Bridging Dynamic and Static Loading

When we first sought to build on Moazen et al. (2022) work, which demonstrated that cyclic frontal bone loading could delay coronal suture fusion in Crouzon mice, a critical hurdle emerged: quantifying mechanical strain during in vivo dynamic loading. Traditional methods struggled to capture real-time deformations in living specimens, necessitating a paradigm shift.

We devised a multiscale approach:

1. Dynamic Loading Characterisation: Using a custom actuator-force sensor system, we measured whole-head displacements in live mice under cyclic loading (0.1 N, 1 Hz). Oscillatory displacements (0.13–0.32 mm) were smaller in mutant mice at P14/P21, suggesting altered cranial compliance as sutures fused.

2. Retained suture deformation: Coronal suture thickness was measured for unloaded, in vivo dynamically loaded, ex vivo dynamically loaded and ex vivo statically loaded animals. All the groups showed similar levels of increased thickness from the control.

3. Ex Vivo Static Loading Innovation: To overcome imaging limitations, we developed a micro-CT-compatible static loading rig and a Python-based digital surface correlation algorithm. This allowed 3D strain mapping across sutures during loading, revealing von Mises strains up to 0.73 in WT coronal sutures.

When comparing both methods, static loading induced comparable permanent suture thickening (0.51–0.70× control) to dynamic regimens, validating it as a proxy for mechanistic studies.

Sutures as Plastic Structures: Redefining Biomechanical Paradigms

Contrary to expectations, our data revealed that cranial sutures are not merely elastic buffers but exhibit plastic deformation under load. Key findings included:

• Retained Deformation: Post-loading coronal suture thickness increased by 38–70% in P7 WT mice, persisting even after force removal.

• Strain Distribution Asymmetry: Unilateral frontal loading generated higher strains ipsilaterally (0.73 ± 0.08 vs. 0.49 ± 0.07 von Mises strain), yet still influenced contralateral sutures. Findings with implications for bilateral therapeutic effects.

• Suture-Specific Responses: Sagittal suture strains decreased markedly from P7 to P14 in both WT and mutant mice, likely due to metopic suture closure altering force distribution.

These results challenged existing finite element models, which had significantly underestimated suture strain magnitudes.

Methodological advances

A pivotal innovation was our in situ CT strain estimation pipeline, which combined:

1. Micro-CT Imaging: High-resolution scans (9.5 µm voxels) of loaded vs. unloaded specimens.

2. Custom Segmentation: Automated bone registration using rigid element alignment to minimise manual bias.

3. Strain estimation: Displacement data fed into ANSYS models to calculate suture strains, despite overestimating bone strain.

This toolkit is already propelling translational work:

• Porcine Model Development: Applying similar protocols to piglet skulls, whose sutural complexity better mirrors human infants.

• BounTI Integration: Our upcoming study leverages this automated segmentation tool to analyse additional loading sites (anterior/posterior parietal, interparietal) and sutures (lambdoid, interparietal) with unprecedented efficiency.

Beyond Frontal Loading: Expanding the Horizon

While the current study focused on frontal bone loading, its limitations, particularly in assessing mutant coronal sutures, inspired our soon-to-be-published work:

• Expanded Scope: Incorporates lambdoid and interparietal sutures, capturing interactions between cranial regions.

• Suture Response in Crouzon Mice: Coronal suture deformation is investigated directly.
• FE Modelling: The comprehensive data produced in both the original study as well as the soon-to-be-published work act as an excellent validation dataset for the development of robust FE Models.

Conclusion: Toward Non-Invasive Futures

Our journey underscores how cranial sutures—far from passive seams—are dynamic, plastic interfaces that balance mechanical demands with growth. By bridging murine models, computational tools, and clinical insight, we’re advancing toward a future where cyclic loading devices could reduce surgical burdens for craniosynostosis patients. With expanded loading protocols and FE frameworks now in testing, the goal of personalised, non-invasive therapies feels closer than ever.