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Updated: Jun 16, 2026

Midface Hypoplasia and Cranial Base Morphology in Syndromic Craniosynostosis: A Comparative Analysis Study Using a Predictive Regression Model
Published on: November 4, 2025
Toward characterization of craniofacial biomechanics
Tomasz D Szwedowski1, Cari M Whyne, Jeffrey A Fialkov
1Orthopaedic Biomechanics Lab, daggerSunnybrook Health Sciences Centre, Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
Abstract:
Surgical reconstruction of craniofacial deformities has advanced significantly in recent years. However, unlike orthopedic surgery of the appendicular skeleton, the biomechanical characterization of the human craniofacial skeleton (CFS) has yet to be elucidated. Attempts to simplify facial skeletal structure into straightforward mechanical device analogies have been insufficient in delineating craniofacial biomechanics. Advanced computational engineering analysis methods offer the potential to accurately and completely define the internal mechanical environment of the CFS. This study developed a finite element (FE) model in the I-deas 10 FEM software package of a preserved cadaveric human CFS and compared the predictions of this model against in vitro strain measurement of simulated occlusal loading forces from a single masseter muscle. The FE model applied shell element modeling to capture the behavior of the thin cortical bone that may play an important role in stabilizing the facial structures against functional loads. In vitro testing included strain measurements at 12 locations for a total of 16 independent channels with less than 150 N of tensile force applied through the masseter muscle into the zygomatic arch origin at 4 different orientations, with 3 trials of 500 recorded data points for each loading orientation. Linear regression analysis yielded a moderate prediction (r = 0.57) between the model and experimentally measured strains. Exclusion of strain comparisons in regions that required greater modeling assumptions greatly improved the correlation (r = 0.70). Future validation studies will benefit from improved placement of strain gauges as guided by FE model predicted strain patterns.
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