Web of Science:
Emergency radiology: roadmap for radiology departments

dc.contributor.authorAydin, S.
dc.contributor.authorEce, B.
dc.contributor.authorCakmak, V.
dc.contributor.authorKocak, B.
dc.contributor.authorOnur, M.R.
dc.date.accessioned2025-06-27T09:01:21Z
dc.date.issued2025.01.01
dc.description.abstractEmergency radiology has evolved into a significant subspecialty over the past 2 decades, facing unique challenges including escalating imaging volumes, increasing study complexity, and heightened expectations from clinicians and patients. This review provides a comprehensive overview of the key requirements for an effective emergency radiology unit. Emergency radiologists play a crucial role in real-time decision-making by providing continuous 24/7 support, requiring expertise across various organ systems and close collaboration with emergency physicians and specialists. Beyond image interpretation, emergency radiologists are responsible for organizing staff schedules, planning equipment, determining imaging protocols, and establishing standardized reporting systems. Operational considerations in emergency radiology departments include efficient scheduling models such as circadian-based scheduling, strategic equipment organization with primary imaging modalities positioned near emergency departments, and effective imaging management through structured ordering systems and standardized protocols. Preparedness for mass casualty incidents requires a well-organized workflow process map detailing steps from patient transfer to image acquisition and interpretation, with clear task allocation and imaging pathways. Collaboration between emergency radiologists and physicians is essential, with accurate communication facilitated through various channels and structured reporting templates. Artificial intelligence has emerged as a transformative tool in emergency radiology, offering potential benefits in both interpretative domains (detecting intracranial hemorrhage, pulmonary embolism, acute ischemic stroke) and non-interpretative applications (triage systems, protocol assistance, quality control). Despite implementation challenges including clinician skepticism, financial considerations, and ethical issues, AI can enhance diagnostic accuracy and workflow optimization. Teleradiology provides solutions for staff shortages, particularly during off-hours, with hybrid models allowing radiologists to work both on-site and remotely. This review aims to guide stakeholders in establishing and maintaining efficient emergency radiology services to improve patient outcomes.
dc.identifier.doi10.1007/s11604-025-01819-0
dc.identifier.eissn1867-108X
dc.identifier.endpage
dc.identifier.issn1867-1071
dc.identifier.issue
dc.identifier.startpage
dc.identifier.urihttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=dspace_ku&SrcAuth=WosAPI&KeyUT=WOS:001512529300001&DestLinkType=FullRecord&DestApp=WOS_CPL
dc.identifier.urihttps://hdl.handle.net/20.500.12597/34494
dc.identifier.volume
dc.identifier.wos001512529300001
dc.language.isoen
dc.relation.ispartofJAPANESE JOURNAL OF RADIOLOGY
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectEmergency radiology
dc.subjectMass casualty incidents
dc.subjectTeleradiology
dc.subjectArtificial intelligence
dc.subjectOperational workflow
dc.subjectInterdisciplinary collaboration
dc.titleEmergency radiology: roadmap for radiology departments
dc.typeReview
dspace.entity.typeWos

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