Related Experiment Video
Updated: May 10, 2026
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
Published on: August 5, 2021
Exploring the scope and applications of digital twin technologies in dentistry: a scoping review
Isha Duggal1, Tulika Tripathi2, Vandana Gupta1
1Department of Dental Surgery, AIIMS-CAPFIMS, Maidangarhi Campus, New Delhi, India.
Background:
Digital Twin (DT) technology creates a dynamic virtual representation of a physical system using real-time data and computational modeling. While DTs have demonstrated profound impact in several medical disciplines, their translation into dentistry is still emerging and has not been comprehensively mapped.
Objective:
To systematically review and delineate the current applications, technological advancements, and prospective opportunities of digital twin (DT) technology in dentistry.
Methods:
A scoping review was conducted following the Joanna Briggs Institute (JBI) methodology and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A systematic search of MEDLINE (PubMed), EMBASE, Scopus, and Web of Science identified English-language publications from January 2000 to April 2025. All empirical and conceptual studies describing DT development, validation, and/or application in dental contexts were eligible. Two reviewers independently conducted screening and study selection, with a third reviewer resolving discrepancies. No automation tools were used.
Results:
A total of 5989 records were retrieved, and 7 studies met the inclusion criteria. Included studies represented orthodontics, prosthodontics, endodontics, and dental education. DT applications primarily involved: patient-specific virtual modeling for diagnosis and treatment simulation, predictive or performance-monitoring frameworks using biomechanical/algorithmic analysis, and simulation-based skill training. Most were conceptual or prototype studies with small samples and limited clinical validation.
Conclusion:
DT technology has substantial potential to enhance precision, simulation, monitoring, and personalization in dentistry. However, current evidence remains constrained by fragmented research, methodological inconsistency and insufficient clinical validation. Future adoption of DT requires standardized data pipelines, robust ethical and regulatory frameworks and interdisciplinary collaboration to achieve clinically meaningful and widely adoptable DT integration in dental care.
