Search Results (271)

Background/Objectives: Clinical differentiation between Parkinson’s disease (PD) and atypical parkinsonism (AP) remains complex. Current diagnostic procedures helpful in their distinction lack specificity, making non-invasive tools like optical coherence tomography (OCT) crucial in evaluating possible retinal changes as potential biomarkers. Our study examined the thickness of the ganglion cell inner plexiform layer complex (GCIPL), peripapillary retinal nerve fiber layer (RNFL) and macular segments in individuals with PD, multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and healthy controls (HC). The objective of our study was to determine if OCT analyses can effectively discriminate PD patients from HC and whether retinal thickness can distinguish typical PD patients from those with AP. Methods: Research was an observational, cross-sectional study. Multiple retinal layers measured with OCT of PD and AP patients were compared with age- and sex-matched HC. An intergroup assessment was conducted. Results: Patients with PD and PSP exhibit a thinner GCIPL compared to HC, with no difference observed in the MSA group. GCIPL thickness between investigational groups does not differentiate between PD and AP. The RNFL and central macula thickness were statistically significantly reduced in all patient groups compared to HC. The RNFL was thinner in PSP compared to PD. Nearly all inner and outer macular segments were thinner in the investigational groups compared to HC. The preservation of outer nasal segments distinguished HC from both typical and AP. Patients with PSP and PD differed in the thickness of all macular segments, being thinner in PSP patients. Conclusions: Thickness of multiple retinal layers and macular regions might serve as a distinguishing feature between PD, AP and HC. Full article

Understanding thrombosis in acute coronary syndromes (ACSs) has evolved through advances in biomarkers, intracoronary imaging, and emerging analytical tools, improving diagnostic accuracy and risk stratification in high-risk patients. This narrative review provides an integrative overview of contemporary evidence from clinical trials, meta-analyses, and international guidelines addressing circulating biomarkers, intracoronary imaging modalities—including optical coherence tomography (OCT), intravascular ultrasound (IVUS), and near-infrared spectroscopy (NIRS)—artificial intelligence–based analytical approaches, and emerging antithrombotic therapies. High-sensitivity cardiac troponins and natriuretic peptides remain the most robust and guideline-supported biomarkers for diagnosis and prognostic assessment in ACS, whereas inflammatory markers and multimarker strategies offer incremental prognostic information but lack definitive validation for routine therapeutic guidance. Intracoronary imaging with IVUS or OCT is supported by current guidelines to guide percutaneous coronary intervention in selected patients with ACS and complex coronary lesions, leading to improved procedural optimization and clinical outcomes compared with angiography-guided strategies. Beyond procedural guidance, OCT enables detailed plaque characterization and mechanistic insights into ACS, while NIRS provides complementary information on lipid-rich plaque burden, primarily for risk stratification based on observational evidence. Artificial intelligence represents a rapidly evolving tool for integrating clinical, laboratory, and imaging data, with promising results in retrospective and observational studies; however, its clinical application in thrombosis management remains investigational due to the lack of outcome-driven randomized trials. In the therapeutic domain, factor XI inhibitors have demonstrated favorable safety profiles with reduced bleeding and preserved antithrombotic efficacy in phase II and early phase III studies, but their definitive role in ACS management awaits confirmation in large, outcome-driven randomized trials. Overall, the integration of biomarkers, intracoronary imaging, and emerging analytical and pharmacological strategies highlights the potential for more individualized cardiovascular care. Nevertheless, careful interpretation of existing evidence, rigorous validation, and alignment with guideline-directed practice remain essential before widespread clinical adoption. Full article

This pilot study assessed the effectiveness of the intravitreal dexamethasone implant (Ozurdex) in retinal vein occlusion (RVO) patients and explored potential pre-treatment biomarkers to improve management and prognosis. Eighteen patients with branch RVO (BRVO) and twenty-four with central RVO (CRVO) receiving two intravitreal injections of Ozurdex (at baseline and between 4 and 6 months) were included. Best-corrected visual acuity (BCVA) and central retinal thickness (CRT) were recorded at baseline and after 3, 6, and 12 months. Retinal morphology was assessed using optical coherence tomography (OCT), and serum biomarkers were analyzed by ELISAs. No significant BCVA improvement was observed in RVO patients, while CRT significantly decreased from 3 to 12 months. Patients without defects of the retinal inner layers, ellipsoid zone, and external limiting membrane showed significantly higher BCVA at 6 and 12 months. Both BRVO and CRVO groups demonstrated significant BCVA improvement and CRT reduction at 6 and 12 months, with better outcomes in BRVO patients. These patients exhibited lower baseline serum levels of xanthine oxidase (XO) and thrombospondin-1 (TSP-1), which inversely correlated with BCVA at 12 months. Ozurdex was effective in real-life RVO treatment, particularly in BRVO. Serum XO and TSP-1 may serve as prognostic biomarkers for RVO. Full article

Background: Vitreoretinal lymphoma (VRL) often presents with features resembling uveitis and is commonly associated with central nervous system lymphoma (CNSL). Intravitreal methotrexate (IVMTX) is widely used as local therapy; however, objective markers for treatment response and prognosis remain limited. This study investigated choroidal structural changes after IVMTX via enhanced depth imaging optical coherence tomography (EDI-OCT) and explored prognostic indicators for subsequent CNSL development. Methods: This retrospective study included 18 patients (27 eyes) with VRL treated with IVMTX at Tokushima University Hospital between 2006 and 2021. EDI-OCT was conducted at baseline and at 1 and 3 months after IVMTX. Choroidal thickness and luminal and stromal areas were quantified through image binarization. The stromal/choroidal area (S/C) ratio and its association with CNSL onset were statistically analyzed. Results: The mean number of IVMTX injections administered over 3 months was 5.9 ± 1.3. Foveal retinal thickness did not significantly change, whereas foveal choroidal thickness significantly decreased from 275.8 ± 15.8 µm at baseline to 257.5 ± 14.7 µm at 1 month (p < 0.01). Total choroidal and stromal areas, particularly in the outer choroidal layer, were significantly decreased after IVMTX (p < 0.0001), whereas the luminal area in the inner layer modestly reduced (p < 0.05). The S/C ratio significantly declined at 1 month post-treatment (p < 0.001). Patients who developed CNSL within 2 years of VRL onset demonstrated higher baseline S/C ratios (p < 0.05). Conclusions: IVMTX induces measurable reductions in choroidal areas and stromal proportion, indicating decreased inflammatory infiltration. The baseline S/C ratio observed on EDI-OCT is a potential noninvasive biomarker of VRL activity and a prognostic indicator for early CNSL development. Full article

Artificial intelligence (AI) and machine learning (ML) are transforming medical diagnostics, but human nail, an easily accessible and rich biological substrate, is still not fully exploited in the digital health field. Nail pathologies are easily diagnosed, non-invasive disease biomarkers, including systemic diseases such as anemia, diabetes, psoriasis, melanoma, and fungal diseases. This review presents the first big synthesis of image analysis for nail lesions incorporating AI/ML for diagnostic purposes. Where dermatological reviews to date have been more wide-ranging in scope, our review will focus specifically on diagnosis and screening related to nails. The various technological modalities involved (smartphone imaging, dermoscopy, Optical Coherence Tomography) will be presented, together with the different processing techniques for images (color corrections, segmentation, cropping of regions of interest), and models that range from classical methods to deep learning, with annotated descriptions of each. There will also be additional descriptions of AI applications related to some diseases, together with analytical discussions regarding real-world impediments to clinical application, including scarcity of data, variations in skin type, annotation errors, and other laws of clinical adoption. Some emerging solutions will also be emphasized: explainable AI (XAI), federated learning, and platform diagnostics allied with smartphones. Bridging the gap between clinical dermatology, artificial intelligence and mobile health, this review consolidates our existing knowledge and charts a path through yet others to scalable, equitable, and trustworthy nail based medically diagnostic techniques. Our findings advocate for interdisciplinary innovation to bring AI-enabled nail analysis from lab prototypes to routine healthcare and global screening initiatives. Full article

Background/Objectives: The search for biomarkers of cognition has garnered significant interest over the past decade, owing to their objective nature, in contrast to the currently available cognition screening tools, which are based on subjective measures. Retina imaging is used in this field because its tissue is considered as an extension of the brain’s vascular and neural structures, reflecting overall brain health. In cognitive disorders, early detection and intervention are essential for achieving the best possible outcomes. To evaluate the physiological correlates of cognitive function in healthy young adults by assessing retinal structures as a non-invasive biomarker of cognitive health. Methods: Eighty healthy young adults participated in this study. Optical Coherence Tomography (OCT) was used to measure retinal morphology, including macular thickness, volume, and retinal nerve fiber layer thickness; then, OCT results were correlated with cognitive assessments using the Montreal Cognitive Assessment (MoCA). Results: Participants with mild cognitive impairment exhibited thinner macular thickness and lower macular volume (p < 0.05, p < 0.001) than participants with normal cognitive function. We also found that macular thickness is positively associated with cognitive function in healthy adults (p < 0.001). The RNFL was found to be normal in all groups, despite changes in macular thickness, indicating that cognitive function in normal individuals depends on macular changes rather than the optic nerve. Conclusions: Macular OCT, which is a cost-effective and widely available tool, can be used to screen for mild cognitive impairment. A clinical trial is recommended to validate these findings and to generate guidelines for assessing cognitive physiology through the retina. Full article

Background/Objectives: Thyroid eye disease (TED) can lead to structural and microvascular changes in the orbit and retina. This study aimed to investigate the associations between Clinical Activity Score (CAS), orbital magnetic resonance imaging (MRI) measurements, and retinal microvascular changes in TED patients. Methods: This cross-sectional study included 38 patients (76 eyes) with TED. Each patient underwent a comprehensive ophthalmological evaluation, CAS assessment, and a detailed medical history. Optical coherence tomography angiography (OCTA) was performed to quantify vessel density (VD) in the superficial and deep capillary plexus (SCP and DCP). Exophthalmos, extraocular muscle thickness and orbital fat thickness were measured on MRI scans to evaluate structural changes. Laboratory analyses included thyroid hormone levels, thyrotropin receptor antibodies (TRAb), anti-thyroid peroxidase antibodies (anti-TPO), and lipid profile. Results: Active TED patients (CAS ≥ 3) had significantly higher TRAb levels (p < 0.001), while anti-TPO did not differ between groups. Active eyes showed significantly higher DCP VD in the whole image (p = 0.013), parafovea (p = 0.012), and perifovea (p = 0.009) across all quadrants, with no difference in SCP or the foveal avascular zone (FAZ). In linear mixed model regression analyses, after adjusting for previous glucocorticosteroid therapy, higher triglycerides, greater medial rectus thickness, and whole-image DCP VD independently predicted higher CAS values (R² = 42, p < 0.001). After adjusting for age and sex, CAS remained significantly positive predictor of DCP VD in the parafovea (R² = 0.22, p < 0.001). Conclusions: Changes in DCP VD reflect TED activity and structural orbital involvement. Full article

Background/Objectives: Alzheimer’s disease (AD) is the leading cause of dementia, which is an inevitable consequence of aging. Early detection of AD, or detection during the pre-AD stage, is beneficial, as it enables timely intervention to reduce modifiable risk factors, which may help prevent or delay the progression to dementia. On the one hand, plasma biomarkers have demonstrated great promise in predicting cognitive decline. On the other hand, in recent years, ocular imaging features, particularly the thickness of retinal layers measured by spectral-domain optical coherence tomography (SD-OCT), are emerging as possible non-invasive, non-contact surrogate markers for early detection and monitoring of neurodegeneration. This pilot study aims to identify retinal layer thickness changes across the entire retina linked to plasma AD biomarkers in cognitively healthy (CH) elderly individuals at risk for AD. Methods: Eleven CH individuals (20 eyes total) were classified in the pre-AD stage by plasma β-amyloid (Aβ)42/40 ratio < 0.10 and underwent SD-OCT. A deep-learning-derived automated algorithm was used to segment retinal layers on OCT (with manual correction when needed). Multiple layer thicknesses throughout the entire retina (including the inner retina, the outer retina, and the choroid) were measured in the inner ring (1–3 mm) and outer ring (3–6 mm) of the Early Treatment Diabetic Retinopathy Study (ETDRS). Relationships between retinal layers and plasma biomarkers were analyzed by ridge regression/bootstrapping. Results: Results showed that photoreceptor inner segment (PR-IS) thinning had the largest size effect with neurofilament light chain. Additional findings revealed thinning or thickening of the other retinal layers in association with increasing levels of glial fibrillary acidic protein and phosphorylated tau at threonine 181 and 217 (p-tau181 and p-tau217). Conclusions: This pilot study suggests that retinal layer-specific signatures exist, with PR-IS thinning as the largest effect, indicating neurodegeneration in pre-AD. Further research is needed to confirm the findings of this pilot study using larger longitudinal pre-AD cohorts and comparative analyses with healthy aging adults. Full article

Background/Objectives: To compare changes in the thickness of retinal layers between patients with amyotrophic lateral sclerosis (ALS) and healthy controls using optical coherence tomography. Amyotrophic lateral sclerosis is a degenerative disease of the upper and lower motoneurons with a rapidly progressive course, but non-motor symptoms such as decreased ocular motility and reduced visual acuity have also been reported. Specific biomarkers or surrogate parameters assessing neurodegeneration in ALS are of interest. Methods: In a retrospective, longitudinal study using optic coherence tomography of the retinal layers, we compared changes in the thickness of the layers between patients with ALS and healthy controls. Correlations to clinical scores, such as the modified ranking scale, were analyzed. Results: In our cohort of patients with early ALS (disease duration 5.15 ± 21.4 months at baseline), we neither observed differences in retinal layer thickness at baseline nor did the thickness changes in any retinal layer differ in comparison to healthy controls at baseline. Moreover, we observed no significant thickness changes over the course of the observational period in our patients with ALS. However, a correlation analysis revealed a negative association of the thickness change rates in the complex of ganglion cell and inner plexiform layer and the inner nuclear layer with a higher modified Rankin scale at follow-up. Conclusions: This study adds to the notion that OCT may not be a suitable tool to monitor atrophy and disease progression in ALS. However, further longitudinal studies with longer follow-up times and larger cohorts are warranted. Full article

Diabetic macular edema (DME) is a leading cause of vision loss, and predicting patients’ response to anti-vascular endothelial growth factor (anti-VEGF) therapy remains a clinical challenge. In this study, we developed an interpretable deep learning model for treatment prediction and biomarker analysis. We retrospectively analyzed 402 eyes from 371 patients with DME. The proposed DME-Receptance Weighted Key Value (RWKV) integrates optical coherence tomography (OCT) and ultra-widefield (UWF) imaging using Causal Attention Learning (CAL), curriculum learning, and global completion (GC) loss to enhance microlesion detection and structural consistency. The model achieved a Dice coefficient of 71.91 ± 8.50% for OCT biomarker segmentation and an AUC of 84.36% for predicting anti-VEGF response, outperforming state-of-the-art methods. By mimicking clinical reasoning with multimodal integration, DME-RWKV demonstrated strong interpretability and robustness, providing a promising AI framework for precise and explainable prediction of anti-VEGF treatment outcomes in DME. Full article

Background/Objectives: Pigment migration is a key biomarker of progression in age-related macular degeneration (AMD). This study assessed the diagnostic performance of ring aperture Retro mode (RAR) imaging for detecting pigment migration and compared its performance with established multimodal imaging techniques. Methods: This retrospective study included 80 eyes from 61 consecutive patients with AMD who underwent multimodal imaging with color fundus images (CFIs), fundus autofluorescence (FAF), RAR imaging (Mirante, NIDEK), and en face optical coherence tomography (OCT) with B-scans (Cirrus HD-OCT 5000, Zeiss). Two independent retina specialists graded the AMD stage and the presence of pigment migration across modalities. Sensitivity and positive predictive value (PPV) of RAR were calculated using en face OCT as the reference standard. Results: RAR demonstrated high diagnostic performance, with a sensitivity of 94.7% and a PPV of 93.4% relative to en face OCT. RAR frequently identified pigment migration that was not visible on CFI or FAF, particularly in early AMD and in eyes with media opacity. Distinct morphologic patterns—including hyperreflective foci, thickened retinal pigment epithelium, refractile drusen, and cuticular drusen—were consistently identifiable on RAR. In four eyes with geographic atrophy, RAR detected perifoveal pigment redistribution at least six months before foveal involvement was confirmed by OCT and FAF. Conclusions: RAR imaging is a rapid, sensitive, and clinically practical technique for detecting pigment migration in AMD. By complementing en face OCT and enhancing visualization in cases where standard imaging is limited, RAR may strengthen early disease surveillance, support prognostic assessment, and improve multimodal diagnostic workflows in routine practice. Full article

Background: Optical coherence tomography angiography (OCT-A) provides quantitative assessment of retinal and peripapillary microvasculature and has emerged as a promising tool for glaucoma diagnostics. However, its sensitivity for detecting early glaucomatous progression over short intervals remains uncertain. This study evaluated cross-sectional and short-term longitudinal OCT-A vessel density (VD) metrics in primary open-angle glaucoma (POAG) and explored their relationships with structural (RNFL) and functional (MD) measures. Methods: Sixty eyes (30 POAG, 30 controls) underwent baseline and 6-month examinations including intraocular pressure (IOP), standard automated perimetry (SAP), structural OCT, and OCT-A (RTVue XR Avanti; AngioVue). Parameters analyzed included peripapillary VD (PP-VD), parafoveal VD (PF-VD), foveal avascular zone (FAZ) metrics, FD-300, and RNFL thickness. Between-group comparisons used t-tests or Mann–Whitney U tests. Effect sizes (Cohen’s d), 95% confidence intervals (CI), and ANCOVA models (adjusted for baseline, age, and sex) were included. Longitudinal change was defined as Δ = 6 months − baseline. Pearson correlations evaluated structure–vascular associations. Results: At baseline, POAG eyes showed significantly lower PP-VD, PF-VD, thinner RNFL, and worse MD (all p < 0.001). Strong correlations were observed between RNFL and PP-VD (r ≈ 0.7). Over 6 months, glaucoma eyes showed small but statistically significant reductions in RNFL (Δ = −1.04 µm), MD (Δ = −0.10 dB), and PP-VD (Δ = −0.57%), whereas controls remained stable. However, the absolute OCT-A changes were small and largely within the known range of test–retest variability. ANCOVA demonstrated a significant adjusted group effect only for PP-VD (B = −1.22%, 95% CI −1.53 to −0.90; p < 0.001). Conclusions: OCT-A demonstrated clear cross-sectional differences between POAG and controls and strong structure–vascular associations. However, with only two measurements over a 6-month interval, the study cannot distinguish true glaucomatous progression from physiological or device-related variability. Short-term changes should therefore be interpreted cautiously. PP-VD remains the most robust and consistent OCT-A parameter, but larger, longer, and prospectively powered studies are required to validate OCT-A as a reliable biomarker for progression. Full article

Background/Objectives: Disorganization of the retinal inner layers (DRIL) is an important biomarker of diabetic macular edema (DME) that has a very strong association with visual acuity (VA) in patients. But the unavailability of annotated training data from experts severely limits the adaptability of models pretrained on real-world images owing to significant variations in the domain, posing two primary challenges for the design of efficient computerized DRIL detection methods. Methods: In an attempt to address these challenges, we propose a novel, self-supervision-based learning framework that employs a huge unlabeled optical coherence tomography (OCT) dataset to learn and detect clinically applicable interpretations before fine-tuning with a small proprietary dataset of annotated OCT images. In this research, we introduce a spatial Bootstrap Your Own Latent (BYOL) with a hybrid spatial aware loss function aimed to capture anatomical representations from unlabeled OCT dataset of 108,309 images that cover various retinal abnormalities, and then adapt the learned interpretations for DRIL classification employing 823 annotated OCT images. Results: With an accuracy of 99.39%, the proposed two-stage approach substantially exceeds the direct transfer learning models pretrained on ImageNet. Conclusions: The findings demonstrate the efficacy of domain-specific self-supervised learning for rare retinal pathological detection tasks with limited annotated data. Full article

Background/Objectives: Reversibility of glaucomatous optic-disc cupping, following intraocular pressure (IOP) reduction, represents a fascinating structural response observed in both pediatric and adult patients. This review summarizes evidence on its mechanisms, diagnostic evaluation, and clinical significance. Methods: A comprehensive review of experimental, clinical, and imaging-based studies investigating optic-disc cupping reversibility was conducted. Findings were categorized by patient population, imaging technique, and follow-up duration. Results: Experimental models established a strong correlation between IOP reduction and optic-disc structural recovery. Pediatric glaucoma demonstrated the greatest reversibility due to enhanced ocular tissue elasticity, whereas adult cases showed limited yet measurable structural changes after sustained IOP lowering. Imaging modalities, including confocal scanning laser ophthalmoscopy and spectral-domain optical coherence tomography (SD-OCT), consistently confirmed quantitative disc-shape changes correlated with pressure reduction. Conclusions: Although optic-disc cupping reversal reflects biomechanical and glial remodeling rather than true neuronal recovery, it remains an important biomarker of successful IOP control. Advanced imaging provides valuable insights into optic-nerve-head (ONH) biomechanics and may improve glaucoma management. Full article

Disability accumulation in multiple sclerosis often occurs independent of relapses and inflammatory activity, yet reliable predictors for early progression remain limited. Our aim was to evaluate the utility of baseline fluid and optical coherence tomography (OCT) biomarkers for predicting early disability progression in newly diagnosed relapsing–remitting MS (RRMS). We performed a monocentric observational cohort study on 72 RRMS patients that were enrolled within 6 months of diagnosis and followed for 2 years. Baseline serum and cerebrospinal fluid (CSF) samples were analyzed for neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP) and chitinase-3-like protein 1 (CHI3L1). Confirmed disability progression at 1 year (1yCDP) was defined by either an increase in Expanded Disability Status Scale or a ≥20% worsening on Nine-Hole Peg Test or Timed 25-Foot Walk. Seventeen patients (23.6%) developed 1yCDP. Elevated baseline CSF GFAP (OR = 5.79, 95% CI 1.72–19.45; p = 0.005) and CSF CHI3L1 thickness (OR = 4.14, 95% CI 1.49–11.49; p = 0.006) and reduced ganglion cell-inner plexiform layer (GCIPL) thickness (OR = 0.90, 95% CI 0.84–0.97; p = 0.006) independently predicted 1yCDP. A multivariate model including age, CSF GFAP and GCIPL achieved AUC = 0.831, with a sensitivity of 87.5% and specificity of 61.5%. This study provides evidence that baseline patient profiling using CSF GFAP, CSF CHI3L1 and GCIPL thickness may help predict early disability progression in RRMS. Full article