The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field
Abstract Potential benefits of precision medicine in cardiovascular disease (CVD) include more accurate phenotyping of individual patients with the same condition or presentation, using multiple clinical, imaging, molecular and other variables to guide diagnosis and treatment. An approach to realisi...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-08-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-022-00640-7 |
| _version_ | 1827775746775449600 |
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| author | Genevieve Coorey Gemma A. Figtree David F. Fletcher Victoria J. Snelson Stephen Thomas Vernon David Winlaw Stuart M. Grieve Alistair McEwan Jean Yee Hwa Yang Pierre Qian Kieran O’Brien Jessica Orchard Jinman Kim Sanjay Patel Julie Redfern |
| author_facet | Genevieve Coorey Gemma A. Figtree David F. Fletcher Victoria J. Snelson Stephen Thomas Vernon David Winlaw Stuart M. Grieve Alistair McEwan Jean Yee Hwa Yang Pierre Qian Kieran O’Brien Jessica Orchard Jinman Kim Sanjay Patel Julie Redfern |
| author_sort | Genevieve Coorey |
| collection | DOAJ |
| description | Abstract Potential benefits of precision medicine in cardiovascular disease (CVD) include more accurate phenotyping of individual patients with the same condition or presentation, using multiple clinical, imaging, molecular and other variables to guide diagnosis and treatment. An approach to realising this potential is the digital twin concept, whereby a virtual representation of a patient is constructed and receives real-time updates of a range of data variables in order to predict disease and optimise treatment selection for the real-life patient. We explored the term digital twin, its defining concepts, the challenges as an emerging field, and potentially important applications in CVD. A mapping review was undertaken using a systematic search of peer-reviewed literature. Industry-based participants and patent applications were identified through web-based sources. Searches of Compendex, EMBASE, Medline, ProQuest and Scopus databases yielded 88 papers related to cardiovascular conditions (28%, n = 25), non-cardiovascular conditions (41%, n = 36), and general aspects of the health digital twin (31%, n = 27). Fifteen companies with a commercial interest in health digital twin or simulation modelling had products focused on CVD. The patent search identified 18 applications from 11 applicants, of which 73% were companies and 27% were universities. Three applicants had cardiac-related inventions. For CVD, digital twin research within industry and academia is recent, interdisciplinary, and established globally. Overall, the applications were numerical simulation models, although precursor models exist for the real-time cyber-physical system characteristic of a true digital twin. Implementation challenges include ethical constraints and clinical barriers to the adoption of decision tools derived from artificial intelligence systems. |
| first_indexed | 2024-03-11T13:54:29Z |
| format | Article |
| id | doaj.art-a89c12ecf5d94282a867fd26e2f2c8ee |
| institution | Directory Open Access Journal |
| issn | 2398-6352 |
| language | English |
| last_indexed | 2024-03-11T13:54:29Z |
| publishDate | 2022-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj.art-a89c12ecf5d94282a867fd26e2f2c8ee2023-11-02T07:20:44ZengNature Portfolionpj Digital Medicine2398-63522022-08-015111210.1038/s41746-022-00640-7The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary fieldGenevieve Coorey0Gemma A. Figtree1David F. Fletcher2Victoria J. Snelson3Stephen Thomas Vernon4David Winlaw5Stuart M. Grieve6Alistair McEwan7Jean Yee Hwa Yang8Pierre Qian9Kieran O’Brien10Jessica Orchard11Jinman Kim12Sanjay Patel13Julie Redfern14University of Sydney, Faculty of Medicine and HealthUniversity of Sydney, Faculty of Medicine and HealthUniversity of Sydney, School of Chemical and Biomolecular EngineeringUniversity of Sydney, Faculty of Medicine and HealthKolling Institute of Medical Research, Royal North Shore HospitalCincinnati Children’s Hospital Medical CenteUniversity of Sydney, Faculty of Medicine and HealthThe University of Sydney, School of Biomedical EngineeringUniversity of Sydney, Charles Perkins CentreUniversity of Sydney, Faculty of Medicine and HealthSiemens Healthcare Pty Ltd; and Centre for Advanced Imaging, University of QueenslandUniversity of Sydney, Charles Perkins CentreUniversity of Sydney, School of Computer ScienceUniversity of Sydney, Faculty of Medicine and HealthUniversity of Sydney, Faculty of Medicine and HealthAbstract Potential benefits of precision medicine in cardiovascular disease (CVD) include more accurate phenotyping of individual patients with the same condition or presentation, using multiple clinical, imaging, molecular and other variables to guide diagnosis and treatment. An approach to realising this potential is the digital twin concept, whereby a virtual representation of a patient is constructed and receives real-time updates of a range of data variables in order to predict disease and optimise treatment selection for the real-life patient. We explored the term digital twin, its defining concepts, the challenges as an emerging field, and potentially important applications in CVD. A mapping review was undertaken using a systematic search of peer-reviewed literature. Industry-based participants and patent applications were identified through web-based sources. Searches of Compendex, EMBASE, Medline, ProQuest and Scopus databases yielded 88 papers related to cardiovascular conditions (28%, n = 25), non-cardiovascular conditions (41%, n = 36), and general aspects of the health digital twin (31%, n = 27). Fifteen companies with a commercial interest in health digital twin or simulation modelling had products focused on CVD. The patent search identified 18 applications from 11 applicants, of which 73% were companies and 27% were universities. Three applicants had cardiac-related inventions. For CVD, digital twin research within industry and academia is recent, interdisciplinary, and established globally. Overall, the applications were numerical simulation models, although precursor models exist for the real-time cyber-physical system characteristic of a true digital twin. Implementation challenges include ethical constraints and clinical barriers to the adoption of decision tools derived from artificial intelligence systems.https://doi.org/10.1038/s41746-022-00640-7 |
| spellingShingle | Genevieve Coorey Gemma A. Figtree David F. Fletcher Victoria J. Snelson Stephen Thomas Vernon David Winlaw Stuart M. Grieve Alistair McEwan Jean Yee Hwa Yang Pierre Qian Kieran O’Brien Jessica Orchard Jinman Kim Sanjay Patel Julie Redfern The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field npj Digital Medicine |
| title | The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field |
| title_full | The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field |
| title_fullStr | The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field |
| title_full_unstemmed | The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field |
| title_short | The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field |
| title_sort | health digital twin to tackle cardiovascular disease a review of an emerging interdisciplinary field |
| url | https://doi.org/10.1038/s41746-022-00640-7 |
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