Craniosynostosis is a condition that occurs when the skull bones in a child fuse too early. The most common form of this condition is sagittal craniosynostosis affecting the sagittal suture in the midline of the skull. The condition can cause the skull to become long and narrow, potentially affecting the brain development.
There are Specialist Craniofacial Units across the world that have developed different approaches to reconstructing the skull. But it is difficult to predict which approach will have the best long-term effect on each individual child.
In response to this, Professor Mehran Moazen from UCL Mechanical Engineering has been using a range of experimental and computational techniques to advance our understanding of the mechanics of craniosynostosis. For example, his team has developed a computational modelling approach to compare mechanics of different treatment approaches for sagittal craniosynostosis with a vision to optimise the management of this condition.
To do the research, Professor Moazen and his team have been working with surgeons and hospitals around the world, including the Oxford Craniofacial Unit (UK), Necker-Enfants Malades Hospital (France), the University of Warmia and Mazury in Olsztyn (Poland) and Sahlgrenska University Hospital (Sweden). They also partnered with the Headlines Craniofacial Support charity. The research has been funded by the Royal Academy of Engineering, Rosetrees Trust, and the Engineering and Physical Sciences Research Council.
Using scans to create virtual models
“Craniosynostosis is a condition affecting 1 in 2,000 births, and its prevalence has increased by two to three times in recent years,” explains Professor Moazen. “Yet its optimum management is still a subject of controversy.”
This is what motivated Professor Moazen to find out if a computational approach could predict the future growth pattern of individuals’ skulls following different types of surgery (see Figure 1). The various surgical interventions that are currently used for sagittal craniosynostosis aim to guide the skull to grow in height, shorten the length, expand across the width and release any pressure across the brain.
As a result, Professor Moazen and his team created a number of models to estimate what the skull shapes and internal skull pressure levels would look like across each of these approaches, six years after the surgery is performed. To do this, they used CT images of the skull of a four-month-old patient prior to surgery, which helped them to create a virtual model. This virtual model was checked against follow-up CT images of the same patient’s skull. The team found they were able to accurately predict skull growth up to the age of six years, as well as the rate of skull healing, across the different surgical scenarios (see Figure 2). The model was also able to analyse the pressure build-up inside the skull, allowing the team to estimate if one approach may result in higher pressure than another.
Virtual surgery on 3D skulls
These models are helping surgeons to perform ‘virtual surgery’ on the skulls of individual patients. This allows them to mimic different surgical approaches and their outcomes to select the best surgical route for each patient.
“Our findings inform craniofacial surgeons on the advantages and disadvantages of different treatments for treating craniosynostosis from a biomechanical perspective,” says Professor Moazen. “This is also informative for the parents of children affected by this condition, as different clinical units across the world offer different treatment options.”
The modelling process allows surgeons to predict the skull morphologies in children in the long term. Ultimately, it should lower the chance of the neurodevelopment of children being affected.
The next steps for Professor Moazen in this area include predicting the growth of the face, as well as the skull morphology for craniosynostosis patients. The current modelling approach was developed and tested on sagittal craniosynostosis, but the team also wants to expand the modelling to other forms of craniosynostosis. And finally, Professor Moazen is also working on a potential new treatment option for the condition.
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Further information
Publications
- Mechanical loading of cranial joints minimizes the craniofacial phenotype in Crouzon syndrome (June 2022)
- A computational framework to predict calvarial growth: optimizing management of sagittal craniosynostosis (May 2022)
- Management of sagittal craniosynostosis: morphological comparison of 8 surgical techniques (October 2021)
- Characterising and modelling bone formation during mouse calvarial development (February 2019)
- Predicting calvarial growth in normal and craniosynostotic mice using a computational approach (December 2017)
- Modelling human skull growth: a validated computational model (May 2017)
UCL Profiles
- Professor Mehran Moazen
- Dr Arsalan Marghoub
Photo credit
- Ce Liang
- Marius Didziokas
