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Gamba IAD, Hartery A. The Virtual Reality Radiology Workstation: Current Technology and Future Applications. Can Assoc Radiol J 2024; 75:479-487. [PMID: 38362857 DOI: 10.1177/08465371241230278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2024] Open
Abstract
Virtual reality (VR) and augmented reality (AR) technology hold potential across many disciplines in medicine to expand the delivery of education and healthcare. VR-AR applications in radiology, in particular, have gained prominence and have demonstrated advantages in many areas within the field. Recently, VR software has emerged to redesign the physical radiology workstation (ie, reading room) to expand the possibilities of diagnostic interpretation. Given the novelty of this technology, there is limited research investigating the potential applications of a simulated radiology workstation. In this review article, we explore VR-simulated reading room technology in its current form and illustrate the practical applications this technology will bring to future radiologists and learners. We also discuss the limitations and barriers to adopting this technology that must be overcome to truly understand its potential benefits. VR reading room technology offers great potential in radiology, but further research is needed to appreciate its benefits and identify areas for improvement. The findings and insights presented in this review contribute to the ongoing discourse on future technological advancements in radiology and healthcare, offering valuable recommendations for further research and practical implementation.
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Affiliation(s)
- Iain A D Gamba
- Memorial University of Newfoundland, St. John's, NL, Canada
| | - Angus Hartery
- Memorial University of Newfoundland, St. John's, NL, Canada
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Yang L, Ene IC, Arabi Belaghi R, Koff D, Stein N, Santaguida PL. Stakeholders' perspectives on the future of artificial intelligence in radiology: a scoping review. Eur Radiol 2022; 32:1477-1495. [PMID: 34545445 DOI: 10.1007/s00330-021-08214-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/11/2021] [Accepted: 07/12/2021] [Indexed: 12/31/2022]
Abstract
OBJECTIVES Artificial intelligence (AI) has the potential to impact clinical practice and healthcare delivery. AI is of particular significance in radiology due to its use in automatic analysis of image characteristics. This scoping review examines stakeholder perspectives on AI use in radiology, the benefits, risks, and challenges to its integration. METHODS A search was conducted from 1960 to November 2019 in EMBASE, PubMed/MEDLINE, Web of Science, Cochrane Library, CINAHL, and grey literature. Publications reflecting stakeholder attitudes toward AI were included with no restrictions. RESULTS Commentaries (n = 32), surveys (n = 13), presentation abstracts (n = 8), narrative reviews (n = 8), and a social media study (n = 1) were included from 62 eligible publications. These represent the views of radiologists, surgeons, medical students, patients, computer scientists, and the general public. Seven themes were identified (predicted impact, potential replacement, trust in AI, knowledge of AI, education, economic considerations, and medicolegal implications). Stakeholders anticipate a significant impact on radiology, though replacement of radiologists is unlikely in the near future. Knowledge of AI is limited for non-computer scientists and further education is desired. Many expressed the need for collaboration between radiologists and AI specialists to successfully improve patient care. CONCLUSIONS Stakeholder views generally suggest that AI can improve the practice of radiology and consider the replacement of radiologists unlikely. Most stakeholders identified the need for education and training on AI, as well as collaborative efforts to improve AI implementation. Further research is needed to gain perspectives from non-Western countries, non-radiologist stakeholders, on economic considerations, and medicolegal implications. KEY POINTS Stakeholders generally expressed that AI alone cannot be used to replace radiologists. The scope of practice is expected to shift with AI use affecting areas from image interpretation to patient care. Patients and the general public do not know how to address potential errors made by AI systems while radiologists believe that they should be "in-the-loop" in terms of responsibility. Ethical accountability strategies must be developed across governance levels. Students, residents, and radiologists believe that there is a lack in AI education during medical school and residency. The radiology community should work with IT specialists to ensure that AI technology benefits their work and centres patients.
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Affiliation(s)
- Ling Yang
- McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada
| | - Ioana Cezara Ene
- McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada
| | - Reza Arabi Belaghi
- University of Tabriz, 29 Bahman Boulevard, Tabriz, East Azerbaijan Province, Iran
| | - David Koff
- Department of Radiology, McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada
| | - Nina Stein
- McMaster Children's Hospital, McMaster University, 1280 Main St W, Hamilton, ON, L8N 3Z5, Canada
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Uppot RN, Laguna B, McCarthy CJ, De Novi G, Phelps A, Siegel E, Courtier J. Implementing Virtual and Augmented Reality Tools for Radiology Education and Training, Communication, and Clinical Care. Radiology 2019; 291:570-580. [PMID: 30990383 DOI: 10.1148/radiol.2019182210] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Advances in virtual immersive and augmented reality technology, commercially available for the entertainment and gaming industry, hold potential for education and clinical use in medicine and the field of medical imaging. Radiology departments have begun exploring the use of these technologies to help with radiology education and clinical care. The purpose of this review article is to summarize how three institutions have explored using virtual and augmented reality for radiology.
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Affiliation(s)
- Raul N Uppot
- From the Department of Radiology, Division of Interventional Radiology, Massachusetts General Hospital, 55 Fruit St, Gray 290, Boston, MA 02114 (R.N.U., C.J.M., G.D.N.); Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, Calif (B.L., A.P., J.C.); and Department of Radiology, University of Maryland Medical Center, Baltimore, Md (E.S.)
| | - Benjamin Laguna
- From the Department of Radiology, Division of Interventional Radiology, Massachusetts General Hospital, 55 Fruit St, Gray 290, Boston, MA 02114 (R.N.U., C.J.M., G.D.N.); Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, Calif (B.L., A.P., J.C.); and Department of Radiology, University of Maryland Medical Center, Baltimore, Md (E.S.)
| | - Colin J McCarthy
- From the Department of Radiology, Division of Interventional Radiology, Massachusetts General Hospital, 55 Fruit St, Gray 290, Boston, MA 02114 (R.N.U., C.J.M., G.D.N.); Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, Calif (B.L., A.P., J.C.); and Department of Radiology, University of Maryland Medical Center, Baltimore, Md (E.S.)
| | - Gianluca De Novi
- From the Department of Radiology, Division of Interventional Radiology, Massachusetts General Hospital, 55 Fruit St, Gray 290, Boston, MA 02114 (R.N.U., C.J.M., G.D.N.); Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, Calif (B.L., A.P., J.C.); and Department of Radiology, University of Maryland Medical Center, Baltimore, Md (E.S.)
| | - Andrew Phelps
- From the Department of Radiology, Division of Interventional Radiology, Massachusetts General Hospital, 55 Fruit St, Gray 290, Boston, MA 02114 (R.N.U., C.J.M., G.D.N.); Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, Calif (B.L., A.P., J.C.); and Department of Radiology, University of Maryland Medical Center, Baltimore, Md (E.S.)
| | - Eliot Siegel
- From the Department of Radiology, Division of Interventional Radiology, Massachusetts General Hospital, 55 Fruit St, Gray 290, Boston, MA 02114 (R.N.U., C.J.M., G.D.N.); Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, Calif (B.L., A.P., J.C.); and Department of Radiology, University of Maryland Medical Center, Baltimore, Md (E.S.)
| | - Jesse Courtier
- From the Department of Radiology, Division of Interventional Radiology, Massachusetts General Hospital, 55 Fruit St, Gray 290, Boston, MA 02114 (R.N.U., C.J.M., G.D.N.); Department of Radiology and Biomedical Imaging, University of California San Francisco Medical Center, San Francisco, Calif (B.L., A.P., J.C.); and Department of Radiology, University of Maryland Medical Center, Baltimore, Md (E.S.)
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