Layer Segmentation Research Articles

Factors Associated with Lamina Cribrosa Microvasculature Determined via Swept-Source Optical Coherence Tomography Angiography.

The lamina cribrosa microvasculature reduction was associated with the posterior deformation of lamina cribrosa, as well as the functional deterioration, in all spectrums of open-angle glaucoma. To investigate the factors associated with the lamina cribrosa vessel density (LCVD) determined via swept-source optical coherence tomography angiography (SS-OCTA). The optic nerve head (ONH) scan was obtained using SS-OCTA (PLEX Elite 9000; Carl Zeiss Meditec, Inc., Dublin, CA, USA). The lamina cribrosa curvature index (LCCI) was assessed using seven horizontal B-scan images across the ONH. The LCVD was calculated from the segmented layer at the level of lamina cribrosa (LC). Primary open angle glaucoma (POAG) eyes were categorized into two groups according to the visual field mean deviation (VF MD) (mild to moderate [≥ -12 dB] and advanced [< -12 dB]). The factors associated with the LCVD were evaluated using linear regression analysis. A total of 127 POAG and 43 healthy eyes were included. POAG eyes showed significantly thinner circumpapillary retinal nerve fiber layer (cpRNFL) and macular ganglion cell inner plexiform layer (mGCIPL), lower LCVD, and greater LCCI compared to healthy eyes (all P<0.05). In the mild to moderate group, lower LCVD was associated with worse VF MD, thinner cpRNFL and mGCIPL, and greater LCCI (all P<0.05). In the advanced group, the LCVD was associated with VF MD and LCCI (both P<0.05). A greater LCVD was correlated with a greater LCCI in the healthy group (P =0.045). Reduced LCVD was associated with an increased LCCI in all spectrums of POAG. LC deformation may affect the ONH microvasculature in glaucoma.

Validation of Deep Learning-based Automatic Retinal Layer Segmentation Algorithms for AMD with Two SD-OCT Devices

PurposeSegmentations of retinal layers in spectral-domain optical coherence tomography (SD-OCT) images serve as a crucial tool for identifying and analyzing the progression of various retinal diseases, encompassing a broad spectrum of abnormalities associated with age-related macular degeneration (AMD). The training of deep-learning algorithms necessitates well-defined ground-truth labels, validated by experts, to delineate boundaries accurately. However, this resource-intensive process has constrained the widespread application of such algorithms across diverse OCT devices. This work validates deep learning image segmentation models across multiple OCT devices by testing robustness in generating clinically relevant metrics. DesignProspective, comparative study. ParticipantsAdults over 50 years of age with no AMD to advanced AMD, as defined in the Age-Related Eye Disease Study (AREDS)), in at least one eye, were enrolled. 402 SD-OCT scans were used in this study. MethodsWe evaluate two separate state-of-the-art segmentation algorithms through a training process using images obtained from one OCT device (Heidelberg-Spectralis) and subsequent testing using images acquired from two OCT devices (Heidelberg-Spectralis and Zeiss-Cirrus). This assessment is performed on a dataset that encompasses a range of retinal pathologies, spanning from disease-free conditions to severe forms of AMD, with a focus on evaluating the device independence of the algorithms. Main Outcome MeasuresPerformance metrics (mean-squared-error, mean-absolute-error, dice-coefficients) for the segmentations of the internal limiting membrane (ILM), retinal-pigment-epithelium (RPE), and RPE to Bruch’s-membrane (BM) region, along with en face thickness maps, volumetric estimations (in mm3). Violin plots and Bland-Altman plots comparing predictions against ground-truth are also presented. ResultsThe UNet and DeepLabv3, trained on Spectralis B-scans, demonstrate clinically useful outcomes when applied to Cirrus test B-scans. Review of the Cirrus test-data by two independent annotators revealed that the aggregated-mean-absolute-error in pixels for ILM was 1.82±0.24 (equivalent to 7.0±0.9 μm) and for RPE was 2.46±0.66 (9.5±2.6 μm). Additionally, the dice-similarity-coefficient for the RPE-drusen complex (RPE-DC) region, comparing predictions to ground truth, reached 0.87±0.01. ConclusionIn the pursuit of task-specific goals such as retinal layer segmentation, a segmentation network has the capacity to acquire domain-independent features from a large training dataset. This enables the utilization of the network to execute tasks in domains where ground truth is hard to generate.

Relationship between autism spectrum disorder and peripapillary intraretinal layer thickness: a pediatric retrospective cross-sectional study.

Autism spectrum disorder (ASD) often presents with atypical visual processing, prompting investigation into its connection with retinal features. This study aimed to (I) compare intraretinal layer thickness in the peripapillary region between ASD and neurotypical (NT) groups, (II) assess associations between intraretinal layer thickness and clinical parameters (social functioning and cognitive levels) in ASD subjects, and (III) evaluate the potential of intraretinal layer thickness as a biomarker for ASD. Participants were recruited through convenience sampling from the Children's Mental Health Research Center at The Affiliated Brain Hospital of Nanjing Medical University and the Department of Ophthalmology at The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, between December 2019 and August 2023. Intraretinal layer thickness in peripapillary region was quantified using optic coherence tomography images with automated layer segmentation performed by OCTExplorer software on 47 individuals with ASD (aged 7-13 years) and age- and sex-matched NT controls. Inter-group comparisons were conducted using unpaired t-tests, Welch's t-tests, or Mann-Whitney U tests as appropriate. Correlations with social functioning (measured by Social Responsiveness Scale scores) and cognitive levels [measured by total intelligence quotient (IQ) scores] were examined using the Spearman correlation coefficient. Stepwise regression analysis was conducted to assess predictive power. Significant inter-group differences (P<0.05) were observed in ganglion cell layer and inner nuclear layer (INL) thickness across global and specific quadrant regions. Participants had a mean age of 9.57±1.83 years in the ASD group and 9.89±1.70 years in the age-matched NT group. While no correlation was found between retinal sublayer thickness and social functioning on ASD subjects (all P>0.05), there was a notable correlation between INL thickness in the infero-nasal quadrant and cognitive level (r=0.381, P=0.014). Stepwise regression analysis identified global INL thickness as a significant predictor of total IQ scores (β=3.986, P=0.034), with an R2 of 0.110 and a root mean square error of 21.900. This study highlights significant differences in retinal features between ASD and NT groups, with implications for understanding ASD pathogenesis and complexity. The findings suggest that easily observable retinal features hold promise as biomarkers for ASD, warranting further investigation.

Critical adsorption of polyelectrolytes onto highly oppositely charged surfaces: Effects of charge renormalization.

The critical adsorption conditions of polyelectrolytes (PEs) onto planar, cylindrical, and spherical surfaces were obtained by solving the Edwards equation using the Wentzel-Kramers-Brillouin (WKB) method. It demonstrated to provide a suitable analytical approach for all three geometries, in conformity with some experimental results for weakly charged micelles. However, our Monte Carlo simulations implementing approximate solutions of the nonlinear Poisson-Boltzmann equation for highly charged surfaces indicated recently the emergence of a limiting value of ionic strength due to a nonlinear dependence of the electrostatic (ES) potential on the surface-charge density σ. Beyond this limiting ionic strength, the PE adsorption no longer occurs, shifting the standard paradigm. In this work, we employ the concept of a renormalized charge and use the WKB method to study the effects of this nonlinearity on the critical adsorption conditions, density profile, and adsorbed layer of PE segments, all in comparison with the results of the linear Debye-Hückel (DH) approach. Charge renormalization makes it possible to use the known WKB solutions in the DH regime also for surfaces with high σ, introducing a saturation effect observed in the nonlinear case. The larger ES screening affects the density profile and the adsorbed layer of PEs, promoting a more dispersed distribution of PEs at higher surface-charge densities. Our analytical results for the critical adsorption curve reproduce the limiting ionic strength for high σ and also recover the DH regime at low σ.

Circumpapillary OCT-based multi-sector analysis of retinal layer thickness in patients with glaucoma and high myopia

Glaucoma is the leading cause of irreversible blindness worldwide. The diagnosis process for glaucoma involves the measurement of the thickness of retinal layers in order to track its degeneration. The elongated shape of highly myopic eyes can hinder this diagnosis process, since it affects the OCT scanning process, producing deformations that can mimic or mask the degeneration caused by glaucoma. In this work, we present the first comprehensive cross-disease analysis that is focused on the anatomical structures most impacted in glaucoma and high myopia patients, facilitating precise differential diagnosis from those solely afflicted by myopia. To achieve this, a fully automatic approach for the retinal layer segmentation was specifically tailored for the accurate measurement of retinal thickness in both highly myopic and emmetropic eyes. To the best of our knowledge, this is the first approach proposed for the analysis of retinal layers in circumpapillary optical coherence tomography images that takes into account the elongation of the eyes in myopia, thus addressing critical diagnostic needs. The results from this study indicate that the temporal superior (mean difference 11.1μm, p<0.05), nasal inferior (13.1μm, p<0.01) and temporal inferior (13.3μm, p<0.01) sectors of the retinal nerve fibre layer show the most significant reduction in retinal thickness in patients of glaucoma and myopia with regards to patients of myopia.

Particle identification in high-granularity 3D calorimeters for space-borne applications

High granularity 3D calorimeters offer the potential to precisely reconstruct the 3D topology of electromagnetic and hadronic showers originating from isotropic sources. This distinctive capability creates the opportunity for applying reconstruction and analysis methods that could yield additional information compared to those based on the traditional layer-by-layer energy deposit analysis common in particle and astroparticle physics experiments utilizing calorimeters with layer segmentation. In this study, we present a strategy for analyzing the energy deposit in a crystal array calorimeter, utilizing the 3D parametrization of both longitudinal and transversal shapes of showers to implement likelihood tests on single events. While this analysis was developed using the High Energy cosmic Radiation Detector (HERD) calorimeter as a case study, its applicability may extend to any high granularity, homogeneous, isotropic calorimeter employed in particle physics experiments.

Exploring optical coherence tomography parameters in eyes with myopic tilted disc

BackgroundTo investigate the impact of optic disc torsion (ODT), horizontal disc tilt (HDT) angle, and ovality index (OI) on different retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) segments in healthy myopic eyes.MethodsODT and OI were measured from fundus photographs. HDT angle, peripapillary RNFL, and macular GCIPL were measured by swept-source optical coherence tomography (SS-OCT). The association between optic disc morphology and the RNFL/GCIPL thickness were evaluated, with age and axial length (AL) adjusted.ResultsAmong 530 healthy myopic eyes of 284 participants (mean age: 41.7 years, mean spherical equivalent: − 7.70 D, and mean AL: 26.6 mm), 335 eyes (63.2%) had temporal disc torsion (temporal group) and 195 eyes (36.8%) had nasal disc torsion (nasal group). For the nasal group, a larger OI was associated with thinner superior-to-superonasal GCIPL (β = − 7.465 to − 6.972, both P = 0.024) and temporal RNFL sectors (β = − 49.596 to − 27.748, P ≤ 0.014). For the temporal group, a larger OI was associated with thinner superior-to-nasal (β = − 50.255 to − 22.093, P ≤ 0.006) and thicker temporal RNFL sectors (β = 29.015 to 56.890, P ≤ 0.003). Additionally, a larger HDT angle was associated with thinner superior-to-nasal RNFL sectors (β = − 0.559 to − 0.242, P ≤ 0.036) and thinner superior-to-superotemporal GCIPL sectors (β = − 0.084 to − 0.069, P ≤ 0.037).ConclusionsThe optic disc tortional direction was associated with the measurement of different RNFL and GCIPL sectors independent of the AL and age. These should be considered when constructing a myopic normative database.

Fully automatic deep convolutional approaches for the screening of neurodegeneratives diseases using multi-view OCT images

The prevalence of neurodegenerative diseases (NDDs) such as Alzheimer’s (AD), Parkinson’s (PD), Essential tremor (ET), and Multiple Sclerosis (MS) is increasing alongside the aging population. Recent studies suggest that these disorders can be identified through retinal imaging, allowing for early detection and monitoring via Optical Coherence Tomography (OCT) scans. This study is at the forefront of research, pioneering the application of multi-view OCT and 3D information to the neurological diseases domain. Our methodology consists of two main steps. In the first one, we focus on the segmentation of the retinal nerve fiber layer (RNFL) and a class layer grouping between the ganglion cell layer and Bruch’s membrane (GCL-BM) in both macular and optic disc OCT scans. These are the areas where changes in thickness serve as a potential indicator of NDDs. The second phase is to select patients based on information about the retinal layers. We explore how the integration of both views (macula and optic disc) improves each screening scenario: Healthy Controls (HC) vs. NDD, AD vs. NDD, ET vs. NDD, MS vs. NDD, PD vs. NDD, and a final multi-class approach considering all four NDDs. For the segmentation task, we obtained satisfactory results for both 2D and 3D approaches in macular segmentation, in which 3D performed better due to the inclusion of depth and cross-sectional information. As for the optic disc view, transfer learning did not improve the metrics over training from scratch, but it did provide a faster training. As for screening, 3D computational biomarkers provided better results than 2D ones, and multi-view methods were usually better than the single-view ones. Regarding separability among diseases, MS and PD were the ones that provided better results in their screening approaches, being also the most represented classes. In conclusion, our methodology has been successfully validated with an extensive experimentation of configurations, techniques and OCT views, becoming the first multi-view analysis that merges data from both macula-centered and optic disc-centered perspectives. Besides, it is also the first effort to examine key retinal layers across four major NDDs within the framework of pathological screening.

Prominin-1-null Xenopus laevis develop subretinal drusenoid-like deposits, cone-rod dystrophy and RPE atrophy.

Prominin-1 (PROM1) variants are associated with inherited, non-syndromic vision loss. We used CRISPR/Cas9 to induce prom1-null mutations in Xenopus laevis and then tracked retinal disease progression from the ages of 6 weeks to 3 years. We found that prom1-null-associated retinal degeneration in frogs was age-dependent and involved retinal pigment epithelium (RPE) dysfunction preceding photoreceptor degeneration. Before photoreceptor degeneration occurred, aging prom1-null frogs developed larger and increasing numbers of cellular debris deposits in the subretinal space and outer segment layer, which resembled subretinal drusenoid deposits (SDDs) in their location, histology and representation as seen by color fundus photography and optical coherence tomography (OCT). Evidence for an RPE origin of these deposits included infiltration of pigment granules into the deposits, thinning of the RPE as measured by OCT, and RPE disorganization as measured by histology and OCT. The appearance and accumulation of SDD-like deposits and RPE thinning and disorganization in our animal model suggests an underlying disease mechanism for prom1-null-mediated blindness that involves death and dysfunction of the RPE preceding photoreceptor degeneration, instead of direct effects upon photoreceptor outer segment morphogenesis, as was previously hypothesized.

Automated segmentation of retinal layers in optical coherence tomography images using Xception70 feature extraction

Optical coherence tomography (OCT) imaging plays a critical role in evaluating retinal layer thickness, serving as a pivotal diagnostic tool for numerous retinal conditions. However, challenges such as speckle noise, poor image contrast, and ambiguous retinal detachments, like drusen, often hinder accurate segmentation of retinal layers. To address these challenges and enhance diagnostic precision, we introduce the Retinal Segmentation Network, or "Ret-Seg Net," a deep neural network-based approach. Leveraging the advanced Xception70 feature extractor, Ret-Seg Net extracts and comprehends the intricate properties of retinal layers. By integrating acquired feature maps from Xception70 into the atrous spatial pyramid-pooling module, Ret-Seg Net extracts multiscale feature information. The encoder-decoder module of Ret-Seg Net achieves automated segmentation of retinal layers in OCT images by reconstructing distinct retinal layer borders. This advanced module accurately recognizes and differentiates retinal layer boundaries, providing precise and reliable segmentation. Validation of our approach using real-time images and the Duke dataset, comprising 310 volumes with 40 B-scans each, demonstrates outstanding performance. Mean intersection over union (MIoU) and sensitivity (Se) metrics achieved remarkable values of 94.52 % and 96.25 % respectively. Furthermore, our approach offers a versatile segmentation framework applicable to various tissues and cell types in clinical settings. Automating segmentation of retinal layers enhances precision in disease identification and monitoring while significantly improving labor efficiency by reducing the need for manual segmentation.

Extracellular Vesicles Derived from Adipose-Derived Mesenchymal Stem Cells Alleviate Apoptosis and Oxidative Stress of Retinal Pigment Epithelial Cells Through Activation of Nrf2 Signaling Pathway.

Purpose: To examine the potential protective effects of adipose-derived mesenchymal stem cell-derived extracellular vesicles (ASC-EVs) on ARPE-19 cells exposed to hydrogen peroxide (H2O2) stress and to evaluate their ability to delay retinal degeneration in Royal College of Surgeons (RCS) rats. Methods: ARPE-19 cells were pre-treated with ASC-EVs for 24 h, followed by exposure to 200 μM H2O2 for an additional 24 h. RCS rats received an intravitreal injection of phosphate-buffered saline in one eye and ASC-EVs in the other eye. Results: ASC-EV pretreatment significantly protected against H2O2 in the Cell Counting Kit-8 assay and was also effective in the lactate dehydrogenase-release assay. It notably reduced early apoptosis (Annexin V-fluorescein isothiocyanate/propidium iodide assay) and late apoptosis (Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling assay), while significantly decreasing intracellular reactive oxygen species, glutathione levels, and superoxide dismutase activity. NFE2L2, HMOX1, and NQO1 mRNA levels, along with Nrf2, HO-1, and NQO1 protein levels, were significantly elevated with ASC-EV pretreatment. Compared with ARPE-19-derived EVs, 11 miRNAs were upregulated and 34 were downregulated in ASC-EVs. In RCS rats, intravitreal injections of ASC-EVs led to significant preservation of the outer nuclear layer and photoreceptor segments, along with increased nuclear Nrf2 expression and elevated HO-1 and NQO1 levels in the inner retina. Eyes that received intravitreal injections of ASC-EVs demonstrated significantly preserved electroretinography a- and b-wave amplitudes at 1 week post-injection, though this effect faded by 2 weeks. Conclusions: ASC-EVs mitigated apoptosis and oxidative stress in ARPE-19 cells subjected to H2O2 exposure and temporarily slowed retinal degeneration in RCS rats via Nrf2 pathway activation by miRNAs.

Azobenzene-Based Main-Chain Liquid Crystalline Polymers Bearing Periodically Installed Alkyl, PEG, or Fluoroalkyl Segments and Photoisomerization Studies

ABSTRACT In the present study, liquid crystalline polymers (LCPs) were prepared by melt-transesterification of azobenzene-bearing diols and diethyl malonate (DEM) derivatized monomers. The effect of the nature and length of the installed pendant segments on the mesomorphic properties of the prepared LCPs was investigated by differential scanning calorimetry (DSC), X-ray diffraction (XRD), and polarized optical microscopy (POM) studies. The formation of layered morphology was inferred from X-ray scattering analysis arising from the colocation of rigid azobenzene moieties in one layer and the flexible pendant segments in alternate layers due to the zigzag folding of the polymer backbone. The linear variation of the interlamellar spacing with the number of carbon atoms in the pendant alkyl segments corroborates the proposed zigzag backbone folding in the polymers. The rate constant values obtained from the photoisomerization studies of the isomeric polymers and model compound, which are in the same ballpark, reveal that the photoisomerization process of such polymers is not affected by the position or size of the azobenzene unit.

PEARLS İN THE DİAGNOSİS AND TREATMENT OF RETİNAL AND CHOROİDAL DİSEASES

Relevance. Retinal and choroidal diseases of the eye are common health issue among people who suffer with environmental insults and sistemic diseases. The aim of the study: to highlight the practical challenges in diagnosing and treating retinal diseases. Material and methods. The choroid and retina are highly vascularized, express a very high metabolic activity, and are prone to be affected by minör environmental insults and systemic diseases. These layers' delicate, small structural sizes present similar aspects and signs due to various local and distant pathologies. Advances in diagnostic tools have enabled clinicians to identify subtle changes within the posterior segment layers, leading to accurate diagnosis and treatment. However, to fulfill their role effectively, clinicians must ask the right questions, conduct thorough evaluations, and possess in-depth knowledge. Results and conclusion. Through the presentation of different cases, common pitfalls will be discussed to help simplify the complexity of diagnosis and facilitate appropriate treatment.

HyFormer: a hybrid transformer-CNN architecture for retinal OCT image segmentation.

Optical coherence tomography (OCT) has become the leading imaging technique in diagnosing and treatment planning for retinal diseases. Retinal OCT image segmentation involves extracting lesions and/or tissue structures to aid in the decisions of ophthalmologists, and multi-class segmentation is commonly needed. As the target regions often spread widely inside the retina, and the intensities and locations of different categories can be close, good segmentation networks must possess both global modeling capabilities and the ability to capture fine details. To address the challenge in capturing both global and local features simultaneously, we propose HyFormer, an efficient, lightweight, and robust hybrid network architecture. The proposed architecture features parallel Transformer and convolutional encoders for independent feature capture. A multi-scale gated attention block and a group positional embedding block are introduced within the Transformer encoder to enhance feature extraction. Feature integration is achieved in the decoder composed of the proposed three-path fusion modules. A class activation map-based cross-entropy loss function is also proposed to improve segmentation results. Evaluations are performed on a private dataset with myopic traction maculopathy lesions and the public AROI dataset for retinal layer and lesion segmentation with age-related degeneration. The results demonstrate HyFormer's superior segmentation performance and robustness compared to existing methods, showing promise for accurate and efficient OCT image segmentation. .

Diverse Data Generation for Retinal Layer Segmentation With Potential Structure Modeling.

Accurate retinal layer segmentation on optical coherence tomography (OCT) images is hampered by the challenges of collecting OCT images with diverse pathological characterization and balanced distribution. Current generative models can produce high-realistic images and corresponding labels without quantitative limitations by fitting distributions of real collected data. Nevertheless, the diversity of their generated data is still limited due to the inherent imbalance of training data. To address these issues, we propose an image-label pair generation framework that generates diverse and balanced potential data from imbalanced real samples. Specifically, the framework first generates diverse layer masks, and then generates plausible OCT images corresponding to these layer masks using two customized diffusion probabilistic models respectively. To learn from imbalanced data and facilitate balanced generation, we introduce pathological-related conditions to guide the generation processes. To enhance the diversity of the generated image-label pairs, we propose a potential structure modeling technique that transfers the knowledge of diverse sub-structures from lowly- or non-pathological samples to highly pathological samples. We conducted extensive experiments on two public datasets for retinal layer segmentation. Firstly, our method generates OCT images with higher image quality and diversity compared to other generative methods. Furthermore, based on the extensive training with the generated OCT images, downstream retinal layer segmentation tasks demonstrate improved results. The code is publicly available at: https://github.com/nicetomeetu21/GenPSM.

Segmented catalyst layer with varied catalyst loading to improve the cost performance of proton exchange membrane electrolysis cell, a numerical investigation

In this work, a steady-state, three-dimensional and non-isothermal numerical model for a proton exchange membrane electrolysis cell (PEMEC) is established. Based on this model, the distribution of catalyst loading is specifically designed according to the flow characteristics of both parallel and serpentine channels. In general, the catalyst loading is progressively reduced from inlet to outlet along the flow direction to match the local water content, leading to an innovative segmented catalyst layer which has not been studied yet for PEMEC applications. The electrochemical behavior of different segmentation schemes is investigated by comparing their polarization curves normalized by either electrode area or catalyst loading, while other physical fields such as velocity, pressure, water mole fraction and temperature distributions are also characterized. The numerical results reveal that a reasonable distribution of catalyst can reduce its amount of usage while still maintaining most of the PEMEC performance. In other words, the cost performance is significantly improved. This is mainly attributed to the full use of uneven water distribution in the flow channel, which improves the catalyst utilization efficiency significantly. This strategy is proved to be effective for both serpentine and parallel channels, ensuring a broad application prospect.

OCT Changes Observed during the Progression of Early Age-Related Macular Degeneration

Automated retinal cell layer segmentation empowers OCT as a precise tool for characterizing morphologic features of retinal health throughout age-related macular degeneration (AMD) progression, particularly in advance of more visible biomarkers such as drusen and macular pigmentary changes. Few studies have examined OCT changes in eyes progressing from early to intermediate disease, or combined examinations of cell layer thickness, reflectivity, and heterogeneity. Therefore, this study analyzed OCTs from eyes progressing from early to intermediate AMD to identify changes in retinal morphology and reflectivity that may serve as biomarkers of early progression. Retrospective cohort study. Patients ≥50 years with a diagnosis of AMD and with high-quality ipsilateral OCTs in both early and intermediate stage disease. Fifty OCTs from 25 patients were automatically segmented using a previously validated artificial intelligence-driven algorithm. Changes in the mean and standard deviation of cell layer thickness and reflectivity with progression through stages were calculated for 90 retinal volumes with the help of a novel Python-based analysis tool. The primary outcomes were significant changes to cell layer thickness, reflectivity, and heterogeneity with progression of AMD. With progression from early to intermediate disease, photoreceptor outer segments diffusely thinned. Within the ellipsoid zone, the fovea and parafovea were thinned with a simultaneous increase in thickness variability and a decrease in parafoveal reflectivity. The retinal pigment epithelium-Bruch's membrane complex underwent diffuse thickening and increased thickness variability alongside a decrease in foveal and parafoveal reflectivity. These findings correlate with the known histopathology of early AMD and identify measurable OCT trends through the earliest stages of disease. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Comparative analysis of one-step and two-step full thickness skin grafting and secondary intention healing for skin defects after surgical management of plantar malignant melanoma.

Plantar malignant melanoma is largely managed surgically, particularly in its early stages. However, the plantar region has a lower survival rate of skin grafts than other regions. Furthermore, complete wound healing occurs over a long period of time, postoperatively. Thus, in this study, we retrospectively analyzed the use of skin grafts to reconstruct skin defects, as postoperative complications of plantar malignant melanoma. Forty-nine patients, (23 males, 26 females; mean age 70.4-years) underwent excisional surgery for plantar malignant melanoma at our hospital, between March 2018 and December 2022. The time from initial surgery to wound healing was analyzed, using a multivariate Cox proportional hazards model, to identify related factors. We excluded cases with lesions in non-weight-bearing areas and cases with segmental layer grafts, based on multivariate analysis, to eliminate bias when comparing a one-step resection and reconstruction technique to resection followed by waiting for granulation to occur before reconstruction. Patients were categorized into three cohorts. The first and second cohorts had undergone one-step and two-step skin grafting, respectively. Patients in the third cohort underwent secondary intention healing without skin grafting. The results revealed that the factors associated with wound-healing time included a defect size of >1800 mm2, in addition to two-step and split-thickness skin grafting. Therefore, Kaplan-Meier curves were constructed across the three cohorts, based on the data of 37 patients. Nine cases of non-weight-bearing areas and three cases of split-thickness skin grafts were excluded from the original total of 49 patients. The median times from the initial surgery to wound healing were 14.6, 12.0, and 21.9 weeks for the one- and two-step skin grafting and secondary intention healing cohorts, respectively. A statistically significant difference in the treatment time between the skin grafting and secondary intention healing cohorts was observed (p < 0.001) Moreover, a statistically significant difference in the treatment time between the one- and two-step skin grafting cohorts was noted (p = 0.046). Thus, two-step skin grafting after surgical treatment for plantar malignant melanoma may shorten the overall treatment duration by allowing granulation to occur.

Segmentation of supragranular and infragranular layers in ultra-high-resolution 7T ex vivo MRI of the human cerebral cortex.

Accurate labeling of specific layers in the human cerebral cortex is crucial for advancing our understanding of neurodevelopmental and neurodegenerative disorders. Building on recent advancements in ultra-high-resolution ex vivo MRI, we present a novel semi-supervised segmentation model capable of identifying supragranular and infragranular layers in ex vivo MRI with unprecedented precision. On a dataset consisting of 17 whole-hemisphere ex vivo scans at 120 $\mu $m, we propose a Multi-resolution U-Nets framework that integrates global and local structural information, achieving reliable segmentation maps of the entire hemisphere, with Dice scores over 0.8 for supra- and infragranular layers. This enables surface modeling, atlas construction, anomaly detection in disease states, and cross-modality validation while also paving the way for finer layer segmentation. Our approach offers a powerful tool for comprehensive neuroanatomical investigations and holds promise for advancing our mechanistic understanding of progression of neurodegenerative diseases.

Thickness-Dependent Segmental Dynamics in Supported Thin Films: Insights from a Dynamically Correlated Network Model.

A large body of experimental studies shows that the local dynamics in supercooled liquids are significantly altered by spatial nanoconfinement. In a previous study, we proposed a concept of a dynamically correlated network (DCN) model, which assumes that segments in a supercooled liquid undergo cooperative rearrangements within a network-like cluster. We further demonstrated that a model modified for freestanding thin films can predict for the glass transition dynamics in atactic polystyrene (PS) films consistent with experimental results. In this study, we adapted the model to apply it to supported thin films by introducing a layer of virtual vacant segments at the free surface and virtual anchoring segments at the liquid/substrate interface. The latter segments, carrying a finite number of virtual segments, reduce mobility at the interface. We evaluated the cooperative cluster size and distribution with respect to temperature and film thickness, along with the average relaxation time and glass transition temperature Tg for supported thin films of PS. The model predicted that the thickness dependence of Tg for PS becomes stronger with increasing time scale, and this result agreed well with experimental data across different timescales from pseudothermodynamic and dynamic measurements. The results provide insights into the origin of the dynamical decoupling between pseudothermodynamic and dynamic glass transition behaviors.