Tomography Image Analysis Research Articles

Age and Gender-Related Changes in Choroidal Thickness: Insights from Deep Learning Analysis of Swept-Source OCT Images.

The choroid is a vital vascular layer of the eye, essential for maintaining ocular health. Understanding its structural variations, particularly choroidal thickness (CT), is crucial for the early detection of diseases, such as age-related macular degeneration (AMD), high myopia (HM), and diabetes mellitus (DM). Recent advancements in deep learning have significantly improved the segmentation and measurement of choroidal layers. This study aims to investigate age- and gender-related changes in CT and its components through deep learning analysis of swept-source optical coherence tomography (SS-OCT) images. A total of 262 participants (136 females and 126 males) were recruited from Peking University International Hospital. Exclusion criteria included ocular pathologies and systemic conditions. SS-OCT was utilized for CT, Sattler layer-choriocapillaris complex thickness (SLCCT), and Haller layer thickness (HLT) measurements. auto-measurement method, based on deep learning algorithms, ensured accuracy. Ethics approval and informed consent were obtained from all participants. Significant thinning of CT and SLCCT was observed after the age of 60, with HLT declining after the age of 30. Females exhibited marked thinning between the ages of 40 and 50, while males began to show thinning at age 60. This research highlights age-related changes in choroidal thickness, with a particular emphasis on gender differences. The findings suggest that females experience earlier thinning, potentially attributable to hormonal changes. Additionally, the study validates the efficiency of deep learning algorithms in measuring choroidal thickness, thereby enhancing the reliability of clinical practice.

Artificial intelligence for the analysis of intracoronary optical coherence tomography images: a systematic review

Abstract Intracoronary optical coherence tomography (OCT) is a valuable tool for, among others, periprocedural guidance of percutaneous coronary revascularization and the assessment of stent failure. However, manual OCT image interpretation is challenging and time-consuming, which limits widespread clinical adoption. Automated analysis of OCT frames using artificial intelligence (AI) offers a potential solution. For example, AI can be employed for automated OCT image interpretation, plaque quantification and clinical event prediction. Many AI models for these purposes have been proposed in recent years. However, these models have not been systematically evaluated in terms of model characteristics, performances and bias. We performed a systematic review of AI models developed for OCT analysis to evaluate the trends and performances, including a systematic evaluation of potential sources of bias in model development and evaluation.

Central nervous system vascular complications associated with the acute form of steroid-responsive meningitis-arteritis.

This retrospective study aims to describe the vascular events in the central nervous system (CNS) associated with the acute form of steroid-responsive meningitis-arteritis (SRMA), to compare the clinical features of dogs with and without such complications and to potentially identify predisposing factors for these events. Dogs with a presumptive diagnosis of SRMA visited between 2018 and 2023 with full medical records that underwent neurological examination, blood testing, cervical computed tomography or magnetic resonance imaging and cerebrospinal fluid (CSF) analysis were included. Thirty-three dogs were included and divided in two groups. Group 1 included 7 (21,2 %) dogs with vascular complications secondary to SRMA (spinal cord ischemic and/or hemorrhagic infarcts, spinal cord subdural hematomas, intracranial subarachnoid hemorrhages), and group 2 included 26 (78,8 %) dogs with non-complicated SRMA. Age, breed, sex, presence of neurological deficits, CSF abnormalities and presence of relapses were factors evaluated for potential association with vascular complications of SRMA. Six dogs in group 1 were Golden Retrievers (85,7 %), and there was a significant association between this breed and the occurrence of vascular complications (P = 0.017). Presence of neurological deficits (P = 0.001) and xanthochromic CSF (P = 0.001) were also associated with vascular complications in dogs with SRMA. Hemorrhagic or ischemic lesions in the CNS can be a complication of the acute form of SRMA, and Golden Retrievers appear to be more affected. Dogs with vascular complications show often neurological deficits and CSF xanthochromia.

Using the coefficient of determination to identify injury regions after stroke in pre-clinical FDG-PET images

Background:In the analysis of brain fluorodeoxyglucose positron emission tomography (FDG-PET) images, intensity normalization is a necessary step to reduce inter-subject variability. However, the choice of the most appropriate normalization method in stroke studies remains unclear, as demonstrated by inconsistent findings in the literature. Materials and methods:Here, we propose a regression- and single-subject-based model for analyzing FDG-PET images without intensity normalization. Two independent data sets were collected before and after middle cerebral artery occlusion (MCAO), with one comprising 120 rats and the other 96 rats. After data preprocessing, voxel intensities in the same region and hemisphere were paired before and after the MCAO scan. A linear regression model was applied to the paired data, and the coefficient of determination R2 was calculated to measure the linearity. The R2 values between the ipsilateral and contralateral hemispheres were compared, and significant regions were defined as those with reduced linearity. Our method was compared with voxel-wise analysis under different intensity normalization methods and validated using the triphenyl tetrazolium chloride (TTC) staining data. Results:The significant regions identified by the proposed method showed a large degree of overlap with the infarcted regions identified by TTC data, as measured by the Dice similarity coefficient (DSC). The average DSC of the proposed method was 59.7%, whereas the DSCs of the existing approaches ranged from 41.4%∼51.3%. Additional validation using receiver operating characteristic (ROC) demonstrated that the area under the curve (AUC) of the average ROC curves reached 0.84 using the proposed method, whereas existing methods achieved AUCs ranging from 0.77∼0.79. The identified regions were consistent across the two independent data sets, and some findings were corroborated by other publications. Conclusions:The proposed model presents a novel quantitative approach for identifying injury regions post-stroke using FDG-PET images. The calculation does not require intensity normalization and can be applied to individual subjects. The method yields more sensitive results compared to existing identification methods.

Alternative Non-Destructive Approach for Estimating Morphometric Measurements of Chicken Eggs from Tomographic Images with Computer Vision.

The egg has natural barriers that prevent microbiological contamination and promote food safety. The use of non-destructive methods to obtain morphometric measurements of chicken eggs has the potential to replace traditional invasive techniques, offering greater efficiency and accuracy. This paper aims to demonstrate that estimates derived from non-invasive approaches, such as 3D computed tomography (CT) image analysis, can be comparable to conventional destructive methods. To achieve this goal, two widely recognized deep learning architectures, U-Net 3D and Fully Convolutional Networks (FCN) 3D, were modeled to segment and analyze 3D CT images of chicken eggs. A dataset of real CT images was created and labeled, allowing the extraction of important morphometric measurements, including height, width, shell thickness, and volume. The models achieved an accuracy of up to 98.69%, demonstrating their effectiveness compared to results from manual measurements. These findings highlight the potential of CT image analysis, combined with deep learning, as a non-invasive alternative in industrial and research settings. This approach not only minimizes the need for invasive procedures but also offers a scalable and reliable method for egg quality assessment.

Micro-void nucleation at fiber-tips within the microstructure of additively manufactured polymer composites bead

The presence of voids within the microstructure of short carbon fiber polymer composites produced by additive manufacturing (AM) technology are known to alter the expected material behavior that impair part performance. Previous research efforts aimed at understanding the formation mechanisms of these micro-voids during the polymer extrusion/deposition process have not kept up with the advancement of this AM technology. The present study investigates the phenomenon of micro-void nucleation at the fiber/matrix interface, especially those that form at fiber tips, by characterizing the microstructural configuration of a 13 % carbon fiber filled ABS polymer composite print bead specimen using 3D X-ray micro computed tomography image acquisition and analysis. The results reveal a high level of micro-voids segregation at the ends of fibers that are relatively larger in size and less spherical as compared to micro-voids isolated within the ABS matrix. Additionally, by simulating the hydrostatic flow-field pressure distribution surrounding a single rigid ellipsoidal fibre in colloidal suspension using Jeffery’s model equations, we show that the pressure drops to a critical value at the fibre tips where the micro-voids nucleation is experimentally observed to occur. The study helps to improve our understanding of the potential mechanisms that may be responsible for micro-void development within beads printed with extrusion/deposition AM.

ANALYSIS OF OPTICAL COHERENCE TOMOGRAPHY DATA IN PATIENTS WITH VARIOUS VARIANTS OF THE GLAUCOMA PROCESS

Today, about 537 million people in the world aged 20 to 79 suffer from diabetes mellitus, in 3% of cases neovascular glaucoma is diagnosed, threatening vision loss. Neovascular glaucoma is one of the most aggressive forms of secondary glaucomas and is often refractory to standard treatment methods. In domestic and foreign literature, there is no single standard for choosing the tactics of surgical treatment of patients with neovascular glaucoma against the background of diabetic retinopathy. In this regard, studies aimed at studying the morphofunctional parameters of eyes with neovascular glaucoma against the background of diabetic retinopathy acquire not only theoretical but also obvious practical interest. In the course of further development of methods for complex effects on eye structures to reduce intraocular pressure and progression of the glaucoma process. An analysis of optical coherence tomography images of 51 patients (51 eyes) was conducted, and the main aspects were identified for further use in choosing the tactics of surgical intervention.

Relationship of Hot Carcass Weight and Back Fat Thickness with the Fatness of Whole Pork Belly and Belly Slices.

This study evaluated the correlation between hot carcass weight (HCW), back fat thickness (BFT), and fatness of whole pork belly and belly slices. Pork bellies were obtained from 50 barrows and 50 gilts. The fat content (v/v) of the whole pork belly and belly slices was measured using computer tomography and hyperspectral image analysis, respectively. Barrows and gilts showed significant differences only for HCW (p<0.05). The fat content of pork belly slices varied with location and was the highest at the 10th thoracic vertebra (TV). Although no significant difference was observed in the fat content between the belly slices of the 6th TV and the 12th-14th TVs (p>0.05), a difference in the fat distribution was observed. HCW and BFT were significantly correlated with the fat content of whole pork belly, but not with the fat content of pork belly slices. Therefore, HCW and BFT are not suitable for monitoring the fatness of pork belly slices, and further research on the factors that can be used for monitoring the fatness of pork belly is necessary.

Modeling aging and retinal degeneration with mitochondrial DNA mutation burden.

Somatic mitochondrial DNA (mtDNA) mutation accumulation has been observed in individuals with retinal degenerative disorders. To study the effects of aging and mtDNA mutation accumulation in the retina, a polymerase gamma (POLG) exonuclease-deficient model, the PolgD257A mutator mice (D257A), was used. POLG is an enzyme responsible for regulating mtDNA replication and repair. Retinas of young and older mice with this mutation were analyzed invivo and exvivo to provide new insights into the contribution of age-related mitochondrial (mt) dysfunction due to mtDNA damage. Optical coherence tomography (OCT) image analysis revealed a decrease in retinal and photoreceptor thickness starting at 6 months of age in mice with the D257A mutation compared to wild-type (WT) mice. Electroretinography (ERG) testing showed a significant decrease in all recorded responses at 6 months of age. Sections labeled with markers of different types of retinal cells, including cones, rods, and bipolar cells, exhibited decreased labeling starting at 6 months. However, electron microscopy analysis revealed differences in retinal pigment epithelium (RPE) mt morphology beginning at 3 months. Interestingly, there was no increase in oxidative stress and parkin-mediated mitophagy in the ages analyzed in the retina or RPE of D257A mice. Additionally, D257A RPE exhibited an accelerated rate of autofluorescence cytoplasmic granule formation and accumulation. Mt markers displayed different abundance in protein lysates obtained from retina and RPE samples. These findings suggest that the accumulation of mtDNA mutations leads to impaired mt function and accelerated aging, resulting in retinal degeneration.

Diagnosis of Respiratory Sarcopenia for Stratifying Postoperative Risk in Non–Small Cell Lung Cancer

Physical biomarkers for stratifying patients with lung cancer into subtypes suggestive of outcomes are underexplored. To investigate the clinical utility of respiratory sarcopenia for optimizing postoperative risk stratification in patients with non-small cell lung cancer (NSCLC). This retrospective cohort study reviewed consecutive patients undergoing lobectomy and mediastinal lymph node dissection for NSCLC at 2 institutions in Tokyo, Japan, between 2009 and 2018. Eligible patients underwent electronic computed tomography image analysis. Follow-up began at the date of surgery and continued until death, the last contact, or March 2022. Data analysis was performed from April 2022 to March 2023. Respiratory sarcopenia was identified by poor respiratory strength (peak expiratory flow rate) and was confirmed by a low pectoralis muscle index (PMI; pectoralis muscle area/body mass index). Patients with poor peak expiratory flow rate but normal PMI received a diagnosis of pre-respiratory sarcopenia. Short-term and long-term postoperative outcomes were compared among patients with a normal status, pre-respiratory sarcopenia, and respiratory sarcopenia. Group differences were analyzed using the Kruskal-Wallis test and Pearson χ2 test for continuous and categorical data, respectively. Survival differences were compared using the log-rank test. Univariable and multivariable analyses were conducted using the Cox proportional hazards model. Of a total of 1016 patients, 806 (497 men [61.7%]; median [IQR] age, 69 [64-76] years) were eligible for electronic computed tomography image analysis. The median (IQR) duration of follow-up for survival was 5.2 (3.6-6.4) years. Respiratory strength was more closely correlated with PMI than pectoralis muscle radiodensity (Pearson r2, 0.58 vs 0.29). Respiratory strength and PMI declined with aging simultaneously (both P for trend < .001). Pre-respiratory sarcopenia was present in 177 patients (22.0%), and respiratory sarcopenia was present in 130 patients (16.1%). The risk of postoperative complications escalated from 82 patients (16.4%) with normal status to 39 patients (22.0%) with pre-respiratory sarcopenia to 39 patients (30.0%) with respiratory sarcopenia (P for trend < .001), as did the risk of delayed recovery after surgery (P for trend < .001). Compared with patients with normal status or pre-respiratory sarcopenia, patients with respiratory sarcopenia exhibited worse 5-year overall survival (438 patients [87.2%] vs 133 patients [72.9%] vs 85 patients [62.5%]; P for trend < .001). Multivariable analysis identified respiratory sarcopenia as a factor independently associated with increased risk of mortality (hazard ratio, 1.83; 95% CI, 1.15-2.89; P = .01) after adjustment for sex, age, smoking status, performance status, chronic heart disease, forced expiratory volume in 1 second, diffusing capacity for carbon monoxide, C-reactive protein, albumin, carcinoembryonic antigen, histology, and pathologic stage. This study identified individuals at higher risk of poor outcomes by screening and staging respiratory sarcopenia. The early diagnosis of respiratory sarcopenia could optimize management strategies and facilitate longitudinal care in patients with NSCLC.

An Easy-to-Handle Route for Bicomponent Porous Tubes Fabrication as Nerve Guide Conduits

Over the past two decades, the development of nerve guide conduits (NGCs) has gained much attention due to the impellent need to find innovative strategies to take care of damaged or degenerated peripheral nerves in clinical surgery. In this view, significant effort has been spent on the development of high-performance NGCs by different materials and manufacturing approaches. Herein, a highly versatile and easy-to-handle route to process 3D porous tubes made of chitosan and gelatin to be used as a nerve guide conduit were investigated. This allowed us to fabricate highly porous substrates with a porosity that ranged from 94.07 ± 1.04% to 97.23 ± 1.15% and average pore sizes—estimated via X-ray computed tomography (XCT) reconstruction and image analysis—of hundreds of microns and an irregular shape with an aspect ratio that ranged from 0.70 ± 0.19 to 0.80 ± 0.15 as a function of the chitosan/gelatin ratio. More interestingly, the addition of gelatin allowed us to modulate the mechanical properties, which gradually reduced the stiffness—max strength from 0.634 ± 0.015 MPa to 0.367 ± 0.021 MPa—and scaffold toughness—from 46.2 kJ/m3 to 14.0 kJ/m3—as the gelatin content increased. All these data fall into the typical ranges of the morphological and mechanical parameters of currently commercialized NGC products. Preliminary in vitro studies proved the ability of 3D porous tubes to support neuroblastoma cell (SH-SY5Y) adhesion and proliferation. In perspective, the proposed approach could also be easily implemented with the integration of other processing techniques (e.g., electrospinning) for the design of innovative bi-layered systems with an improved cell interface and molecular transport abilities.

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.

Uncommon presentation of Castleman disease in the duodenum: a case description and computed tomography imaging analysis.

Uncommon presentation of Castleman disease in the duodenum: a case description and computed tomography imaging analysis.

Retinal and Corneal OCT Results of Patients Hospitalized and Treated in the Acute Phase of COVID-19.

Objective: This study aimed to assess changes in the morphology of the retina and cornea in patients treated and hospitalized during the acute active phase of SARS-CoV-2 infection. Methods: A total of 24 patients with symptomatic early COVID-19 disease and 38 healthy participants from a control group were enrolled in our study. Among them, 20 received oxygen therapy at flow rates ranging from 1-10 L, while four received high-flow intranasal oxygen therapy (HFNOT). Some patients were treated with other types of therapy, such as Remdesivir, COVID-19 convalescent plasma therapy, or Tocilizumab. In the study, we focused on the analysis of optical coherence tomography (OCT) images of the cornea and retina including corneal thickness, central retinal thickness, retinal nerve fiber layer (RNFL), and optic disc parameters. The measurements were acquired using Spectral-domain OCT REVO FC 130. Results: The analysis did not show significant changes between the examined ophthalmological parameters before and after therapy. Furthermore, there were no detected significant differences between the tested parameters of the retina and cornea in COVID-19-positive patients compared to the control group. Conclusions: No ophthalmological manifestations of COVID-19 disease were observed during the study. Taking into account the results of other publications, the lack of an unambiguous position on this topic requires further research.

Evaluation of Biocomposite Cements for Bone Defect Repair in Rat Models.

Repairing or reconstructing significant bone defects is typically challenging. In the present study, two composite cements were used as scaffolds in a sub-critical femoral defect in rats. A control group and two experimental batches were used to compare the outcomes. This research aimed to investigate the osteogenic potential and toxicological tolerance of the bioproducts through histopathology and computed tomography imaging analysis at 14, 28, 56, and 90 days post-implantation. The biomaterials used in the investigation consisted of a 65% bioactive salinized inorganic filler and a 25% weight organic matrix. The organic part of the biomaterial was composed of Bis-GMA (bisphenol A-glycidyl methacrylate), UDMA (urethane dimethacrylate), HEMA (2-Hydroxyethyl methacrylate), and TEGDMA (triethylene glycol dimethacrylate), while the inorganic filler was composed of silica, barium glass, hydroxyapatite, and fluor aluminosilicate glass. The first findings of this research are encouraging, revealing that there is a slight difference between the groups treated with biomaterials, but it might be an effective approach for managing bone abnormalities. Material C1 exhibited a faster bone defect healing time compared to material C2, where bone fractures occurred in some individuals. It is unclear if the fractures were caused by the presence of the biomaterial C2 or whether additional variables were to blame. By the end of the research, the mice appeared to tolerate the biomaterials without exhibiting any inflammatory or rejection responses.

Development of fluid pathways and associated diagenetic variations in a natural CO2 leaking fault zone.

Abstract Permeability within fault zones can vary through time due to repeated deformation events and rock–fluid interactions. Understanding the history of fault zone alteration is critical when building hydrogeologic models and evaluating the risk of mechanical rock failure during subsurface storage. Newly acquired drill core recovered within the fault damage zone and fault core of the Little Grand Wash fault (LGWF) is combined with observations from outcrop, optical petrography, computerized tomography image analysis, and ultrasonic velocity measurements to characterize the rock types and preserved structural deformation features within this fault zone. These data are used to understand the history of mechanical rock failure and mineralization associated with this fluid-charged fault system. We identify multiple structural features and use their cross-cutting relationships to understand the history of deformation and their association with changes in fault zone permeability and rock mechanical properties. At the LGWF zone, structural deformation features vary temporally and are used to recognize a decoupling between fault slip and fluid flow. The formation of most open-mode veins occurred after shear failure within the LGWF zone. Early-developed shear bands are cut by carbonate veins, that are in turn cut by shear fractures, followed by a second phase of vein formation and ultimately by folding in the fault core. This sequence of formation reflects changes in mechanical rock properties due to subsurface rock–fluid interactions and indicates that the alteration of rock matrix by secondary carbonate cement results in increased unconfined compressive strength, decreased permeability, and increased ultrasonic velocity. In this fault zone, and possibly other fault zones, the changes in rock properties associated with deformation can be detected through their geophysical response.

Generalized Framework for Liquid Neural Network upon Sequential and Non-Sequential Tasks

This paper introduces a novel approach to neural networks: a Generalized Liquid Neural Network (GLNN) framework. This design excels at handling both sequential and non-sequential tasks. By leveraging the Runge Kutta DOPRI method, the GLNN enables dynamic simulation of complex systems across diverse fields. Our research demonstrates the framework’s capabilities through three key applications. In predicting damped sinusoidal trajectories, the Generalized LNN outperforms the neural ODE by approximately 46.03% and the conventional LNN by 57.88%. Modelling non-linear RLC circuits shows a 20% improvement in precision. Finally, in medical diagnosis through Optical Coherence Tomography (OCT) image analysis, our approach achieves an F1 score of 0.98, surpassing the classical LNN by 10%. These advancements signify a significant shift, opening new possibilities for neural networks in complex system modelling and healthcare diagnostics. This research advances the field by introducing a versatile and reliable neural network architecture.

Disease Activity and Therapeutic Response to Pegcetacoplan for Geographic Atrophy Identified by Deep Learning-Based Analysis of OCT

PurposeTo quantify morphological changes of the photoreceptors (PR) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of optical coherence tomography (OCT) images. DesignPost-hoc longitudinal image analysis SubjectsPatients with GA due to age-related macular degeneration from two prospective randomized phase III clinical trials (OAKS and DERBY) MethodsDeep learning-based segmentation of RPE loss and PR degeneration, defined as loss of the ellipsoid zone (EZ) layer on OCT, over 24 months on SD-OCT images Main outcome measuresChange in the mean area of RPE loss and EZ loss over time in the pooled sham arms and the monthly (PM)/every other month (PEOM) treatment arms Results897 eyes of 897 patients were included. There was a therapeutic reduction of RPE loss growth by 22%/20% in OAKS and 27%/21% in DERBY for PM/PEOM compared to sham, respectively, at 24 months. The reduction on the EZ level was significantly higher with 53%/46% in OAKS and 47%/46% in DERBY for PM/PEOM compared to sham at 24 months. The baseline EZ-RPE difference had an impact on disease activity and therapeutic response. The therapeutic benefit for RPE loss growth increased with larger EZ-RPE difference quartiles from 21.9%, 23.1%, 23.9% to 33.6% for PM vs. sham (all p<0.01) and from 13.6% (p=0.11), 23.8%, 23.8% to 20.0% for PEOM vs. sham (p<0.01) in quartiles 1,2,3 and 4, respectively, at 24 months. Regarding EZ layer maintenance, the therapeutic reduction of loss increased from 14.8% (p=0.09), 33.3%, 46.6% to 77.8% (p<0.0001) between PM and sham and from 15.9% (p=0.08), 33.8%, 52.0% to 64.9% (p<0.0001) between PEOM and sham for quartiles 1-4 at 24 months. ConclusionOCT-based AI analysis objectively identifies and quantifies PR and RPE degeneration in GA. Reductions in further PR degeneration consistent with EZ loss on OCT are even higher than the effect on RPE loss in phase 3 trials of pegcetacoplan treatment. The EZ-RPE difference has a strong impact on disease progression and therapeutic response. Identification of patients with higher EZ-RPE loss difference may become an important criterion for the management of GA secondary to AMD.

Cone-beam computed tomography imaging and three-dimensional analysis of midfoot joints during non-weightbearing and weightbearing in 11 healthy feet.

Studies report that Lisfranc injury is more common than thought. Several imaging methods for assessing the stability of Lisfranc injury have been described but many are impossible to standardize and not accurate enough. To present a three-dimensional (3D) method for analyzing the changes in the joint space width of the midfoot joint and the joints of the medial part of the Lisfranc complex in healthy individuals. Non-weightbearing and weightbearing cone-beam computed tomography (CBCT) images of 11 healthy feet were acquired and analyzed with 3D software. The mean range of joint space width changes of each joint was computed from the changes in individual image pairs. 3D analysis software was used to analyze the medial part of the Lisfranc complex. In this sample of healthy feet, the changes in the joint spaces in the medial part of Lisfranc complex, calculated with 3D analysis software, was less than 0.6 mm. The distance between bones increased or decreased, depending on which part of the joint surface the measurements were taken. In this study, we present a 3D analysis method to evaluate midfoot joint space width changes. Our analysis revealed that in healthy feet there are only minimal changes in the joint space width between weightbearing and non-weightbearing indicating minimal movement of the midtarsal joints. The 3D analysis of weightbearing CBCT data provides a promising tool for analyzing the small midfoot joints in a variety of conditions.

The effect of platelet-rich plasma and sodium alginate hydrogel on corneal wound healing after corneal alkali burns in rats with computer-assisted anterior segment optical coherence tomography image analysis

Our objective was to determine the effect of a semi-synthetic sodium alginate hydrogel and its combination with platelet-rich plasma (PRP) on histopathological, biochemical, clinical, and anterior segment optical coherence tomography (AS-OCT) data. Alkali chemical burn of the cornea was induced. Injured rats were randomly divided into five equal groups and topically treated with phosphate-buffered saline (sham), platelet-rich plasma (PRP), 0.5% sodium citrate, a semi-synthetic sodium alginate hydrogel, or a combination of PRP and hydrogel (combined group) three times daily. The degree of corneal opacity (CO), corneal epithelial staining (CES), percentage of corneal epithelial defects (CEDP), degree of ciliary hyperemia (CH), neovascularization size (NVS), and extent of neovascularization (NVE) were evaluated. AS-OCT was performed at nine days, and then rats were sacrificed. Histological examination and enzyme-linked immunosorbent assays were performed to detect the concentrations of IL-1β and MMP-9 in the cornea. There were no significant differences between the groups regarding CEDP, CO, CES, CH, NVS, or NVE on the first day after corneal alkali burn injury (p > 0,05). At the last examination, CO was significantly lower in the PRP group than in the sham group (p = 0,044), while the CO concentrations were similar in terms of NVS (p > 0,05). Similarly, in terms of tissue MMP-9 levels, there were no significant differences between groups (p > 0,05). However, there was a significant difference in tissue IL-1β levels between the groups (p < 0,001). In the PRP and combined groups, the level of IL-1β was significantly lower than that in the sham group (p = 0,043 and p = 0,036, respectively). There was a significant difference in epithelial necrosis between the PRP, and it was the lowest in the combined group (p = 0,003). Epithelial thickness was highest in the combined group (p = 0,002). CEDP was significantly different at the last visit between the groups (p = 0.042). The fastest epithelial closing rate was observed for the combined group (p = 0,026). There was a significant negative correlation between tissue MMP-9 levels and corneal solidity and between tissue MMP-9 levels and the corneal area according to the AS-OCT measurements (p = 0,012 and p = 0,027, respectively). When used alone, topical hydrogel application did not significantly enhance the healing of corneal wounds. However, when combined with PRP, it leads to an increased rate of epithelial closure and neovascularization. This combination did not exacerbate inflammation or corneal opacity compared to PRP alone. The anticoagulant citrate solution in the PRP tube did not prove effective. The synergistic use of PRP and hydrogel could enhance epithelial thickness and reduce epithelial necrosis. The use of new parameters for corneal wound healing assessment was facilitated through AS-OCT image processing.