Optical coherence tomography: A guide to interpretation of common macular diseases

Pachychoroid disease spectrum: how multimodal imaging and OCT angiography have improved our knowledge

Pachychoroid spectrum disorders (PSDs) represent a group of chorioretinal disorders characterized by abnormal choroidal thickening and various pathological changes in the choroid, retinal pigment epithelium, and retina. This review provides a comprehensive analysis of current multimodal imaging techniques in the diagnosis and management of PSDs. We examine the role of various imaging modalities including optical coherence tomography (OCT), OCT angiography (OCTA), en face OCT, fluorescein angiography (FA), indocyanine green angiography (ICGA), infrared imaging (IR), and fundus autofluorescence (FAF) in evaluating PSDs. Each imaging modality provides unique insights: OCT reveals characteristic choroidal thickening and structural changes; OCTA demonstrates alterations in choroidal flow and neovascularization; en face OCT allows detailed visualization of choroidal vasculature and intervortex anastomoses; FA shows patterns of leakage; ICGA reveals choroidal hyperpermeability and pachyvessels; IR imaging assists in RPE evaluation; and FAF highlights RPE dysfunction. The integration of these imaging techniques has enhanced our understanding of the pathophysiology of PSDs and improved our ability to diagnose, monitor, and treat these conditions. This review particularly emphasizes how OCTA has advanced our knowledge of choroidal circulation and neovascularization in PSDs. We also discuss future directions in imaging technology and their potential impact on personalized therapeutic approaches, including optimized photodynamic therapy based on imaging biomarkers. The synergistic use of multimodal imaging represents a cornerstone in the management of PSDs, enabling more precise diagnosis and tailored treatment strategies.

Wide-field OCT volumetric segmentation using semi-supervised CNN and transformer integration

Wide-field optical coherence tomography (OCT) imaging can enable monitoring of peripheral changes in the retina, beyond the conventional fields of view used in current clinical OCT imaging systems. However, wide-field scans can present significant challenges for retinal layer segmentation. Deep Convolutional Neural Networks (CNNs) have shown strong performance in medical imaging segmentation but typically require large-scale, high-quality, pixel-level annotated datasets to be effectively developed. To address this challenge, we propose an advanced semi-supervised learning framework that combines the detailed capabilities of convolutional networks with the broader perspective of transformers. This method efficiently leverages labelled and unlabelled data to reduce dependence on extensive, manually annotated datasets. We evaluated the model performance on a dataset of 74 volumetric OCT scans, each performed using a prototype swept-source OCT system following a wide-field scan protocol with a 15 × 9 mm field of view, comprising 11,750 labelled and 29,016 unlabelled images. Wide-field retinal layer segmentation using the semi-supervised approach show significant improvements (P-value < 0.001) of up to 11% against a UNet baseline model. Comparisons with a clinical spectral-domain-OCT system revealed significant correlations of up to 0.91 (P-value < 0.001) in retinal layer thickness measurements. These findings highlight the effectiveness of semi-supervised learning with cross-teaching between CNNs and transformers for automated OCT layer segmentation.

Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study

PURPOSE

To evaluate the predictive accuracy of various machine learning (ML) statistical models in forecasting postoperative visual acuity (VA) outcomes following macular hole (MH) surgery using preoperative optical coherence tomography (OCT) parameters.

METHODS

This retrospective study included 158 eyes (151 patients) with full-thickness MHs treated between 2017 and 2023 by the same surgeon and using the same intraoperative surgical technique. Data from electronic medical records and OCT scans were extracted, with OCT-derived qualitative and quantitative MH characteristics recorded. Six supervised ML models-ANCOVA, Random Forest (RF) regression, K-Nearest Neighbor, Support Vector Machine, Extreme Gradient Boosting, and Lasso regression-were trained using an 80:20 training-to-testing split. Model performance was evaluated on an independent testing dataset using the XLSTAT software. In total, the ML statistical models were trained and tested on 14,652 OCT data points from 1332 OCT images.

RESULTS

Overall, 91% achieved MH closure post-surgery, with a median VA gain of -0.3 logMAR units. The RF regression model outperformed other ML models, achieving the lowest mean square error (MSE = 0.038) on internal validation. The most significant predictors of VA were postoperative MH closure status (variable importance = 43.078) and MH area index (21.328). The model accurately predicted the post-operative VA within 0.1, 0.2 and 0.3 logMAR units in 61%, 78%, and 87% of OCT images, respectively.

CONCLUSION

The RF regression model demonstrated superior predictive accuracy for forecasting postoperative VA, suggesting ML-driven approaches may improve surgical planning and patient counselling by providing reliable insights into expected visual outcomes based on pre-operative OCT features.

CLINICAL TRIAL REGISTRATION NUMBER

Not applicable.

A bibliometric and visualization analysis of electrochemical biosensors for early diagnosis of eye diseases

Electrochemical biosensors can provide an economical, accurate and rapid method for early screening of disease biomarkers in clinical medicine due to their high sensitivity, selectivity, portability, low cost and easy manufacturing, and multiplexing capability. Tear, a fluid naturally secreted by the human body, is not only easily accessible but also contains a great deal of biological information. However, no bibliometric studies focus on applying electrochemical sensors in tear/eye diseases. Therefore, we utilized VOSviewer and CiteSpace, to perform a detailed bibliometric analysis of 114 papers in the field of research on the application of tear in electrochemical biosensors screened from Web of Science with the combination of Scimago Graphica and Microsoft Excel for visualization to show the current research hotspots and future trends. The results show that the research in this field started in 2008 and experienced an emerging period in recent years. Researchers from China and the United States mainly contributed to the thriving research areas, with 41 and 29 articles published, respectively. Joseph Wang from the University of California San Diego is the most influential author in the field, and Biosensors & Bioelectronics is the journal with the most published research and the most cited journal. The highest appearance keywords were "biosensor" and "tear glucose," while the most recent booming keywords "diagnosis" and "in-vivo" were. In conclusion, this study elucidates current trends, hotspots, and emerging frontiers, and provides future biomarkers of ocular and systemic diseases by electrochemical sensors in tear with new ideas and opinions.

Primary Visual Pathway Changes in Individuals With Chronic Mild Traumatic Brain Injury

Importance

Individuals with mild traumatic brain injury (TBI) often report vision problems despite having normal visual acuity and fundus examinations. Diagnostics are needed for these patients.

Objective

To determine if a battery of assessments or machine-learning approaches can aid in diagnosing visual dysfunction in patients with mild TBI.

Design, Setting, and Participants

This prospective, observational, case-control study was conducted between May 2018 and November 2021. The study setting was at a level 1 trauma research hospital. Participant eligibility included adult males and females with recorded best-corrected visual acuity and normal fundus examination. Individuals in the case group had a history of mild TBI; controls had no history of TBI. Exclusion criteria included a history of ocular, neurological, or psychiatric disease, moderate-severe TBI, recent TBI, metal implants, age younger than 18 years, and pregnancy. Cases and controls were sex- and age-matched. Data analysis was performed from July 2023 to March 2024.

Exposures

History of mild TBI in the case group.

Main Outcomes and Measures

The single-session visit included the Neurobehavioral Symptom Inventory and measurements of oculomotor function, optical coherence tomography, contrast sensitivity, visual evoked potentials, visual field testing, and magnetic resonance imaging.

Results

A total of 28 participants (mean [SD] age, 35.0 [12.8] years; 15 male [53.6%]) with mild TBI and 28 controls (mean [SD] age, 35.8 [8.5] years; 19 female [67.9%]) were analyzed. Participants with mild TBI showed reduced prism convergence test breakpoint (-8.38; 95% CI, -14.14 to -2.62; P = .008) and recovery point (-8.44; 95% CI, -13.82 to -3.06; P = .004). Participants with mild TBI also had decreased contrast sensitivity (-0.07; 95% CI, -0.13 to -0.01; P = .04) and increased visual evoked potential binocular summation index (0.32; 95% CI, 0.02-0.63; P = .02). A subset of participants exhibited reduced peripapillary retinal nerve fiber layer thickness, increased optic nerve/sheath size, and brain cortical volumes. Machine learning identified subtle differences across the primary visual pathway, including the optic radiations and occipital lobe regions, independent of visual symptoms.

Conclusions and Relevance

Results of this case-control study suggest that the visual system was affected in individuals with mild TBI, even in those who did not self-report vision problems. These findings support the utility of a battery of assessments or machine-learning approaches to accurately diagnose this population.

Evaluating retinal thickness classification in children: A comparison between pediatric and adult optical coherence tomography databases

PURPOSE

This study investigates the agreement of children's retinal thickness classification by color category between Topcon 3D OCT-1's built-in adult reference data and our new pediatric database and assesses the correlation of retinal thickness with age and spherical equivalent (SE).

METHODS

160 eyes of 160 healthy children (74 boys, 86 girls) aged 6-18 years (mean: 11.60 ± 3.28 years) were evaluated in this cross-sectional study. The peripapillary retinal nerve fibre layer (pRNFL) and macular thickness were determined for the 1st, 5th, 95th, and 99th percentile points. Cohen's κ value and specific agreement between pediatric data and adult reference database were estimated. The correlation between retinal thickness with age and SE was also determined.

RESULTS

The mean thickness for the total RNFL, average macular, and central macula were 112.05±8.65 μm, 280.24±12.46 μm, and 220.55±17.53 μm, respectively. The overall agreement between the classification of the adult database and pediatric data for pRNFL was ≥90%, with discrepancies in 46 out of 150 eyes (30.67%); for macula, it was above 72%, with discrepancies in 93 out of 153 eyes (60.78%); and for ganglion cell complex and ganglion cell + inner plexiform layer (GCIPL) the agreement was above 84% and 85%, respectively. A significant level of agreement between pediatric data and adult reference data was achieved for temporal RNFL (κ = 0.65), macular perifoveal superior (κ = 0.67), and inferior (κ = 0.63) and inferior GCIPL (κ = 0.67). The correlations between age and retinal thickness were not significant (all p>0.05). Most retinal thickness parameters were positively associated with SE (Pearson's coefficient, r = 0.26 to 0.49, all p<0.05).

CONCLUSIONS

The overall agreement for pRNFL and macular thickness measurements in children with the adult reference database was between 72% and 90%. Children's retinal thickness was not significantly correlated with age but was positively associated with spherical equivalent.

Emerging clinical evidence of a dual role for Ang-2 and VEGF-A blockade with faricimab in retinal diseases

Anti-vascular endothelial growth factor (VEGF) therapies have transformed the treatment of retinal diseases. However, VEGF signaling is only one component of the complex, multifactorial pathophysiology of retinal diseases, and many patients have residual disease activity despite ongoing anti-VEGF treatment. The angiopoietin/tyrosine kinase with immunoglobulin and epidermal growth factor receptor-2 (Ang/Tie2) signaling pathway is critical to endothelial cell homeostasis, survival, integrity, and vascular stability. Ang-2 can interfere with Ang-1/Tie2 signaling and is increased in several retinal diseases. Lack of Tie2 signaling due to elevated Ang-2 levels drives vascular instability through pericyte dropout, neovascularization, vascular leakage, inflammation, and fibrosis. Although Ang-2 and VEGF can synergistically promote vascular instability and neovascularization, Ang-2 may also mediate vascular instability independently of VEGF. Faricimab is a bispecific antibody designed for intraocular use that inhibits two distinct pathways via Ang-2 and VEGF-A blockade. Clinical biomarkers of vascular instability are important for evaluating disease control and subsequent treatment decisions. These biomarkers include measurement/evaluation with optical coherence tomography (OCT) of intraretinal fluid, subretinal fluid, central subfield thickness, and pigment epithelial detachments (PEDs), and fluorescein angiography imaging of macular leakage and PEDs. Hyperreflective foci (HRF), thought to be representative of activated microglia, indicating an inflammatory microenvironment, and epiretinal membranes (ERMs), a marker for retinal fibrotic proliferation in diabetic macular edema (DME), are both also identified using OCT. Here we summarize data (secondary endpoint and prespecified exploratory analyses as well as post hoc analyses) from six Phase III trials suggest that dual therapy Ang-2/VEGF-A inhibition with faricimab (6 mg) has a greater effect on reducing/resolving biomarkers of vascular instability than aflibercept (2 mg), by both controlling neovascularization and vascular leakage (with resultant resolution of exudation associated with DME, neovascular age-related macular degeneration, and retinal vein occlusion), as well as by targeting inflammation (reduction of HRF in DME) and retinal fibrotic proliferation (reducing the risk of ERMs in eyes with DME). Modulation of both the Ang-2 and VEGF-A pathways with faricimab may therefore provide greater disease control than anti-VEGF monotherapy, potentially leading to extended treatment durability and improved long-term outcomes.

A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study

Objective

Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate the value of clinical and radiological features in preoperatively predicting visual outcomes after surgery.

Methods

Patients undergoing endoscopic transsphenoidal surgery (ETS) for pituitary adenoma were included in this retrospective and prospective study. Preoperative MRI, visual acuity, visual field, and postoperative visual recovery data were collected. Logistic regression analysis was used to assess the importance of clinical and MRI features, and a prediction model was developed.

Results

The cohort included 198 patients (150 retrospective, 48 prospective). In the retrospective data, visual recovery was observed in 111 patients (74.0%), while non-recovery was observed in 39 patients (26.0%). In the prospective data, visual recovery was observed in 27 patients (56.25%) and non-recovery in 21 patients (43.75%). Blindness, headache, adenoma area, and adenoma upward growth distance were negatively correlated with visual recovery (p < 0.05), while the pituitary gland area was positively correlated (p = 0.001). Logistic regression selected three clinical features: blindness, headache, and visual impairment course. Two additional imaging features, pituitary gland maximum area, and adenoma maximum area, were incorporated into the prediction model. The area under the curve of the prediction model was 0.944 in the retrospective cohort and 0.857 in the prospective cohort. Accuracy was 88% and 81.25%, respectively.

Conclusion

This study successfully developed a clinical practical model combining clinical and radiological features to preoperatively predict visual recovery for patients with pituitary adenoma. The model has the potential to provide personalized counseling for individual patients.

Bilateral occlusive retinal vasculitis secondary to intravitreal faricimab injection: a case report and review of literature

BACKGROUND

This article describes a rare occurrence of bilateral retinal occlusive vasculitis secondary to intravitreal faricimab injection.

CASE PRESENTATION

A 72-year-old female with age-related macular degeneration presented with bilateral retinal occlusive vasculitis following intravitreal faricimab injections. The patient was treated with 3 days of intravenous methylprednisolone followed by oral prednisolone taper and topical steroid therapy. Resolution of retinal occlusive vasculitis was observed 2 months post treatment.

CONCLUSIONS

Retinal occlusive vasculitis is a rare complication of intravitreal anti-vascular endothelial growth factor (anti-VEGF), particularly with faricimab injections. We also present a review of literature regarding retinal occlusive vasculitis following intravitreal anti-VEGF injections and propose further information regarding its pathophysiology.

Retinal morphology across the menstrual cycle: insights from the UK Biobank

Oestradiol and progesterone levels are higher in menstruating women than men of the same age, and their receptors are present in their neurosensory retina and retinal pigment epithelium. However, the impact of this hormonal environment on retinal physiology in women remains unclear. Using self-reported menstrual cycle phases as a surrogate for fluctuating hormonal levels, we investigated associations with retinovascular indices on colour fundus photograph and retinal thickness in optical coherence tomography across regularly menstruating women in the UK Biobank. We found no differences in retinal thickness across the cycle; however, vessel density, arteriolar and venular, and fractal dimension were higher in the luteal phase than follicular. The calibre of the central retinal vessels did not differ. This study suggests that the menstrual cycle phase might be associated with retinal microvasculature density in non-invasive imaging. It raises awareness for this understudied area, providing insights into neuroscience fields and epidemiological studies.

Frequency of Central Serous Chorioretinopathy in a Tertiary Care Center in Pakistan

BACKGROUND

Central serous chorioretinopathy (CSC) is a significant cause of vision loss in men aged 20 to 60, characterized by serous detachment of the neurosensory retina from the retinal pigment epithelium (RPE). This study aims to assess the frequency of CSC among patients at a tertiary care center in Pakistan, offering insights into its epidemiology and management within this setting.

METHODOLOGY

A retrospective observational study was conducted at the ophthalmology department of a tertiary care center from January 2019 to December 2023. Patients aged 20 years and above diagnosed with CSC based on clinical examination, fluorescein angiography (FA), and optical coherence tomography (OCT) were included. Data were collected from electronic medical records, encompassing demographic, clinical, and treatment information. Statistical analysis was performed using IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, NY, USA) with descriptive statistics summarizing demographic and clinical characteristics, and chi-square tests and t-tests examining associations between variables.

RESULTS

A total of 83 patients (112 eyes) were studied, with 83.13% being male and 16.87% female. Unilateral CSC was observed in 65.06% of cases, while 34.94% had bilateral involvement. The age group 25-40 years had the highest incidence (57.83%), with Unani medication (39.58%) and systemic hypertension (45.71%) being the most common contributing factors. The most frequent presenting symptom was vision impairment (48.19%).

CONCLUSION

CSC primarily affects middle-aged men, with observed associations to factors such as traditional Unani medication and systemic hypertension. This study highlights the importance of tailored treatment strategies and the need for further research into CSC's pathogenesis and management in Pakistan.

Predictive relevance of optical coherence tomography indices in conjunction with visual acuity and surgical outcomes of idiopathic macular hole

Idiopathic macular hole (IMH) is a condition that arises from a combination of interactions among several forces on the fovea, remarkably from vitreous traction in the anteroposterior and tangential directions. Recent studies have highlighted the significance of microincision vitrectomy surgery, and IMH surgery was performed with minimal invasiveness, and visual improvement was an expected outcome. This study aimed to observe the pre-operative optical coherence tomography (OCT) indices correlated with visual acuity in the closure of IMH after surgery. Primarily, the findings were associated with clinical characteristics, including OCT indices, change in best corrected visual acuity (BCVA), clinical factors associated with IMH closure, and prognostic factors for the visual outcomes. This retrospective study included pre- and post-operative BCVA and OCT indices of 110 eyes with IMH. Each OCT variable was subjected to stepwise regression analysis regarding therapeutic factors that predict the need for IMH closure. Our results revealed that the hole form factor (HFF, r = 0.196), macular hole index (MHI, r = 0.669), and tractional hole index (THI, r = 0.085) had a positive correlation with visual acuity. However, basal hole diameter (BHD, r = -0.696) and minimum hole diameter (MHD, r = -0.407) showed a negative correlation. Out of them, HFF, MHI, BHD, and MHD were observed to be statistically significant (p < 0.05). The mean follow-up time was 149 ± 63.22 (85-300) days. The mean baseline BCVA was 0.75 ± 0.44 logMAR (Logarithm of the Minimum Angle of Resolution) units, which was improved to 0.29 ± 0.27 logMAR units at the final follow-up. The surgical success closure rate was 100 % among subjects with IMH. In conclusion, OCT indices were significant indicators of visual success rates in IMH, and OCT measurement could be employed as a single key index in predicting the IMH closure rate. Also, our findings suggested that OCT indices could be utilized as a safe and effective predictor of visual and anatomical outcomes in the case of IMH.

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.

Aflibercept or ranibizumab for diabetic macular edema

Background

Vascular endothelial growth factor (VEGF) is the primary substance involved in retinal barrier breach. VEGF overexpression may cause diabetic macular edema (DME). Laser photocoagulation of the macula is the standard treatment for DME; however, recently, intravitreal anti-VEGF injections have surpassed laser treatment. Our aim was to evaluate the efficacy of intravitreal injections of aflibercept or ranibizumab for managing treatment-naive DME.

Methods

This single-center, retrospective, interventional, comparative study included eyes with visual impairment due to treatment-naive DME that underwent intravitreal injection of either aflibercept 2 mg/0.05 mL or ranibizumab 0.5 mg/0.05 mL at Al-Azhar University Hospitals, Egypt between March 2023 and January 2024. Demographic data and full ophthalmological examination results at baseline and 1, 3, and 6 months post-injection were collected, including the best-corrected distance visual acuity (BCDVA) in logarithm of the minimum angle of resolution (logMAR) notation, slit-lamp biomicroscopy, dilated fundoscopy, and central subfield thickness (CST) measured using spectral-domain optical coherence tomography.

Results

Overall, the 96 eyes of 96 patients with a median (interquartile range [IQR]) age of 57 (10) (range: 20-74) years and a male-to-female ratio of 1:2.7 were allocated to one of two groups with comparable age, sex, diabetes mellitus duration, and presence of other comorbidities (all P >0.05). There was no statistically significant difference in baseline diabetic retinopathy status or DME type between groups (both P >0.05). In both groups, the median (IQR) BCDVA significantly improved from 0.7 (0.8) logMAR at baseline to 0.4 (0.1) logMAR at 6 months post-injection (both P = 0.001), with no statistically significant difference between groups at all follow-up visits (all P >0.05). The median (IQR) CST significantly decreased in the aflibercept group from 347 (166) µm at baseline to 180 (233) µm at 6 months post-injection, and it decreased in the ranibizumab group from 360 (180) µm at baseline to 190 (224) µm at 6 months post-injection (both P = 0.001), with no statistically significant differences between groups at all follow-up visits (all P >0.05). No serious adverse effects were documented in either group.

Conclusions

Ranibizumab and aflibercept were equally effective in achieving the desired anatomical and functional results in patients with treatment-naïve DME in short-term follow-up without significant differences in injection counts between both drugs. Larger prospective, randomized, double-blinded trials with longer follow-up periods are needed to confirm our preliminary results.

Non-mechanical steering of the optical beam in spectral-domain optical coherence tomography

We demonstrate in a proof-of-concept experiment spectral-domain optical coherence tomography where steering of the optical beam that probes the sample in a transverse scan does not make use of any mechanical element. Steering is done with the help of a phase-only spatial light modulator, that introduces a spatially-dependent phase between the two orthogonal polarization components of an optical beam, and some optical elements that control the polarization of light. We demonstrate that making use of the non-mechanical beam steering system considered here, we can reproduce the main traits of imaging with standard OCT that makes use of mechanical-assisted optical beam steering.

Optical Coherence Tomography in Inherited Macular Dystrophies: A Review

Macular dystrophies (MDs) constitute a collection of hereditary retina disorders leading to notable visual impairment, primarily due to progressive macular atrophy. These conditions are distinguished by bilateral and relatively symmetrical abnormalities in the macula that significantly impair central visual function. Recent strides in fundus imaging, especially optical coherence tomography (OCT), have enhanced our comprehension and diagnostic capabilities for MD. OCT enables the identification of neurosensory retinal disorganization patterns and the extent of damage to retinal pigment epithelium (RPE) and photoreceptor cells in the dystrophies before visible macular pathology appears on fundus examinations. It not only helps us in diagnostic retinal and choroidal pathologies but also guides us in monitoring the progression of, staging of, and response to treatment. In this review, we summarize the key findings on OCT in some of the most common MD.

Genetic susceptibility to schizophrenia through neuroinflammatory pathways is associated with retinal thinning: Findings from the UK-Biobank

The human retina is part of the central nervous system and can be easily and non-invasively imaged with optical coherence tomography. While imaging the retina may provide insights on central nervous system-related disorders such as schizophrenia, a typical challenge are confounders often present in schizophrenia which may negatively impact retinal health. Here, we therefore aimed to investigate retinal changes in the context of common genetic variations conveying a risk of schizophrenia as measured by polygenic risk scores. We used population data from the UK Biobank, including White British and Irish individuals without diagnosed schizophrenia, and estimated a polygenic risk score for schizophrenia based on the newest genome-wide association study (PGC release 2022). We hypothesized that greater genetic susceptibility to schizophrenia is associated with retinal thinning, especially within the macula. To gain additional mechanistic insights, we conducted pathway-specific polygenic risk score associations analyses, focusing on gene pathways that are related to schizophrenia. Of 65484 individuals recruited, 48208 participants with available matching imaging-genetic data were included in the analysis of whom 22427 (53.48%) were female and 25781 (46.52%) were male. Our robust principal component regression results showed that polygenic risk scores for schizophrenia were associated with retinal thinning while controlling for confounding factors (b = -0.03, p = 0.007, pFWER = 0.01). Similarly, we found that polygenic risk for schizophrenia specific to neuroinflammation gene sets revealed significant associations with retinal thinning (b = -0.03, self-contained p = 0.041 (reflecting the level of association), competitive p = 0.05 (reflecting the level of enrichment)). These results go beyond previous studies suggesting a relationship between manifested schizophrenia and retinal phenotypes. They indicate that the retina is a mirror reflecting the genetic complexities of schizophrenia and that alterations observed in the retina of individuals with schizophrenia may be connected to an inherent genetic predisposition to neurodegenerative aspects of the condition. These associations also suggest the potential involvement of the neuroinflammatory pathway, with indications of genetic overlap with specific retinal phenotypes. The findings further indicate that this gene pathway in individuals with a high polygenic risk for schizophrenia could contribute through acute-phase proteins to structural changes in the retina.

Assessment of area and structural irregularity of retinal layers in diabetic retinopathy using machine learning and image processing techniques

Diabetes retinopathy prevention necessitates early detection, monitoring, and treatment. Non-invasive optical coherence tomography (OCT) shows structural changes in the retinal layer. OCT image evaluation necessitates retinal layer segmentation. The ability of our automated retinal layer segmentation to distinguish between normal, non-proliferative (NPDR), and proliferative diabetic retinopathy (PDR) was investigated in this study using quantifiable biomarkers such as retina layer smoothness index (SI) and area (S) in horizontal and vertical OCT images for each zone (fovea, superior, inferior, nasal, and temporal). This research includes 84 eyes from 57 individuals. The study shows a significant difference in the Area (S) of inner nuclear layer (INL) and outer nuclear layer (ONL) in the horizontal foveal zone across the three groups (p < 0.001). In the horizontal scan, there is a significant difference in the smoothness index (SI) of the inner plexiform layer (IPL) and the upper border of the outer plexiform layer (OPL) among three groups (p < 0.05). There is also a significant difference in the area (S) of the OPL in the foveal zone among the three groups (p = 0.003). The area (S) of the INL in the foveal region of horizontal slabs performed best for distinguishing diabetic patients (NPDR and PDR) from normal individuals, with an accuracy of 87.6%. The smoothness index (SI) of IPL in the nasal zone of horizontal foveal slabs was the most accurate at 97.2% in distinguishing PDR from NPDR. The smoothness index of the top border of the OPL in the nasal zone of horizontal slabs was 84.1% accurate in distinguishing NPDR from PDR. Smoothness index of IPL in the temporal zone of horizontal slabs was 89.8% accurate in identifying NPDR from PDR patients. In conclusion, optical coherence tomography can assess the smoothness index and irregularity of the inner and outer plexiform layers, particularly in the nasal and temporal regions of horizontal foveal slabs, to distinguish non-proliferative from proliferative diabetic retinopathy. The evolution of diabetic retinopathy throughout severity levels and its effects on retinal layer irregularity need more study.

A novel lipophenol quercetin derivative to prevent macular degeneration: Intravenous and oral formulations for preclinical pharmacological evaluation

Drugs with properties against oxidative and carbonyl stresses are potential candidates to prevent dry age-related macular degeneration (Dry-AMD) and inherited Stargardt disease (STGD1). Previous studies have demonstrated the capacity of a new lipophenol drug: 3-O-DHA-7-O-isopropyl-quercetin (Q-IP-DHA) to protect ARPE19 and primary rat RPE cells respectively from A2E toxicity and under oxidative and carbonyl stress conditions. In this study, first, a new methodology has been developed to access gram scale of Q-IP-DHA. After classification of the lipophenol as BCS Class IV according to physico-chemical and biopharmaceutical properties, an intravenous formulation with micelles (M) and an oral formulation using lipid nanocapsules (LNC) were developed. M were formed with Kolliphor® HS 15 and saline solution 0.9 % (mean size of 16 nm, drug loading of 95 %). The oral formulation was optimized and successfully allowed the formation of LNC (25 nm, 96 %). The evaluation of the therapeutic potency of Q-IP-DHA was performed after IV administration of micelles loaded with Q-IP-DHA (M-Q-IP-DHA) at 30 mg/kg and after oral administration of LNC loaded with Q-IP-DHA (LNC-Q-IP-DHA) at 100 mg/kg in mice. Results demonstrated photoreceptor protection after induction of retinal degeneration by acute light stress making Q-IP-DHA a promising preventive candidate against dry-AMD and STGD1.

Retinal changes after fluocinolone acetonide implant (ILUVIEN®) for DME: SD-OCT imaging assessment using ESASO classification

INTRODUCTION

A detailed understanding of the anatomical and structural changes occurring in the retina following intravitreal fluocinolone acetonide implantation may help improve the management and prognosis of persistent or recurrent diabetic macular edema (DME).

METHODS

Overall, 45 eyes (from 35 patients) with refractory center-involved DME received an intravitreal fluocinolone acetonide implant. They were monitored at baseline and at 6, 12, 24, and 36 months for best-corrected visual acuity (BCVA), central foveal thickness (CFT), and the seven retinal parameters used in the classification of diabetic maculopathy recently developed at the European School for Advanced Studies in Ophthalmology (ESASO).

RESULTS

Within 6 months of implantation, significant improvements were evident in BCVA, CFT, maculopathy stage, and the percentage of eyes with: intraretinal cysts; CFT > 30% above the upper normal value; and disrupted or absent ellipsoid zone (EZ) and/or external limiting membrane (ELM). Significant improvements were still maintained at 36 months post-implantation. At month 36, early treatment with the implant (i.e., after < 6 previous intravitreal injections for DME) trended toward being more effective than later treatment in improving BCVA, CFT, maculopathy stage, and the percentage of eyes with CFT > 30% above the upper normal value. However, statistical significance was not achieved.

CONCLUSION

In persistent or recurrent DME, fluocinolone acetonide implantation can be effective in improving maculopathy stage and reducing the percentage of eyes with: intraretinal cysts; CFT > 30% above the upper normal value; and disrupted or absent EZ and/or ELM. It can also increase BCVA and reduce CFT.

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.

Macular Edema Following Silicone Oil Tamponade for Retinal Detachment: A Literature Review

Macular edema (ME) is a major cause of reduced vision following intraocular surgery. Although the pathophysiology of ME is not completely understood, inflammatory mediators play a key role. The incidence of ME following pars plana vitrectomy with silicone oil tamponade varies between 13% and 27%. ME usually resolves spontaneously following silicone oil removal, but treatment may be required for resistant cases. In this review, the mechanisms of ME formation after pars plana vitrectomy, its incidence, and its possible therapeutic approaches are discussed.

Correlation between refractive errors and ocular biometric parameters in children and adolescents: a systematic review and meta-analysis

BACKGROUND

Refractive errors are one of the most common ocular conditions among children and adolescents, with myopia showing an increasing prevalence and early onset in this population. Recent studies have identified a correlation between refractive errors and ocular biometric parameters.

METHODS

A systematic search was conducted in electronic databases including PubMed, EMBASE, Cochrane Library, Web of Science, and Medline from January 1, 2012, to May 1, 2023. Various ocular biometric parameters were summarized under different refractive states, including axial length (AL), central corneal thickness (CCT), anterior chamber depth (ACD), lens thickness (LT), corneal curvature (CC), Corneal curvature radius (CR),axial length-to-corneal radius ratio (AL/CR ratio), choroidal thickness (ChT), retinal thickness (RT), retinal nerve fiber layer thickness (RNFL), and retinal blood density (VD). The differences in these parameters among different refractive states were analyzed using Stata software with fixed or random-effects models, taking into account the assessed heterogeneity level.

RESULTS

This meta-analysis included a total of 69 studies involving 128,178 eyes, including 48,795 emmetropic eyes, 60,691 myopic eyes, 13,983 hyperopic eyes, 2,040 low myopic eyes, 1,201 moderate myopic eyes, and 1,468 high myopic eyes. The results of our study demonstrated that, compared to the control group (emmetropic group), the myopic group and low, moderate, and high myopic groups showed significant increases in AL, AL/CR ratio, and ACD, while the hyperopic group exhibited significant decreases. Compared to the control group, the myopic group had a significantly increase for CC, while CR, CCT, perifoveal RT, subfoveal ChT, foveal ChT, parafoveal ChT, perifoveal (except nasal) ChT, and pRNFL (except temporal) significantly decreased. Compared to the control group, the hyperopic group had a significantly increase for subfoveal ChT, foveal ChT, parafoveal ChT, perifoveal ChT, and nasal pRNFL. Compared to the control group, the low and moderate myopic groups had a significantly decreases for the CCT, parafoveal RT (except nasal), perifoveal RT (except nasal), and pRNFL (except superior and temporal). Compared to the control group, the high myopic group had a significantly increase for CR, while LT, perifoveal ChT (except nasal), parafoveal RT, perifoveal RT, and pRNFL (except temporal) had significant decreased.

CONCLUSION

The changes of ocular biometric parameters in children and adolescents are closely related to refractive errors. Ocular biometric parameters devices, as effective non-invasive techniques, provide objective biological markers for monitoring refractive errors such as myopia.

Optical coherence tomography angiography in diabetic retinopathy

There remain many unanswered questions on how to assess and treat the pathology and complications that arise from diabetic retinopathy (DR). Optical coherence tomography angiography (OCTA) is a novel and non-invasive three-dimensional imaging method that can visualize capillaries in all retinal layers. Numerous studies have confirmed that OCTA can identify early evidence of microvascular changes and provide quantitative assessment of the extent of diseases such as DR and its complications. A number of informative OCTA metrics could be used to assess DR in clinical trials, including measurements of the foveal avascular zone (FAZ; area, acircularity, 3D para-FAZ vessel density), vessel density, extrafoveal avascular zones, and neovascularization. Assessing patients with DR using a full-retinal slab OCTA image can limit segmentation errors and confounding factors such as those related to center-involved diabetic macular edema. Given emerging data suggesting the importance of the peripheral retinal vasculature in assessing and predicting DR progression, wide-field OCTA imaging should also be used. Finally, the use of automated methods and algorithms for OCTA image analysis, such as those that can distinguish between areas of true and false signals, reconstruct images, and produce quantitative metrics, such as FAZ area, will greatly improve the efficiency and standardization of results between studies. Most importantly, clinical trial protocols should account for the relatively high frequency of poor-quality data related to sub-optimal imaging conditions in DR and should incorporate time for assessing OCTA image quality and re-imaging patients where necessary.

Imaging Histology Correlations of Intraretinal Fluid in Neovascular Age-Related Macular Degeneration

Purpose

Fluid presence and dynamism is central to the diagnosis and management of neovascular age-related macular degeneration. On optical coherence tomography (OCT), some hyporeflective spaces arise through vascular permeability (exudation) and others arise through degeneration (transudation). Herein we determined whether the histological appearance of fluid manifested this heterogeneity.

Methods

Two eyes of a White woman in her 90s with anti-vascular endothelial growth factor treated bilateral type 3 neovascularization secondary to age-related macular degeneration were osmicated, prepared for submicrometer epoxy resin sections, and correlated to eye-tracked spectral domain OCT. Examples of intraretinal tissue fluid were sought among similarly prepared donor eyes with fibrovascular scars, in a web-based age-related macular degeneration histopathology resource. Fluid stain intensity was quantified in reference to Bruch's membrane and the empty glass slide.

Results

Exudative fluid by OCT was slightly reflective and dynamically responded to anti-vascular endothelial growth factor. On histology, this fluid stained moderately, possessed a smooth and homogenous texture, and contained blood cells and fibrin. Nonexudative fluid in degenerative cysts and in outer retinal tubulation was minimally reflective on OCT and did not respond to anti-vascular endothelial growth factor. By histology, this fluid stained lightly, possessed a finely granular texture, and contained mainly tissue debris. Quantification supported the qualitative impressions of fluid stain density. Cells containing retinal pigment epithelium organelles localized to both fluid types.

Conclusions

High-resolution histology of osmicated tissue can distinguish between exudative and nonexudative fluid, some of which is transudative.

Translational Relevance

OCT and histological features of different fluid types can inform clinical decision-making and assist in the interpretation of newly available automated fluid detection algorithms.

Advancing Diabetic Retinopathy Diagnosis: Leveraging Optical Coherence Tomography Imaging with Convolutional Neural Networks

Diabetic retinopathy (DR) is a vision-threatening complication of diabetes, necessitating early and accurate diagnosis. The combination of optical coherence tomography (OCT) imaging with convolutional neural networks (CNNs) has emerged as a promising approach for enhancing DR diagnosis. OCT provides detailed retinal morphology information, while CNNs analyze OCT images for automated detection and classification of DR. This paper reviews the current research on OCT imaging and CNNs for DR diagnosis, discussing their technical aspects and suitability. It explores CNN applications in detecting lesions, segmenting microaneurysms, and assessing disease severity, showing high sensitivity and accuracy. CNN models outperform traditional methods and rival expert ophthalmologists' results. However, challenges such as dataset availability and model interpretability remain. Future directions include multimodal imaging integration and real-time, point-of-care CNN systems for DR screening. The integration of OCT imaging with CNNs has transformative potential in DR diagnosis, facilitating early intervention, personalized treatments, and improved patient outcomes. Abbreviations: DR = Diabetic Retinopathy, OCT = Optical Coherence Tomography, CNN = Convolutional Neural Network, CMV = Cytomegalovirus, PDR = Proliferative Diabetic Retinopathy, AMD = Age-Related Macular Degeneration, VEGF = vascular endothelial growth factor, RAP = Retinal Angiomatous Proliferation, OCTA = OCT Angiography, AI = Artificial Intelligence.

Electrochemical nano-biosensor based on electrospun indium zinc oxide nanofibers for the determination of complement component 3 protein

Age-related macular degeneration (AMD) is a progressive chronic neurodegenerative retinal disease leading to vision loss, irreversible blindness, and visual impairment in older adults worldwide. Complement component 3 (C3) protein has been identified as the most predominant biomarker towards early diagnosis of AMD; therefore, there is an utmost requirement for non-invasive detection of C3 protein in the tear fluids of AMD patients. Considering this, we report an insightful electrochemical sensor capable of detecting clinically relevant concentrations ranging from 10 fg/mL to 1 μg/mL using electrospun indium-doped zinc oxide (InZnO) nanofibers as the transducing layer. The InZnO nanofibers have facilitated high anti-C3 antibody loading of 3.42 × 10^-9 mol/cm² and enhanced the overall charge transport mechanism at the sensor interface. The biofunctionalization process of the biosensor was investigated thoroughly using X-ray photoelectron spectroscopy (XPS) as well as different electrochemical techniques. The target C3 proteins were captured on the fabricated biosensor surface and determined through changes in charge transfer resistance (R_CT) while executing electrochemical impedance spectroscopy (EIS) and peak current (I_p) in the case of cyclic voltammetry (CV) and differential pulse voltammetry (DPV), respectively. The InZnO nanofiber-based nano-biosensor demonstrated a very low limit of detections (LODs) of 5.214 fg/mL and 0.241 fg/mL with an excellent sensitivity of 4.6709 (ΔR/R) (g/mL)^-1 cm^-2 and 54.4939 (ΔI_p/I_p)% (g/mL)^-1 cm^-2 for EIS and DPV techniques, respectively. By virtue of high antibody loading, ultrasensitive and ultra-selective capability, the indium-doped ZnO nanofibers show huge potential to be used as a high-performance diagnostic platform for AMD diagnosis.

Optical Coherence Tomography: Focus on the Pathology of Macula in Scleritis Patients

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.

Deep Learning Classification of Drusen, Choroidal Neovascularization, and Diabetic Macular Edema in Optical Coherence Tomography (OCT) Images

Background Age-related macular degeneration (AMD), diabetic retinopathy (DR), drusen, choroidal neovascularization (CNV), and diabetic macular edema (DME) are significant causes of visual impairment globally. Optical coherence tomography (OCT) imaging has emerged as a valuable diagnostic tool for these ocular conditions. However, subjective interpretation and inter-observer variability highlight the need for standardized diagnostic approaches. Methods This study aimed to develop a robust deep learning model using artificial intelligence (AI) techniques for the automated detection of drusen, CNV, and DME in OCT images. A diverse dataset of 1,528 OCT images from Kaggle.com was used for model training. The performance metrics, including precision, recall, sensitivity, specificity, F1 score, and overall accuracy, were assessed to evaluate the model's effectiveness. Results The developed model achieved high precision (0.99), recall (0.962), sensitivity (0.985), specificity (0.987), F1 score (0.971), and overall accuracy (0.987) in classifying diseased and healthy OCT images. These results demonstrate the efficacy and efficiency of the model in distinguishing between retinal pathologies. Conclusion The study concludes that the developed deep learning model using AI techniques is highly effective in the automated detection of drusen, CNV, and DME in OCT images. Further validation studies and research efforts are necessary to evaluate the generalizability and integration of the model into clinical practice. Collaboration between clinicians, policymakers, and researchers is essential for advancing diagnostic tools and management strategies for AMD and DR. Integrating this technology into clinical workflows can positively impact patient care, particularly in settings with limited access to ophthalmologists. Future research should focus on collecting independent datasets, addressing potential biases, and assessing real-world effectiveness. Overall, the use of machine learning algorithms in conjunction with OCT imaging holds great potential for improving the detection and management of drusen, CNV, and DME, leading to enhanced patient outcomes and vision preservation.

Influence of mydriasis on foveal duplication artifact

In this case report, we describe a rare imaging finding of foveal duplication identified on spectral domain optical coherence tomography (OCT) through undilated pupils in a 49-year-old asymptomatic anxious lady with type 2 diabetes mellitus who visited the retina clinic for diabetic retinopathy screening. A simple patient counseling for cooperation during a repeat OCT scan with dilated pupils revealed that the twin fovea-like duplication was an illusion. This case illustrates the necessity of pupillary dilation and reimaging in the presence of unusual artifacts, such as foveal duplication, to prevent clinicians from ordering unnecessary additional tests.

PseudoSegRT: efficient pseudo-labelling for intraoperative OCT segmentation

PURPOSE

Robotic ophthalmic microsurgery has significant potential to help improve the success of challenging procedures and overcome the physical limitations of the surgeon. Intraoperative optical coherence tomography (iOCT) has been reported for the visualisation of ophthalmic surgical manoeuvres, where deep learning methods can be used for real-time tissue segmentation and surgical tool tracking. However, many of these methods rely heavily on labelled datasets, where producing annotated segmentation datasets is a time-consuming and tedious task.

METHODS

To address this challenge, we propose a robust and efficient semi-supervised method for boundary segmentation in retinal OCT to guide a robotic surgical system. The proposed method uses U-Net as the base model and implements a pseudo-labelling strategy which combines the labelled data with unlabelled OCT scans during training. After training, the model is optimised and accelerated with the use of TensorRT.

RESULTS

Compared with fully supervised learning, the pseudo-labelling method can improve the generalisability of the model and show better performance for unseen data from a different distribution using only 2% of labelled training samples. The accelerated GPU inference takes less than 1 millisecond per frame with FP16 precision.

CONCLUSION

Our approach demonstrates the potential of using pseudo-labelling strategies in real-time OCT segmentation tasks to guide robotic systems. Furthermore, the accelerated GPU inference of our network is highly promising for segmenting OCT images and guiding the position of a surgical tool (e.g. needle) for sub-retinal injections.

On Machine Learning in Clinical Interpretation of Retinal Diseases Using OCT Images

Optical coherence tomography (OCT) is a noninvasive imaging technique that provides high-resolution cross-sectional retina images, enabling ophthalmologists to gather crucial information for diagnosing various retinal diseases. Despite its benefits, manual analysis of OCT images is time-consuming and heavily dependent on the personal experience of the analyst. This paper focuses on using machine learning to analyse OCT images in the clinical interpretation of retinal diseases. The complexity of understanding the biomarkers present in OCT images has been a challenge for many researchers, particularly those from nonclinical disciplines. This paper aims to provide an overview of the current state-of-the-art OCT image processing techniques, including image denoising and layer segmentation. It also highlights the potential of machine learning algorithms to automate the analysis of OCT images, reducing time consumption and improving diagnostic accuracy. Using machine learning in OCT image analysis can mitigate the limitations of manual analysis methods and provide a more reliable and objective approach to diagnosing retinal diseases. This paper will be of interest to ophthalmologists, researchers, and data scientists working in the field of retinal disease diagnosis and machine learning. By presenting the latest advancements in OCT image analysis using machine learning, this paper will contribute to the ongoing efforts to improve the diagnostic accuracy of retinal diseases.

Ocular and inflammatory markers associated with Gulf War illness symptoms

To examine the utility of ocular coherence tomography (OCT) metrics, in conjunction with systemic markers of inflammation, in identifying individuals with Gulf War Illness (GWI) symptoms. Prospective case-control study of 108 Gulf War Era veterans, split into 2 groups based on the presence of GWI symptoms, defined by the Kansas criteria. Information on demographics, deployment history, and co-morbidities were captured. 101 individuals underwent OCT imaging and 105 individuals provided a blood sample which was analyzed for inflammatory cytokines using an enzyme-linked immunosorbent assay-based chemiluminescent assay. The main outcome measure was predictors of GWI symptoms, examined with multivariable forward stepwise logistic regression analysis followed by receiver operating characteristic (ROC) analysis. The mean age of the population was 55 ± 4, 90.7% self-identified as male, 53.3% as White, and 54.3% as Hispanic. A multivariable model that considered demographics and co-morbidities found that a lower inferior temporal ganglion cell layer-inner plexiform layer (GCL‒IPL) thickness, higher temporal nerve fiber layer (NFL) thickness, lower interleukin (IL)-1β levels, higher IL-1α levels, and lower tumor necrosis factor-receptor I levels correlated with GWI symptoms. ROC analysis demonstrated an area under the curve of 0.78 with the best cut-off value for the prediction model having a sensitivity of 83% and specificity of 58%. RNFL and GCL‒IPL measures, namely increased temporal thickness and decreased inferior temporal thickness, respectively, in conjunction with a number of inflammatory cytokines, had a reasonable sensitivity for the diagnosis of GWI symptoms in our population.

Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns

Age-related macular degeneration is a visual disorder caused by abnormalities in a part of the eye's retina and is a leading source of blindness. The correct detection, precise location, classification, and diagnosis of choroidal neovascularization (CNV) may be challenging if the lesion is small or if Optical Coherence Tomography (OCT) images are degraded by projection and motion. This paper aims to develop an automated quantification and classification system for CNV in neovascular age-related macular degeneration using OCT angiography images. OCT angiography is a non-invasive imaging tool that visualizes retinal and choroidal physiological and pathological vascularization. The presented system is based on new retinal layers in the OCT image-specific macular diseases feature extractor, including Multi-Size Kernels ξcho-Weighted Median Patterns (MSKξMP). Computer simulations show that the proposed method: (i) outperforms current state-of-the-art methods, including deep learning techniques; and (ii) achieves an overall accuracy of 99% using ten-fold cross-validation on the Duke University dataset and over 96% on the noisy Noor Eye Hospital dataset. In addition, MSKξMP performs well in binary eye disease classifications and is more accurate than recent works in image texture descriptors.

A vision transformer architecture for the automated segmentation of retinal lesions in spectral domain optical coherence tomography images

Neovascular age-related macular degeneration (nAMD) is one of the major causes of irreversible blindness and is characterized by accumulations of different lesions inside the retina. AMD biomarkers enable experts to grade the AMD and could be used for therapy prognosis and individualized treatment decisions. In particular, intra-retinal fluid (IRF), sub-retinal fluid (SRF), and pigment epithelium detachment (PED) are prominent biomarkers for grading neovascular AMD. Spectral-domain optical coherence tomography (SD-OCT) revolutionized nAMD early diagnosis by providing cross-sectional images of the retina. Automatic segmentation and quantification of IRF, SRF, and PED in SD-OCT images can be extremely useful for clinical decision-making. Despite the excellent performance of convolutional neural network (CNN)-based methods, the task still presents some challenges due to relevant variations in the location, size, shape, and texture of the lesions. This work adopts a transformer-based method to automatically segment retinal lesion from SD-OCT images and qualitatively and quantitatively evaluate its performance against CNN-based methods. The method combines the efficient long-range feature extraction and aggregation capabilities of Vision Transformers with data-efficient training of CNNs. The proposed method was tested on a private dataset containing 3842 2-dimensional SD-OCT retina images, manually labeled by experts of the Franziskus Eye-Center, Muenster. While one of the competitors presents a better performance in terms of Dice score, the proposed method is significantly less computationally expensive. Thus, future research will focus on the proposed network's architecture to increase its segmentation performance while maintaining its computational efficiency.

Effect of shape deprivation on retinal thickness in myopic mice using an OCT method

Purpose

The purpose of this study was to study in retina thickness changes in myopic mice using optical coherence tomography (OCT).

Methods

There were 18 mice in the form-deprivation myopia (FDM) group，in which the left eye was not treated as a control;18 untreated mice served as a normal control group. The diopter of all mice was measured 21 days after birth (P21), before form deprivation. After 4 weeks of form deprivation (P49), the refraction, fundus, and retinal sublayer thickness of all mice were measured.

Results

After 4 weeks of form deprivation, the refractive power of the right eye in the FDM group was significantly higher than that in the left eye (p < 0.05). There was no significant change in the refractive power of the left eye in the FDM group compared with the normal control group. The retina, nerve fiber layer (NFL), inner nuclear layer (INL), and outer nuclear layer (ONL) in the right eye of the FDM group were significantly thinner than those of both the FDM and control groups (p < 0.05). There was no significant change in photoreceptor (PR).

Conclusion

Our study highlights that the myopic mice have decreased R thickness, which might reflect the potential pathological mechanism of myopia.

Evaluating the utility of deep learning for predicting therapeutic response in diabetic eye disease

Purpose

Deep learning (DL) is a technique explored within ophthalmology that requires large datasets to distinguish feature representations with high diagnostic performance. There is a need for developing DL approaches to predict therapeutic response, but completed clinical trial datasets are limited in size. Predicting treatment response is more complex than disease diagnosis, where hallmarks of treatment response are subtle. This study seeks to understand the utility of DL for clinical problems in ophthalmology such as predicting treatment response and where large sample sizes for model training are not available.

Materials and Methods

Four DL architectures were trained using cross-validated transfer learning to classify ultra-widefield angiograms (UWFA) and fluid-compartmentalized optical coherence tomography (OCT) images from a completed clinical trial (PERMEATE) dataset (n=29) as tolerating or requiring extended interval Anti-VEGF dosing. UWFA images (n=217) from the Anti-VEGF study were divided into five increasingly larger subsets to evaluate the influence of dataset size on performance. Class activation maps (CAMs) were generated to identify regions of model attention.

Results

The best performing DL model had a mean AUC of 0.507 ± 0.042 on UWFA images, and highest observed AUC of 0.503 for fluid-compartmentalized OCT images. DL had a best performing AUC of 0.634 when dataset size was incrementally increased. Resulting CAMs show inconsistent regions of interest.

Conclusions

This study demonstrated the limitations of DL for predicting therapeutic response when large datasets were not available for model training. Our findings suggest the need for hand-crafted approaches for complex and data scarce prediction problems in ophthalmology.

Predictive value of macular ganglion cell-inner plexiform layer thickness in visual field defect of pituitary adenoma patients: a case-control study

OBJECTIVE

The present study explored the association between preoperative macular ganglion cell-inner plexiform layer thickness (GCIPL) and retinal nerve fiber layer thickness (RNFL) measured by optical coherence tomography (OCT) and the recovery of visual field (VF) defect after surgery in pituitary adenoma patients.

METHODS

This case-control study included patients with pituitary adenoma in the Neurosurgery Department of Shanxi Provincial People's Hospital between October 2019 and June 2021. Cranial MRI examination, three-dimensional OCT, and VF testing (Humphrey Field Analyzer II750) were performed before and at 6months after the surgery.

RESULTS

Fifty-three pituitary adenoma patients (81 eyes) were enrolled; 15 patients (23 eyes) were in the visual field did not recover group (VFNR), and 38 patients (58 eyes) were in the visual field recovered group (VFR). The temporal RNFL (P = 0.002) and average RNFL (P = 0.009) in the VFNR group were significantly lower than in the VFR group. The superior nasal GCIPL (P = 0.001), inferior nasal GCIPL (P = 0.001) and average GCIPL (P = 0.01) were significantly lower in the VFNR group than in the VFR group (all P < 0.01).The multivariable logistic regression analysis showed that nasal inferior GCIPL was an independent risk factor for VF recovery (odds ratio (OR) = 1.376,95% confidence interval (CI):1.089-1.739,P = 0.007). In the received operating characteristics (ROC) analysis, the area under the ROC curve (AUROCs) was the highest for nasal inferior GCIPL (AUROC = 0.739).

CONCLUSIONS

In patients who underwent resection of pituitary adenoma, nasal inferior GCIPL was an independent risk factor of visual field defect recover after surgery.

Prognostic Factor Study of Macular Edema Recurrence in Retinal Vein Occlusion after Conbercept Treatment: A Post Hoc Analysis of the FALCON Study

Objective

The study was aimed at exploring the potential predictive factors associated with the recurrence of macular edema (ME) secondary to vein occlusion (RVO) after intravitreal antivascular endothelial growth factor (VEGF) loading treatment in the FALCON study.

Methods

This is a post hoc analysis of 30 patients with central RVO and 30 patients with branch RVO. All patients received a monthly administration of intravitreal conbercept during the 3-month loading phase and pro re nata (PRN) treatment during the 6-month follow-up period. Based on the recurrence of ME at the first follow-up visit, patients were classified into the recurrence group or nonrecurrence group. The primary endpoint was to explore the risk factors for recurrence among baseline characteristics, fluorescein angiography (FA) patterns, and optical coherence tomography (OCT).

Results

In general, 38 patients (64.4%) experienced ME recurrence at the first follow-up visit (3 months), regardless of disease type (p = 0.32). Significant improvements in VA were noted in both the nonrecurrence and recurrence groups (p < 0.001), however, without significant between-group differences (p = 0.1). A significant reduction in CRT in both groups (p < 0.001) was identified, and patients without recurrence showed a greater reduction in CRT compared with those with recurrence (p < 0.001). In addition, logistic regression analyses indicated the corrections of ME recurrence with baseline macular volume and the disruption of the outer limiting membrane at the fovea.

Conclusion

This study suggested that OCT parameters, including baseline macular volume and outer limiting membrane disruption, and reduction in CRT after loading therapy were more predictive of ME recurrence than FA patterns or visual changes following conbercept loading therapy.

Universal photonics tomography

3D imaging is essential for the study and analysis of a wide variety of structures in numerous applications. Coherent photonic systems such as optical coherence tomography (OCT) and light detection and ranging (LiDAR) are state-of-the-art approaches, and their current implementation can operate in regimes that range from under a few millimeters to over more than a kilometer. We introduce a general method, which we call universal photonics tomography (UPT), for analyzing coherent tomography systems, in which conventional methods such as OCT and LiDAR may be viewed as special cases. We demonstrate a novel approach (to our knowledge) based on the use of phase modulation combined with multirate signal processing to collect positional information of objects beyond the Nyquist limits.

Robust Fovea Detection in Retinal OCT Imaging using Deep Learning

The fovea centralis is an essential landmark in the retina where the photoreceptor layer is entirely composed of cones responsible for sharp, central vision. The localization of this anatomical landmark in optical coherence tomography (OCT) volumes is important for assessing visual function correlates and treatment guidance in macular disease. In this study, the "PRE U-net" is introduced as a novel approach for a fully automated fovea centralis detection, addressing the localization as a pixel-wise regression task. 2D B-scans are sampled from each image volume and are concatenated with spatial location information to train the deep network. A total of 5586 OCT volumes from 1,541 eyes was used to train, validate and test the deep learning method. The test data is comprised of healthy subjects and patients affected by neovascular age-related macular degeneration (nAMD), diabetic macula edema (DME) and macular edema from retinal vein occlusion (RVO), covering the three major retinal diseases responsible for blindness. Our experiments demonstrate that the PRE U-net significantly outperforms state-of-the-art methods and improves the robustness of automated localization, which is of value for clinical practice.

Diabetic Retinopathy: An Overview of Treatments

Diabetic retinopathy (DR), substantially impacts the quality of life of diabetic patients, it remains, in developed countries, the leading cause of vision loss in working-age adults (20-65 years). Currently, about 90 million diabetics suffer from DR. DR is a silent complication that in its early stages is asymptomatic. However, over time, chronic hyperglycemia can lead to sensitive retinal damage, leading to fluid accumulation and retinal haemorrhage (HM), resulting in cloudy or blurred vision. It can, therefore, lead to severe visual impairment or even blindness if left untreated. It can be classified into nonproliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). NPDR is featured with intraretinal microvasculature changes and can be further divided into mild, moderate, and severe stages that may associate with diabetic macular oedema (DME). PDR involves the formation and growth of new blood vessels (retinal neovascularisation) under low oxygen conditions. Early identification and treatment are key priorities for reducing the morbidity of diabetic eye disease. In the early stages of DR, a tight control of glycemia, blood pressure, plasma lipids, and regular monitoring can help prevent its progression to more advanced stages. In advanced stages, the main treatments of DR include intraocular injections of anti-vascular endothelial growth factor (VEGF) antibodies, laser treatments, and vitrectomy. The aim of this review is to provide a comprehensive overview of the published literature pertaining to the latest progress in the treatment of DR.

Macular Thickness and Microvasculature Loss in Glaucoma Suspect Eyes

PURPOSE

To characterize the change of ganglion cell complex (GCC) thickness and macular vessel density in glaucoma suspect eyes with ocular hypertension (OHT) or glaucomatous optic neuropathy (GON).

DESIGN

Prospective, longitudinal study.

PARTICIPANTS

Eight-three eyes (24 healthy, 30 OHT, and 29 GON) of 65 patients who underwent at least 3 visits were included from the Diagnostic Innovations in Glaucoma Study. The mean follow-up was at least 3 years.

METHODS

OCT angiography (OCTA)-based vessel density and OCT-based structural thickness of the 3 × 3-mm¹ GCC scan slab were evaluated at each visit. The rates of vessel density and thickness change were compared across diagnostic groups using a linear mixed-effects model.

MAIN OUTCOME MEASURES

Change rates of macula GCC thickness and superficial vessel density.

RESULTS

Significant mean rates of both GCC thinning and vessel density loss were detectable in OHT and GON groups. Of the individual suspect eyes, 49.1% showed significant loss (P < 0.05) with either vessel density or GCC thickness. Of the GON eyes, 31.0% showed both significant GCC loss and vessel density loss, 51.7% showed only significant GCC loss, whereas 17.2% showed only significant vessel density loss. Vessel density loss was faster than GCC thinning in half of the suspect eyes based on percent loss analysis. The age and scan quality-adjusted GCC thinning rates of the OHT group (-0.59 μm/year; P = 0.025) and GON group (-0.79 μm/year; P = 0.058) were faster than those of the healthy group (-0.11 μm/year), whereas the rate of vessel density loss was not significantly different among the diagnostic groups (all P > 0.2). Higher mean intraocular pressure during follow-up was associated with faster GCC thinning in the OHT group (P = 0.065) and GON groups (P = 0.015), but was not associated with the rate of vessel density decrease.

CONCLUSIONS

Whereas the rate of GCC thinning was faster on average in suspect eyes than in healthy eyes, some suspect eyes showed significant loss of vessel density and faster vessel density loss than GCC thinning. OCT and OCTA are complementary and useful for evaluating eyes with OHT or GON.

Zone-wise examination of optical coherence tomography features and their correspondence to multifocal electroretinography in eyes with nonproliferative diabetic retinopathy

PURPOSE

To examine (1) the retinal structure by optical coherence tomography (OCT) and function by means of multifocal electroretinography (mfERG) in eyes with and without nonproliferative diabetic retinopathy (NPDR) (2) for correspondence between local retinal function and OCT zones with retinal lesions.

METHODS

One hundred and thirty-two eligible participants (30 with nonproliferative DR (NPDR) and 102 with diabetes with no DR) underwent comprehensive ophthalmic examination, optical coherence tomography for retinal thickness measures, mfERG, and ultra-wide field fundus photography. OCT Early Treatment Diabetic Retinopathy Study (ETDRS) grid was overlaid on to mfERG plots.

RESULTS

Those with NPDR had significantly thicker full retinal measures in the nine (ETDRS) zones compared to no DR. mfERG P1 latencies in rings 1-6 were significantly delayed, while the response densities in rings 4-6 were lower in the NPDR group. Significant negative correlation was noted between OCT thickness and mfERG P1 response densities in many ETDRS zones. Significant positive correlation was noted between P1 latencies and OCT thickness in a few zones. The combination of cystic spaces, microaneurysms, and hard exudates were present in all zones and were associated with a decrease in P1 response densities compared to no lesions. Reduced P1 response densities were associated with a sporadic delay in the mfERG latencies and vice versa. The number of lesions did not show correspondence to the mfERG measures.

CONCLUSIONS

In eyes with NPDR, retinal function is differentially correlated with the DR lesions on OCT and can be assessed using multimodal imaging modalities.

Associations of refractive errors and retinal changes measured by optical coherence tomography: A systematic review and meta-analysis

Studies reporting alteration in retinal thickness using optical coherence tomography (OCT) have been performed in different populations with various degrees of refractive error, producing inconsistent results. Therefore, we performed a meta-analysis to evaluate the alterations in retinal OCT measurements in myopic and hyperopic patients compared to controls. Evaluation of different retinal layers' thickness may have significance for developing novel approaches for preventing, diagnosing, and treating refractive errors and their complications. We searched PubMed and EMBASE to identify articles that reported OCT measurements of different retinal layers and regions, including macular, foveal, parafoveal, perifoveal, foveolar, ganglion cell complex (GCC), retinal nerve fiber layer (RNFL), peripapillary retinal nerve fiber layer (pRNFL), and ganglion cell and inner plexiform layer (GC-IPL) thickness in addition to macular volume, and optic disc area in myopes and hyperopes comparing their differences with controls. We applied either a fixed-effects or random-effects model for the meta-analysis of these differences based on the assessed heterogeneity level. Furthermore, subgroup analyses and metaregression, as well as publication bias and quality assessment, were conducted for the eligible studies. Forty-seven studies with a total of 12223 eyes, including 8600 cases and 3623 non-cases, are included in this meta-analysis. Our results showed that, in comparison to controls, highly myopic eyes had a significantly lower value for mean macular thickness, macular GCC, macular GC-IPL, parafoveal, perifoveal, foveal, foveolar, RNFL, and pRNFL thickness. Compared to controls, moderately myopic eyes showed a significantly thinner mean macular GCC layer and pRNFL. On the other hand, hyperopic eyes had significantly thicker average pRNFL than controls. Several other significant differences were also observed in various regional analyses. The findings of the current study affirm the retinal OCT measurement differences between myopic and hyperopic eyes compared to controls, emphasizing OCT measurements' advantages as potential biomarkers of ocular pathologies.

Reproducibility of Retinal Nerve Fiber Layer and Macular Thickness Measurements Using Spectral Domain Optical Coherence Tomography

The objective of the research was to assess the reproducibility of retinal nerve fiber layer (RNFL) and macular thickness using spectral domain optical coherence tomography and to establish whether the same investigator can get the same or similar results when performing the scan thrice in an hour, without reference to the previous scan and the repeat function. Materials and Methods. In this prospective observational study, 200 subjects who fulfilled the inclusion and exclusion criteria were scanned 3 times according to predefined guidelines at 0, 30 and 60 minutes on the same day, by the same investigator, using spectral domain optical coherence tomography for measurements of RNFL and macular thickness; observations were statistically analyzed and correlated. Results. In RNFL thickness, the temporal sector showed the worst reproducibility as compared to other sectors. RNFL was the greatest in the superior quadrant and the thinnest in the temporal quadrant. For macular thickness, the temporal sector (mid zone) showed the worst reproducibility, while in the outer zone, the inferior sector showed the worst reproducibility; macular thickness was the thinnest at the central zone (innermost 1-mm ring), the thickest within the inner 3-mm ring and diminished peripherally. Conclusions. RNFL and macular thickness measurements using spectral domain optical coherence tomography by the same observer at 0, 30 and 60 minutes were very reproducible, except for the sectors specifically mentioned. The greater the thickness of the RNFL in any sector the better was the reproducibility in that sector. For macular thickness, the temporal sector (mid zone) showed the worst reproducibility.

Treat-and-Extend Regimens for the Management of Neovascular Age-related Macular Degeneration and Polypoidal Choroidal Vasculopathy: Consensus and Recommendations From the Asia-Pacific Vitreo-retina Society

PURPOSE

Review and provide consensus recommendations on use of treat-and-extend (T&E) regimens for neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV) management with relevance for clinicians in the Asia-Pacific region.

METHODS

A systematic search of MEDLINE, EMBASE, and Cochrane databases, and abstract databases of the Asia-Pacific Vitreo-retina Society, European Society of Retina Specialists, American Academy of Ophthalmology, and Controversies in Ophthalmology: Asia-Australia congresses, was conducted to assess evidence for T&E regimens in nAMD. Only studies with ≥100 study eyes were included. An expert panel reviewed the results and key factors potentially influencing the use of T&E regimens in nAMD and PCV, and subsequently formed consensus recommendations for their application in the Asia-Pacific region.

RESULTS

Twenty-seven studies were included. Studies demonstrated that T&E regimens with aflibercept, ranibizumab, or bevacizumab in nAMD, and with aflibercept in PCV, were efficacious and safe. The recommendation for T&E is, after ≥3 consecutive monthly loading doses, treatment intervals can be extended by 2 to 4 weeks up to 12 to 16 weeks. When disease activity recurs, the recommendation is to reinject and shorten intervals by 2 to 4 weeks until fluid resolution, after which treatment intervals can again be extended. Intraretinal fluid should be treated until resolved; however, persistent minimal subretinal fluid after consecutive treatments may be tolerated with treatment intervals maintained or extended if the clinical condition is stable.

CONCLUSIONS

T&E regimens are efficacious and safe for nAMD and PCV, can reduce the number of visits, and minimize the overall burden for clinicians and patients.

Bacillary layer detachment on optical coherence tomography in exudative age-related macular degeneration

PURPOSE

To report the bacillary layer detachment on optical coherence tomography in exudative age-related macular degeneration.

METHODS

Retrospective, observational cases.

CASE DESCRIPTIONS

Two cases of exudative age-related macular degeneration, one diagnosed as polypoidal choroidal vasculopathy following exudative age-related macular degeneration and other as wet age-related macular degeneration with choroidal neovascular membrane showed separation of myoid and ellipsoid zones of photoreceptor layer on optical coherence tomography. This is termed as BALAD. Other associated features noted were the presence of subretinal hyperreflective material, submacular hemorrhage and subretinal fluid. Both cases were treated with monthly intravitreal injections of Inj. Ranibizumab (0.5 mg/0.05 ml). Following 3 intravitreal injections at monthly intervals, reattachment of the bacillary layer detachment were noted in case 1 while the bacillary layer detachment persisted in case 2.

CONCLUSION

Multimodal imaging using optical coherence tomography in these cases revealed the separation of the bacillary layer following exudative age-related macular degeneration; a finding which is not routinely described in literature.

BACILLARY LAYER DETACHMENT: MULTIMODAL IMAGING AND HISTOLOGIC EVIDENCE OF A NOVEL OPTICAL COHERENCE TOMOGRAPHY TERMINOLOGY: Literature Review and Proposed Theory

PURPOSE

To clarify the histologic basis of bacillary layer detachment (BALAD) through a review of the current literature and an analysis of retinal imaging.

METHODS

The literature for previous reports of BALAD were reviewed. An analysis of retinal images was performed to support anatomical conclusions.

RESULTS

A total of 164 unique patients with BALAD on optical coherence tomography (OCT) were identified from the published literature. Twenty-two underlying etiologies, all associated with subretinal exudation, were identified. Forty-one different OCT terminologies were found. The defining OCT feature of BALAD was a split at the level of the photoreceptor inner segment myoid creating a distinctive intraretinal cavity. Resolution of BALAD was followed by a rapid restoration of the ellipsoid zone. Histology of age-related macular degeneration eyes suggests that individual photoreceptors can shed inner segments. Furthermore, detachment of the entire layer of inner segments is a common postmortem artifact. It is proposed that BALAD occurs when outwardly directed forces promoting attachment of photoreceptor outer segments to the retinal pigment epithelium exceed the tensile strength of the photoreceptor inner segment myoid.

CONCLUSION

This review serves to strengthen the OCT nomenclature "bacillary layer detachment," based on specific reflectance information obtained by OCT and previously published histologic observations.