Search Results (843)

Objective: The accurate visualization of root canal systems on periapical radiographs is critical for successful endodontic treatment. This study aimed to evaluate and compare the effectiveness of several image enhancement algorithms—including a novel Total Variation–Contrast-Limited Adaptive Histogram Equalization (TV-CLAHE) technique—in improving the detectability of root canal configurations in mandibular incisors, using cone-beam computed tomography (CBCT) as the gold standard. A null hypothesis was tested, assuming that enhancement methods would not significantly improve root canal detection compared to original radiographs. Method: A retrospective analysis was conducted on 60 periapical radiographs of mandibular incisors, resulting in 420 images after applying seven enhancement techniques: Histogram Equalization (HE), Contrast-Limited Adaptive Histogram Equalization (CLAHE), CLAHE optimized with Pelican Optimization Algorithm (CLAHE-POA), Global CLAHE (G-CLAHE), k-Caputo Fractional Differential Operator (KCFDO), and the proposed TV-CLAHE. Four experienced observers (two radiologists and two dentists) independently assessed root canal visibility. Subjective evaluation was performed using an own scale inspired by a 5-point Likert scale, and the detection accuracy was compared to the CBCT findings. Quantitative metrics including Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), image entropy, and Structural Similarity Index Measure (SSIM) were calculated to objectively assess image quality. Results: Root canal detection accuracy improved across all enhancement methods, with the proposed TV-CLAHE algorithm achieving the highest performance (93–98% accuracy), closely approaching CBCT-level visualization. G-CLAHE also showed substantial improvement (up to 92%). Statistical analysis confirmed significant inter-method differences (p < 0.001). TV-CLAHE outperformed all other techniques in subjective quality ratings and yielded superior SNR and entropy values. Conclusions: Advanced image enhancement methods, particularly TV-CLAHE, significantly improve root canal visibility in 2D radiographs and offer a practical, low-cost alternative to CBCT in routine dental diagnostics. These findings support the integration of optimized contrast enhancement techniques into endodontic imaging workflows to reduce the risk of missed canals and improve treatment outcomes. Full article

Background: Positive identification is at the forefront of tasks for forensic practitioners when a set of remains is discovered. Standard means of identification include fingerprints, dental, and DNA analyses; however, additional methods are utilized by forensic practitioners to identify remains when these primary methods of identification are not applicable. Comparative radiography has become a frequently employed approach for positive identification, specifically focused on individualizing characteristics evident in human skeletal variation. Regions that display wide ranges of morphological variation within the human skeleton include the cranium as well as the thorax. With regard to the cranium specifically, paranasal sinuses have been recognized as unique features and are valuable for identification purposes. Objectives: This paper explores the basic information of the anatomy and development, range of variation, and the importance of paranasal sinuses in forensic contexts. Results: This article discusses how practitioners can best use the morphological information contained in the paranasal sinuses and how to compare the antemortem and postmortem datasets involving different imaging modalities for positive identification purposes, in order to provide practical concepts that may assist in cases where paranasal sinuses may be used for forensic human identification. Conclusions: Understanding the development of paranasal sinuses, the imaging techniques applied for their visualization, as well as the principles of identification, is key to conducting proper antemortem vs. postmortem comparisons and effectively utilizing paranasal sinuses in forensic identification contexts. Full article

Background/Objectives: Historically, echocardiographic imaging of the right heart has been challenging because its abnormal geometry is not conducive to reproducible anatomical and functional assessment. With the development of advanced echocardiographic techniques, it is now possible to complete an integrated assessment of the right heart that has fewer assumptions, resulting in increased accuracy and precision. Echocardiography continues to be the first-line imaging modality for diagnostic analysis and the management of acute and chronic right heart failure because of its portability, versatility, and affordability compared to cardiac computed tomography, magnetic resonance imaging, nuclear scintigraphy, and positron emission tomography. Virtually all echocardiographic parameters have been well-validated and have demonstrated prognostic significance. The goal of this narrative review of the echocardiographic parameters of the right heart chambers and hemodynamic alterations associated with right ventricular dysfunction is to present information that must be acquired during each examination to deliver a comprehensive assessment of the right heart and to discuss their clinical significance in right heart failure. Methods: Using a literature search in the PubMed database from 1985 to 2025 and the Cochrane database, which included but was not limited to terminology that are descriptive of right heart anatomy and function, disease states involving acute and chronic right heart failure and pulmonary hypertension, and the application of conventional and advanced echocardiographic modalities that strive to elucidate the pathophysiology of right heart failure, we reviewed randomized control trials, observational retrospective and prospective cohort studies, societal guidelines, and systematic review articles. Conclusions: In addition to the conventional 2-dimensional echocardiography and color, spectral, and tissue Doppler measurements, a contemporary echocardiographic assessment of a patient with suspected or proven right heart failure must include 3-dimensional echocardiographic-derived measurements, speckle-tracking echocardiography strain analysis, and hemodynamics parameters to not only characterize the right heart anatomy but to also determine the underlying pathophysiology of right heart failure. Complete and point-of-care echocardiography is available in virtually all clinical settings for routine care, but this imaging tool is particularly indispensable in the emergency department, intensive care units, and operating room, where it can provide an immediate assessment of right ventricular function and associated hemodynamic changes to assist with real-time management decisions. Full article

This review presents a comprehensive overview of various ultrasound imaging techniques employed in the evaluation of the canine knee joint. It critically analyzes studies conducted on both human and animal subjects, with a focus on the diagnostic accuracy of B-mode ultrasound, Doppler examination, contrast-enhanced ultrasound, and elastography in both normal and pathological conditions. The review underscores the necessity of strict adherence to the protocols of each ultrasound modality and emphasizes the importance of a thorough understanding of the anatomical region to achieve optimal outcomes. The findings suggest that these ultrasound techniques can significantly enhance the diagnostic process, providing valuable insights into anatomy, size, blood supply, and tissue elasticity. Additionally, in cases where advanced imaging modalities such as computed tomography (CT) or magnetic resonance imaging (MRI) are cost-prohibitive or less accessible, ultrasound serves as a reliable alternative, delivering high diagnostic accuracy and critical information regarding mechanical changes in the joint and neovascularization. Full article

A healthy vasculature with well-regulated perfusion and pulsatility is essential for the brain. One vascular structure that has received little attention is the carotid siphon. The proximal portion of the siphon is stiff due to the narrow location in the skull base, whilst the distal portion is highly flexible. This flexible part in combination with the specific curves lead to lower pulsatility at the cost of energy deposition in the arterial wall. This deposited energy contributes to damage and calcification. Severe siphon calcification stiffens the distal part of the siphon, leading to less damping of the pulsatility. Increased blood flow pulsatility is a possible cause of stroke and cognitive disorders. In this review, based on comprehensive multimodality imaging, we first describe the anatomy and physiology of the carotid siphon. Subsequently, we review the in vivo imaging data, which indeed suggest that the siphon attenuates pulsatility. Finally, the data as available in the literature are shown to provide convincing evidence that severe siphon calcifications and the calcification pattern are linked to incident stroke and dementia. Interventional studies are required to test whether this association is causal and how an assessment of pulsatility and the siphon calcification pattern can improve personalized medicine, working to prevent and treat brain disease. Full article

Proper joint function has a significant impact on people’s quality of life. Joints are the point of connection between two or more bones and consist of at least three elements: joint surfaces, the joint capsule, and the joint cavity. Joint diseases are a serious social problem. Risk factors for the development of these diseases include overweight and obesity, gender, and intestinal microbiome disorders. Another factor that is considered to influence joint diseases is trace elements. Under normal conditions, elements such as iron (Fe), copper (Cu), cobalt (Co), iodine (I), manganese (Mn), zinc (Zn), silver (Ag), cadmium (Cd), mercury (Hg), lead (Pb), nickel (Ni) selenium (Se), boron (B), and silicon (Si) are part of enzymes involved in reactions that determine the proper functioning of cells, regulate redox metabolism, and determine the maturation of cells that build joint components. However, when the normal concentration of the above-mentioned elements is disturbed and toxic elements are present, dangerous joint diseases can develop. In this article, we focus on the role of trace elements in joint function. We describe the molecular mechanisms that explain their interaction with chondrocytes, osteocytes, osteoblasts, osteoclasts, and synoviocytes, as well as their proliferation, apoptosis, and extracellular matrix synthesis. We also focus on the role of these trace elements in the pathogenesis of joint diseases: rheumatoid arthritis (RA), osteoarthritis (OA), psoriatic arthritis (PsA), ankylosing spondylitis (AS), and systemic lupus erythematosus (SLE). We describe the roles of increased or decreased concentrations of individual elements in the pathogenesis and development of joint diseases and their impact on inflammation and disease progression, referring to molecular mechanisms. We also discuss their potential application in the treatment of joint diseases. Full article

Museums play an essential role in preserving both cultural and natural heritage, safeguarding samples that offer invaluable insights into our history and scientific understanding. The integration of micro-computed tomography (micro-CT) has significantly advanced the study, restoration, and conservation of these priceless objects. This work explores the application of micro-CT across three critical areas of museum practice: sample virtualization, restoration assessment, and the analysis of fossil specimens. Specifically, micro-CT scanning was applied to fossils stored in the G.A.M.P.S. collection (Scandicci, Italy), enabling the creation of highly detailed non-invasive 3D models for digital archiving and virtual exhibitions. At the Opificio delle Pietre Dure in Florence, micro-CT was employed to evaluate fossil bone restoration treatments, focusing on the internal impact of menthol as a consolidant and its effects on the structural integrity of the material. Furthermore, micro-CT was utilized to investigate a sealed bee preserved in its cocoon within a paleosol in Costa Vicentina (Portugal), providing unprecedented insights into its internal anatomy and state of preservation, all while maintaining the integrity of the specimen. The results of this study underscore the versatility of micro-CT as a powerful non-destructive tool for advancing the fields of conservation, restoration, and scientific analysis of cultural and natural heritage. By integrating high-resolution imaging with both virtual and hands-on conservation strategies, micro-CT empowers museums to enhance research capabilities, improve preservation methodologies, and foster greater public engagement with their collections. Full article

Background: Artificial intelligence (AI) and machine learning (ML) have been reshaping maternal, fetal, neonatal, and reproductive healthcare by enhancing risk prediction, diagnostic accuracy, and operational efficiency across the perinatal continuum. However, no comprehensive synthesis has yet been published. Objective: To conduct a scoping review of reviews of AI/ML applications spanning reproductive, prenatal, postpartum, neonatal, and early child-development care. Methods: We searched PubMed, Embase, the Cochrane Library, Web of Science, and Scopus through April 2025. Two reviewers independently screened records, extracted data, and assessed methodological quality using AMSTAR 2 for systematic reviews, ROBIS for bias assessment, SANRA for narrative reviews, and JBI guidance for scoping reviews. Results: Thirty-nine reviews met our inclusion criteria. In preconception and fertility treatment, convolutional neural network-based platforms can identify viable embryos and key sperm parameters with over 90 percent accuracy, and machine-learning models can personalize follicle-stimulating hormone regimens to boost mature oocyte yield while reducing overall medication use. Digital sexual-health chatbots have enhanced patient education, pre-exposure prophylaxis adherence, and safer sexual behaviors, although data-privacy safeguards and bias mitigation remain priorities. During pregnancy, advanced deep-learning models can segment fetal anatomy on ultrasound images with more than 90 percent overlap compared to expert annotations and can detect anomalies with sensitivity exceeding 93 percent. Predictive biometric tools can estimate gestational age within one week with accuracy and fetal weight within approximately 190 g. In the postpartum period, AI-driven decision-support systems and conversational agents can facilitate early screening for depression and can guide follow-up care. Wearable sensors enable remote monitoring of maternal blood pressure and heart rate to support timely clinical intervention. Within neonatal care, the Heart Rate Observation (HeRO) system has reduced mortality among very low-birth-weight infants by roughly 20 percent, and additional AI models can predict neonatal sepsis, retinopathy of prematurity, and necrotizing enterocolitis with area-under-the-curve values above 0.80. From an operational standpoint, automated ultrasound workflows deliver biometric measurements at about 14 milliseconds per frame, and dynamic scheduling in IVF laboratories lowers staff workload and per-cycle costs. Home-monitoring platforms for pregnant women are associated with 7–11 percent reductions in maternal mortality and preeclampsia incidence. Despite these advances, most evidence derives from retrospective, single-center studies with limited external validation. Low-resource settings, especially in Sub-Saharan Africa, remain under-represented, and few AI solutions are fully embedded in electronic health records. Conclusions: AI holds transformative promise for perinatal care but will require prospective multicenter validation, equity-centered design, robust governance, transparent fairness audits, and seamless electronic health record integration to translate these innovations into routine practice and improve maternal and neonatal outcomes. Full article

Surgery remains a healthcare intervention with significant risks for patients. Novel technologies can now enhance the peri-operative workflow, with artificial intelligence (AI) and extended reality (XR) to assist with pre-operative planning. This review focuses on innovation in AI, XR and imaging for hepato-biliary surgery planning. The clinical challenges in hepato-biliary surgery arise from heterogeneity of clinical presentations, the need for multiple imaging modalities and highly variable local anatomy. AI-based models have been developed for risk prediction and multi-disciplinary tumor (MDT) board meetings. The future could involve an on-demand and highly accurate AI-powered decision tool for hepato-biliary surgery, assisting the surgeon to make the most informed decision on the treatment plan, conferring the best possible outcome for individual patients. Advances in AI can also be used to automate image interpretation and 3D modelling, enabling fast and accurate 3D reconstructions of patient anatomy. Surgical navigation systems utilizing XR are already in development, showing an early signal towards improved patient outcomes when used for hepato-biliary surgery. Live visualization of hepato-biliary anatomy in the operating theatre is likely to improve operative safety and performance. The technological advances in AI and XR provide new applications in pre-operative planning with potential for patient benefit. Their use in surgical simulation could accelerate learning curves for surgeons in training. Future research must focus on standardization of AI and XR study reporting, robust databases that are ethically and data protection-compliant, and development of inter-disciplinary tools for various healthcare applications and systems. Full article

Background/Objectives: Posterior inferior cerebellar artery (PICA) aneurysms are one of the most difficult cerebrovascular lesions to treat and account for 0.5–3% of all intracranial aneurysms. They have deep anatomical locations, broad-neck configurations, high perforator density, and a close association with the brainstem, which creates considerable technical challenges for either microsurgical or endovascular treatment. Despite its acceptance as the standard of care for most posterior circulation aneurysms, PICA aneurysms are often associated with flow diversion using a coil or flow diversion due to incomplete occlusions, parent vessel compromise and high rate of recurrence. This case aims to describe the utility of microsurgical clipping as a durable and definitive option demonstrating the value of tailored surgical planning, preservation of anatomy and ancillary technologies for protecting a genuine outcome in ruptured PICA aneurysms. Methods: A 66-year-old male was evaluated for an acute subarachnoid hemorrhage from a ruptured and broad-necked fusiform left PICA aneurysm at the vertebra–PICA junction. Endovascular therapy was not an option due to morphology and the center of the recurrence; therefore, a microsurgical approach was essential. A far-lateral craniotomy with a partial C1 laminectomy was carried out for proximal vascular control, with careful dissection of the perforating arteries and precise clip application for the complete exclusion of the aneurysm whilst preserving distal PICA flow. Results: Post-operative imaging demonstrated the complete obliteration of the aneurysm with unchanged cerebrovascular flow dynamics. The patient had progressive neurological recovery with no new cranial nerve deficits or ischemic complications. Long-term follow-up demonstrated stable aneurysm exclusion and full functional independence emphasizing the sustainability of microsurgical intervention in challenging PICA aneurysms. Conclusions: This case intends to highlight the current and evolving role of microsurgical practice for treating posterior circulation aneurysms, particularly at a time when endovascular alternatives are limited by anatomy and hemodynamics. Advances in artificial intelligence cerebral aneurysm rupture prediction, high-resolution vessel wall imaging, robotic-assisted microsurgery and new generation flow-modifying implants have the potential to revolutionize treatment paradigms by embedding precision medicine principles into aneurysm management. While the discipline of cerebrovascular surgery is expanding, it can be combined together with microsurgery, endovascular technologies and computational knowledge to ensure individualized, durable, and minimally invasive treatment options for high-risk PICA aneurysms. Full article

Precise medical image segmentation is crucial for advancing computer-aided diagnosis. Although deep learning-based medical image segmentation is now widely applied in this field, the complexity of human anatomy and the diversity of pathological manifestations often necessitate the use of image annotations to enhance segmentation accuracy. In this process, the scarcity of annotations and the lightweight design requirements of associated text encoders collectively present key challenges for improving segmentation model performance. To address these challenges, we propose MedLangViT, a novel language–vision multimodal model for medical image segmentation that incorporates medical descriptive information through lightweight text embedding rather than text encoders. MedLangViT innovatively leverages medical textual information to assist the segmentation process, thereby reducing reliance on extensive high-precision image annotations. Furthermore, we design an Enhanced Channel-Spatial Attention Module (ECSAM) to effectively fuse textual and visual features, strengthening textual guidance for segmentation decisions. Extensive experiments conducted on two publicly available text–image-paired medical datasets demonstrated that MedLangViT significantly outperforms existing state-of-the-art methods, validating the effectiveness of both the proposed model and the ECSAM. Full article

Background/Objectives: This case study presents the first documented use of a low-cost, simulated, patient-specific three-dimensional (3D) printed model to support presurgical planning for an infant with Apert syndrome in a resource-limited setting. The primary objectives are to (1) demonstrate the value of 3D printing as a simulation tool for preoperative planning in low-resource environments and (2) identify opportunities for future AI-enhanced simulation models in craniofacial surgical planning. Methods: High-resolution CT data were segmented using InVesalius 3, with mesh refinement performed in ANSYS SpaceClaim (version 2021). The cranial model was fabricated using fused deposition modeling (FDM) on a Creality Ender-3 printer with Acrylonitrile Butadiene Styrene (ABS) filament. Results: The resulting 3D-printed simulated model enabled the surgical team to assess cranial anatomy, simulate incision placement, and rehearse osteotomies. These steps contributed to a reduction in operative time and fewer complications during surgery. Conclusions: This case demonstrates the value of accessible 3D printing as a simulation tool in surgical planning within low-resource settings. Building on this success, the study highlights potential points for AI integration, such as automated image segmentation and model reconstruction, to increase efficiency and scalability in future 3D-printed simulation models. Full article

Accurate segmentation of cardiac MR images using deep neural networks is crucial for cardiac disease diagnosis and treatment planning, as it provides quantitative insights into heart anatomy and function. However, achieving high segmentation accuracy relies heavily on extensive, precisely annotated datasets, which are costly and time-consuming to obtain. This study addresses this challenge by proposing a novel data augmentation framework based on a condition-guided diffusion generative model, controlled by multiple cardiac labels. The framework aims to expand annotated cardiac MR datasets and significantly improve the performance of downstream cardiac segmentation tasks. The proposed generative data augmentation framework operates in two stages. First, a Label Diffusion Module is trained to unconditionally generate realistic multi-category spatial masks (encompassing regions such as the left ventricle, interventricular septum, and right ventricle) conforming to anatomical prior probabilities derived from noise. Second, cardiac MR images are generated conditioned on these semantic masks, ensuring a precise one-to-one mapping between synthetic labels and images through the integration of a spatially-adaptive normalization (SPADE) module for structural constraint during conditional model training. The effectiveness of this augmentation strategy is demonstrated using the U-Net model for segmentation on the enhanced 2D cardiac image dataset derived from the M&M Challenge. Results indicate that the proposed method effectively increases dataset sample numbers and significantly improves cardiac segmentation accuracy, achieving a 5% to 10% higher Dice Similarity Coefficient (DSC) compared to traditional data augmentation methods. Experiments further reveal a strong correlation between image generation quality and augmentation effectiveness. This framework offers a robust solution for data scarcity in cardiac image analysis, directly benefiting clinical applications. Full article

Objectives: This study sought to assess the impact of diabetes and hypertension on wound healing and recovery in orthopedic patients, with an emphasis on laboratory correlations. Materials and Methods: This study included 67 orthopedic patients, divided into a geriatric group (n = 49, ≥65 years) and a control group (n = 18). Clinical and laboratory assessments were performed at admission and discharge. Data were analyzed statistically. Results: Geriatric patients showed a higher triglyceride glucose-body mass index (TyG-BMI), glucose, cholesterol, C-reactive protein (CRP), interleukin-6 (IL-6), and leukocytes and lower hemoglobin and platelets (PLTs), with poorer healing and well-being. Elevated CRP, IL-6, and urea and decreased protein and hemoglobin persisted in this group. Diabetes improved outcomes in older adults, while hypertension worsened them in younger patients. Favorable outcomes correlated with higher triglycerides, fibrinogen, hemoglobin, and red blood cells (RBCs), while they did not correlate with elevated CRP, IL-6, leptin, urea, creatinine, and white blood cells (WBCs). Conclusions: Key predictors of healing and well-being included CRP, hemoglobin, RBC, and hematocrit in older patients and hypertension, CRP, hemoglobin, and leptin in younger individuals. Age-specific metabolic and inflammatory profiles influence recovery trajectories and may be used to predict problems in both recovery and patients’ well-being. Further research is required to better understand the correlations between these factors. Full article

Background/Objectives: To assess quantitatively the correlation between the lung ultrasound severity scores (LUSSs) and chest CT severity scores (CTSSs) derived from low-dose computed tomography (LDCT) for evaluating pulmonary inflammation in COVID-19 patients. Methods: In this prospective observational study, from an initial cohort of 1000 patients, 555 adults (≥18 years) with confirmed COVID-19 were enrolled based on inclusion criteria. All underwent LDCT imaging, scored by the CTSS (0–25 points), quantifying involvement across five lung lobes. Lung ultrasound examinations using standardized semi-quantitative scales for the B-line (LUSS B) and consolidation (LUSS C) were performed in a subgroup of 170 patients; 110 had follow-up imaging after one week. Correlation analyses included Spearman’s and Pearson’s coefficients. Results: Significant positive correlations were found between the CTSS and both the LUSS B (r = 0.32; p < 0.001) and LUSS C (r = 0.24; p = 0.006), with the LUSS B showing a slightly stronger relationship. Each incremental increase in the LUSS B corresponded to an average increase of 0.18 CTSS points, whereas a one-point increase in the LUSS C corresponded to a 0.27-point CTSS increase. The mean influence of the LUSS on CTSS was 8.0%. Neither ultrasound score significantly predicted ICU admission or mortality (p > 0.05). Conclusion: Standardized lung ultrasound severity scores show a significant correlation with low-dose CT in assessing pulmonary involvement in COVID-19, particularly for the B-line artifacts. Lung ultrasound represents a valuable bedside tool, complementing—but not substituting—CT in predicting clinical severity. Integrating both imaging modalities may enable the acquisition of complementary bedside information and facilitate dynamic monitoring of disease progression. Full article