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Restoring Mandibular Anatomy After Complex Trauma: Clinical Applications of a Statistical Shape Model.

Stephen A L Y Youssef1,2, Cornelis Klop1,2, Juliana F Sabelis1,2

  • 1Department of Oral and Maxillofacial Surgery, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.

Journal of Clinical Medicine
|February 13, 2026
PubMed
Summary

Restoring jaw anatomy after severe trauma is difficult without traditional references. A statistical shape model (MAGIC-SSM) offers a novel solution for diagnosis and planning in complex mandibular reconstruction.

Keywords:
computer-assisted surgerymandibular reconstructionmaxillofacial injuriespatient-specific implantsstatistical shape modelingthree-dimensional imagingvirtual surgical planning

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Area of Science:

  • Oral and Maxillofacial Surgery
  • Biomedical Engineering
  • Medical Imaging

Background:

  • Restoring mandibular anatomy after complex trauma is challenging due to the loss of conventional references like dental occlusion and mandibular continuity.
  • Severe post-traumatic deformities often lack sufficient landmarks for accurate surgical planning and reconstruction.
  • Existing methods struggle when anatomical and occlusal references are compromised, necessitating alternative approaches.

Purpose of the Study:

  • To describe the clinical application of a mandibular statistical shape model (MAGIC-SSM) as an alternative anatomical reference.
  • To evaluate the utility of MAGIC-SSM in diagnosis, virtual planning, and postoperative assessment for severe post-traumatic mandibular deformities.
  • To demonstrate the feasibility of using population-based geometry to guide mandibular reconstruction in the absence of conventional landmarks.

Main Methods:

  • Utilized the MAGIC-SSM, an open-source, 3D statistical shape model derived from a normative population dataset.
  • Applied MAGIC-SSM for reference alignment in three clinical cases with severe post-traumatic mandibular deformities.
  • Employed distance mapping for quantitative evaluation of postoperative outcomes where indicated.

Main Results:

  • The MAGIC-SSM provided a valuable additional anatomical reference for surgical decision-making.
  • The model supported secondary correction, hybrid reconstruction with patient-specific implants, and quantitative postoperative evaluation.
  • Population-based geometry from the model aided in restoring mandibular form and symmetry.

Conclusions:

  • The MAGIC-SSM offers a feasible anatomical framework for complex mandibular trauma reconstruction when conventional guides are lost.
  • This statistical shape model assists in restoring mandibular form and symmetry by replacing lost spatial references with population-based geometry.
  • Further validation is required to establish the reproducibility and reliability of clinician-guided MAGIC-SSM application.