Current Accuracy of Augmented Reality Neuronavigation Systems: Systematic Review and Meta-Analysis

Abstract Background Augmented reality neuronavigation (ARN) systems can overlay three-dimensional anatomy and pathology without the need for a two-dimensional external monitor. Accuracy is crucial for their clinical applicability. We performed a systematic review regarding the reported accuracy of ARN systems and compared them with the accuracy of conventional infrared neuronavigation (CIN). Objective Explore the current navigation accuracy of ARN systems and compare them with CIN. Methods Pubmed and Embase were searched for ARN and CIN systems. For ARN: type of system, method of patient-to-image registration, accuracy method and accuracy of the system was noted. For CIN: navigation accuracy, expressed as target registration error (TRE), was noted. A meta-analysis was performed comparing the TRE of ARN and CIN systems. Results 35 studies were included, 12 for ARN and 23 for CIN. ARN systems were divided into head-mounted display and heads-up display. In ARN, four methods were encountered for patient-to-image registration, of which point-pair matching was the one most frequently used. Five methods for assessing accuracy were described. 94 TRE measurements of ARN systems were compared with 9058 TRE measurements of CIN systems. Mean TRE was 2.5 mm (CI 95% 0.7 – 4.4) for ARN systems and 2.6 mm (CI 95% 2.1 – 3.1) for CIN systems. Conclusions In ARN, there seems to be lack of agreement regarding the best method to assess accuracy. Nevertheless, ARN systems seem able to achieve an accuracy comparable with CIN systems. Future studies should be prospective and compare TREs which should be measured in a standardized fashion.