Dynamic navigation-assisted extraction of impacted maxillary anterior teeth: a model-based accuracy study

动态导航辅助拔除阻生上颌前牙:基于模型的精度研究

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Abstract

BACKGROUND: Accurate extraction of impacted teeth remains a technically demanding procedure. This study aimed to develop a model-based experimental protocol to assess the surgical accuracy of a dynamic navigation system (DNS) assisted extraction of impacted maxillary anterior teeth. METHODS: A standardized custom model simulating impacted maxillary supernumerary teeth was constructed. Preoperative planning, including the definition of osteotomy boundaries and tooth sectioning planes, was performed using integrated intraoral scanning and cone-beam computed tomography (CBCT) data. During surgery, the DNS guided critical surgical procedural steps, including tooth localization, osteotomy, and segmentation. Postoperative CBCT imaging was used to compare actual surgical outcomes with the preoperative plan by quantifying three-dimensional deviations. Outcome measures included root mean square (RMS) deviation, angular deviation, and other geometric discrepancies. Total osteotomy area and operative time were also recorded. RESULTS: Fourteen models were evaluated, with seven assigned to the DNS-assisted group and seven to the control group. Compared with the preoperative plan, the DNS group demonstrated significantly lower RMS deviation in segmentation plane accuracy than the control group (0.43 ± 0.18 mm vs. 0.85 ± 0.38 mm; P = 0.02). Angular deviation was reduced in the DNS group (8.97° vs. 14.76°; P = 0.04), along with curvature RMS (1.72 rad vs. 3.54 rad; P = 0.04) and maximum deviation (0.77 mm vs. 1.30 mm; P < 0.01). DISCUSSION: These results indicate that DNS-assisted extraction of impacted maxillary anterior teeth significantly enhances surgical accuracy compared with conventional techniques, improving procedural accuracy, stability, and overall safety.

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