ArticleCureus2024
Visual Behaviour During the Interpretation of Cone-Beam Computed Tomography Images of Traumatic Dental Injuries: An Eye-Tracking Study.
Article in Cureus, 2024. 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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Who cites it
1 citing paper in PubMed.
- Deep learning-based automated assessment of alveolar bone loss in CBCT for periodontitis.Clinical oral investigations · 2026Article
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4 authors.
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Abstract
backgroundThis cross-sectional observational study aimed to investigate the visual attention patterns of postgraduate endodontic residents during the interpretation of cone-beam computed tomography (CBCT) scans for traumatic dental injuries (TDIs) using eye-tracking technology.
methodsA cohort of 10 residents who were recruited from King Abdulaziz University Dental Hospital (KAUDH) underwent interpretation of seven CBCT images of TDIs. Eye-tracking metrics, including dwell time, entry time, end time, and the number of revisits, were recorded and analyzed using nonparametric statistical tests.
resultsEye-tracking data revealed that patients with lateral luxation and extrusive luxation pathologies had the longest mean dwell times (1.82 seconds and 1.50 seconds, respectively). These findings were statistically significant compared to other pathologies (p<0.001). Conversely, horizontal root fractures and periapical radiolucency were identified more quickly by the participants (mean entry times of 6.60 seconds and 8.84 seconds, respectively).
conclusionsThe findings indicate variability in visual attention metrics depending on the type of TDI, suggesting that certain injuries may require more focused attention for accurate diagnosis. Specifically, lateral and extrusive luxation injuries attracted longer dwell times, possibly due to their unique diagnostic challenges. This research provides a basis for future studies aiming to optimize education and training related to CBCT interpretation of traumatic dental injuries.
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