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Digital twins assisted surgery: A conceptual framework for transforming surgical training and navigation
Justicia Kyeremeh1, Lisa Asciak2, James P Blackmur3
1Department of Surgery, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; Urological Malignancies Virtual Institute, CRUK Cambridge Centre, University of Cambridge, Cambridge, UK.
Summary
Digital Twins Assisted Surgery (DTAS) offers a novel approach to surgical training and decision-making. This innovative method uses real-time data and 3D modeling to enhance surgical precision and patient safety.
Area of Science:
- Surgical innovation and medical technology
- Digital health and computational medicine
Background:
- Modern surgical procedures are increasingly complex, necessitating advanced training methods.
- Digital Twins Assisted Surgery (DTAS) presents a novel solution for surgical education and intraoperative decision support.
Purpose of the Study:
- To propose a conceptual framework for integrating DTAS into surgical education.
- To illustrate the application of DTAS in preoperative planning, intraoperative guidance, and skill development.
Main Methods:
- Development of a conceptual framework for DTAS integration.
- Presentation of hypothetical case examples for DTAS application in surgical training.
Main Results:
- DTAS shows potential to enhance surgical precision, skill acquisition, and patient safety.
- Integration of real-time data, 3D modeling, and predictive analytics can improve surgical outcomes.
Conclusions:
- DTAS has the potential to revolutionize surgical training and navigation.
- Further pilot studies and validation trials are required to assess DTAS integration and clinical impact.
