ArticleJMIR serious games2026
Usability Study of Augmented Reality Visualization Modalities on Localization Accuracy in the Head and Neck: Randomized Crossover Trial.
Article in JMIR serious games, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Artificial Intelligence in Head and Neck Surgical Oncology: A State-of-the-Art Review.Journal of clinical medicine · 2026Review
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Augmented reality head-mounted displays could overcome the spatial dissociation between medical imaging and the surgical field, which may be particularly important in anatomically dense regions, such as the head and neck. Although many head-mounted displays offer markerless inside-out tracking at a fraction of the cost of navigation systems, their overlay accuracy with superimposition (SI) modality onto the surgical field remains limited. The virtual twin (VT), displaying holography adjacent to the surgical field, may offer a viable alternative. However, its performance is still unclear. Objective: This study aimed to compare the accuracy and efficiency of the two visualization modalities, SI and VT, for anatomical localization in the head and neck region. Methods: In a randomized crossover trial to compare two augmented reality visualization modalities (SI and VT), 38 participants used a HoloLens 2 to localize point, line-based, and volume-based anatomical structures on head phantoms. Their performance was evaluated with respect to accuracy, workload, time, and user experience. Results: SI achieved significantly better point localization accuracy than VT both in absolute (mean 14.4, SD 4.2 mm vs mean 15.8, SD 5.5 mm; P=.003) and relative accuracy (mean 3.4, SD 2.2 mm vs mean 6.0, SD 5.0 mm; P<.001). In line-based structures, accuracy was comparable between SI (average surface distance [ASD], mean 23.4, SD 4.1 mm; Hausdorff distance [HD], mean 31.5, SD 7.8 mm) and VT (ASD=mean 23.0, SD 4.5 mm; P=.51; HD=mean 31.0, SD 7.5 mm; P=.57). However, SI showed significantly higher deviation than VT in volume-based structure (ASD=mean 37.1, SD 13.8 mm vs mean 34.1, SD 14.2 mm; P=.01; HD=mean 52.0, SD 16.8 mm vs mean 49.1, SD 15.8 mm; P=.03). Participants were faster with SI (P=.02), while workload NASA-TLX (National Aeronautics and Space Administration Task Load Index) scores did not demonstrate a significant difference (P=.79). Conclusions: Given that SI did not clearly outperform VT under overlaid soft tissue and viewing challenges, VT remains a viable alternative in certain surgical scenarios where high accuracy is not required. Future research should focus on optimizing viewing angle guidance and the linkage between the anatomical target and the skin surface.
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