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Augmented Reality in Navigated Surgery: A Systematic Review of Clinical Accuracy and System Performance
Noa Nicolai1, Sander J C Tabernée Heijtmeijer2,3, Mohamed Benmahdjoub4,5
13D Lab, University Medical Center Utrecht, Netherlands.
Objective:
To evaluate the current state of clinically tested augmented reality and mixed reality, hereafter referred to as AR, navigation systems, with a focus on accuracy, usability, and factors influencing clinical implementation.
Methods:
A systematic search was conducted in Embase, PubMed, Scopus, and Web of Science Core Collection including studies published between January 1, 2018, and July 14, 2025. Only clinical studies involving patients were included. Data extraction covered study characteristics, surgical specialty, AR system type, reported accuracy, usability assessments, and implementation-related factors.
Results:
Of 1956 screened records, 61 studies met the inclusion criteria. The applications spanned oral and maxillofacial surgery (k=17), neurosurgery (k=12), spinal surgery (k=11), and orthopedics (k=10), among others. Reported accuracy metrics varied substantially across studies. Moreover, AR navigation often reduced radiation exposure during surgery and sometimes shortened operative time, although timing effects varied by specialty. Usability was rarely measured with standardized tools and was mostly described qualitatively. Common limitations were limited accuracy, ergonomic issues, and workflow-integration challenges. Grading of Recommendations Assessment, Development, and Evaluation ratings were generally low or very low owing to small samples, heterogeneous methods, and risk of bias.
Conclusion:
Although AR navigation demonstrates encouraging technical performance and potential reductions in radiation exposure, the underlying evidence is predominantly of very low certainty, and any impression of pooled robustness should be avoided. Furthermore, clinical integration is hindered by technical, ergonomic, and workflow-related barriers. Future work should incorporate robust methodological designs aimed at improving registration accuracy, overcoming hardware shortcomings, and systematically evaluating usability through validated, standardized tools.
