Postoperative helmet therapy following fronto-orbital advancement and cranial vault remodeling in patients with unilateral coronal synostosis

Geometric learning and statistical modeling for surgical outcomes evaluation in craniosynostosis using 3D photogrammetry

BACKGROUND AND OBJECTIVE

Accurate and repeatable detection of craniofacial landmarks is crucial for automated quantitative evaluation of head development anomalies. Since traditional imaging modalities are discouraged in pediatric patients, 3D photogrammetry has emerged as a popular and safe imaging alternative to evaluate craniofacial anomalies. However, traditional image analysis methods are not designed to operate on unstructured image data representations such as 3D photogrammetry.

METHODS

We present a fully automated pipeline to identify craniofacial landmarks in real time, and we use it to assess the head shape of patients with craniosynostosis using 3D photogrammetry. To detect craniofacial landmarks, we propose a novel geometric convolutional neural network based on Chebyshev polynomials to exploit the point connectivity information in 3D photogrammetry and quantify multi-resolution spatial features. We propose a landmark-specific trainable scheme that aggregates the multi-resolution geometric and texture features quantified at every vertex of a 3D photogram. Then, we embed a new probabilistic distance regressor module that leverages the integrated features at every point to predict landmark locations without assuming correspondences with specific vertices in the original 3D photogram. Finally, we use the detected landmarks to segment the calvaria from the 3D photograms of children with craniosynostosis, and we derive a new statistical index of head shape anomaly to quantify head shape improvements after surgical treatment.

RESULTS

We achieved an average error of 2.74 ± 2.70 mm identifying Bookstein Type I craniofacial landmarks, which is a significant improvement compared to other state-of-the-art methods. Our experiments also demonstrated a high robustness to spatial resolution variability in the 3D photograms. Finally, our head shape anomaly index quantified a significant reduction of head shape anomalies as a consequence of surgical treatment.

CONCLUSION

Our fully automated framework provides real-time craniofacial landmark detection from 3D photogrammetry with state-of-the-art accuracy. In addition, our new head shape anomaly index can quantify significant head phenotype changes and can be used to quantitatively evaluate surgical treatment in patients with craniosynostosis.

Denominator of Cranial Vault Asymmetry Index: Choosing Between Longer and Shorter Diagonal Lengths

Since it was proposed in this journal in 2001, the cranial vault asymmetry index (CVAI) has been an important parameter for assessing cranial shape. However, different publications currently use different variables in the denominator of the CVAI formula. We thus investigated the use of long and short diagonal lengths as variables in the denominator of the CVAI formula. We searched the databases of PubMed, Google Scholar, and Scopus for articles published between 2016 and 2022 that cited the original work article of CVAI. Articles were included if they were written in English and if the denominator of the CVAI formula was specified. For multiple articles by the same author, only the most recent article was included. In total, 30 articles were included; 10 articles used the longer diagonal length as the denominator and 20 articles used the shorter diagonal length. No uniform trend was observed by a country or journal of publication. Application of the CVAI formula using different denominators yielded interchangeable results, and the resulting values had only negligible differences clinically. However, it would be necessary to create a standard formula for using the CVAI as a parameter for reporting cranial shape assessments consistently.

The clinical manifestations, molecular mechanisms and treatment of craniosynostosis

Craniosynostosis is a major congenital craniofacial disorder characterized by the premature fusion of cranial suture(s). Patients with severe craniosynostosis often have impairments in hearing, vision, intracranial pressure and/or neurocognitive functions. Craniosynostosis can result from mutations, chromosomal abnormalities or adverse environmental effects, and can occur in isolation or in association with numerous syndromes. To date, surgical correction remains the primary treatment for craniosynostosis, but it is associated with complications and with the potential for re-synostosis. There is, therefore, a strong unmet need for new therapies. Here, we provide a comprehensive review of our current understanding of craniosynostosis, including typical craniosynostosis types, their clinical manifestations, cranial suture development, and genetic and environmental causes. Based on studies from animal models, we present a framework for understanding the pathogenesis of craniosynostosis, with an emphasis on the loss of postnatal suture mesenchymal stem cells as an emerging disease-driving mechanism. We evaluate emerging treatment options and highlight the potential of mesenchymal stem cell-based suture regeneration as a therapeutic approach for craniosynostosis.