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 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.

Digital Twins for Predictive, Preventive Personalized, and Participatory Treatment of Immune-Mediated Diseases

“…3,6,27,28 This will involve multiple challenges and unanswered questions, which are discussed below. 29…”

“…Compared with today’s treatment approaches, that prioritization would be much more accurate because it is based on computationally predicted effects on a high-resolution model of that patient, rather than previously observed effects on a limited number of phenotypic and molecular variables in groups of patients. 9–12…”

Der digitale Zwilling für die perioperative Medizin – ein spannender Blick in die Zukunft klinischer Forschung

“…B. Raumfahrt, Maschinenbau, Städtebau) Verbreitung gefunden [ 1 ]. Der digitale Zwilling, als virtuelle Repräsentation physischer Entitäten und Prozesse, erregt aber auch in der Medizin zunehmend Aufmerksamkeit [ 2 ]. Dabei ist zum besseren Verständnis des Themenfeldes zunächst eine Begriffserklärung auch mit Bezug auf das generelle Feld des maschinellen Lernens (ML) nötig, welches gemeinhin mit sog.…”

“…Bei der Entwicklung, Validierung und breite klinische Einsetzbarkeit von digitalen Zwillingen bestehen noch erhebliche Hürden. Diese wurden jüngst auch für das Feld der kardiovaskulären Medizin systematisch aufgezeigt [ 2 ]. So stehen in Deutschland der klinischen Anwendung aktuell methodisch-translationale wie auch infrastrukturelle Herausforderungen im Krankenhaus entgegen.…”

Causal Falsification of Digital Twins

“…This modelling approach promises to radically transform planning and decision-making across a breadth of fields, since it allows actions to be chosen with a full understanding of the range of possible outcomes that may result. Early research on digital twins has considered use-cases including aviation [6], manufacturing [76,36,40], healthcare [70,12,10,11], civil engineering [65], climate modelling [5], and agriculture [28]. For a comprehensive overview of the surrounding literature and outlook of this emerging technology, we refer the reader to [69,3,30,56].…”