macula, the LVCL or MVCL between the two groups. CONCLUSION: The choroidal thickness of the IMH eyes was significantly thinner than that of the iERM eyes, which was mainly observed in 3 mm of the macular centre and the MVCL and SVCL layers of the choroid. The choroidal vascular index of the IMH eyes was higher than that of the iERM eyes. These findings suggest that the choroid may be involved in the pathogenesis of IMH and iERM.

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images.

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathological procedures, and the response and evaluation of therapeutic effectiveness in various fields of clinical practices, including primary eye diseases and systemic diseases such as diabetes. Therefore, precise diagnosis, classification, and automated image analysis models are crucial. In this paper, we propose an enhanced optical coherence tomography (EOCT) model to classify retinal OCT based on modified ResNet (50) and random forest algorithms, which are used in the proposed study's training strategy to enhance performance. The Adam optimizer is applied during the training process to increase the efficiency of the ResNet (50) model compared with the common pre-trained models, such as spatial separable convolutions and visual geometry group (VGG) (16). The experimentation results show that the sensitivity, specificity, precision, negative predictive value, false discovery rate, false negative rate accuracy, and Matthew's correlation coefficient are 0.9836, 0.9615, 0.9740, 0.9756, 0.0385, 0.0260, 0.0164, 0.9747, 0.9788, and 0.9474, respectively.

Tail Artifact Removal via Transmittance Effect Subtraction in Optical Coherence Tail Artifact Images.

Optical Coherence Tomography Angiography (OCTA) has revolutionized non-invasive, high-resolution imaging of blood vessels. However, the challenge of tail artifacts in OCTA images persists. In response, we present the Tail Artifact Removal via Transmittance Effect Subtraction (TAR-TES) algorithm that effectively mitigates these artifacts. Through a simple physics-based model, the TAR-TES accounts for variations in transmittance within the shallow layers with the vasculature, resulting in the removal of tail artifacts in deeper layers after the vessel. Comparative evaluations with alternative correction methods demonstrate that TAR-TES excels in eliminating these artifacts while preserving the essential integrity of vasculature images. Crucially, the success of the TAR-TES is closely linked to the precise adjustment of a weight constant, underlining the significance of individual dataset parameter optimization. In conclusion, TAR-TES emerges as a powerful tool for enhancing OCTA image quality and reliability in both clinical and research settings, promising to reshape the way we visualize and analyze intricate vascular networks within biological tissues. Further validation across diverse datasets is essential to unlock the full potential of this physics-based solution.

Multi-Scale-Denoising Residual Convolutional Network for Retinal Disease Classification Using OCT.

Macular pathologies can cause significant vision loss. Optical coherence tomography (OCT) images of the retina can assist ophthalmologists in diagnosing macular diseases. Traditional deep learning networks for retinal disease classification cannot extract discriminative features under strong noise conditions in OCT images. To address this issue, we propose a multi-scale-denoising residual convolutional network (MS-DRCN) for classifying retinal diseases. Specifically, the MS-DRCN includes a soft-denoising block (SDB), a multi-scale context block (MCB), and a feature fusion block (FFB). The SDB can determine the threshold for soft thresholding automatically, which removes speckle noise features efficiently. The MCB is designed to capture multi-scale context information and strengthen extracted features. The FFB is dedicated to integrating high-resolution and low-resolution features to precisely identify variable lesion areas. Our approach achieved classification accuracies of 96.4% and 96.5% on the OCT2017 and OCT-C4 public datasets, respectively, outperforming other classification methods. To evaluate the robustness of our method, we introduced Gaussian noise and speckle noise with varying PSNRs into the test set of the OCT2017 dataset. The results of our anti-noise experiments demonstrate that our approach exhibits superior robustness compared with other methods, yielding accuracy improvements ranging from 0.6% to 2.9% when compared with ResNet under various PSNR noise conditions.

Automated Age-Related Macular Degeneration Detector on Optical Coherence Tomography Images Using Slice-Sum Local Binary Patterns and Support Vector Machine.

Artificial intelligence has revolutionised smart medicine, resulting in enhanced medical care. This study presents an automated detector chip for age-related macular degeneration (AMD) using a support vector machine (SVM) and three-dimensional (3D) optical coherence tomography (OCT) volume. The aim is to assist ophthalmologists by reducing the time-consuming AMD medical examination. Using the property of 3D OCT volume, a modified feature vector connected method called slice-sum is proposed, reducing computational complexity while maintaining high detection accuracy. Compared to previous methods, this method significantly reduces computational complexity by at least a hundredfold. Image adjustment and noise removal steps are excluded for classification accuracy, and the feature extraction algorithm of local binary patterns is determined based on hardware consumption considerations. Through optimisation of the feature vector connection method after feature extraction, the computational complexity of SVM detection is significantly reduced, making it applicable to similar 3D datasets. Additionally, the design supports model replacement, allowing users to train and update classification models as needed. Using TSMC 40 nm CMOS technology, the proposed detector achieves a core area of 0.12 mm2 while demonstrating a classification throughput of 8.87 decisions/s at a maximum operating frequency of 454.54 MHz. The detector achieves a final testing classification accuracy of 92.31%.

Analysis of the Asymmetry between Both Eyes in Early Diagnosis of Glaucoma Combining Features Extracted from Retinal Images and OCTs into Classification Models.

This study aims to analyze the asymmetry between both eyes of the same patient for the early diagnosis of glaucoma. Two imaging modalities, retinal fundus images and optical coherence tomographies (OCTs), have been considered in order to compare their different capabilities for glaucoma detection. From retinal fundus images, the difference between cup/disc ratio and the width of the optic rim has been extracted. Analogously, the thickness of the retinal nerve fiber layer has been measured in spectral-domain optical coherence tomographies. These measurements have been considered as asymmetry characteristics between eyes in the modeling of decision trees and support vector machines for the classification of healthy and glaucoma patients. The main contribution of this work is indeed the use of different classification models with both imaging modalities to jointly exploit the strengths of each of these modalities for the same diagnostic purpose based on the asymmetry characteristics between the eyes of the patient. The results show that the optimized classification models provide better performance with OCT asymmetry features between both eyes (sensitivity 80.9%, specificity 88.2%, precision 66.7%, accuracy 86.5%) than with those extracted from retinographies, although a linear relationship has been found between certain asymmetry features extracted from both imaging modalities. Therefore, the resulting performance of the models based on asymmetry features proves their ability to differentiate healthy from glaucoma patients using those metrics. Models trained from fundus characteristics are a useful option as a glaucoma screening method in the healthy population, although with lower performance than those trained from the thickness of the peripapillary retinal nerve fiber layer. In both imaging modalities, the asymmetry of morphological characteristics can be used as a glaucoma indicator, as detailed in this work.

Inner Retinal Layer Changes Reflect Changes in Ambulation Score in Patients with Primary Progressive Multiple Sclerosis.

The establishment of surrogate markers to detect disability progression in persons with multiple sclerosis (PwMS) is important to improve monitoring of clinical deterioration. Optical coherence tomography (OCT) could be such a tool. However, sufficient longitudinal data of retinal neuroaxonal degeneration as a marker of disease progression exist only for PwMS with a relapsing-remitting course (RRMS) so far. In contrast, longitudinal data of retinal layers in patients with primary-progressive MS (PPMS) are inconsistent, and the association of OCT parameters with ambulatory performance in PwMS has rarely been investigated. We aimed to investigate the relative annual rates of change in retinal layers in PwMS (RRMS and PPMS) compared with healthy controls (HC) using OCT and to evaluate their association with ambulatoryfunctionalscore (AS) worsening in PPMS. A retrospective analysis of a longitudinal OCT dataset of the retinal layers of PwMS and HC from two MS centers in Germany was performed. Walking ability was measured over a standardized distance of 500 m, and changes during the observation period were categorized using the AS and the expanded disability status scale (EDSS). 61 HC with 121 eyes and 119 PwMS (PPMS: 57 patients with 108 eyes; RRMS: 62 patients with 114 eyes) were included. The median follow-up time for PwMS was 3 years. The relative annual change of pRNFL (peripapillary retinal nerve fiber layer) and INL (inner nuclear layer) was significantly different in PwMS compared with HC. RRMS and PPMS subgroups did not differ in the annual atrophy rates. In patients with PPMS, worsening of the AS was significantly associated with increased thinning of the TMV (total macular volume), GCIP (ganglion cell and inner plexiform layer), and ONPL (outer nuclear and outer plexiform layer) (all p-value < 0.05, r > 0.30). For every -0.1% decrease in the TMV, GCIP, and ONPL, the risk of a deterioration in the AS increased by 31% (hazard ratio (HR): 1.309), 11% (HR: 1.112), and 16% (HR: 1.161), respectively. In addition, worsening EDSS in PPMS was significantly associated with the relative annual atrophy rates of pRNFL, TMV, and GCIP (all p-value < 0.05). Disability progression in PPMS can be measured using OCT, and increasing annual atrophy rates of the inner retinal layers are associated with worsening ambulation. OCT is a robust and side-effect-free imaging tool, making it suitable for routine monitoring of PwMS.

Foveal Hypoplasia in CRB1-Related Retinopathies.

The CRB1 gene plays a role in retinal development and its maintenance. When disrupted, it gives a range of phenotypes such as early-onset severe retinal dystrophy/Leber congenital amaurosis (EOSRD/LCA), retinitis pigmentosa (RP), cone-rod dystrophy (CORD) and macular dystrophy (MD). Studies in CRB1 retinopathies have shown thickening and coarse lamination of retinal layers resembling an immature retina. Its role in foveal development has not yet been described; however, this retrospective study is the first to report foveal hypoplasia (FH) presence in a CRB1-related retinopathy cohort. Patients with pathogenic biallelic CRB1 variants from Moorfields Eye Hospital, London, UK, were collected. Demographic, clinical data and SD-OCT analyses with FH structural grading were performed. A total of 15 (48%) patients had EOSRD/LCA, 11 (35%) MD, 3 (9%) CORD and 2 (6%) RP. FH was observed in 20 (65%; CI: 0.47-0.79) patients, all of whom were grade 1. A significant difference in BCVA between patients with FH and without was found (p = 0.014). BCVA continued to worsen over time in both groups (p < 0.001), irrespective of FH. This study reports FH in a CRB1 cohort, supporting the role of CRB1 in foveal development. FH was associated with poorer BCVA and abnormal retinal morphology. Nonetheless, its presence did not alter the disease progression.

Optical Coherence Tomography (OCT): A Brief Look at the Uses and Technological Evolution of Ophthalmology.

Medical imaging is the mainstay of clinical diagnosis and management. Optical coherence tomography (OCT) is a non-invasive imaging technology that has revolutionized the field of ophthalmology. Since its introduction, OCT has undergone significant improvements in image quality, speed, and resolution, making it an essential diagnostic tool for various ocular pathologies. OCT has not only improved the diagnosis and management of ocular diseases but has also found applications in other fields of medicine. In this manuscript, we provide a brief overview of the history of OCT, its current uses and diagnostic capabilities to assess the posterior segment of the eye, and the evolution of this technology from time-domain (TD) to spectral-domain (SD) and swept-source (SS). This brief review will also discuss the limitations, advantages, disadvantages, and future perspectives of this technology in the field of ophthalmology.