Search Results (17,570)

Background: The aim of this retrospective study was to evaluate correlations between Optical Coherence Tomography (OCT) and Adaptive Optics (AO) of selected retinal parameters in individuals with increased BMI (≥25.0), including a subgroup analysis for hypertension (HTN). Methods: Sixty-three patients (120 eyes) were assessed using AngioVue OCT and rtx1TM AO devices. Retinal thickness (RT), optic nerve head (ONH), ganglion cell complex (GCC), retinal nerve fiber layer (RNFL), and photoreceptor (cone) parameters—density, spacing, regularity, dispersion—were analyzed. Results: A negative correlation between BMI and RT in the parafoveal superior and inferior quadrants was observed. Higher BMI was associated with thinner GCC in the superior and nasal parafoveal regions. Additionally, age negatively correlated with cone density and regularity, and positively with cone spacing and dispersion. Numerous correlations were noted between GCC values in OCT and cone parameters in AO, consistent across both HTN and non-HTN subgroups. Conclusions: The findings suggested that AO may detect retinal changes earlier than OCT. Multimodal imaging provides valuable insights into early structural changes associated with elevated BMI. Long-term monitoring is recommended to evaluate the progression and clinical impact of these findings. Full article

Background: Periapical lesions are common consequences of pulp necrosis but may remain undetectable on conventional intraoral radiographs, becoming evident only on cone-beam computed tomography (CBCT). Improving lesion recognition on plain radiographs is therefore of high clinical relevance. Methods: This retrospective, single-center study analyzed 56 matched pairs of intraoral periapical radiographs (RVG) and CBCT scans. A total of 109 regions of interest (ROIs) were included, which were classified as CBCT-positive/RVG-negative (onlyCBCT, n = 64) or true negative (noLesion, n = 45). Radiomic texture features were extracted from circular ROIs on RVG images using PyRadiomics. Feature distributions were compared using Mann–Whitney U tests with false discovery rate correction, and classification was performed using a logistic regression model with nested cross-validation. Results: Forty-four radiomic texture features showed statistically significant differences between onlyCBCT and noLesion ROIs, predominantly with small to medium effect sizes. For a 40-pixel ROI radius, the classifier achieved a mean area under the ROC curve of 0.71, mean accuracy of 68%, and mean sensitivity of 73%. Smaller ROIs (20–40 pixels) yielded higher AUCs and substantially better accuracy than larger sampling regions (≥60 pixels). Conclusions: Quantifiable radiomic signatures of periapical pathology are present on conventional radiographs even when lesions are visually occult. Radiomics may serve as a complementary decision support tool for identifying CBCT-only periapical lesions in routine clinical imaging. Full article

Objective: Glaucoma is a complex optic neuropathy characterized by the progressive loss of retinal ganglion cells (RGCs). Animal models are crucial tools for deciphering its multidimensional pathogenesis and evaluating novel therapeutic strategies. This review aims to systematically summarize the establishment methods, application advances, and future development trends of various glanimal models. Methods: The literature for this review was identified through systematic searches of electronic databases, including PubMed, Web of Science Core Collection, and Google Scholar. The search strategy utilized a combination of keywords and their variants: “glaucoma”, “animal models”, “retinal ganglion cells”, “intraocular pressure”, “neuroprotection”, “immune inflammation”, “fibrosis”, and “filtration surgery”. The search focused on articles published between 2015 and 2025 to cover the major advances of the last decade. The scope encompassed original research articles, reviews, and meta-analyses. Results: Diverse glanimal models successfully replicate different facets of glaucoma, elucidating multidimensional pathogenesis involving mechanical stress, immune inflammation, excitotoxicity, oxidative stress, and fibrosis. These models have played an indispensable role in screening neuroprotective agents, evaluating anti-fibrotic strategies, and validating the application of advanced imaging and functional assessment technologies. Current research is evolving towards model standardization, multi-factor simulation, and the integration of novel drug delivery systems and immunomodulatory strategies. Conclusions: The diversification of glanimal models provides a powerful platform for in-depth investigation of disease mechanisms and the development of innovative therapies. Future research should focus on establishing standardized models that better mimic the clinical pathological state and deeply integrating multimodal assessment technologies with targeted therapies. This will facilitate the translation of basic research into clinical applications, ultimately achieving personalized precision medicine for glaucoma. Full article

In this study, we propose a YOLO-based object detection algorithm for the automated and accurate identification of the fifth wave (Wave V) in auditory brainstem response (ABR) graphs. The ABR test plays a critical role in the diagnosis of hearing disorders, with the fifth wave serving as a key marker for clinical assessment. However, conventional manual detection is time-consuming and subject to variability depending on the examiner’s expertise. To address these limitations, we developed a real-time detection method that utilizes a YOLO object detection model applied to ABR graph images. Prior to YOLO training, we employed a U-Net-based preprocessing algorithm to automatically remove existing annotated peaks from the ABR images, thereby generating training data suitable for peak detection. The proposed model was evaluated in terms of precision, recall, and mean average precision (mAP). The experimental results demonstrate that the YOLO-based approach achieves high detection performance across these metrics, indicating its potential as an effective tool for reliable Wave V peak localization in audiological applications. Full article

Background/Objectives: AI models such as ChatGPT-4 have shown strong performance in dermatology; however, the diagnostic value of AI-generated clinical image descriptions remains underexplored. This study assesses whether ChatGPT-4’s image descriptions can support accurate dermatologic diagnosis and evaluates their potential integration into the Electronic Medical Record (EMR) system. Materials & Methods: In this Exploratory cross-sectional study, we analyzed images and descriptions from teledermatology consultations conducted between December 2023 and February 2024. ChatGPT-4 generated clinical descriptions for each image, which two senior dermatologists then used to formulate differential diagnoses. Diagnoses based on ChatGPT-4’s output were compared to those derived from the original clinical notes written by teledermatologists. Concordance was categorized as Top1 (exact match), Top3 (correct within top three), Partial, or No match. Results: The study included 154 image descriptions from 67 male and 87 female patients, aged 0 to 93 years. ChatGPT-4 descriptions averaged 74.3 ± 33.1 words, compared to 7.9 ± 3.0 words for teledermatologists. At least one of the two dermatologists achieved a Top 3 concordance rate of 82.5% using ChatGPT-4’s descriptions and 85.3% with teledermatologist descriptions. Conclusions: Preliminary findings highlight the potential integration of ChatGPT-4-generated descriptions into EMRs to enhance documentation. Although AI descriptions were longer, they did not enhance diagnostic accuracy, and expert validation remained essential. Full article

Background: Hip joint disorders exhibit diverse and overlapping radiological features, complicating early diagnosis and limiting the diagnostic value of single-modality imaging. Isolated imaging or clinical data may therefore inadequately represent disease-specific pathological characteristics. Methods: This retrospective study included 605 hip joints from Center A (2018–2024), comprising normal hips, osteoarthritis, osteonecrosis of the femoral head (ONFH), and femoroacetabular impingement (FAI). An independent cohort of 24 hips from Center B (2024–2025) was used for external validation. A multimodal deep learning framework was developed to jointly analyze radiographs, CT volumes, and clinical texts. Features were extracted using ResNet50, 3D-ResNet50, and a pretrained BERT model, followed by attention-based fusion for four-class classification. Results: The combined Clinical+X-ray+CT model achieved an AUC of 0.949 on the internal test set, outperforming all single-modality models. Improvements were consistently observed in accuracy, sensitivity, specificity, and decision curve analysis. Grad-CAM visualizations confirmed that the model attended to clinically relevant anatomical regions. Conclusions: Attention-based multimodal feature fusion substantially improves diagnostic performance for hip joint diseases, providing an interpretable and clinically applicable framework for early detection and precise classification in orthopedic imaging. Full article

Background and Clinical Significance: Acute aortic dissection is the most common and most severe manifestation of acute aortic syndrome. An isolated dissecting aneurysm of the abdominal aorta is defined as a dissecting aneurysm distal to the diaphragm and is an extremely rare disease. Detection of an intimal flap between two lumens using different imaging methods is a definitive diagnostic sign of aortic dissection. A number of studies have validated ultrasound, including point-of-care ultrasound, as the standard initial imaging modality for the diagnosis of aortic dissection. Case Presentation: We present a 39-year-old patient who was sent to our institution under the suspicion of renal colic. The clinical findings revealed pale discoloration of the skin with sweating and abdominal pain. An emergency ultrasound showed an abdominal aortic aneurysm with an intimal flap, as well as free perirenal fluid on the left side. Multislice computed tomography aortography was then performed and the findings indicated rupture of a dissecting aneurysm of the abdominal aorta with a large retroperitoneal hematoma. The patient was then sent to a tertiary institution where he underwent emergency surgery and successfully recovered. Conclusions: Isolated abdominal aortic dissection is a rare condition with often non-specific clinical presentation, making imaging crucial for diagnosis. Ultrasound plays an important role as an initial imaging modality, as the detection of direct or indirect signs of dissection enables timely referral for CT aortography, confirmation of the diagnosis, and initiation of appropriate treatment. Full article

Background and Clinical Significance: Fibrolipoma is an uncommon histological variant of lipoma characterized by mature adipose tissue with a significant fibrous component. Intraoral lipomas are rare (only about 1–4% of all lipomas) and lipomas arising in the buccal fat pad (buccal space) are particularly uncommon. Case Presentation: A 47-year-old male presented with a painless, slowly enlarging swelling in the left cheek region. Physical examination revealed a soft, non-tender mass in the buccal space, causing mild bulging of the cheek. Contrast-enhanced computed tomography and magnetic resonance imaging demonstrated a well-circumscribed lesion within the left buccal fat pad suggestive of a lipoma. The tumor was excised entirely via an intraoral approach under general anesthesia. Histopathological examination showed lobules of mature adipocytes interspersed with dense fibrous connective septa consistent with a diagnosis of a fibrolipoma. The postoperative course was uneventful. Conclusions: This case highlights that fibrolipoma, while rare in the maxillofacial region, should be included in the differential diagnosis of buccal space tumors. Imaging studies can aid in identifying the fatty nature and extent of such lesions, but definitive diagnosis relies on histopathology. The buccal fat pad’s anatomy allows an intraoral surgical approach in appropriate cases, providing direct access and excellent cosmetic outcomes. Complete excision is curative in benign fibrolipomas, and careful surgical technique prevents injury to adjacent structures. Full article

Type 2 diabetes mellitus (T2DM) is characterized not only by chronic hyperglycemia but also by profound adipose tissue dysfunction, including impaired lipid handling, low-grade inflammation, mitochondrial dysfunction, and extracellular matrix (ECM) remodeling. These adipose tissue alterations play a central role in the development of systemic insulin resistance, ectopic lipid accumulation, and cardiometabolic complications. Glucagon-like peptide-1 receptor agonists (GLP-1RAs), particularly semaglutide, have emerged as highly effective therapies for T2DM and obesity. While their glucose-lowering and appetite-suppressive effects are well established, accumulating evidence indicates that semaglutide exerts pleiotropic metabolic actions that extend beyond glycemic control, with adipose tissue representing a key target organ. This review synthesizes current preclinical and clinical evidence on the molecular and cellular mechanisms through which semaglutide modulates adipose tissue biology in T2DM. We discuss depot-specific effects on visceral and subcutaneous adipose tissue, regulation of adipocyte lipid metabolism and lipolysis, enhancement of mitochondrial biogenesis and oxidative capacity, induction of beige adipocyte programming, modulation of adipokine and cytokine secretion, immunometabolic remodeling, and attenuation of adipose tissue fibrosis and ECM stiffness. Collectively, available data indicate that semaglutide promotes a functional shift in adipose tissue from a pro-inflammatory, lipid-storing phenotype toward a more oxidative, insulin-sensitive, and metabolically flexible state. These adipose-centered adaptations likely contribute to improvements in systemic insulin sensitivity, reduction in ectopic fat deposition, and attenuation of cardiometabolic risk observed in patients with T2DM. Despite compelling mechanistic insights, much of the current evidence derives from animal models or in vitro systems. Human adipose tissue-focused studies integrating molecular profiling, advanced imaging, and longitudinal clinical data are therefore needed to fully elucidate the extra-glycemic actions of semaglutide and to translate these findings into adipose-targeted therapeutic strategies. Full article

Background/Objectives: To develop and validate a predictive model that combines morphological features and dual-energy CT (DECT) parameters to non-invasively distinguish metastatic from benign axillary lymph nodes in patients with breast cancer (BC). Methods: In this retrospective study, 117 patients (median age, 65 years; 111 women and 6 men) who underwent DECT followed by axillary lymphadenectomy between April 2015 and July 2023, were analyzed. A total of 375 lymph nodes (180 metastatic, 195 benign) were evaluated. Two radiologists recorded morphological criteria (adipose hilum status, cortical appearance, extranodal extension, and short-axis diameter) and placed regions of interest to measure dual-energy parameters: attenuation at 40 and 70 keV, iodine concentration, water concentration and spectral slope. Normalized iodine concentration was calculated using the aorta as reference. Univariate analysis identified variables associated with metastasis. Multivariate logistic regression with cross-validation was used to construct two models: one based solely on morphological features and one integrating water concentration. Results: On univariate testing, all DECT parameters and morphological criteria differed significantly between metastatic and benign nodes (p < 0.01). In multivariate analysis, water concentration emerged as the only independent DECT predictor (odds ratio = 0.97; p = 0.002) alongside cortical abnormality, absence of adipose hilum, extranodal extension and short-axis diameter. The morphologic model achieved an area under the receiver operating characteristic curve (AUC) of 0.871. Increasing water concentration increased the AUC to 0.883 (ΔAUC = 0.012; p = 0.63, not significant), with internal cross-validation confirming stable performance. Conclusions: A model combining standard morphologic criteria with water concentration quantification on DECT accurately differentiates metastatic from benign axillary nodes in BC patients. Although iodine-based metrics remain valuable indicators of perfusion, water concentration offers additional tissue composition information. Future multicenter prospective studies with standardized imaging protocols are warranted to refine parameter thresholds and validate this approach for routine clinical use. Full article

Background: Cellulite is a highly prevalent condition with dermal and subcutaneous alterations poorly captured by visual grading systems. Ultrasound has emerged as a non-invasive imaging modality capable of objectively quantifying morphological features relevant to cellulite. This systematic review evaluated the evidence on ultrasound for the diagnosis, structural characterization, and treatment monitoring of cellulite, identifying methodological limitations and research gaps. Methods: This systematic review (PROSPERO:CRD420251185486) followed the PRISMA statement. Searches were conducted in PubMed, Scopus, and CENTRAL up to November 2025. Risk of bias was evaluated using ROBINS-I and the Newcastle–Ottawa Scale. Results: Nine studies involving 785 participants were included. Ultrasound frequencies ranged from 12 to 35 MHz, with some scanners operating across broader bandwidths. Despite variability in devices, acquisition protocols, and clinical comparators, all studies consistently demonstrated that ultrasound quantifies key structural characteristics of cellulite. Diagnostic investigations reported moderate-to-strong correlations (r ≈ 0.31–0.64) between ultrasound-derived measures and clinical severity scores. Interventional studies showed measurable reductions in dermal and subcutaneous thickness, decreased adipose protrusion height, and improved dermal echogenicity across multiple treatment modalities. Ultrasound frequently detected microstructural remodeling not readily visible on clinical examination. Conclusions: Ultrasound is a valuable imaging modality for objectively characterizing cellulite and monitoring treatment-induced tissue remodeling. Standardized acquisition protocols, validated analytic criteria, and larger controlled studies are needed to support integration into routine dermatologic and esthetic practice. The quantitative and reproducible nature of ultrasound-derived parameters also provides a suitable foundation for future integration with data-driven and artificial intelligence–based image analysis frameworks. Full article

Background: Patients who undergo pelvic lymphadenectomy for gynecologic or genitourinary cancers have an increased risk of developing lower extremity lymphedema. Although total lymphadenectomy is performed, bilateral lower extremity lymphedema is rare. A state-of-the-art radiologic technique, single-photon emission computed tomography (SPECT) with radioisotope injection, was used to establish lymph flow physiology and identify retrograde lymphatic flow in patients with lower extremity lymphedema after lymphadenectomy. Methods: Data from patients who underwent treatment for lower extremity lymphedema were collected from January 2017 to December 2018. These patients had gynecological or genitourinary cancers and had undergone pelvic lymphadenectomy. Among them, 10 were evaluated for reverse lymph flow using SPECT. The radioisotope was injected solely into the subdermal area of the healthy foot, not the affected foot, in contrast to other studies. Four hours later, SPECT images were obtained and analyzed. The radiologic results were correlated with clinical observations. Results: Most patients had undergone surgery for gynecological cancers. The mean disease duration was 9.4 ± 8.1 years. Retention in the pelvis and hip was confirmed in seven out of ten patients; six patients showed reverse lymphatic flow in the affected limb. Conclusions: SPECT-CT imaging after tracer injection into the unaffected limb revealed retrograde lymphatic flow toward the clinically affected side in a substantial proportion of patients with unilateral lower-extremity lymphedema. Full article

Deep vision foundation models such as DINOv3 offer strong visual representation capacity, but their direct deployment in medical image segmentation remains difficult due to the limited availability of annotated clinical data and the computational cost of full fine-tuning. This study proposes an adaptation framework called StrDiSeg that integrates lightweight bottleneck adapters between selected transformer layers of DINOv3, enabling task-specific learning while preserving pretrained knowledge. An attention-enhanced U-Net decoder with multi-scale feature fusion further refines the representations. Experiments were performed on two publicly available ischemic stroke lesion segmentation datasets—AISD (Non Contrast CT) and ISLES22 (DWI). The proposed method achieved Dice scores of 0.516 on AISD and 0.824 on ISLES22, outperforming baseline models and demonstrating strong robustness across different clinical imaging modalities. These results indicate that adapter-based fine-tuning provides a practical and computationally efficient strategy for leveraging large pretrained vision models in medical image segmentation. Full article

Primary hyperoxalurias (PHs) are rare autosomal recessive disorders characterized by overproduction of oxalate, a metabolic end product that readily forms calcium oxalate crystals. Excess hepatic oxalate leads to recurrent kidney stones, nephrocalcinosis, and progressive renal injury, often culminating in end-stage kidney disease (ESKD). Once renal clearance declines, systemic oxalate accumulation can cause multisystem deposition. PH encompasses three types—PH1, PH2, and PH3—caused by deficiencies in the hepatic enzymes AGT, GRHPR, and HOGA1, respectively, resulting in accumulation of glyoxylate and subsequent oxalate overproduction. Clinical presentation varies from infantile oxalosis to adult-onset recurrent nephrolithiasis, with PH1 generally being the most severe. Diagnosis relies on urinary oxalate measurements, plasma oxalate in advanced chronic kidney disease, urinary metabolite profiling, imaging, and genetic testing. Management includes hyperhydration, citrate supplementation, pyridoxine for responsive PH1 patients, dialysis and transplantation when required, while RNA interference therapies targeting glycolate oxidase or LDHA have demonstrated substantial biochemical efficacy in PH1 and represent promising emerging therapeutic options, although long-term clinical outcome data remain limited and broader applicability to other PH types is still under investigation. Future strategies focus on modulating intestinal oxalate absorption, gut microbiome therapies, oxalate-degrading enzymes, and novel gene-editing approaches. Early diagnosis and individualized management are critical to prevent kidney injury and systemic oxalosis. In this review, we summarize the genetic, biochemical, and clinical features of PH and discuss current and emerging therapeutic strategies. Full article

Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is one of the most common extra-articular manifestations of rheumatoid arthritis (RA) and a leading cause of mortality in RA patients. The diverse and nonspecific clinical presentations of RA-ILD make early diagnosis particularly challenging. In recent years, with a deeper understanding of the pathogenesis of RA-ILD and rapid advancements in medical imaging, artificial intelligence (AI) technologies, and biomarker research, notable progress has been achieved in the diagnostic approaches for RA-ILD. This review summarizes the latest research developments in the diagnosis of RA-ILD, with a focus on the clinical practice guidelines released in 2025. It discusses the application of high-resolution computed tomography (HRCT), the potential of AI in assisting HRCT-based diagnosis, and the discovery and validation of biomarkers. Furthermore, the review addresses current diagnostic challenges and explores future directions, providing clinicians and researchers with a cutting-edge perspective on RA-ILD diagnosis. Full article