Turky, Mohammed and Dummer, Paul M. H.  ORCID: https://orcid.org/0000-0002-0726-7467
2026.
Digital twins technology in endodontics: From reactive to predictive - A new frontier towards personalized
root canal treatment.
British Dental Journal
240
, pp. 21-25.
10.1038/s41415-025-9456-y
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Abstract
Objectives To describe the potential of digital twin (DT) technology to enhance personalized root canal treatment (RCT) within endodontics. Discussion DT models are gaining traction as transformative tools for enabling individualized decision-making across different medical disciplines. These models leverage multimodal patient data to simulate physiological and clinical outcomes. In endodontics, DTs could facilitate the simulation of intricate parameters. The application of DTs will empower clinicians to formulate more tailored treatment plans and improve prognostic predictions. Beyond their clinical applications, DT can enrich research settings, linking laboratory research with tailored patient care. While deploying DTs in endodontics remains largely aspirational, it can shift the paradigm from standardized approaches to personalized treatments. Key challenges to address include data standardization, interoperability among systems, ethical regulations, and the need for specialized clinician training. This article suggests actionable strategies for the translational development of DTs in endodontics. Conclusion DT models can reshape the vision in endodontics, facilitating real-time, patient-specific simulation and clinical decision-making. Moreover, DTs present a cohesive framework that could enhance precision in endodontic practice while also expediting the translation of research findings into clinical applications. This advancement may lead to the development of personalized and predictive approaches to RCT, significantly improving patient outcomes.
| Item Type: | Article |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Dentistry |
| Publisher: | Nature Publishing Group |
| ISSN: | 0007-0610 |
| Date of First Compliant Deposit: | 13 January 2026 |
| Date of Acceptance: | 10 September 2025 |
| Last Modified: | 13 Jan 2026 17:15 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/183879 |
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