Search Results (25,364)

Background: Amino acid tracer positron emission tomography–magnetic resonance imaging (PET-MRI) was shown to be superior to MRI alone for evaluating central nervous system (CNS) tumours in adults. This study aimed to investigate the utility of amino acid PET-MRI in children with CNS tumours. Methods: We reviewed the amino acid PET-MRI findings of children with suspected or confirmed CNS neoplasms managed in a territory-wide referral centre in Hong Kong from 2022 to 2025. Maximal standardized uptake values (SUVmax) were captured, and tumour-to-background SUVmax ratios (TBRmax) were measured with reference to adjacent or contralateral normal brain structures. Comparisons were made among patients with clinical high-grade and low-grade/non-neoplastic lesions. Results: Thirty-seven patients were included, with 63 PET-MRIs performed. PET-MRI was performed as part of initial diagnostics in 41% of the cases, for response assessment in 48%, and evaluation of residual/relapsed disease in 11%. High-grade lesions had a significantly higher SUVmax and TBRmax compared to low-grade/non-malignant lesions (median SUVmax 3.7 vs. 1.6, p = 0.00006; median TBRmax 2.06 vs. 0.91, p = 0.00002). Optimal SUVmax and TBRmax cut-offs by ROC analysis were 2.38 and 1.62, respectively. Similar performance was reproduced by focusing on the subset of patients with suspected CNS germ cell tumours (CNS-GCT). The impact of amino acid PET availability is considerable, as clinical management was modified in 65% of patients. Conclusions: Our study demonstrates the performance and clinical utility of amino acid PET-MRI in the management of children with CNS pathologies. Amino acid PET-MRI contributes to the diagnosis, monitoring, and treatment guidance of these patients, providing crucial information for decision-making. Full article

Background/Objectives: This study aims to report and compare data from the PRO-AOSD (patient-reported outcomes adult-onset Still’s disease) survey in patients with AOSD from the perspective of patients and their treating physicians. Methods: PRO-AOSD comprised blinded patient and physician surveys. The surveys were designed to assess perceived symptoms and physical impairment. Outcomes reported here include patient demographics; physicians’ assessment of the patient’s health state; physician-reported laboratory findings; pain; disease activity; symptoms; physicians’ treatment goals; and the impact of lifestyle factors on disease improvement. Results: Adult patients with AOSD were recruited from 19 centers in Germany. A total of 124 patients were included, with 74 (59.7%) females; the mean age was 45.5 years. The mean time from first symptom to diagnosis was 2 years, and the mean time was 7 years from diagnosis to survey completion (N = 123). Of 107 patients, most (81.3%) had inactive disease defined by CRP levels. At the time of the survey, around two-thirds of patients were receiving biologic therapy, with 84.1% (69/82) reporting an improvement in symptoms. Many patients had previously received antibiotics (47.6% [n = 58] and 30.4% [n = 37], per patient and physician reports, respectively). Persistent symptoms were reported more frequently by patients than by physicians, including back pain (39.5%), fatigue and weakness (38.7%), and joint inflammation (27.4%). Physicians classified 35.5% of patients as symptom-free. Patients reported exercise as having a positive impact on symptoms (52.4%), while stress (74.2%) and sleep deprivation (62.9%) were reported to worsen symptoms. Targeting systemic manifestations, such as the absence of fever (58.1%, n = 72), was considered the most important treatment goal by physicians. Conclusions: Data from PRO-AOSD highlight distinct differences between patients’ and physicians’ interpretations of the same cases of AOSD. Prior presentation: These data were presented at the German Congress of Rheumatology (DGRh; 30 August–2 September 2023; Leipzig, Germany). Full article

Retinal diseases are among the leading causes of vision impairment worldwide, and early detection is essential for enabling personalized treatments and preventing irreversible vision loss. In this paper, we propose a method aimed to identify and localize retinal conditions, i.e., Age-Related Macular Degeneration, Diabetic Retinopathy, and Choroidal Neovascularization, using explainable deep learning. For this purpose, we consider seven fine-tuned convolutional neural networks: MobileNet, LeNet, StandardCNN, CustomCNN, DenseNet, Inception, and EfficientNet. Moreover, we develop a novel architecture i.e., NeoNet, specifically designed for the detection of retinal diseases, achieving an accuracy of 99.5%. Furthermore, with the aim to provide explaianability behind the model decision, we highlight the most critical regions within retinal images influencing the predictions of the model. The obtained results show the ability of the model to detect pathological features, thereby supporting earlier and more accurate diagnosis of retinal diseases. Full article

Acute respiratory infections (ARIs) continue to pose a major global health threat, particularly among vulnerable populations. These infections often present with similar clinical symptoms, complicating accurate diagnosis and facilitating unmonitored transmissions. Genomic surveillance has emerged as an invaluable tool for pathogen identification and monitoring of such infectious pathogens; however, its implementation is frequently limited by high costs. The widespread use of high-throughput sequencing during the COVID-19 pandemic has created an opportunity to repurpose existing genomic platforms for broader respiratory virus surveillance. In this study, we evaluated the feasibility of adapting the Illumina COVIDSeq assay—initially designed for SARS-CoV-2 whole-genome sequencing—for use with Influenza A/B, Respiratory Syncytial Virus (RSV), and Rhinovirus. Positive control samples were processed using two approaches for library preparation: four virus-specific multiple workflows and a combined rapid workflow. Both workflows incorporated pathogen-specific primers for amplification and followed the Illumina COVIDSeq protocol for library preparation and sequencing. Sequencing quality metrics were analysed, including Phred scores, read length distribution, and coverage depth. The study did not identify significant differences in genome coverage and genetic diversity metrics between workflows. Genome Detective consistently identified the correct species across both methods. The findings of this study demonstrate that the COVIDSeq assay can be effectively adapted for multi-pathogen genomic surveillance and that the combined rapid workflow can offer a cost- and labour-efficient alternative with minimal compromise to data quality. Full article

The use of questionnaire survey results as a clinical diagnostic method for schizophrenia lacks a certain degree of objectivity; thus, markers of schizophrenia in different brain signals have been widely investigated. The objective of this investigation was to explore potential markers of schizophrenia by investigating nonequilibrium features in magnetoencephalography (MEG) signals. We propose a new method to quantify the nonequilibrium features of MEG signals: the multiscale permutation time irreversibility (MsPTIRR) index. The results revealed that the MsPTIRR indices of the MEG recordings of patients with schizophrenia were significantly lower than those of the healthy controls (HCs). Moreover, the MsPTIRR indices of the MEG recordings of patients with schizophrenia and HCs differed significantly in the frontal, occipital, and temporal lobe regions. Furthermore, the MsPTIRR indices of the MEG recordings differed significantly between patients with schizophrenia and HCs in the $\theta$, $\alpha$ and $\beta$ bands. Abnormal nonequilibrium features mined in MEG recordings using the MsPTIRR index may be used as potential markers for schizophrenia, assisting in the clinical diagnosis of this disorder. Full article

Background/Objectives: This study examines the effect of the 2024 update to the AMA Guides to the Evaluation of Permanent Impairment, Sixth Edition, on lower limb impairment determinations in comparison to the 2008 edition. It also explores the broader influence of these changes on regulatory, economic, and adjudicative considerations relevant to physician application and interpretation. Methods: Two experienced evaluators independently reviewed 23 standardized lower limb case scenarios, applying both the 2008 and 2024 methodologies. Each assessment was based solely on clinical history, physical examination findings, and diagnostic test results. Impairment values were then calculated and analyzed for consistency across editions. Results: The 2024 lower limb impairment framework produced outcomes that closely mirrored those of the 2008 edition, with intraclass correlation coefficients of 0.9962 for the lower limb and 0.9951 for whole-person impairment, underscoring the strong consistency between editions. Conclusions: The revised 2024 edition for lower limb assessment enhances procedural clarity and integrates improved diagnosis-based impairment tools without disrupting prior impairment values. These refinements are intended to improve utility for clinical and nonclinical stakeholders, ensuring reliable evaluations while minimizing systemic disruption. Full article

Background: Invasive fungal infections (IFIs) remain a major cause of morbidity and mortality among immunocompromised patients, despite advances in antifungal therapy. Conventional diagnostics are limited, highlighting the need for novel biomarkers. Circulating microRNAs (miRNAs) and cell-free DNA (cfDNA) have emerged as promising tools due to their roles in immune regulation, pathogen–host interactions, and disease monitoring. This systematic review and meta-analysis evaluate their diagnostic and prognostic potential in fungal infections. Methods: A systematic search of PubMed, Web of Science, SCOPUS, and EMBASE was conducted up to May 2025 in line with PRISMA guidelines (PROSPERO protocol CRD42021287150). Eligible studies included clinical research on confirmed fungal infections assessing cfDNA or miRNAs. Random-effects meta-analyses were performed for cfDNA, and miRNA findings were synthesized descriptively. Results: In total, 526 studies were included. cfDNA positivity was observed in 12% of all tested samples (95% CI: 0.06–0.22) and in 79% of patients with proven fungal infections (95% CI: 0.62–0.90), supporting its value as a minimally invasive, culture-independent diagnostic marker. Six studies on miRNAs identified disease-specific signatures, including miR-132 and miRNA panels for aspergillosis, with high diagnostic accuracy (AUC ≥ 0.98). miR-146a, miR-223, and miR-545 further correlated with prognosis and mortality. Conclusions: cfDNA and miRNAs show strong potential for early diagnosis, prognosis, and treatment monitoring in IFIs. Standardized methodologies and large-scale validation are essential for clinical translation. Full article

Background: Rare pediatric neurological diseases (RPND) often remain undiagnosed for years, creating prolonged and costly diagnostic odysseys. Combining Human Phenotype Ontology (HPO)-based deep phenotyping with exome sequencing (ES) and reverse phenotyping offers the potential to improve diagnostic yield, accelerate diagnosis, and support sustainable healthcare in resource-limited settings. Objectives: To evaluate the diagnostic yield and clinical impact of an integrated approach combining deep phenotyping, ES, and reverse phenotyping in children with suspected RPNDs. Methods: In this multicenter observational study, eighty-one children from eleven hospitals in South Kazakhstan were recruited via the Central Asian and Transcaucasian Rare Pediatric Neurological Diseases Consortium. All patients underwent standardized HPO-based phenotyping and ES, with variant interpretation following ACMG guidelines. Reverse phenotyping and interdisciplinary discussions were used to refine clinical interpretation. Results: A molecular diagnosis was established in 34 of 81 patients (42%) based on pathogenic or likely pathogenic variants. Variants of uncertain significance (VUS) were identified in an additional 9 patients (11%), but were reported separately and not included in the diagnostic yield. Reverse phenotyping clarified or expanded clinical features in one-third of genetically diagnosed cases and provided supportive evidence in most VUS cases, although their classification remained unchanged. Conclusions: Integrating deep phenotyping, ES, and reverse phenotyping substantially improved diagnostic outcomes and shortened the diagnostic odyssey. This model reduces unnecessary procedures, minimizes delays, and provides a scalable framework for advancing equitable access to genomic diagnostics in resource-constrained healthcare systems. Full article

Background/Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized outcomes for patients with melanoma. As such, it is important to understand factors that may influence response as well as toxicity to these therapies. Impaired glucose control is often a sign of pathologic inflammation and may alter immune system regulation, but it is unclear whether glucose control impacts patients with melanoma on ICIs. Methods: After reviewing patients with melanoma treated with ICIs at our institution between 2014 and 2024, we assessed whether longitudinal glucose control is associated with patient outcomes (response, progression-free survival, overall survival, and treatment toxicity) during ICI therapy. Results: There was no significant difference in baseline glucose values between responders and non-responders (102.5 vs. 106.0, p = 0.093). Having a baseline glucose over 200 or any glucose over 200 was not significantly associated with response (p = 0.79, p = 0.20), progression-free survival (p = 0.64, p = 0.45), overall survival (p = 0.56, p = 0.36), or toxicity (p = 0.29, p = 0.11). Although a diagnosis of diabetes mellitus was not significantly associated with response (p = 0.84), progression-free survival (p = 0.12), or toxicity (p = 0.11), it was associated with improved overall survival (p = 0.0034) in the small number of patients with diabetes. Conclusions: Overall, we observed that glucose control was not strongly associated with efficacy or toxicity in patients treated with ICIs. Full article

Background: Hypophosphatemia is a frequently underestimated metabolic disorder, yet it can be one of the first biochemical findings in primary hyperparathyroidism (PHPT). Current diagnostic and surgical criteria for PHPT do not include serum phosphate, despite its potential value as an early marker. Methods: We report the case of a 79-year-old woman with type 2 diabetes mellitus, hypertension and osteoarthritis, followed since 2015 for persistent hypophosphatemia (0.8 mg/dL) and stress fractures. Results: Initial calcium and vitamin D levels were normal, but PTH was elevated. Bone scintigraphy revealed multiple stress fractures, while ultrasound and sestamibi scan were inconclusive. Despite cholecalciferol and calcitriol supplementation, hypophosphatemia persisted. From 2023, progressive hypercalcemia developed (10.9 mg/dL), with sustained hypophosphatemia (1.7 mg/dL), persistently high PTH (121 pg/mL) and markedly elevated FGF-23 (1694 kRU/L). Renal phosphate wasting was demonstrated, with reduced tubular reabsorption. An 18F-fluorocholine PET-CT performed in 2024 identified two right parathyroid adenomas, establishing the diagnosis of PHPT. The patient was referred for parathyroidectomy. Conclusions: Hypophosphatemia may serve as a complementary biomarker in the diagnostic and therapeutic approach to PHPT, but only after other potential causes of low phosphate levels have been excluded, as illustrated in this case. Its consideration could facilitate the early identification of PHPT and improve clinical decision-making, particularly in patients who do not meet classical surgical indications. Full article

Immunocompromised outpatients, including people living with HIV/AIDS (PLWH), diabetes, cancer, and organ transplant recipients, are at high risk of antimicrobial resistance (AMR) due to their weakened immune systems and use of immunosuppressive therapies. The high prevalence of prophylactic and therapeutic antibiotic use in this vulnerable population, coupled with frequent contact with healthcare facilities and limited outpatient antimicrobial resistance surveillance systems, contributes to the increase in antimicrobial resistance. The majority of available data pertains to inpatients, and there is a lack of comprehensive outpatient information on pathogen distribution, resistance patterns, and diagnostic challenges. Moreover, nonspecific clinical presentations, diminished inflammatory responses, and limitations of traditional diagnostic methods complicate infection diagnosis in this population. Increasing resistance surveillance, developing rapid diagnostic tools, and implementing accurate and personalized approaches are key strategies to reduce the burden of disease, mortality, and healthcare costs in the immunocompromised outpatient population. This study was designed as a narrative review based on a comprehensive search of major databases and guidelines. It aims to examine the available evidence and address the challenges associated with AMR in immunocompromised outpatients. Full article

Background/Objectives: Sturge–Weber syndrome (SWS) is a rare neuro-oculocutaneous disorder characterized by leptomeningeal angioma, naevus flammeus, and ocular manifestations, including diffuse choroidal hemangioma (DCH). This study compares the diagnostic performance of near-infrared reflectance (NIR) imaging and enhanced depth imaging spectral-domain optical coherence tomography (EDI-SDOCT) with fundus photography in detecting DCH. Methods: Seventeen patients with SWS underwent comprehensive ophthalmologic evaluation, including fundus photography, NIR, and EDI-SDOCT imaging. Sensitivity, specificity, and accuracy of fundus photography, NIR, and EDI-SDOCT were calculated. Results: Sixteen patients had evaluable data. DCH was identified by fundus photography in five (31%), NIR in three (18.75%), and EDI-SDOCT in fourteen patients (87.50%). EDI-SDOCT alone demonstrated 100% sensitivity and 100% accuracy, outperforming both NIR (21.4% sensitivity; 31.6% accuracy) and fundus photography (35.7% sensitivity; 43.8% accuracy). When positive findings on NIR and/or SDOCT were combined, sensitivity and accuracy reached 100%. EDI-SDOCT provided detailed morphologic visualization of the choroid, allowing for early diagnosis of DCH even in pediatric cases with limited patient cooperation. Conclusions: EDI-SDOCT significantly improves the detection of DCH in SWS compared with fundus photography and NIR. Given its superior sensitivity and accuracy, incorporating EDI-SDOCT into routine clinical assessment may enable earlier diagnosis and reduce retinal complications in SWS. Full article

Background: Myocarditis is a recognized complication of COVID-19, but prevalence estimates vary by disease phase and diagnostic method. Methods: We conducted a systematic review and meta-analysis of 54 studies including 32,500 patients, stratified by acute COVID-19, post-COVID, and MIS-C phases. Results: The pooled prevalence of myocarditis was 1.2% (95% CI: 0.8–1.6) in acute COVID-19, 7.4% (95% CI: 5.1–9.8) in post-COVID, and 39.8% (95% CI: 32.4–47.2) in MIS-C. CMR-based diagnosis yielded higher prevalence than clinical criteria (8.1% vs. 0.9%). Major cardiac outcomes included reduced LVEF in 22% and ventricular arrhythmias in 15% of cases. Heterogeneity across studies remained high (I² = 98%). Conclusions: Myocarditis prevalence in COVID-19 varies widely across phases and diagnostic methods. Findings suggest a need for cautious screening approaches, particularly in MIS-C and selected post-COVID or athlete populations, while emphasizing the importance of standardized reporting and long-term follow-up data. Full article

Background: Nurses play a central role in the management of inflammatory joint diseases (IJD), of which the success depends on patient adherence to treatment, self-monitoring, timely detection of adverse drug reactions (ADRs), and adopting a healthy lifestyle. This study sought to examine the opinions of patients with IJD regarding the educational and supportive contributions of nurses. Methods: The research is based on a cross-sectional survey of patients with IJD treated with biologic disease-modifying antirheumatic drugs (bDMARDs) in two rheumatology clinics in Plovdiv, Bulgaria, from the beginning of August 2024 to the end of January 2025. The group included patients of three diagnoses: (1) rheumatoid arthritis (RA), (2) psoriatic arthritis (PsA), and (3) axial spondyloarthritis (axSpA). Results: Regardless of the diagnosis, and after adjusting for covariates, patients rated the roles of nurses in disease treatment and management, the acquisition of self-injection skills for bDMARDs, the implementation of a healthy lifestyle, and the maintenance of psychological well-being at the higher end of the 0 to 4 scale. However, the axSpA patients were less affirmative in their responses compared to the RA and PsA patients. In the RA and PsA groups, the working patients were associated with the lowest ratings, followed by retirees with disability. Conclusions: Our findings indicate that nurse-led education in patient self-management skills is greatly appreciated by patients with IJD. Further developments in specialized training programs tailored to the specific needs of different diagnoses and in consideration of patients’ social status will lead to increased patient satisfaction and a better overall quality of life. Full article

Background: This narrative review summarizes recent progress in artificial intelligence (AI), especially radiomics and deep learning, for non-invasive diagnosis and molecular profiling of gliomas. Methodology: A thorough literature search was conducted on PubMed, Scopus, and Embase for studies published from January 2020 to July 2025, focusing on clinical and technical research. In key areas, these studies examine AI models’ predictive capabilities with multi-parametric Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET). Results: The domains identified in the literature include the advancement of radiomic models for tumor grading and biomarker prediction, such as Isocitrate Dehydrogenase (IDH) mutation, O6-methylguanine-dna methyltransferase (MGMT) promoter methylation, and 1p/19q codeletion. The growing use of convolutional neural networks (CNNs) and generative adversarial networks (GANs) in tumor segmentation, classification, and prognosis was also a significant topic discussed in the literature. Deep learning (DL) methods are evaluated against traditional radiomics regarding feature extraction, scalability, and robustness to imaging protocol differences across institutions. Conclusions: This review analyzes emerging efforts to combine clinical, imaging, and histology data within hybrid or transformer-based AI systems to enhance diagnostic accuracy. Significant findings include the application of DL to predict cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletion and chemokine CCL2 expression. These highlight the expanding capabilities of imaging-based genomic inference and the importance of clinical data in multimodal fusion. Challenges such as data harmonization, model interpretability, and external validation still need to be addressed. Full article