ReviewHealth science reports2025
The Use of Metaverse in Radiology: A Systematic Review.
Review in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- The Use of Metaverse in Radiology: A Systematic Review.Health science reports · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: The integration of the metaverse in radiology represents a transformative advancement in medical imaging, which is pivotal for the diagnosis and treatment of diseases. This review examines how the metaverse, characterized by 3D and decentralized virtual reality environments, enhances the interpretation of medical images, including X-rays, MRIs, CT scans, ultrasounds, and mammograms. Methods: This systematic review searched PubMed, Scopus, and Web of Science for English-language studies on metaverse applications in radiology published until June 2024. Inclusion criteria encompassed original research articles focusing on metaverse applications in radiology. Data extraction involved three independent reviewers utilizing a structured form to collect information on study characteristics and outcomes. Results: Of 212 articles found through the initial search, 21 studies were eligible for review inclusion. Most of the studies (52%) were developmental research and China was the country with the most published studies (33%). Reviewing the outcomes of studies revealed significant advancements in medical technology, encompassing the development of novel diagnostic tools, successful integration of imaging technologies, and innovative modeling and simulation approaches. MRI and CT were the most common techniques, reflecting their primary role in diagnostic imaging and the potential of metaverse applications to enhance their effectiveness. Conclusion: The metaverse enables significant advancements in radiology, including new diagnostic tools, imaging integration, and simulation approaches. Future research should explore practical applications, patient outcomes, and best practices to optimize its integration into clinical workflows and improve patient care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.