The Emergency Medical Treatment and Labor Act (EMTALA) was enacted in 1986 to combat "patient dumping", where principally uninsured patients or those requiring complex care were discharged prematurely or diverted to safety-net hospitals. The law mandates medical screening and stabilization prior to transfer for all patients regardless of ability to pay. Radiology is central to EMTALA compliance, and the statute has significantly influenced radiology practice, facilitating the rise of emergency radiology as a subspecialty. Though EMTALA led to the standardization of emergency imaging protocols and improved access to timely diagnostic evaluation, it also contributed to increased imaging driven by defensive medicine, patient expectations and ER overcrowding. This article presents and analyzes trends in radiology services utilization, shifts in the culture of the field and the relationships between radiologists, other physicians and healthcare facilities.
Physicians operate at the intersection of 2 conflicting imperatives: the clinical mandate to avoid missed diagnoses and the ethical requirement to avoid unnecessary interventions. While advanced imaging can reduce diagnostic uncertainty, overuse introduces systemic inefficiencies, financial waste, and physical harm. This article argues that the solution lies in transitioning from an information maximization mindset to a satisficing framework, rooted in the theory of bounded rationality. Beyond biological risks, additional imaging often identifies insignificant incidental findings, triggering diagnostic cascades and psychological distress. Over-ordering may be motivated by defensive medicine, patient satisfaction pressures, and financial conflicts of interest. A satisficing framework clarifies when additional information is no longer needed. When satisficing, one stops acquiring information once current information is sufficient for action, whereas under a Value of Information (VOI) framework, one stops when the expected incremental benefit of additional information no longer exceeds its incremental costs and harms. Both frameworks reflect that the relationship between clinical utility and imaging data volume is nonlinear; eventually, incremental contributions diminish while cumulative costs continue to rise. Putting this approach into practice requires leveraging Clinical Decision Support Systems (CDSS), minimalist protocols, and increased visibility regarding opportunity costs. Robust safety protocols, including departmental reviews of exception rates and peer reviews, can be used to ensure that satisficing does not lead to increased diagnostic errors. Ultimately, quality in radiology should be defined by whether imaging appropriately informs management, rather than by the volume of data gathered. The goal is to provide the information necessary to act safely and effectively while recognizing when to stop.
U.S. healthcare spending has remained persistently high despite repeated efforts at correction. This essay offers a structural explanation. Waste, excess prices, and administrative complexity matter, but much spending growth reflects durable features of the sector that cannot be readily eliminated. Baumol's cost disease provides the core framework: in labor-intensive services with limited productivity gains, costs rise because wages in them must keep pace with more productive sectors. Medical technology more often expands capacity, utilization, and clinical expectations than it reduces labor inputs. The U.S. physician training pathway is unusually long and expensive, and federal residency caps have artificially constrained physician supply, reinforcing a high compensation floor. The healthcare and social assistance sector functions as a de facto industrial policy, as it is the nation's largest employment sector and the top employer in 38 states, making aggregate cost compression politically costly in ways that are structural, not incidental. Domestic multiplier effects deepen that political durability. Five distinctively American features further limit centralized cost control: population scale and decentralization, higher per capita income, a heavier chronic disease burden, the absence of a national health technology assessment authority, and weaker redistributive institutions. Given the constraints, the aspiration to make American healthcare dramatically cheaper without major disruption is unrealistic. A more credible agenda is to foster local stewardship within a structurally high-cost system.
Emergency radiology operates in a high-acuity, time-sensitive environment where imaging is tightly integrated into real-time clinical decision-making. Growing imaging demand, increasing case complexity, and workforce constraints have intensified pressure on emergency radiologists. Artificial intelligence (AI) has emerged as a potential tool to support imaging prioritization, interpretation, and operational efficiency. However, to meaningfully advance care delivery, the role of AI must be considered beyond algorithm performance, including its implementation, reliability, and real-world clinical impact. In this narrative review, we examine the role of AI across the emergency radiology workflow through three lenses: current capabilities, limitations of the supporting evidence, and practical considerations for clinical implementation. We review applications spanning pre-image acquisition, image acquisition and reconstruction, computer-aided triage and detection, reporting, and follow-up, integrating published evidence with practical insights. Discrepancies between reported and real-world performance, the influence of human-AI interaction on clinical decision-making, and the potential for subtle errors and bias are also discussed. As national regulatory and local governance frameworks continue to evolve, including emerging challenges posed by large language models, gaps remain between reported and real-world AI performance. In emergency radiology, the true impact of AI will depend on how seamlessly and effectively these tools are integrated into existing clinical workflows. Local validation, ongoing performance monitoring, and multidisciplinary institutional oversight are essential to identify performance variability, mitigate biases, and support reliable use in a high-stakes clinical environment.
Intra-abdominal free air is a critical radiologic finding that commonly indicates hollow viscus perforation. Prompt recognition of this finding on plain radiography and computed tomography (CT), 2 of the most commonly used modalities in the setting of suspected hollow viscus perforation, is thus crucial for timely surgical intervention. Diagnosing intra-abdominal free air can be challenging, as it may result from a wide range of both pathologic and benign etiologies. Common pathologic causes include perforation due to peptic ulcer disease (PUD) and diverticulitis and common benign causes include iatrogenic sources such as recent surgery and peritoneal dialysis. Intrinsic limitations of various imaging modalities as well as the condition of the patient also complicate the detection of intra-abdominal free air. As such, it is important to not only detect free air on imaging but to also contextualize it, which can help differentiate surgical from non-surgical causes and guide appropriate management. The goals of this review are to highlight the many causes of free air and the utility of various imaging modalities in its diagnosis, to provide clues to differentiate benign versus surgical etiologies of free air, to suggest a management framework, and to review emerging techniques and future directions in free air detection.
Large total joint arthroplasties (TJA), including total shoulder arthroplasty (TSA; anatomic [aTSA] and reverse [rTSA]), total knee arthroplasty (TKA), and total hip arthroplasty (THA), are among the most commonly performed and cost-effective orthopedic procedures in the United States. Utilization continues to rise due to an aging population with increasing functional demands, younger age at implantation, expanded indications, favorable clinical outcomes, and improved implant longevity. Despite excellent implant survivorship, complications remain clinically important. Imaging plays a central role in the evaluation of the painful arthroplasty, particularly in the emergency setting. Familiarity with normal postoperative appearances and characteristic imaging findings of complications is essential for accurate diagnosis and timely management. This review describes contemporary TSA, THA, and TKA designs and presents an imaging-based approach for evaluation of the painful arthroplasty in the emergency setting. The imaging findings of common complications, such as periprosthetic joint infection (PJI), aseptic loosening, osteolysis, instability, periprosthetic fracture (PPF) and component failure, are reviewed.
Rapid MRI protocols are increasingly used in pediatric emergency imaging, providing fast, high-quality images without ionizing radiation, intravenous contrast, or sedation. These focused exams, using limited, optimized sequences, maintain diagnostic accuracy and can enhance patient flow in emergency settings. It is essential for radiologists to be familiar with key MR imaging findings of both common and rare pediatric emergency conditions, such as appendicitis, ovarian torsion, osteomyelitis, and childhood stroke. This article reviews the clinical indications and protocols for various rapid MRI exams and includes a case-based review of high-yield diagnoses.
Computed tomography (CT) perfusion has become a cornerstone of acute ischemic stroke imaging, extending treatment eligibility beyond conventional time windows and enabling individualized, tissue-based decision-making. Despite its widespread adoption, CT perfusion interpretation remains susceptible to technical, physiologic, and workflow-related pitfalls, which can significantly impact clinical management. Awareness of these pitfalls is essential to guide subsequent management decisions and to avoid inappropriate inclusion or exclusion of patients from endovascular therapy.
Photon counting computed tomography offers spectral capabilities on every scan, significant radiation exposure reductions with improved image quality, and improved spatial resolution. Spectral reconstructions, such as iodine maps and virtual non-contrast images improve the diagnostic capabilities of CT. In the emergency department, photon counting CT has proven benefits in assessing acute conditions, characterizing incidental masses and renal stones. In this review, we highlight some of the benefits of photon counting CT as it pertains to emergency abdominal imaging.
Aortopulmonary shared sheath hematoma is a rare complication of acute aortic syndromes and can occur in the setting of focal rupture of the ascending aortic wall into the common aortopulmonary adventitia. It has been described in the setting of ascending aortic dissection, intramural hematoma, or ruptured aortic aneurysm. Aortic wall rupture into this shared space leads to a hematoma that can extend along the pulmonary arteries and result in extraluminal compression and narrowing of the pulmonary arteries. It is essential for radiologists to recognize the imaging features of aortopulmonary shared sheath hematoma to promptly alert the clinical team, to ensure accurate diagnosis, and to guide urgent management.
Primary chronic pain syndromes are increasingly understood through advanced neuroimaging techniques, which reveal consistent structural, functional, and molecular alterations in the central nervous system. Multi-modal Magnetic Resonance Imaging-including diffusion, structural, and functional approaches-demonstrates reduced gray matter, disrupted neural network connectivity, and altered activation in key pain-processing regions such as the insula, thalamus, and anterior cingulate cortex, with distinct patterns for pain anticipation and stimulus processing. Positron emission tomography/CT imaging further elucidates neurobiological mechanisms, identifying changes in glucose metabolism, neurotransmitter systems, and neuroinflammation, particularly through elevated Translocator Protein (marker of microglial activation) signals and altered opioid and dopaminergic pathways in chronic pain populations. Recent studies highlight the potential of imaging biomarkers for diagnosis, patient stratification, and prediction of treatment response, with machine learning and multivariate pattern analysis improving specificity and classification accuracy. Integrating imaging, molecular, and psychosocial data enables the creation of composite signatures for personalized pain management. Despite these advances, challenges remain in standardizing imaging, validating biomarkers, and implementing findings into routine clinical practice. Ongoing research for imaging pain syndromes focuses on harmonization efforts, large-scale multicenter collaborations, and the integration of artificial intelligence to optimize biomarker utilization and strengthen clinical decision-support systems. This review explores how advanced Magnetic Resonance Imaging and Positron emission tomography/CT techniques have transformed the understanding of primary chronic pain syndromes, facilitating precision diagnosis and targeted therapeutic strategies.
Cerebrospinal fluid (CSF) leaks, whether spontaneous or iatrogenic, can lead to debilitating post-dural puncture or intracranial hypotension-related headaches characterized by orthostatic symptoms. Epidural blood patching (EBP) has become a mainstay treatment once conservative measures (bed rest, hydration, and caffeine) fail. An EBP involves injecting autologous blood into the epidural space to seal dural defects, with success rates ranging from ∼70%-90% for post-dural puncture (iatrogenic) leaks but only ∼30% for spontaneous leaks on the first attempt. For patients with persistent CSF leakage despite repeat EBPs (refractory cases), fibrin sealant ("fibrin glue") injections provide an alternative minimally invasive therapy. Fibrin sealants polymerize into a clot that can patch the dural tear and withstand normal CSF pressures. Several case series report that targeted fibrin glue therapy (alone or combined with blood) yields additional successes, especially in patients who have failed standard blood patches. However, outcomes vary widely, with success rates for fibrin patches in the literature ranging from as low as ∼12%-30% in complex spontaneous leaks to as high as 80%-90% in some cohorts. This review provides a comprehensive overview of CSF leak etiologies and management, focusing on the techniques, efficacy, and indications of EBPs and fibrin glue sealant patches, as well as current evidence and evolving strategies to optimize treatment of these challenging cases.
White matter diseases encompass a heterogeneous spectrum of central nervous system disorders, with neuroimaging serving a pivotal role in their diagnosis and evaluation. Recent advances in imaging techniques and diagnostic frameworks have refined the evaluation of both common and rare entities. Updated criteria for multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin oligodendrocyte glycoprotein antibody-associated disease increasingly incorporate advanced MRI biomarkers, such as the central vein sign and paramagnetic rim lesions, are improving diagnostic specificity and enabling earlier diagnosis. The improved recognition of adult-onset leukodystrophies and other clinically significant conditions, including progressive multifocal leukoencephalopathy, CADASIL, and Susac syndrome, has been driven by characteristic MRI patterns and quantitative imaging approaches. In parallel, artificial intelligence and machine learning techniques, including automated lesion segmentation and radiomics, are emerging as valuable tools for objective lesion quantification, disease classification, and prediction of disease activity.
Psychoradiology is an emerging interdisciplinary subspecialty bridging psychiatry, neuroradiology, and neuroscience to explore the neurobiological basis of mental illness. Using multimodal imaging techniques such as magnetic resonance imaging, functional magnetic resonance imaging, diffusion tensor imaging, magnetic resonance spectroscopy, positron emission tomography, and single photon emission computed tomography, psychoradiology enables the investigation of structural, functional, and neurochemical abnormalities underlying psychiatric disorders. Although neuroimaging has advanced over 4 decades, its clinical diagnostic yield in primary psychiatric syndromes remains limited, serving mainly to exclude secondary structural causes. Recent research demonstrates disease-specific changes in brain morphology, connectivity, and metabolism across schizophrenia, depression, and bipolar disorder, supporting their characterization as intrinsic brain disorders. The integration of imaging findings with clinical and computational models presents emerging opportunities for precision psychiatry. As psychoradiology transitions from research to clinical application, it holds promise for developing imaging biomarkers that inform disease subtyping, prognosis, and individualized treatment response.
Neurodegenerative disorders have traditionally been classified according to clinical syndromes or patterns of anatomical involvement on neuroimaging. However, growing evidence demonstrates that similar clinical phenotypes may arise from distinct molecular pathologies, while a single pathogenic protein may manifest with diverse clinical and imaging presentations. This has led to the emergence of the proteinopathy paradigm, which conceptualizes neurodegeneration as a disorder of protein misfolding, aggregation, and consequent pathologic changes. This review provides an imaging-focused overview of the major central nervous system proteinopathies, including prion diseases, amyloid-β-related disorders, tauopathies, synucleinopathies, and TAR DNA-binding protein 43-associated diseases. We discuss the presence of distinct and often predictable radiological phenotypes in these conditions, which can help in diagnosis, predict clinical progression, and explain clinical phenotype. Conventional magnetic resonance imaging remains central to structural pattern recognition, while advanced techniques such as diffusion-weighted imaging, susceptibility-weighted imaging, perfusion imaging, and quantitative volumetry may enhance diagnostic confidence. Molecular imaging with fluorodeoxyglucose positron emission tomography and emerging amyloid and tau tracers further enables in vivo characterization of disease-specific metabolic and molecular signatures. By integrating molecular mechanisms with imaging findings, this review highlights the role of neuroimaging as a bridge between microscopic protein pathology and macroscopic disease expression. Understanding proteinopathy-specific imaging patterns allows a shift from symptom-led diagnosis toward a biology-driven framework, improving diagnostic accuracy, prognostication, and the potential for targeted therapeutic monitoring in neurodegenerative disease.
