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Shah C, Nachand D, Wald C, Chen PH. Keeping Patient Data Secure in the Age of Radiology Artificial Intelligence: Cybersecurity Considerations and Future Directions. J Am Coll Radiol 2023; 20:828-835. [PMID: 37488026 DOI: 10.1016/j.jacr.2023.06.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/14/2023] [Indexed: 07/26/2023]
Abstract
Artificial intelligence (AI)-based solutions are increasingly being incorporated into radiology workflows. Implementation of AI comes along with cybersecurity risks and challenges that practices should be aware of and mitigate for a successful and secure deployment. In this article, these cybersecurity issues are examined through the lens of the "CIA" triad framework-confidentiality, integrity, and availability. We discuss the implications of implementation configurations and development approaches on data security and confidentiality and the potential impact that the insertion of AI can have on the truthfulness of data, access to data, and the cybersecurity attack surface. Finally, we provide a checklist to address important security considerations before deployment of an AI application, and discuss future advances in AI addressing some of these security concerns.
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Affiliation(s)
- Chintan Shah
- Associate Staff, Section of Neuroradiology and Section of Imaging Informatics, Safety, Improvement, Quality and Experience Officer-Neuroradiology, Department of Radiology, Imaging Institute, Cleveland Clinic, Cleveland, Ohio.
| | - Douglas Nachand
- Staff, Section of Abdominal Imaging and Section of Imaging Informatics, Cleveland Clinic, Cleveland, Ohio
| | - Christoph Wald
- Professor of Radiology, Tufts University Medical School, Lahey Health, Boston, Massachusetts; Chair, Lahey Radiology, Chair, ACR Informatics Commission. https://twitter.com/waldchristoph
| | - Po-Hao Chen
- Chief Informatics Officer, Imaging Institute, Medical Director for Enterprise Radiology, IT Division, Staff, Section of Musculoskeletal Imaging, Cleveland Clinic, Cleveland, Ohio Chair, Informatics Advisory Council, ACR; Co-Chair, 2023 Data Science Summit, ACR. https://twitter.com/howardpchen
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Walsh G, Stogiannos N, van de Venter R, Rainey C, Tam W, McFadden S, McNulty JP, Mekis N, Lewis S, O'Regan T, Kumar A, Huisman M, Bisdas S, Kotter E, Pinto dos Santos D, Sá dos Reis C, van Ooijen P, Brady AP, Malamateniou C. Responsible AI practice and AI education are central to AI implementation: a rapid review for all medical imaging professionals in Europe. BJR Open 2023; 5:20230033. [PMID: 37953871 PMCID: PMC10636340 DOI: 10.1259/bjro.20230033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/27/2023] [Accepted: 05/30/2023] [Indexed: 11/14/2023] Open
Abstract
Artificial intelligence (AI) has transitioned from the lab to the bedside, and it is increasingly being used in healthcare. Radiology and Radiography are on the frontline of AI implementation, because of the use of big data for medical imaging and diagnosis for different patient groups. Safe and effective AI implementation requires that responsible and ethical practices are upheld by all key stakeholders, that there is harmonious collaboration between different professional groups, and customised educational provisions for all involved. This paper outlines key principles of ethical and responsible AI, highlights recent educational initiatives for clinical practitioners and discusses the synergies between all medical imaging professionals as they prepare for the digital future in Europe. Responsible and ethical AI is vital to enhance a culture of safety and trust for healthcare professionals and patients alike. Educational and training provisions for medical imaging professionals on AI is central to the understanding of basic AI principles and applications and there are many offerings currently in Europe. Education can facilitate the transparency of AI tools, but more formalised, university-led training is needed to ensure the academic scrutiny, appropriate pedagogy, multidisciplinarity and customisation to the learners' unique needs are being adhered to. As radiographers and radiologists work together and with other professionals to understand and harness the benefits of AI in medical imaging, it becomes clear that they are faced with the same challenges and that they have the same needs. The digital future belongs to multidisciplinary teams that work seamlessly together, learn together, manage risk collectively and collaborate for the benefit of the patients they serve.
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Affiliation(s)
- Gemma Walsh
- Division of Midwifery & Radiography, City University of London, London, United Kingdom
| | | | | | - Clare Rainey
- School of Health Sciences, Ulster University, Derry~Londonderry, Northern Ireland
| | - Winnie Tam
- Division of Midwifery & Radiography, City University of London, London, United Kingdom
| | - Sonyia McFadden
- School of Health Sciences, Ulster University, Coleraine, United Kingdom
| | | | - Nejc Mekis
- Medical Imaging and Radiotherapy Department, University of Ljubljana, Faculty of Health Sciences, Ljubljana, Slovenia
| | - Sarah Lewis
- Discipline of Medical Imaging Science, Sydney School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Tracy O'Regan
- The Society and College of Radiographers, London, United Kingdom
| | - Amrita Kumar
- Frimley Health NHS Foundation Trust, Frimley, United Kingdom
| | - Merel Huisman
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | | | | | - Cláudia Sá dos Reis
- School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne, Switzerland
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Mascarenhas M, Afonso J, Ribeiro T, Andrade P, Cardoso H, Macedo G. The Promise of Artificial Intelligence in Digestive Healthcare and the Bioethics Challenges It Presents. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:medicina59040790. [PMID: 37109748 PMCID: PMC10145124 DOI: 10.3390/medicina59040790] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/27/2023] [Accepted: 04/02/2023] [Indexed: 04/29/2023]
Abstract
With modern society well entrenched in the digital area, the use of Artificial Intelligence (AI) to extract useful information from big data has become more commonplace in our daily lives than we perhaps realize. Medical specialties that rely heavily on imaging techniques have become a strong focus for the incorporation of AI tools to aid disease diagnosis and monitoring, yet AI-based tools that can be employed in the clinic are only now beginning to become a reality. However, the potential introduction of these applications raises a number of ethical issues that must be addressed before they can be implemented, among the most important of which are issues related to privacy, data protection, data bias, explainability and responsibility. In this short review, we aim to highlight some of the most important bioethical issues that will have to be addressed if AI solutions are to be successfully incorporated into healthcare protocols, and ideally, before they are put in place. In particular, we contemplate the use of these aids in the field of gastroenterology, focusing particularly on capsule endoscopy and highlighting efforts aimed at resolving the issues associated with their use when available.
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Affiliation(s)
- Miguel Mascarenhas
- Faculty of Medicine, University of Porto, 4200-437 Porto, Portugal
- Precision Medicine Unit, Department of Gastroenterology, Hospital São João, 4200-437 Porto, Portugal
- WGO Training Center, 4200-437 Porto, Portugal
| | - João Afonso
- Precision Medicine Unit, Department of Gastroenterology, Hospital São João, 4200-437 Porto, Portugal
- WGO Training Center, 4200-437 Porto, Portugal
| | - Tiago Ribeiro
- Precision Medicine Unit, Department of Gastroenterology, Hospital São João, 4200-437 Porto, Portugal
- WGO Training Center, 4200-437 Porto, Portugal
| | - Patrícia Andrade
- Faculty of Medicine, University of Porto, 4200-437 Porto, Portugal
- Precision Medicine Unit, Department of Gastroenterology, Hospital São João, 4200-437 Porto, Portugal
- WGO Training Center, 4200-437 Porto, Portugal
| | - Hélder Cardoso
- Faculty of Medicine, University of Porto, 4200-437 Porto, Portugal
- Precision Medicine Unit, Department of Gastroenterology, Hospital São João, 4200-437 Porto, Portugal
- WGO Training Center, 4200-437 Porto, Portugal
| | - Guilherme Macedo
- Faculty of Medicine, University of Porto, 4200-437 Porto, Portugal
- Precision Medicine Unit, Department of Gastroenterology, Hospital São João, 4200-437 Porto, Portugal
- WGO Training Center, 4200-437 Porto, Portugal
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Tagliafico AS, Campi C, Bianca B, Bortolotto C, Buccicardi D, Francesca C, Prost R, Rengo M, Faggioni L. Blockchain in radiology research and clinical practice: current trends and future directions. Radiol Med 2022; 127:391-397. [PMID: 35194720 PMCID: PMC8863512 DOI: 10.1007/s11547-022-01460-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 01/21/2022] [Indexed: 12/31/2022]
Abstract
Blockchain usage in healthcare, in radiology, in particular, is at its very early infancy. Only a few research applications have been tested, however, blockchain technology is widely known outside healthcare and widely adopted, especially in Finance, since 2009 at least. Learning by history, radiology is a potential ideal scenario to apply this technology. Blockchain could have the potential to increase radiological data value in both clinical and research settings for the patient digital record, radiological reports, privacy control, quantitative image analysis, cybersecurity, radiomics and artificial intelligence. Up-to-date experiences using blockchain in radiology are still limited, but radiologists should be aware of the emergence of this technology and follow its next developments. We present here the potentials of some applications of blockchain in radiology.
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Affiliation(s)
- Alberto Stefano Tagliafico
- IRCCS Ospedale Policlinico San Martino, Genova, Genoa, Italy. .,Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
| | - Cristina Campi
- Dipartimento Di Matematica, Università Di Genova, via Dodecaneso 35, 16146, Genova, Italy
| | - Bignotti Bianca
- IRCCS Ospedale Policlinico San Martino, Genova, Genoa, Italy
| | - Chandra Bortolotto
- Dipartimento Di Radiologia, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | | | - Coppola Francesca
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy
| | - Roberto Prost
- Azienda Ospedaliera Brotzu, Cagliari, Sardegna, Italy
| | - Marco Rengo
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome - I.C.O.T. Hospital, Via Franco Faggiana, 1668, 04100, Latina, Italy
| | - Lorenzo Faggioni
- Diagnostic and Interventional Radiology, University Hospital of Pisa, Via Paradisa 2, 56100, Pisa, Italy
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