Evidence map›Paper›PMID 40540107›Full record

ReviewJapanese journal of radiology2025

Emergency radiology: roadmap for radiology departments.

Sonay Aydin, Bunyamin Ece, Vefa Cakmak, Burak Kocak, Mehmet Ruhi Onur

Abstract readReview
In one paragraph

Review in Japanese journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sonay AydinDepartment of Radiology, Faculty of Medicine, Erzincan Binali Yildirim University, Erzincan, Türkiye.ORCID http://orcid.org/0000-0002-3812-6333
Bunyamin EceDepartment of Radiology, Faculty of Medicine, Kastamonu University, Kastamonu, Türkiye. bunyaminece@kastamonu.edu.tr.ORCID http://orcid.org/0000-0001-6288-8410
Vefa CakmakDepartment of Radiology, Faculty of Medicine, Pamukkale University, Denizli, Türkiye.ORCID http://orcid.org/0000-0001-7002-5594
Burak KocakDepartment of Radiology, Basaksehir Cam and Sakura City Hospital, Istanbul, Türkiye.ORCID http://orcid.org/0000-0002-7307-396X
Mehmet Ruhi OnurDepartment of Radiology, Faculty of Medicine, Hacettepe University, Ankara, Türkiye.ORCID http://orcid.org/0000-0003-1732-7862

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emergency 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.

Indexed as

Emergency Service, HospitalRadiology Department, HospitalDiagnostic ImagingHumansWorkflowArtificial intelligenceEmergency radiologyInterdisciplinary collaborationMass casualty incidentsOperational workflowTeleradiology

Identifiers

PMID40540107
PMCPMC12479673

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.