Digital Twin Technology in Dentistry: Applications, Challenges, and Future Perspectives in Precision Oral Healthcare

Abstract

Background Digital twin technology creates virtual replicas enabling real-time monitoring, simulation, and predictive analysis. Whilst extensively explored in medical disciplines, its integration in dentistry remains emerging. Complex anatomical structures, individualised treatment requirements, and precision demands position digital twin technology as promising for enhancing clinical outcomes and patient care. Aim This review examines current applications of digital twin technology in dentistry, identifies associated benefits and challenges, and explores future directions for research and practice. Method A comprehensive narrative review searched PubMed, Scopus, Web of Science, and IEEE Xplore for articles published between 2015 and 2026. Search terms included combinations of "digital twin", "virtual twin", "virtual patient model", "digital replica", "dentistry", "oral health", and related dental specialty terms, combined using Boolean operators. Articles focusing on digital twin applications, implementation strategies, technological frameworks, and clinical outcomes were included. Results Digital twin technology demonstrates diverse applications across orthodontics, prosthodontics, oral surgery, endodontics, and periodontics. Key applications include treatment planning, surgical simulation, prosthesis design, outcome prediction, and patient education. The technology integrates three-dimensional imaging, intraoral scanning, electronic health records, and biomechanical simulations to create comprehensive virtual representations. Where genuine bidirectional digital twin frameworks are implemented, benefits include enhanced precision, reduced treatment time, improved outcomes, and personalised care. However, challenges related to data integration, computational requirements, costs, and standardisation persist. Conclusion Digital twin technology holds substantial promise for advancing dental practice through improved treatment planning, enhanced precision, and personalised care. As technological infrastructure develops and integration challenges are addressed, applications are expected to expand significantly, transforming clinical workflows and elevating standards. However, the current evidence base remains largely preliminary, and large-scale clinical validation is needed before definitive conclusions can be drawn.