Leveraging Digital Twins for Improved Orthopaedic Evaluation and Treatment

Overview

Journal J Exp Orthop

Publisher Wiley

Specialty Orthopedics

Date 2024 Nov 12

PMID 39530111

Authors

Michael C Dean

Jacob F Oeding

Pedro Diniz

Romain Seil

Kristian Samuelsson

Affiliations

Soon will be listed here.

Abstract

Purpose: The purpose of this article is to explore the potential of digital twin technologies in orthopaedics and to evaluate how their integration with artificial intelligence (AI) and deep learning (DL) can improve orthopaedic evaluation and treatment. This review addresses key applications of digital twins, including surgical planning, patient-specific outcome prediction, augmented reality-assisted surgery and simulation-based surgical training.

Methods: Existing studies on digital twins in various domains, including engineering, biomedical and orthopaedics are reviewed. We also reviewed advancements in AI and DL relevant to digital twins. We focused on identifying key benefits, challenges and future directions for the implementation of digital twins in orthopaedic practice.

Results: The review highlights that digital twins offer significant potential to revolutionise orthopaedic care by enabling precise surgical planning, real-time outcome prediction and enhanced training. Digital twins can model patient-specific anatomy using advanced imaging techniques and dynamically update with real-time data, providing valuable insights during surgery and postoperative care. However, challenges such as the need for large-scale data sets, technological limitations and integration issues must be addressed to fully realise these benefits.

Conclusion: Digital twins represent a promising frontier in orthopaedic research and practice, with the potential to improve patient outcomes and enhance surgical precision. To enable widespread adoption, future research must focus on overcoming current challenges and further refining the integration of digital twins with AI and DL technologies.

Level Of Evidence: Level V.

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