The design, fabrication, and clinical application of a universal donor tooth model in autotransplantation.

Objective: To design and fabricate a universal donor tooth model for autotransplantation and evaluate its clinical application efficacy.

Methods: CBCT data of 1003 third molars were collected as donor tooth data and classified after preprocessing. Multi-point cloud registration was performed for each classified dataset, and the registered point clouds were fused to obtain the distribution of point clouds under a unified reference. After filtering, a preliminary model was generated. The point cloud boundaries of the preliminary model were extracted, and statistical calculations identified 12 model variants based on maxillary/mandibular position, single-root/multi-root anatomy, and dimensional variations. A total of 117 patients who received single-tooth autotransplantation were randomly divided into a universal model group and a customized model group. The two groups used the universal model and a customized 3D model printed preoperatively based on donor tooth CT data, respectively, to assist in preparing the alveolar socket of the recipient site. Statistical analysis was made on the observation indexes between the two groups.

Results: The number of times the alveolar socket of the recipient site was prepared with a donor tooth after preparation using universal model was significantly larger in the universal model group than that in the customized model group (P = 0.047), there were no statistically significant differences in initial postoperative stability (P = 0.069) or healing outcomes at 6 months postoperatively (P = 0.747).

Conclusion: The universal model for autotransplantation can simplify preoperative preparation, shorten the operation period, reduce surgical trauma and time costs. There is no significant difference in short-term healing outcomes between patients using the universal model and those using customized model, which is worthy of popularizing.

Clinical Significance Statement: The 3D printing technology has been widely used in the autotransplantation. However, obtaining the donor tooth model before operation requires preparation of technology, time and cost. The universal model of donor tooth based on clinical big data design can simplify preoperative preparation, reduce surgical trauma and time costs, and result a good short-term healing outcomes.