Search Results (107)

Background/Objectives: To determine the optimal reconstruction parameters for accurate visualization of peripheral in-stent restenosis using photon-counting detector CT (PCD-CT), and to evaluate its potential advantages over energy-integrated detector CT (EID-CT). Methods: Endovascular peripheral stents with varying degrees of in-stent restenosis were scanned in a custom-made phantom using EID-CT (Somatom Force) and PCD-CT (Naeotom Alpha) under clinical acquisition protocols. EID-CT images were reconstructed with Bv40 and Bv59 kernels at 512 matrices. PCD-CT data were acquired in standard-resolution (SR) and ultra-high-resolution (UHR) modes. In both modes, images were reconstructed with multiple kernels (Bv40, Bv56 and Bv72) and matrix sizes (512 and 1024 matrix). In SR mode, additional virtual monoenergetic images (40–100 keV) were generated, while UHR mode included only polychromatic reconstructions. Quantitative image quality (noise, contrast, contrast-to-noise ratio [CNR]) was measured, and two blinded readers performed qualitative assessments of restenosis visualization. Results: PCD-CT with SR mode at VMI 40 keV achieved the highest image contrast and CNR, significantly outperforming EID-CT and PCD-CT_UHR under matched conditions (all p < 0.05). The sharper reconstruction kernel further enhanced the image contrast and improved subjective visualization despite increased image noise. Both readers ranked PCD-CT_{SR-Bv72-40keV} at 1024 matrix highest for detecting all degrees of restenosis, with excellent inter-reader agreement (ρ > 0.80). Conclusions: PCD-CT in SR mode at VMI 40 keV, specifically using the Bv72 kernel with a 1024 matrix, optimizes the visualization of peripheral in-stent restenosis. Compared to EID-CT, PCD-CT provides superior image quality and detectability of restenosis. Full article

Background/Objectives: Anterior segment optical coherence tomography (AS-OCT) and optical coherence tomography angiography (AS-OCTA) have enhanced the evaluation of the cornea, ocular surface, and ocular surface diseases (OSD), offering high-resolution structural and anterior segment vascular imaging. This review summarizes recent advances in these modalities and their clinical applications. Methods: A comprehensive literature search was conducted using PubMed, Web of Science, and Google Scholar with the terms OCT, OCTA, anterior segment, and ocular surface disease. Studies published in the past five years were included, emphasizing more recent developments such as ultra-high-resolution AS-OCT (UHR-AS-OCT) and swept-source AS-OCTA technologies. Results: UHR-AS-OCT provides non-invasive, sub-micron imaging of the cornea and the ocular surface, including tear film morphology and epithelial thickness to correlate with clinical tests such as tear break-up time, and fluorescein staining. Advances in AS-OCTA allow dye-free, depth-resolved imaging of corneal and conjunctival vasculature. These vascular biomarkers have shown promising utility in conditions such as limbal stem cell deficiency, chemical ocular injury, and ocular surface squamous neoplasia. Improvements in image acquisition, motion correction, and segmentation algorithms have enhanced accuracy and repeatability, supporting broader clinical translation. Conclusions: AS-OCT and AS-OCTA have become useful adjunctive imaging tools for the cornea and ocular surface evaluation. Their non-invasive, quantitative, and reproducible metrics may enable earlier diagnosis, objective staging, and longitudinal monitoring of OSD. Integration of OCT-based imaging with artificial intelligence and multimodal data, including tear proteomics and meibography, may optimize personalized treatment for ocular surface disorders. Full article

Objective: To evaluate the performance of photon-counting detector CT (PCD-CT) angiography for the detection and quantification of vascular stenosis. Methods: Web of Science, PubMed, and Cochrane databases were searched from January 1980 to December 2025 to identify studies assessing PCD-CT angiography for the detection and quantification of vascular stenosis, using invasive angiography as the reference standard. The risk of bias of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Diagnostic performance metrics, including sensitivity and specificity and quantification values, were extracted from the included studies and a formal narrative synthesis was performed. The meta-analysis included studies reporting true-positive, false-positive, true-negative, and false-negative data. A meta-analysis was conducted only when a minimum of two eligible studies assessed diagnostic performance within the given vascular territory. Statistical analyses were performed using R software (v4.5.0), applying a random-effects model for the meta-analysis. Results: Of 415 identified studies, 20 were included in the systematic review, comprising a total of 9165 participants, with the majority (17/20, 85%) focusing on coronary artery stenosis. In the meta-analysis of three studies, ultra-high-resolution (UHR) PCD-CT demonstrated excellent diagnostic performance for detecting coronary stenosis for patients with ≥50%, having a pooled sensitivity of 96.1% (95% confidence level (CI): 89.3–99.6), specificity of 87.5% (95% CI: 78.2–93.3), positive predictive value (PPV) of 91.9% (95% CI: 70.3–98.2), and negative predictive value (NPV) of 94.8% (95% CI: 86.0–98.6). Compared with conventional energy-integrating detector CT (EID-CT), PCD-CT consistently showed superior diagnostic performance, particularly in the specificity and PPV. In terms of stenosis quantification, PCD-CT showed closer agreement with reference standards than EID-CT, leading to the reclassification of coronary stenosis severity in up to 49% of patients. Evidence for non-coronary vascular territories, including intracranial and peripheral arteries remains limited but suggests promising diagnostic performance. For lower-limb arterial stenosis, the reported sensitivity was 77.4–91%, and specificity was 72.1–91%. For intracranial in-stent stenosis, PCD-CT demonstrated a sensitivity of 100% and a specificity of 89%. Conclusions: PCD-CT angiography provides high diagnostic performance and improved stenosis quantification for coronary artery stenosis. UHR PCD-CT has excellent diagnostic performance for detecting coronary stenosis and consistently outperforms conventional EID-CT, especially in the specificity and positive predictive value. Full article

This study examines a comprehensive class of coupled nonlinear $\varrho$-Hilfer fractional neutral impulsive integro-differential systems with mixed delays and non-local initial conditions. The primary contribution of this study is the creation of a unified analytical framework that encompasses coupled interactions, neutral-type dependencies, and impulsive disturbances, which have been studied separately by researchers. We utilize the Banach contraction principle and Krasnoselskii’s fixed-point theorem to provide suitable conditions for the existence and uniqueness of solutions within the product space of piecewise continuous weighted functions. In addition to existence, we examine Ulam–Hyers–Rassias (UHR) stability using a generalized Gronwall inequality, which guarantees the system’s robustness against functional perturbations. We also develop a controllability framework and a feedback control law that steer the system towards the desired terminal states. The theoretical results are supported by a numerical simulation using a complex kernel, implemented via a modified predictor-corrector algorithm, which validates the practical effectiveness of the proposed control and stability outcomes. Full article

Background/Objectives: Peritoneal membrane failure remains a major limitation of peritoneal dialysis (PD). Systemic inflammation contributes to membrane dysfunction, yet simple predictive biomarkers are lacking. The uric acid-to-HDL cholesterol ratio (UHR) represents a novel integrative marker of metabolic-inflammatory burden, but its association with membrane failure has not been investigated. Methods: This retrospective cohort study included adult patients who initiated PD between 1997 and 2023. Baseline UHR was calculated from laboratory measurements obtained within the first three months after PD initiation. The primary outcome was peritoneal membrane failure, defined as permanent transfer to hemodialysis due to ultrafiltration failure, inadequate solute clearance, or progressive membrane dysfunction. Receiver operating characteristic, Kaplan–Meier, and Cox regression analyses were used to evaluate the association between UHR and membrane failure. Results: Among 214 patients, 62 (29%) developed membrane failure during follow-up. Baseline UHR was significantly higher in patients with membrane failure. A UHR cut-off value of 14 was identified for risk stratification. In multivariable Cox regression analysis, UHR >14 was independently associated with an increased risk of membrane failure (hazard ratio 1.836, 95% CI 1.040–3.241). A history of kidney transplantation prior to PD initiation also emerged as a strong independent predictor of membrane failure. Conclusions: Elevated baseline UHR is independently associated with peritoneal membrane failure in PD patients. As a simple and readily available biomarker, UHR may support early risk stratification and individualized management. Prospective multicenter studies are warranted to validate these findings. Full article

This paper investigates qualitative properties of fractional delay differential equations formulated in terms of the Atangana–Baleanu–Caputo (ABC) fractional derivative of order $1<\varrho <2$. Three related problem settings are examined: equations with variable delay, the constant-delay case, and a multi-delay extension involving several discrete delay terms. For each formulation, sufficient conditions ensuring existence and uniqueness of solutions are established in both the supremum norm and an exponentially weighted Maksoud norm. The analysis is carried out using Banach’s fixed point theorem in conjunction with progressive contractions and suitable Lipschitz-type conditions. In addition, Ulam–Hyers (UH) and Ulam–Hyers–Rassias (UHR) stability results are derived, providing quantitative estimates on the sensitivity of solutions with respect to perturbations. To complement the theoretical findings, numerical examples are presented, one of which illustrates the behavior of approximate solutions for various fractional orders. Full article

Objective: To investigate the relationship between glycemic control and inflammation–nutrition indices in older adults with type 2 diabetes mellitus and to evaluate their prognostic value for 30-day mortality. Methods: This retrospective cohort study included 372 hospitalized patients aged ≥65 years with type 2 diabetes. Laboratory data were used to calculate the hemoglobin–albumin–lymphocyte–platelet (HALP) score, the endothelial activation and stress index (EASIX), and the uric acid-to-high-density lipoprotein cholesterol ratio (UHR). Cox regression analyses were performed to identify independent predictors of 30-day mortality, and combined stratification models using HALP, EASIX, and UHR were evaluated for risk discrimination. Results: Thirty-day mortality occurred in 57 patients (15.3%). HbA1c levels were not significantly associated with mortality (p = 0.615). Non-survivors had higher UHR, and EASIX, and lower HALP score levels (all p < 0.05). In multivariate Cox regression, age (HR 1.066, 95% CI 1.024–1.109, p = 0.002), length of hospital stay (HR 1.050, 95% CI 1.026–1.074, p < 0.001), ICU admission (HR 2.394, 95% CI 1.227–4.672, p = 0.010), and UHR (HR 1.028, 95% CI 1.013–1.042, p < 0.001) were independent predictors of mortality. Stratification by EASIX and UHR revealed that patients with both high EASIX or UHR and low HALP had the highest mortality risk, with adjusted HRs up to 4.206 (95% CI 1.930–9.166, p < 0.001). Conclusions: Among older adults with type 2 diabetes, short-term mortality is more strongly associated with inflammation, endothelial stress, and nutritional status than with glycemic control. Combined inflammation–nutrition indices (HALP, EASIX, UHR) provide superior risk stratification and help identify high-risk patients early. Full article

Background: Approximately 20–30% of ultra-high risk (UHR) individuals transition to psychosis within 2–3 years. Neurobiological markers predicting conversion remain critical for precision prevention strategies. Objective: To systematically identify and evaluate structural and functional neuroimaging biomarkers at UHR baseline that predict subsequent conversion to psychosis. Methods: Following PRISMA 2020 guidelines, we searched five databases from January 2000 to February 2025. Two independent reviewers screened studies and assessed quality using the Newcastle–Ottawa Scale. Eligible studies examined baseline neuroimaging measures (structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy) as predictors of psychosis conversion in UHR cohorts. Results: Twenty-five studies comprising 2436 UHR individuals (627 converters, 25.7%) were included (80.0% high quality). Reduced baseline gray matter volume in medial temporal structures (hippocampus: Cohen’s d = −0.45 to −0.68; parahippocampal gyrus: d = −0.52 to −0.71) and prefrontal cortex (d = −0.41 to −0.68) consistently predicted conversion. Progressive gray matter loss in superior temporal gyrus distinguished converters (d = −0.72). Reduced prefrontal–temporal functional connectivity predicted conversion (AUC = 0.73–0.82). Compromised white matter integrity in uncinate fasciculus (fractional anisotropy: d = −0.47 to −0.71) and superior longitudinal fasciculus predicted transition. Elevated striatal glutamate predicted conversion (d = 0.52–0.76). Thalamocortical dysconnectivity showed large effects (Hedges’ g = 0.66–0.88). Multimodal imaging models achieved 78–85% classification accuracy. Conclusions: Neuroimaging biomarkers, particularly medial temporal and prefrontal structural alterations, functional dysconnectivity, and white matter abnormalities, demonstrate moderate-to-large effect sizes in predicting UHR conversion. Multimodal approaches combining structural, functional, and neurochemical measures show promise for individualized risk prediction and early intervention targeting in precision prevention strategies. Full article

With Transformers achieving outstanding performance on individual remote sensing (RS) tasks, we are now approaching the realization of a unified model that excels across multiple tasks through multi-task learning (MTL). Compared to single-task approaches, MTL methods offer improved generalization, enhanced scalability, and greater practical applicability. Recently, vision-language models (VLMs) have achieved promising results in RS image understanding, grounding, and ultra-high-resolution (UHR) image reasoning, respectively. Moreover, the unified text-based interface demonstrates significant potential for MTL. Hence, in this work, we present RSCoVLM, a simple yet flexible VLM baseline for RS MTL. Firstly, we create the data curation procedure, including data acquisition, offline processing and integrating, as well as online loading and weighting. This data procedure effectively addresses complex RS data enviroments and generates flexible vision-language conversations. Furthermore, we propose a unified dynamic-resolution strategy to address the diverse image scales inherent in RS imagery. For UHR images, we introduce the Zoom-in Chain mechanism together with its corresponding dataset, LRS-VQA-Zoom. The strategies are flexible and effectively mitigate the computational burdens. Additionally, we significantly enhance the model’s object detection capability and propose a novel evaluation protocol that ensures fair comparison between VLMs and conventional detection models. Extensive experiments demonstrate that RSCoVLM achieves state-of-the-art performance across diverse tasks, outperforming existing RS VLMs and even rivaling specialized expert models. All the training and evaluating tools, model weights, and datasets have been fully open-sourced to support reproducibility. We expect that this baseline will promote further progress toward general-purpose RS models. Full article

Background: Photon-counting computed tomography (PCCT) represents a major technological advance in clinical CT imaging, offering superior spatial resolution, enhanced material discrimination, and potential radiation dose reduction compared to conventional energy-integrating detector systems. As the first clinically approved PCCT scanner becomes available, establishing a comprehensive characterization of its image quality is essential to understand its performance and clinical impact. Methods: Image quality was evaluated using a commercial quality assurance phantom with acquisition protocols typically used for three anatomical regions—head, abdomen/thorax, and inner ear—representing diverse clinical scenarios. Each region was scanned using both ultra-high-resolution (UHR, 120 × 0.2 mm slices) and conventional (144 × 0.4 mm slices) protocols. Conventional metrics, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), slice thickness accuracy, and uniformity, were assessed following international standards. Task-based analysis was also performed through target transfer function (TTF), noise power spectrum (NPS), and detectability index (d′) to evaluate diagnostic relevance. Results: UHR protocols provided markedly improved spatial resolution, particularly in the inner ear imaging, as confirmed by TTF analysis, though with increased noise and reduced low-contrast detectability in certain conditions. CT numbers showed linear correspondence with known attenuation coefficients across all protocols. Conclusions: This study establishes a detailed technical characterization of the first clinical PCCT scanner, demonstrating significant improvements in terms of spatial resolution and accuracy of the quantitative image analysis, while highlighting the need for noise–contrast optimization in high-resolution imaging. Full article

Background and Objectives: Hematological parameters are increasingly being investigated as readily accessible biomarkers for the diagnosis of obstructive sleep apnea syndrome (OSAS). In our study, we aimed to investigate the relationship between OSAS and albumin indices and the uric acid-to-HDL ratio (UHR). Methods: The demographic and laboratory data and AHI (apnea–hypopnea index) values of 613 patients who underwent polysomnography were obtained retrospectively from their files. Blood parameters such as white blood cells (WBCs), red blood cell distribution width (RDW), red blood cells (RBCs), hemoglobin (Hb), hematocrit (Hct), platelets (PLTs), C-reactive protein (CRP), albumin, blood urea nitrogen (BUN), and high-density lipoproteins (HDLs) were obtained from the files. Laboratory indices such as the BUN-to-albumin ratio (BAR), neutrophil-to-albumin ratio (NAR), RDW-to-albumin ratio (RAR), CRP-to-albumin ratio (CAR), and UHR were calculated. OSAS was categorized as simple snoring (SS) (control) (AHI < 5), mild (5 ≤ AHI < 15), moderate (15 ≤ AHI < 30), and severe (AHI ≥ 30). The patients were also grouped as severe (AHI ≥ 30) and non-severe (5 > AHI < 30) OSAS and compared in terms of laboratory parameters and indices. Results: Of the 613 participants, 366 (59.7%) were men, and the average age of participants was 55.22 ± 11.13 years. The biomarkers such as RBCs, Hb, Htc, CRP, BUN, creatinine, uric acid, HDLs, CAR, RAR, BAR, and UHR showed significant differences between OSAS patients and controls. WBCs, basophils, RBCs, RDW, Htc, PLTs, HDLs, uric acid, RAR, NAR, and UHR indices were significantly different between the severe OSAS and non-severe OSAS groups (p < 0.05). BAR (OR = 1.151; CI = 1.056 − 1.256; p = 0.001) and UHR (OR = 2.257; 95% CI = 1.507 − 3.382; p < 0.001) were the most important indices predicting OSAS, while RAR (OR = 1.844; CI = 1.224 − 2.778; p = 0.003) and UHR (OR = 2.203; 95% CI = 1.496 − 3.243; p < 0.001) were the strongest indices associated with severe OSAS. Conclusion: In our study, RAR, BAR, and UHR indices were closely associated with the presence and severity of OSAS. These indices can be considered low-cost, readily available methods for predicting OSAS patients. Full article

On the spectrum of complexity for general surgery operations, umbilical hernia repair (UHR) is on the light side. After inguinal hernias, they are the most commonly repaired hernias and, as such, umbilical hernias are an important component of a general surgery practice. Since the time at which WJ Mayo published his seminal technique on the repair of umbilical hernias, multiple strategies for the management of umbilical hernias have emerged ranging from watchful waiting to open repair, as well as minimally invasive approaches. The present perspective maintains that each approach has its merits depending on the patient, surgeon, and institution. However, randomized controlled trials and clinical practice guidelines have favored some approaches over others. Similarly, recommendations have been developed regarding body mass index classification as well as hernia size for mesh placement. Other factors important to UHR are the choice of anesthesia and smoking cessation for elective repair. Though we do not contest well-designed randomized controlled trials (RTCs), or clinical guidelines, we offer our perspective on the care of these common hernias. Full article

Semantic segmentation of ultra-high-resolution remote sensing (UHR-RS) imagery plays a critical role in land use and land cover analysis, yet it remains computationally intensive due to the enormous input size and high spatial complexity. Existing studies have commonly employed strategies such as patch-wise processing, multi-scale model architectures, lightweight networks, and representation sparsification to reduce resource demands, but they have often struggled to maintain long-range contextual awareness and scalability for inputs of arbitrary size. To address this, we propose RingFormer-Seg, a scalable Vision Transformer framework that enables long-range context learning through multi-device parallelism in UHR-RS image segmentation. RingFormer-Seg decomposes the input into spatial subregions and processes them through a distributed three-stage pipeline. First, the Saliency-Aware Token Filter (STF) selects informative tokens to reduce redundancy. Next, the Efficient Local Context Module (ELCM) enhances intra-region features via memory-efficient attention. Finally, the Cross-Device Context Router (CDCR) exchanges token-level information across devices to capture global dependencies. Fine-grained detail is preserved through the residual integration of unselected tokens, and a hierarchical decoder generates high-resolution segmentation outputs. We conducted extensive experiments on three benchmarks covering UHR-RS images from 2048 × 2048 to 8192 × 8192 pixels. Results show that our framework achieves top segmentation accuracy while significantly improving computational efficiency across the DeepGlobe, Wuhan, and Guangdong datasets. RingFormer-Seg offers a versatile solution for UHR-RS image segmentation and demonstrates potential for practical deployment in nationwide land cover mapping, supporting informed decision-making in land resource management, environmental policy planning, and sustainable development. Full article

Background/Objectives: Brain-derived neurotrophic factor (BDNF) is a neurotrophin critical for neurogenesis and synaptic plasticity, and alterations in its peripheral levels have been associated with schizophrenia and other psychotic disorders. However, findings on peripheral BDNF levels in individuals at ultra-high risk (UHR) for psychosis have been inconsistent. This review synthesizes current evidence comparing peripheral BDNF levels in UHR populations with those in healthy controls (HCs), first-episode psychosis (FEP), and chronic schizophrenia (CS), focusing on BDNF’s potential relevance as a biomarker of psychosis risk and subsequent clinical course. Methods: A systematic search of PubMed, Scopus, and Web of Science identified studies reporting baseline peripheral BDNF levels in UHR individuals compared with HC, FEP, or CS. Of 755 records retrieved, 608 unique titles/abstracts were screened, 49 full texts reviewed, and 8 studies included. Two reviewers independently screened, extracted data, and assessed risk of bias. Given marked clinical and methodological variability, results were synthesized narratively. Results: Eight studies met eligibility criteria and were synthesized across three analytical categories: (1) UHR vs. HC; (2) UHR vs. FEP or CS; and (3) longitudinal outcomes. Findings were inconsistent; some studies reported lower BDNF in UHR relative to comparison groups, whereas others found no differences or higher levels, often influenced by clinical or methodological factors. Longitudinal analyses did not reveal consistent prognostic value, and heterogeneity precluded meta-analysis. Conclusions: Findings across studies were inconsistent and limited by small samples, as well as by methodological heterogeneity. While current evidence does not support its prognostic use, peripheral BDNF may still hold potential as part of a biomarker framework if evaluated in larger, standardized, and rigorously controlled studies. Full article

This paper investigates a novel class of weighted fuzzy fractional Volterra–Fredholm integro-differential equations (FWFVFIDEs) subject to integral boundary conditions. The analysis is conducted within the framework of Caputo-weighted fractional calculus. Employing Banach’s and Krasnoselskii’s fixed-point theorems, we establish the existence and uniqueness of solutions. Stability is analyzed in the Ulam–Hyers (UHS), generalized Ulam–Hyers (GUHS), and Ulam–Hyers–Rassias (UHRS) senses. A modified Adomian decomposition method (MADM) is introduced to derive explicit solutions without linearization, preserving the problem’s original structure. The first numerical example validates the theoretical findings on existence, uniqueness, and stability, supplemented by graphical results obtained via the MADM. Further examples illustrate fuzzy solutions by varying the uncertainty level (r), the variable (x), and both parameters simultaneously. The numerical results align with the theoretical analysis, demonstrating the efficacy and applicability of the proposed method. Full article