Academic Journal
Prediction of Three-Dimensional Soft Tissue Changes Following Mandibular PEEK Implantation (Proof of Concept).
| Τίτλος: | Prediction of Three-Dimensional Soft Tissue Changes Following Mandibular PEEK Implantation (Proof of Concept). |
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| Συγγραφείς: | Zwijnenberg, Tom L.1 (AUTHOR) t.zwijnenberg@3dvsp.com, Schepers, Rutger H.2 (AUTHOR), Jansma, Johan1,2 (AUTHOR), Glas, Haye H.1,2 (AUTHOR) |
| Πηγή: | Journal of Personalized Medicine. Aug2026, Vol. 16 Issue 8, p427. 15p. |
| Θεματικοί όροι: | *Artificial implants, *Mandible, *Maxillofacial surgery, *Three-dimensional modeling, *Finite element method, *Cone beam computed tomography, Surgery practice |
| Περίληψη: | Background/Objectives: Polyetheretherketone (PEEK) implants are increasingly being used for mandibular reconstruction and augmentation, yet predicting the resulting facial soft tissue changes remains challenging. Accurate pre-operative prediction of soft tissue deformation is essential for surgical planning and patient counselling. To the best of our knowledge, this study presents the first application of a computational model for predicting three-dimensional facial soft tissue deformation induced by PEEK implants. Methods: Four patient cases with pre-operative and post-operative cone-beam computed tomography scans were analysed. A mass tensor model was employed to predict soft tissue changes based on the pre-operative soft tissue shape, mandibular anatomy, and the designed PEEK implant. Model accuracy was quantified by comparing predicted outcomes to post-operative scans using landmark-based analysis of chin and jaw positions, as well as surface distance mapping, with a mean error below 2 mm adopted as the criterion for clinically acceptable accuracy. Results: Landmark-based analysis revealed a mean absolute error of 0.9 ± 0.8 mm between the predicted and actual positions. The mean surface distances were 1.3 mm for the jaw–chin region and 1.0 mm for the entire facial region. Conclusions: These results demonstrate the potential of a computational approach for real-time prediction of facial soft tissue changes following PEEK implant placement, achieving clinically relevant accuracy at the cohort level, with a tendency towards under-prediction and one case exceeding the threshold. [ABSTRACT FROM AUTHOR] |
| Βάση Δεδομένων: | Academic Search Index |
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