Search Results (3,369)

Artificial intelligence (AI) is reshaping the field of diagnostic radiology; however, its applications in interventional radiology and pediatric interventional radiology (PIR) remain limited despite clear clinical needs and the rich multimodal data environment characteristic of pediatric procedural care. In this narrative review, I summarize the current state of AI technologies relevant to PIR and outline future perspectives for their clinical integration. Peer-reviewed literature and position statements identified through MEDLINE/PubMed, Embase, Scopus, and major society publications up to the first quarter of 2026 are synthesized, focusing on AI applications across the PIR care pathway, including dose-sparing image acquisition and reconstruction, automated image interpretation and computer-aided diagnosis, data-driven procedural planning and navigation, and post-procedural risk prediction and monitoring. After briefly introducing core machine learning and deep learning concepts, pediatric-specific challenges are discussed, including radiation sensitivity, growth-related anatomical variability, regulatory constraints, and the scarcity of large, annotated datasets, as well as existing and emerging applications along the PIR care pathway: AI-assisted dose reduction and image reconstruction, automated image interpretation, segmentation, and computer-aided diagnosis; data-driven procedural planning, including three-dimensional modelling, augmented reality, AI-enabled/AI-adjacent robotics, and AI-directed procedural navigation; and post-procedural risk prediction and outcome monitoring. Finally, emerging paradigms, including explainable AI, federated learning, and multimodal integration, are highlighted, and research priorities, collaborative frameworks, and governance principles required to ensure safe, equitable, and effective AI deployment in PIR are outlined. In doing so, this review delineates the current evidence gaps and priority directions for clinically meaningful AI adoption in PIR. Although AI has the potential to improve patient care, it has not yet been specifically designed, validated, or deployed in children. Existing work demonstrates feasibility across the PIR workflow, but most tools remain weakly linked to pediatric clinical endpoints. Full article

Vitamin D is a fat-soluble secosteroid essential for skeletal development and calcium homeostasis, but it also exerts pleiotropic effects on numerous biological processes via its active metabolites. Vitamin D metabolites act as steroid hormones that regulate cell-cycle progression, proliferation, differentiation, apoptosis, immune responses, and multiple intracellular signaling pathways. Moreover, they modulate the expression of genes involved in carcinogenesis. As circulating vitamin D levels are influenced by diet, fortified foods, and supplementation, they represent a potentially modifiable factor. Whether vitamin D status affects cancer risk or disease progression in carriers of pathogenic BRCA1 variants remains unclear and continues to be actively investigated. Clarifying this relationship could have significant clinical implications for risk stratification and prevention in this high-risk population. This narrative review summarizes current evidence from epidemiological, clinical, and molecular studies examining the role of vitamin D in BRCA1 pathogenic variant carriers. It also highlights key limitations in the existing literature and identifies critical directions for future research, emphasizing the need for well-designed prospective studies in representative cohorts. Full article

Osteoporotic vertebral fractures (OVFs) are the most common fragility fractures, representing a substantial burden on healthcare systems worldwide. Although up to 30% of OVFs may be clinically silent, a subset of patients experiences an unfavorable course, developing painful pseudoarthrosis/nonunion, progressive vertebral collapse, and even neurological compromise. While initial OVF management is typically nonoperative, a considerable proportion of patients ultimately require surgical intervention. However, clear and universally accepted surgical indications are lacking, rendering clinical decision-making complex and highly individualized. In this context, evaluating the spine’s ability to withstand physiological loads in the presence of potential instability is a critical step in the treatment algorithm. Nevertheless, spinal stability remains a dynamic and multifactorial concept that requires comprehensive assessment integrating both clinical and radiological parameters. This narrative review synthesizes the current state-of-the-art literature on the assessment of stability in OVFs, with particular clinical emphasis on clinical applicability. It revisits classical trauma-derived concepts and adapts them to the specific context of OVFs. We examine the respective roles of radiography, CT and MRI in evaluating fracture characteristics and spinal stability and summarize the main clinical and radiological markers. Furthermore, we distinguish between predictors of fracture progression and indirect indicators of established or evolving instability. Finally, we review current classification systems and outline general treatment considerations, focusing on how imaging findings may guide clinical decision-making in OVFs. Overall, this review provides a comprehensive framework of key imaging and clinical features that should be systematically assessed to estimate the risk of spinal instability. Full article

Thoracolumbar stump ribs are one of the essential indicators of thoracolumbar transitional vertebrae or enumeration anomalies. While some studies manually assess these anomalies and describe the ribs qualitatively, this study aims to automate thoracolumbar stump rib detection and analyze their morphology quantitatively. To this end, we train a high-resolution deep learning model for rib segmentation using nnUNet and achieve significant improvements over existing models (Dice score 0.997 vs. 0.779, p-value < 0.01). In addition, we employ a novel iterative algorithm and piecewise linear interpolation to estimate rib length, achieving a success rate of 98.2%. When analyzing morphological features, we show that stump ribs articulate more posteriorly at the vertebrae ($-19.2\pm 3.8$ vs. $-13.8\pm 2.5$ mm, p-value < 0.01), are thinner ($260.6\pm 103.4$ vs. $563.6\pm 127.1$${\mathrm{mm}}^2$, p-value < 0.01), and are oriented more downwards and sideways within the first centimeters in contrast to full-length ribs. We show that with partially visible ribs, these features can achieve an F1-score of 0.84 and an AUC of 0.98 in differentiating stump ribs from regular ones. We publish the model weights and masks for public use. Full article

Background and Clinical Significance: Tumefactive Multiple Sclerosis (TMS) represents a rare and diagnostically challenging form of demyelinating disease characterized by large space-occupying lesions that can closely mimic intracranial neoplasms, abscesses, and other inflammatory or vascular conditions. Case Presentation: The case highlights the overlapping radiologic features that frequently lead to diagnostic uncertainty and underscores the importance of careful interpretation of multimodal imaging and ancillary studies. Overall a comprehensive multidisciplinary evaluation is essential to reduce the risk of misdiagnosis and avoid unnecessary invasive interventions. Conclusions: This review summarizes current evidence regarding the diagnostic approach, imaging characteristics, and therapeutic strategies for tumefactive demyelinating lesions. Additionally, we present a clinical case that illustrates the diagnostic complexity of this entity, in which neuroimaging findings and cerebrospinal fluid analysis supported a demyelinating rather than neoplastic process. Full article

Artificial intelligence (AI) is increasingly integrated into emergency general surgery (EGS), where rapid diagnosis, accurate decision-making, and timely intervention are essential for improving patient outcomes. Recent advances in machine learning, deep learning, computer vision, and predictive analytics have enabled AI-assisted systems to support clinicians throughout the perioperative workflow. Current applications include radiologic image interpretation, diagnosis of acute abdominal conditions, surgical workflow recognition, intraoperative anatomical guidance, postoperative complication prediction, and intensive care monitoring. AI technologies may improve diagnostic accuracy, optimize operative planning, enhance surgical safety, and facilitate personalized perioperative management. In minimally invasive surgery, computer vision and real-time data analysis have shown promising results for intraoperative decision support and surgical education. However, important limitations remain, including concerns regarding data quality, algorithm transparency, ethical governance, regulatory approval, and implementation disparities between healthcare systems. In addition, much of the current evidence is derived from retrospective or highly specialized datasets, limiting broad clinical applicability. This narrative review summarizes the current clinical applications of AI in emergency general surgery and discusses emerging technologies, existing challenges, and future perspectives regarding the integration of AI into acute surgical care. Full article

Cone-beam computed tomography (CBCT) is widely used in dentomaxillofacial imaging, but its expanding use requires cautious appraisal of stochastic risk and dose optimization. This updated structured narrative review summarizes evidence on organ dose, effective dose, modeled cancer-risk estimation, cumulative exposure, diagnostic reference levels, and patient shielding in dental CBCT. PubMed/MEDLINE and Scopus searches were updated to 15 May 2026. Overall, 24 primary studies were synthesized: 9 addressing dose, diagnostic reference levels, cumulative exposure, or cancer-risk modeling, and 15 evaluating shielding or radiation-protection strategies. Dose and modeled risk varied markedly according to scanner type, field of view, exposure parameters, anatomical region, age, sex, and repeat imaging. The salivary glands, oral mucosa, thyroid, and eye lens were the most relevant exposed organs; children, female patients, and patients undergoing repeated imaging represented the most vulnerable groups. Shielding studies reported substantial dose reductions in selected protocols, but the benefit depended on shield design, positioning, field of view, and image-quality impact. Dental CBCT should be prescribed only when three-dimensional information is expected to change management and should be optimized through the smallest adequate field of view, low-dose protocols, cumulative-dose awareness, and selective shielding when diagnostically appropriate. Full article

Background: Lateral cephalometric radiographs and large-field cone-beam computed tomography (CBCT) routinely used in orthodontics and maxillofacial radiology can reveal incidental pituitary tumors in the sellar region. Given the regular use of these imaging modalities, a structured overview of how pituitary tumors present on dental radiographs and how often they occur is clinically relevant. Methods: A scoping review was conducted according to PRISMA-ScR. MEDLINE via PubMed, Livivo, and Google Scholar were searched up to 20 January 2026 using MeSH terms and keywords for pituitary tumors and dental radiology. Human studies in English or German reporting on radiological presentation, clinical manifestation and epidemiology of pituitary tumors in the context of dental imaging were included. Study selection was performed independently by two reviewers. Results: Of 150 records, 15 studies were included: 2 case–control studies, 5 observational studies, 6 case reports, 1 questionnaire-based study and 1 neurosurgical guideline. Pituitary tumors most frequently presented with enlargement, deformation, or double contour of the sella turcica; growth hormone-producing adenomas additionally showed cephalometric changes such as mandibular and frontal sinus enlargement. The evidence is largely descriptive and does not permit robust estimates of prevalence or diagnostic accuracy but consistently identifies radiological “red flags” and recurrent clinical constellations, especially in acromegaly or unexplained craniofacial changes. Conclusions: Pituitary tumors, among the most common brain tumors, may first be suspected on routine dental radiographs. Distinct radiographic abnormalities combined with suggestive clinical features should prompt timely endocrine and neuroradiological evaluation, underscoring the need for heightened awareness among dental professionals. Full article

Background: Chest radiography remains central to post-procedural assessment of central venous catheter (CVC) placement in intensive care units. Multimodal large language models (MLLMs) can process medical images, but their reliability for practical radiography tasks remains uncertain. This study assessed the diagnostic performance of MLLMs and intensivists for CVC access classification, CVC tip assessment, and pneumothorax-related radiographic findings. Methods: In this retrospective diagnostic performance study, consecutive portable anteroposterior chest radiographs obtained after CVC placement in adult critically ill patients were independently evaluated by four intensivists and five MLLMs. A radiologist consensus served as the reference standard. Interobserver agreement and diagnostic performance were assessed using Fleiss’ kappa, Gwet AC1, Cohen’s kappa, accuracy, sensitivity, specificity, precision, F1 score, balanced accuracy, and Matthews correlation coefficient. Results: The final cohort included 183 unique radiographs. Intensivist reviewers showed high performance for CVC access classification but lower and more heterogeneous performance for CVC tip-position assessment. Among MLLMs, CVC access accuracy ranged from 0.339 to 0.874, whereas CVC tip assessment was dominated by almost universal classification of tips as appropriate, with near-zero specificity and chance-level balanced accuracy. For pneumothorax-related findings, all MLLMs classified every case as negative. Intensivist reviewers had higher balanced accuracy than MLLMs for CVC access classification (difference, 0.420; 95% CI, 0.349–0.490; p < 0.001) and CVC tip assessment (difference, 0.247; 95% CI, 0.205–0.290; p < 0.001). Pneumothorax analyses were exploratory because only five positive cases were present. Conclusions: The evaluated MLLMs showed unreliable diagnostic performance compared with experienced intensivists. Apparent performance was influenced by class imbalance and dominant-response behavior, supporting cautious task-specific validation and complete diagnostic performance reporting. Full article

Diagnostic imaging is central to clinical decision-making across many care pathways, yet the expertise needed to use these images well is unevenly distributed across health systems, with workforce limitations identified as a major barrier to equitable access, particularly in low- and middle-income countries. Digital education has emerged as one response to this gap, offering scalability, asynchronous and just-in-time access, and the cost-efficiency required for global deployment. This paper examines the digital education portfolio of the International Atomic Energy Agency’s Nuclear Medicine and Diagnostic Imaging Section, hosted mainly on the open-access Human Health Campus, which in 2025 recorded approximately 45,800 active users and 150,000 views across 159 countries. The portfolio combines structured e-learning courses, interactive webinars, virtual conference access through the Livestream programme, and a broader repository of publications, teaching cases, and reference resources, supported by an internal e-learning framework and learning management system infrastructure. Partnerships with international scientific societies further extend the reach of expert knowledge and professional exchange. The paper argues that these initiatives are best understood not as content delivery alone but as a coordinated strategy to support diagnostic quality at the level of the practising physician, extending access to expertise and strengthening the conditions for better practice, while remaining a complement to, rather than a substitute for, supervised clinical training. Full article

99mTc-pyrophosphate (PYP) scintigraphy is widely used for the noninvasive evaluation of transthyretin cardiac amyloidosis. Although interpretation primarily focuses on myocardial uptake, confirmation of appropriate systemic radiotracer biodistribution is essential. We report a case in which an examination presumed to be 99mTc-PYP scintigraphy demonstrated free 99mTc-pertechnetate-like biodistribution. A 75-year-old woman with chronic kidney disease and conduction disturbance underwent 99mTc-PYP scintigraphy for suspected cardiac amyloidosis. The initial study, recorded as the administration of 740 MBq 99mTc-PYP, was imaged 3 h after injection. Planar imaging showed mild apparent activity over the cardiac region; however, SPECT/CT demonstrated no definite myocardial uptake. Instead, intense uptake was observed in the stomach and thyroid gland, with complete absence of skeletal activity. This distribution was inconsistent with correctly administered 99mTc-PYP and suggested free 99mTc-pertechnetate biodistribution, likely due to radiopharmaceutical preparation or administration error. A repeat 99mTc-PYP scan 1.5 months later showed expected skeletal uptake without gastric or thyroid activity and again demonstrated no myocardial uptake. The study was interpreted as negative for cardiac amyloidosis. Gastric and thyroid uptake with absent skeletal activity on presumed 99mTc-PYP scintigraphy should be considered nondiagnostic rather than negative. Full article

Non-cystic fibrosis bronchiectasis (NCFB) is a heterogeneous chronic airway disease characterized by irreversible bronchial dilatation, impaired mucociliary clearance, and recurrent infection. Historically, research and clinical practice have focused mainly on bacteria, particularly Pseudomonas aeruginosa, as major drivers of exacerbations and disease progression, whereas the contribution of fungi has received far less attention. Over the last decade, evidence from mycobiome studies, large registries, and prospective cohorts has increasingly identified Aspergillus spp. as clinically relevant contributors in a substantial subset of patients with bronchiectasis. Data from the European Bronchiectasis Registry (EMBARC) indicate that approximately one quarter of patients exhibit Aspergillus-related immunological signals, including allergic bronchopulmonary aspergillosis (ABPA), Aspergillus sensitization, and elevated Aspergillus-specific IgG, and that these phenotypes are associated with more severe disease and worse clinical outcomes. Mechanistic studies further suggest that Aspergillus-related disease in bronchiectasis is underpinned by distinct molecular and immunological programs involving epithelial dysfunction, impaired mucociliary clearance, innate fungal sensing, inflammasome-related signaling, and divergent type-2 versus non-type-2 inflammatory responses. In parallel, mycobiome and multi-biome studies indicate that Aspergillus should be interpreted within a broader airway interactome shaped by cross-kingdom relationships with bacterial pathogens and by host immune tone. In this review, we synthesize current evidence on the epidemiology, molecular pathobiology, inflammatory endotypes, biomarker profiles, clinical–radiologic spectrum, and therapeutic implications of Aspergillus in bronchiectasis. Current evidence suggests that Aspergillus-related findings in bronchiectasis should be interpreted within a structured clinical, radiological, microbiological, and immunological framework rather than considered solely as isolated culture results. However, most data remain observational or extrapolated from related airway diseases, and bronchiectasis-specific interventional evidence is limited. A cautious biomarker-informed approach may help standardize phenotyping, identify patients requiring closer follow-up, and define priorities for future prospective trials. Full article

Background/Objectives: CT-guided lung biopsy is an essential diagnostic procedure but is associated with complications such as pneumothorax and pulmonary hemorrhage. While patient- and lesion-related factors are well established, operator-modifiable parameters remain less clearly defined. This study aimed to evaluate complication rates and identify independent predictors, with a particular focus on modifiable procedural factors. Methods: This retrospective study included 309 consecutive patients undergoing CT-guided transthoracic lung biopsy. Patient, lesion, and procedural variables—including needle–pleura angle and patient positioning—were analyzed. Complications were classified according to the Society of Interventional Radiology (SIR) system. Multivariate logistic regression analyses were performed to identify independent predictors. Results: Complications occurred in 20.4% of patients, with pneumothorax (14.2%) and hemorrhage (4.9%) being the most frequent. A needle angle ≤ 65° was independently associated with major complications (OR = 8.12, p = 0.025). Perilesional emphysema (OR = 19.38, p = 0.004) and pleural effusion (OR = 30.72, p = 0.001) were also strong predictors. Supine positioning significantly increased hemorrhage risk (OR = 9.03, p = 0.043). Conclusions: Operator-modifiable factors, particularly needle angle and patient positioning, may influence complication risk. Optimization of these parameters may provide a practical approach to improving procedural safety in CT-guided lung biopsy. Full article

Introduction: Cryoablation is an established nephron-sparing option for small renal masses, particularly in patients unsuitable for surgery. However, definitive histopathological assessment post-ablation is limited due to the in situ nature of treatment. This report details a case of delayed partial nephrectomy after cryoablation, enabling comprehensive histopathological evaluation of long-term treatment effects. Case presentation: A 50-year-old man with uncontrolled hypertension, diabetes, and triple-vessel coronary disease presented with a 2.5 cm right renal mass. Cardiovascular instability deferred initial surgery. Following coronary intervention requiring anticoagulation, percutaneous cryoablation was performed using CT-guided 3D reconstruction for precise probe placement and ice-ball confirmation. After 388 days, laparoscopic partial nephrectomy was performed. Histopathology revealed a 1.9 cm clear cell renal cell carcinoma. Approximately one-third of tissue showed post-cryoablation changes. Three distinct zones were identified: viable carcinoma, coagulative necrosis with preserved glomerular outlines, and viable parenchyma. Serial follow-up over 2 years showed transient creatinine elevation normalizing by 3 months, with no recurrence or metastasis. Conclusions: This case provides rare whole-lesion histopathological assessment after renal cryoablation, illustrating heterogeneous long-term tissue response and supporting cryoablation as a disease-control or bridging strategy in medically high-risk patients. Full article

Background: Robotic-assisted bronchoscopy enables precise navigation to peripheral pulmonary lesions and expands minimally invasive diagnostic options in thoracic surgery. At our institution, the ION™ Endoluminal System (Intuitive Surgical, Sunnyvale, CA, USA) was introduced to improve diagnostic accuracy in challenging peripheral targets. It is widely recognized that a defined number of procedures is required to achieve procedural proficiency and optimal clinical outcomes when adopting a novel platform. Therefore, this retrospective single-center study aimed to evaluate the learning curve associated with the implementation of this technology in a thoracic surgery center. Methods: In this retrospective study, all consecutive patients who underwent robotic-assisted bronchoscopies performed using the ION™ Endoluminal System (Intuitive Surgical, Sunnyvale, CA, USA) for the diagnosis of peripheral pulmonary lesions between August 2024 and March 2026 were analyzed. A total of 128 lesions in 89 patients were initially identified. Cases involving marker placement without diagnostic biopsy, as well as procedures not performed by the primary operator, were excluded. After applying exclusion criteria, 109 procedures in 76 patients were included. The mean patient age was 65.4 ± 9.1 years, and 44 patients were female (57.9%). To assess the learning curve, procedures were chronologically divided into three groups: early (cases 1–36), intermediate (37–73), and late (74–109). Outcome measures included procedure time, number of biopsies per lesion, tumor size, and diagnostic yield. Group comparisons were performed using non-parametric and chi-square tests. Procedural learning was assessed by cumulative sum (CUSUM) analysis of procedure time. Results: The overall diagnostic yield was 85.3% (93/109). The diagnostic yield increased over time from 73.0% in the early phase to 83.3% in the intermediate phase and 94.6% in the late phase. The overall comparison was statistically insignificant (χ² p = 0.117); however, there was a significant linear trend across phases, indicating progressive improvement with exposure to the application of this technology. Procedure time decreased significantly from a median of 49.0 min in the early phase to 31.0 min in the intermediate phase and 30.0 min in the late phase (p < 0.001). At the same time, the number of biopsies per lesion increased significantly (p < 0.001). Tumor size did not differ significantly between groups (p = 0.170). Conclusions: Robotic-assisted bronchoscopy demonstrates a clear learning curve, characterized by increasing diagnostic yield and significantly reduced procedure time during the implementation phase. The technique can be effectively integrated into the thoracic surgical diagnostic workflow and represents a valuable addition to minimally invasive diagnostics for peripheral pulmonary lesions. Full article