Digital twin technology in surgery: A narrative review of applications, evidence, and implementation challenges

Abstract

Digital twin technology, which creates virtual replicas of physical entities that are continuously updated with real-time data, has emerged as a transformative innovation in healthcare. In surgical practice, digital twins offer unprecedented opportunities to enhance precision, personalisation, and patient outcomes through simulation, planning, and predictive analytics. This narrative review aims to examine the current applications of digital twin technology in surgical practice, evaluate its potential benefits and limitations, critically assess the maturity level of reported applications, and identify future directions for research and implementation. A comprehensive narrative review was conducted using the PubMed, Scopus, Web of Science, and IEEE Xplore databases. Publications from 2015 to 2025 were included, focusing on peer-reviewed articles, clinical trials, case studies, and technical reports describing digital twin applications in surgical contexts. Digital twin technology has demonstrated significant potential across multiple surgical domains, including preoperative planning, intraoperative guidance, postoperative monitoring, and surgical training. Its applications span cardiovascular, orthopaedic, neurological, and oncological surgeries. Evidence quality varies considerably across specialties, ranging from proof-of-concept to early clinical deployment, with orthopaedic surgery demonstrating the strongest current evidence base. Implementation faces challenges, including data integration, computational complexity, validation requirements, and regulatory considerations. Potential pathways forward include interoperability standards, reduced-order modelling, federated learning, and proactive regulatory engagement. Digital twin technology represents a paradigm shift in surgical practice, enabling personalised, data-driven approaches to patient care. While promising results have been reported, further research is needed to establish standardised protocols, validate clinical outcomes, and address technical and ethical challenges before widespread adoption. • Digital twins create dynamic virtual replicas of patients updated in real time • Applications span cardiovascular, neurological, orthopaedic, and oncological surgeries • Real-time intraoperative guidance enhances precision and surgical navigation • Postoperative monitoring enables early complication detection and prediction • Immersive VR training improves technical skills and reduces learning curves

Ähnliche Arbeiten