Optical Coherence Tomography Images Research Articles

Segmentation of choroidal area in optical coherence tomography images using a transfer learning-based conventional neural network: a focus on diabetic retinopathy and a literature review

BackgroundThis study aimed to evaluate the effectiveness of DeepLabv3+with Squeeze-and-Excitation (DeepLabv3+SE) architectures for segmenting the choroid in optical coherence tomography (OCT) images of patients with diabetic retinopathy.MethodsA total of 300 B-scans were selected from 21 patients with mild to moderate diabetic retinopathy. Six DeepLabv3+SE variants, each utilizing a different pre-trained convolutional neural network (CNN) for feature extraction, were compared. Segmentation performance was assessed using the Jaccard index, Dice score (DSC), precision, recall, and F1-score. Binarization and Bland-Altman analysis were employed to evaluate the agreement between automated and manual measurements of choroidal area, luminal area (LA), and Choroidal Vascularity Index (CVI).ResultsDeepLabv3+SE with EfficientNetB0 achieved the highest segmentation performance, with a Jaccard index of 95.47, DSC of 98.29, precision of 98.80, recall of 97.41, and F1-score of 98.10 on the validation set. Bland-Altman analysis indicated good agreement between automated and manual measurements of LA and CVI.ConclusionsDeepLabv3+SE with EfficientNetB0 demonstrates promise for accurate choroid segmentation in OCT images. This approach offers a potential solution for automated CVI calculation in diabetic retinopathy patients. Further evaluation of the proposed method on a larger and more diverse dataset can strengthen its generalizability and clinical applicability.

Automatic fovea detection and choroid segmentation for choroidal thickness assessment in optical coherence tomography.

To develop an automated model for subfoveal choroidal thickness (SFCT) detection in optical coherence tomography (OCT) images, addressing manual fovea location and choroidal contour challenges. Two procedures were proposed: defining the fovea and segmenting the choroid. Fovea localization from B-scan OCT image sequence with three-dimensional reconstruction (LocBscan-3D) predicted fovea location using central foveal depression features, and fovea localization from two-dimensional en-face OCT (LocEN-2D) used a mask region-based convolutional neural network (Mask R-CNN) model for optic disc detection, and determined the fovea location based on optic disc relative position. Choroid segmentation also employed Mask R-CNN. For 53 eyes in 28 healthy subjects, LocBscan-3D's mean difference between manual and predicted fovea locations was 170.0 µm, LocEN-2D yielded 675.9 µm. LocEN-2D performed better in non-high myopia group (P=0.02). SFCT measurements from Mask R-CNN aligned with manual values. Our models accurately predict SFCT in OCT images. LocBscan-3D excels in precise fovea localization even with high myopia. LocEN-2D shows high detection rates but lower accuracy especially in the high myopia group. Combining both models offers a robust SFCT assessment approach, promising efficiency and accuracy for large-scale studies and clinical use.

Minimize flow-induced uncertainty in polarization sensitive optical coherence tomography imaging using eigen decomposition.

Blood flow alters the scattering behavior of penetration light, causing instability in the polarization state to emerge at the underlying tissue during polarization-sensitive optical coherence tomography (PSOCT). We propose an eigen decomposition method to meet this challenge, where the static and dynamic scattering signals are separated for PSOCT to provide the polarization measurements of the tissue of interest that is located beneath the blood flow. Using flow phantoms made by Intralipid solution and 3D-printed birefringent material, we show the flow-induced effects on the measurements of sample birefringent properties of optical axis, phase retardation, and degree of polarization uniformity. We demonstrate the usefulness of the proposed method through in vivo imaging of the human nail fold.

The Current Status of OCT and OCTA Imaging for the Diagnosis of Long COVID

The Current Status of OCT and OCTA Imaging for the Diagnosis of Long COVID

Precision Segmentation of Subretinal Fluids in OCT Using Multiscale Attention-Based U-Net Architecture.

This paper presents a deep-learning architecture for segmenting retinal fluids in patients with Diabetic Macular Oedema (DME) and Age-related Macular Degeneration (AMD). Accurate segmentation of multiple fluid types is critical for diagnosis and treatment planning, but existing techniques often struggle with precision. We propose an encoder-decoder network inspired by U-Net, processing enhanced OCT images and their edge maps. The encoder incorporates Residual and Inception modules with an autoencoder-based multiscale attention mechanism to extract detailed features. Our method shows superior performance across several datasets. On the RETOUCH dataset, the network achieved F1 Scores of 0.82 for intraretinal fluid (IRF), 0.93 for subretinal fluid (SRF), and 0.94 for pigment epithelial detachment (PED). The model also performed well on the OPTIMA and DUKE datasets, demonstrating high precision, recall, and F1 Scores. This architecture significantly enhances segmentation accuracy and edge precision, offering a valuable tool for diagnosing and managing retinal diseases. Its integration of dual-input processing, multiscale attention, and advanced encoder modules highlights its potential to improve clinical outcomes and advance retinal disease treatment.

Intraretinal hyperreflective line: potential biomarker in various retinal disorders.

The intraretinal hyperreflective line (IHL) is a novel posterior segment finding demonstrable using careful optical coherence tomography (OCT) examination. It likely indicates a reaction against photoreceptor, Muller cell, and/or retinal pigment epithelial damage. This study analyzed the spectral-domain OCT characteristics of IHLs to disclose their presence in various retinal conditions. A retrospective review of the charted and imaging records of participants with IHL was conducted at Dokuz Eylul University Department of Ophthalmology between January 2019 and August 2023. The inclusion criterion was the detection of an IHL on good-quality B-scan spectral-domain OCT. An IHL was defined as a vertical line extending from the ellipsoid zone band (or lower) through the outer nuclear layer to the internal limiting membrane in the central fovea. Associated retinal conditions were recorded as potential causative factors for the presence of IHL. IHL was observed on spectral-domain OCT in 40 eyes of 38 participants with several retinal diseases assessment. Fourteen eyes (35%) underwent vitreoretinal surgery pre-IHL detection (12 were operated for full-thickness macular hole [FTMH], one for epiretinal membrane [ERM], and one for rhegmatogenous retinal detachment). In six eyes (15%) a microhole coexisted. Four eyes (10%) had a concurrent lamellar macular hole. The IHL preceded the occurrence of FTMH in three eyes (7.5%), and diabetic macular edema and type 2 idiopathic macular telangiectasia (MacTel-2) were present in three eyes (7.5%) each. The remaining conditions included vitreomacular traction (VMT), nonarteritic anterior ischemic optic neuropathy with central retinal artery occlusion, commotio retinae, exudative age-related macular degeneration, ERM, non-infectious idiopathic posterior uveitis, and Coats' disease, each affecting one eye (2.5%). Of the two participants with bilateral involvement, one was diagnosed with MacTel-2 and the other had IHL with VMT in the right eye that was detected post-vitreoretinal surgery for FTMH in the left eye. Although IHLs are mostly identified in eyes with vitreomacular surface diseases, clinicians may encounter IHLs in other types of retinal pathology. Further large-scale, multicenter, long-term studies on the presence of IHLs in OCT imaging are required to provide more substantial insight on this biomarker.

The relationship between ON-OFF function and OCT structural and angiographic parameters in early diabetic retinal disease.

This study measured associations between ON and OFF functional indicators and structural optical coherence tomography (OCT) and OCT angiography (OCTA) markers in diabetic retinal disease. Fifty-four participants with type 1 or type 2 diabetes (mean age = 34.1 years; range 18-60) and 48 age-matched controls (mean age = 35.4 years, range 18-59) underwent visual psychophysical testing, OCT and OCTA retinal imaging. Psychophysical tasks measuring (A) contrast increment and decrement sensitivity and (B) response times to increment and decrement targets were assessed as surrogate measures of ON and OFF retinal ganglion cell function. The group with diabetes had worse foveal contrast increment and decrement thresholds (p = 0.04) and were slower to search for increment and decrement targets relative to controls (p = 0.009). Individuals with diabetes had a less circular foveal avascular zone (FAZ) (p < 0.001) but did not differ from controls in foveal vessel density and FAZ area. Functional and structural outcome measures related to the peripheral retina were also comparable between those with and without diabetes. Functional responses to increments and decrements were not significantly correlated with FAZ circularity or vessel density in individuals with diabetes. Diabetic retinal disease results in impaired performance on measures of inferred ON and OFF pathway function in addition to vascular deficits measurable with OCTA. Future longitudinal studies may determine the temporal relationship between these deficits, and whether they predict future diabetic retinopathy.

Multifocal electroretinogram changes after panretinal photocoagulation in early proliferative diabetic retinopathy.

Panretinal photocoagulation (PRP) impacts macular function in eyes with early proliferative diabetic retinopathy (PDR). Herein, we used the multifocal electroretinogram (mfERG) to objectively investigate this concept. In this prospective interventional case series, we enrolled patients with treatment-naive early PDR, absence of clinically significant macular edema, and requirement for PRP. All participants underwent detailed ocular examinations. We measured the best-corrected distance visual acuity (BCDVA), conducted optical coherence tomography imaging to measure central macular thickness (CMT), and performed mfERG at baseline and 3 months post-PRP. Amplitude and latency of the mfERG response were evaluated within the innermost four of the five concentric rings. We enrolled 29 eyes of 23 patients with a mean (standard deviation) age of 54.3 (8.8) years and male-to-female ratio of 1:1.3. The mean BCDVA was unchanged post-treatment (P > 0.05), and the BCDVA in 26 eyes (89.7%) was either improved or unchanged, whereas in three eyes (10.3%) it decreased. The mean CMT was unchanged post-PRP (P > 0.05). Concerning the mfERG, the mean P1 amplitudes decreased significantly in all four concentric rings from the foveola at 3 months post-PRP compared with baseline values (all P < 0.05); however, the latencies were unchanged (all P > 0.05). At baseline, BCDVA correlated significantly with both the amplitude (r = + 0.55; P < 0.05) and latency (r = - 0.38; P < 0.05) of the mfERG in the central ring, whereas a significant correlation was detected with only the amplitude at 3 months post-PRP (r = + 0.52; P < 0.05). Macular function was decreased 3 months post-PRP in patients with early PDR, as indicated by decreased amplitude of the mfERG, whereas the functional and anatomical parameters were stable. The mfERG served as an objective tool for measuring retinal function and predicting visual outcomes post-PRP in eyes with early PDR. A higher amplitude in the mfERG correlated substantially with a better visual outcome post-PRP. Further multi-center longitudinal studies with robust designs including different PDR severity levels may reveal additional objective after-effects of PRP.

Optical coherence tomography enables longitudinal evaluation of cell graft-directed remodeling in stroke lesions.

Stem cell grafting can promote glial repair of adult stroke injuries during the subacute wound healing phase, but graft survival and glial repair outcomes are perturbed by lesion severity and mode of injury. To better understand how stroke lesion environments alter the functions of cell grafts, we employed optical coherence tomography (OCT) to longitudinally image mouse cortical photothrombotic ischemic strokes treated with allogeneic neural progenitor cell (NPC) grafts. OCT angiography, signal intensity, and signal decay resulting from optical scattering were assessed at multiple timepoints across two weeks in mice receiving an NPC graft or an injection of saline at two days after stroke. OCT scattering information revealed pronounced axial lesion contraction that naturally occurred throughout the subacute wound healing phase that was not modified by either NPC or saline treatment. By analyzing OCT signal intensity along the coronal plane, we observed dramatic contraction of the cortex away from the imaging window in the first week after stroke which impaired conventional OCT angiography but which enabled the detection of NPC graft-induced glial repair. There was moderate, but variable, NPC graft survival at photothrombotic strokes at two weeks which was inversely correlated with acute stroke lesion sizes as measured by OCT prior to treatment, suggesting a prognostic role for OCT imaging and reinforcing the dominant effect of lesion size and severity on graft outcome. Overall, our findings demonstrate the utility of OCT imaging for both tracking and predicting natural and treatment-directed changes in ischemic stroke lesion cores.

Early vascular healing after neXt-generation drug-eluting stent implantation in Patients with non-ST elevation acute Coronary syndrome: a randomized optical coherence Tomography imaging study (EXPECT).

Early vascular healing after drug-eluting stent (DES) implantation is associated with better outcomes and lower incidence of in-stent thrombosis. To examine vascular healing response in patients with non-ST elevation acute coronary syndrome (NSTE-ACS) undergoing percutaneous coronary intervention (PCI) guided by optical coherence tomography (OCT) versus angiography alone. Sixty patients were randomized 1:1:1 to OCT-guided PCI with 3-month OCT follow-up (O3 group, n = 20), angiography-guided PCI with 3-month OCT follow-up (A3 group, n = 20), or angiography-guided PCI with 6-month OCT follow-up (A6 group, n = 20). The primary endpoint was the proportion of covered struts at 3- or 6-month follow-up. The proportion of covered struts in the O3 group was significantly higher than in the A3 group (95.2% vs. 92.3%, p < 0.001), but lower than in the A6 group (95.2% vs. 97.4%, p < 0.001). The O3 group had a lower proportion of incomplete strut apposition (ISA) than the A3 group (0.46% vs. 0.76%, p = 0.006), and higher than the A6 group (0.46% vs. 0.27%, p = 0.018) at follow-up. The optimal cut-off value of ISA after implantation of DES for predicting stent coverage at 3 and 6-month follow-up was 200μm and 308μm, respectively. Only one patient experienced target lesion revascularization in the A3 group during a 3-year clinical follow-up. In patients with NSTE-ACS undergoing PCI with DES, OCT guidance achieved higher strut coverage compared with angiography guidance at 3-month follow-up. However, the difference in the strut coverage between the OCT-guided group and the angiography-guided group at 6 months indicates that the degree of endothelialization may be more time-dependent instead of invasive device guidance.

Multi-resolution visual Mamba with multi-directional selective mechanism for retinal disease detection.

Retinal diseases significantly impact patients' quality of life and increase social medical costs. Optical coherence tomography (OCT) offers high-resolution imaging for precise detection and monitoring of these conditions. While deep learning techniques have been employed to extract features from OCT images for classification, convolutional neural networks (CNNs) often fail to capture global context due to their focus on local receptive fields. Transformer-based methods, on the other hand, suffer from quadratic complexity when handling long-range dependencies. To overcome these limitations, we introduce the Multi-Resolution Visual Mamba (MRVM) model, which addresses long-range dependencies with linear computational complexity for OCT image classification. The MRVM model initially employs convolution to extract local features and subsequently utilizes the retinal Mamba to capture global dependencies. By integrating multi-scale global features, the MRVM enhances classification accuracy and overall performance. Additionally, the multi-directional selection mechanism (MSM) within the retinal Mamba improves feature extraction by concentrating on various directions, thereby better capturing complex, orientation-specific retinal patterns. Experimental results demonstrate that the MRVM model excels in differentiating retinal images with various lesions, achieving superior detection accuracy compared to traditional methods, with overall accuracies of 98.98\% and 96.21\% on two public datasets, respectively. This approach offers a novel perspective for accurately identifying retinal diseases and could contribute to the development of more robust artificial intelligence algorithms and recognition systems for medical image-assisted diagnosis.

Intravitreal Dexamethasone Implants for Macular Edema Secondary to Acute Retinal Necrosis

ABSTRACT Purpose To assess the effectiveness and risk of intravitreal injection of dexamethasone implants in treating macular edema (ME) secondary to acute retinal necrosis (ARN). Methods In this retrospective, noncomparative case series study, five patients who developed secondary ME after ARN and received an intravitreal dexamethasone implant injection were enrolled. The features of secondary ME on OCT and the outcomes of dexamethasone intravitreal implanting were presented. Results The mean age of the patients was 59 years (range, 51–61 years). All patients had unilateral involvement, and all 5 eyes showed mild to moderate anterior uveitis, retinal necrosis, and vasculitis. Herpes zoster virus was detected in all eyes using PCR, and timely antiviral and anti-inflammatory treatment was performed. Aqueous humor samples were negative for herpes zoster virus DNA, and resolution of viral retinitis was noted upon the occurrence of ME. Additionally, three eyes received pars plana vitrectomy with silicone oil prior to ME development. All eyes presented with intraretinal fluid, hyper-reflective foci, and impairments of the external limiting membrane/ellipsoid zone at varying degrees on OCT images. Epiretinal membrane was exhibited in 80% of eyes, but no vitreoretinal traction was detected. Subretinal fluid was visible in 60% of eyes. ME was relieved effectively in all eyes after intravitreal dexamethasone implanting. One of these patients experienced three episodes of ME. No recurrence of retinal necrosis or corticosteroid-associated ocular hypertension was observed during the follow-up period. Conclusion Intravitreal injection of dexamethasone implants can effectively alleviate ME secondary to ARN and improve visual acuity with no adverse reactions.

Rheumatic fever and long-term use of benzathine penicillin as possible risk factors for extensive macular atrophy with pseudodrusen in a Brazilian cohort

BackgroundAlthough there has been a large increase in the number of extensive macular atrophy with pseudodrusen (EMAP) cases, the basic aspects of this disease remain unknown. Brazilian patients have a common past history of rheumatic fever (RF) and/or benzathine penicillin (BP) treatment possibly related to the disease. We analyzed how RF and BP might be correlated with EMAP in Brazilian patients.DesignObservational, retrospective, case-control study.MethodsThe databases of three private eye clinics in Brazil were searched for patients with an EMAP-like appearance. Each patient was asked about a previous history of RF and/or long-term use of BP. Patients underwent best-corrected visual acuity (BCVA) measurement, color fundus imaging, fundus autofluorescence (FAF) imaging, optical coherence tomography (OCT) imaging, and electroretinography (ERG). The following characteristics were analyzed: subretinal drusenoid deposits (SDD), pigment mottling, retinal pigment epithelial/basement membrane (RPE/BM) separation, outer retinal or RPE atrophy, and identification of a paving stone-like appearance. The choroidal thickness was measured using enhanced depth imaging OCT. The central atrophic area was measured manually on ultra-wide-field FAF.ResultsA total of 154 eyes of 77 patients (women, 66.2%; mean age, 58.6 years) with EMAP were included; 90.9% of patients were diagnosed with RF; 94.8% had been treated with BP and treatment was started at an average age of 7.3 years (mean duration, 11.8 years). The treatment duration was significant for the area of atrophy (P = 0.027) in which each 1-year increase in treatment duration led to an average reduction of 6.91 mm2 in area. The age at diagnosis of RF was significant (P = 0.026) for SDD. The increase of 1 year in the diagnosis of RF (late disease) led to a reduction of 24% in the chance of central SDD being present. On OCT, 65.5% eyes had SDD and more than 70% had a split RPE/BM and outer retinal or RPE atrophy. The choroidal thickness in patients with EMAP was significantly (P < 0.001) thinner than the control group. The ERG was abnormal in all eyes.ConclusionThese findings may suggest a relation between RF and EMAP in Brazilian patients. Patients with EMAP should be questioned about a history of RF.

Dry age-related macular degeneration classification from optical coherence tomography images based on ensemble deep learning architecture.

Dry age-related macular degeneration (AMD) is a retinal disease, which has been the third leading cause of vision loss. But current AMD classification technologies did not focus on the classification of early stage. This study aimed to develop a deep learning architecture to improve the classification accuracy of dry AMD, through the analysis of optical coherence tomography (OCT) images. We put forward an ensemble deep learning architecture which integrated four different convolution neural networks including ResNet50, EfficientNetB4, MobileNetV3 and Xception. All networks were pre-trained and fine-tuned. Then diverse convolution neural networks were combined. To classify OCT images, the proposed architecture was trained on the dataset from Shenyang Aier Excellence Hospital. The number of original images was 4,096 from 1,310 patients. After rotation and flipping operations, the dataset consisting of 16,384 retinal OCT images could be established. Evaluation and comparison obtained from three-fold cross-validation were used to show the advantage of the proposed architecture. Four metrics were applied to compare the performance of each base model. Moreover, different combination strategies were also compared to validate the merit of the proposed architecture. The results demonstrated that the proposed architecture could categorize various stages of AMD. Moreover, the proposed network could improve the classification performance of nascent geographic atrophy (nGA). In this article, an ensemble deep learning was proposed to classify dry AMD progression stages. The performance of the proposed architecture produced promising classification results which showed its advantage to provide global diagnosis for early AMD screening. The classification performance demonstrated its potential for individualized treatment plans for patients with AMD.

Application of Targeted Optical Coherence Tomography in Oral Cancer: A Cross-Sectional Preliminary Study.

The diagnosis of oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) represent a significant challenge in oral medicine. Optical coherence tomography (OCT) shows promise for evaluating oral tissue microstructure but lacks standardized diagnostic protocols tailored to the structural variability and lesions of oral mucosa. This cross-sectional observational study aims to evaluate the diagnostic accuracy of targeted biopsy-based and site-coded OCT protocols for common OPMDs and OSCC. Adult patients clinically diagnosed with OPMDs, including oral leukoplakia (OL), oral lichen planus (OLP), and OSCC were enrolled. Clinical and OCT evaluation before and after punch scalpel-site registration preceding diagnostic biopsy on the target site was performed. Blinded observers analyzed the OCT scans for OCT-based diagnoses. Sensitivity, specificity, and diagnostic accuracy for OCT evaluations before and after punch scalpel-site registration were statistically compared with histological findings. A dataset of 2520 OCT scans and 210 selected images from 21 patients was obtained. Sensitivity and specificity post-target site registration were high for OSCC (98.57%, 100.00%), OL (98.57%, 98.57%), and OLP (97.14%, 98.57%). The positive predictive values ranged from 97.14% to 100.00%, while negative predictive values ranged from 98.57% to 99.29%. Inter-observer agreements were strong for OSCC (0.84) and moderate for OL (0.54) and OLP (0.47-0.49). Targeted OCT scans significantly improved diagnostic accuracy for all conditions (p < 0.001). This preliminary study supports using site-targeted OCT scans followed by a site-targeted punch biopsy, enhancing precision in oral diagnostics. This approach is foundational for developing pioneering automated algorithms guiding oral cancer and pre-cancer diagnosis via OCT imaging.

Hierarchical convolution neural network models for classifying the segmented OCT and OCTA images using U-Net model

Hierarchical convolution neural network models for classifying the segmented OCT and OCTA images using U-Net model

Critical Impact of Working Distance on OCT Imaging: Correction of Optical Distortion and Its Effects on Measuring Retinal Curvature.

To assess the impact of working distance (WD) on optical distortion in optical coherence tomography (OCT) imaging and to evaluate the effectiveness of optical distortion correction in achieving consistent retinal Bruch's membrane (BM) layer curvature, regardless of variations in WD. Ten subjects underwent OCT imaging with four serial macular volume scans, each employing distinct WD settings adjusted by balancing the sample and reference arm of the OCT interferometer (eye length settings changed). Either of two types of 30° standard objectives (SOs) was used. A ray tracing model was used to correct optical distortion, and BM layer curvature (represented as the second derivative of the curve) was measured. Linear mixed effects (LME) modeling was used to analyze factors associated with BM layer curvature, both before and after distortion correction. WD exhibited significant associations with axial length (β = -1.35, P < 0.001), SO type (P < 0.001), and eye length settings (P < 0.001). After optical distortion correction, the mean ± SD BM layer curvature significantly increased from 16.80 ± 10.08µm-1 to 49.31 ± 7.50µm-1 (P < 0.001). The LME model showed a significant positive association between BM layer curvature and WD (β = 1.94, P < 0.001). After distortion correction, the percentage change in BM layer curvature due to a 1-mm WD alteration decreased from 9.75% to 0.25%. Correcting optical distortion in OCT imaging significantly mitigates the influence of WD on BM layer curvature, enabling a more accurate analysis of posterior eye morphology, especially when variations in WD are unavoidable.

Optical Coherence Tomography Image Analysis for Detection of Alzheimer’s Disease: A Comprehensive Structured Review

Optical Coherence Tomography (OCT) has emerged as a promising non-invasive imaging modality for the early detection of Alzheimer’s Disease (AD). This systematic literature review aims to consolidate current research on OCT image analysis for AD detection, addressing the growing need for early and accurate diagnostic tools. Despite the advances in neuroimaging, early diagnosis of AD remains challenging due to its asymptomatic nature in initial stages and the invasiveness of traditional methods. To achieve this, we conducted an extensive search of related articles from reputable databases (Scopus and Web of Science), focusing on studies published between 2022-2024. The flow of study was based on PRISMA framework. The database found (n = 29) final primary data. This review was divided into three themes, (1) retinal and ocular biomarkers for AD, (2) optical coherence tomography angiography (OCTA) and imaging techniques, and (3) machine learning and computational approaches for Alzheimer’s disease diagnosis. Key findings include the enlargement of the periarteriole capillary-free zone and changes in retinal nerve fibre layer thickness as potential AD biomarkers. Based on the review, the implementation of image analysis for OCT images have shown substantial potential for AD detection. By evaluating the past studies, gaps for the current research were discovered including the need for larger, more diverse cohorts and longitudinal studies to validate these biomarkers. In summary, detection of AD is possible through thorough OCT image analysis, but further research could be suggested to enhance its clinical applicability and reliability.

Acute effects of swimming goggle wearing on intraocular pressure, anterior chamber biometrics, and optic nerve head morphology

Swimming goggles (SG) are widely used in water sports, and this study aimed to evaluate the acute effects of wearing SG on intraocular pressure (IOP), anterior chamber biometrics, axial length (AL), and optic nerve head (ONH) morphology. Twenty-eight healthy young adults participated in this cross-sectional study, with assessed parameters including IOP, central corneal thickness (CCT), anterior chamber depth (ACD), anterior chamber angle (ACA), AL, and optical coherence tomography (OCT) imaging of the ONH, specifically Bruch membrane opening (BMO), Bruch membrane opening-minimum rim width (BMO-MRW), lamina cribrosa depth (LCD), and prelaminar tissue (PLT). Measurements were taken at four time points: before wearing SG, at the 1st and 10th minutes of wearing, and immediately after removal. The results showed a significant increase in IOP at the 1st and 10th minutes of SG wear compared to pre-wear and post-removal values. Additionally, decreases in CCT, ACD, and ACA, along with an increase in AL, were observed while wearing SG. However, these changes reverted to baseline after the goggles were removed. No significant alterations were detected in ONH parameters during the study. The findings suggest that wearing SG induces an acute rise in IOP and changes in anterior segment parameters, likely due to oculopression, but does not appear to affect ONH morphology in the short term. Further studies are needed to investigate any potential long-term effects.

Macular changes after cataract surgery.

This article aims to highlight if the central macular retina suffers changes after cataract surgery, and to evaluate the eventually discovered changes regarding persistence. This retrospective study, which lasted over three years (2021-2023), included patients who underwent cataract surgery performed by one surgeon. Spectral-domain optical coherence tomography (SD-OCT) imaging assessed macular changes and measured the central macular thickness. A total of 240 eyes with diagnosed senile cataract were included in this study. The mean age was 66 years ± 4 years. Preoperative central foveal thickness was 210 ± 27.3 µm, the postoperative thickness on day 1 was 234.3 ± 40.2 µm, at 6 months 230.5 ± 35.2 µm, and the 1-year follow-up 229.2 ± 30.3 µm. Macular changes after cataract surgery are easily confirmed by SD-OCT. The evaluation and monitoring of macular changes can be done by using central macular thickness assessment. The study provides data from a Romanian pool of patients. The values correlated well with those from similar studies of SD-OCT examinations, but differences were still observed, as there were different devices for performing SD-OCTs.