Abstract
Background/Objectives: Restoration of mandibular anatomy following complex trauma remains challenging when conventional anatomical and occlusal references, such as dental occlusion, contralateral morphology, condylar position, or mandibular continuity are lost. This technical note describes the clinical application of a mandibular statistical shape model as an alternative anatomical reference for diagnosis, virtual planning, and postoperative evaluation in patients with severe post-traumatic deformities.
Methods: The MAGIC-SSM, an open-source, age-, and sex-specific three-dimensional model derived from a normative population dataset, enables reconstruction of plausible mandibular geometry in the absence of residual landmarks. Three clinical cases were analyzed using MAGIC-SSM-based reference alignment, with distance mapping applied when indicated.
Results: The model provided an additional anatomical reference that supported decision-making in secondary correction, hybrid reconstruction with patient-specific implants, and quantitative evaluation of postoperative outcomes.
Conclusions: By replacing lost spatial references with population-based geometry, the MAGIC-SSM offered support for restoring mandibular form and symmetry. These preliminary findings illustrate the feasibility of applying the MAGIC-SSM as an anatomical framework in complex trauma when conventional guides are absent. As its clinical application involved clinician-guided alignment and scaling, reproducibility and reliability remain to be established and require further validation.
| Original language | English |
|---|---|
| Article number | 1223 |
| Pages (from-to) | 1-11 |
| Number of pages | 11 |
| Journal | Journal of Clinical Medicine |
| Volume | 15 |
| Issue number | 3 |
| Early online date | 4 Feb 2026 |
| DOIs | |
| Publication status | Published - Feb 2026 |
Bibliographical note
Publisher Copyright:© 2026 by the authors.
Keywords
- computer-assisted surgery
- mandibular reconstruction
- maxillofacial injuries
- patient-specific implants
- statistical shape modeling
- three-dimensional imaging
- virtual surgical planning
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