An Overview of Modelling Craniosynostosis Using the Finite Element Method

Malde, Oyvind; Libby, Joseph; Moazen, Mehran

doi:10.1159/000490833

Cited by 23 publications

(17 citation statements)

References 64 publications

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“…There are limited finite element studies on the biomechanics of craniosynostosis 23 despite huge potentials of this method to advance treatment of this condition. Our group in the past few years has been using this technique to predict the calvarial growth in humans 17 and in a mouse model of this condition 19,20 .…”

Section: Discussionmentioning

confidence: 99%

“…Finite element (FE) method is a powerful numerical technique used to analyse a wide variety of engineering problems 15 FE method has the potential to predict the morphological changes during the skull growth [16][17][18][19][20] and to compare the biomechanics of different reconstruction techniques. This can advance our understanding of the optimum management, not only of sagittal synostosis but all forms of craniosynostosis [21][22][23] . However, FE models first need to be validated and we need to understand the sensitivity of these models to build confidence in their outcomes.…”

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confidence: 99%

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Predicting calvarial morphology in sagittal craniosynostosis

Malde

Cross

Lim

et al. 2020

Sci Rep

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early fusion of the sagittal suture is a clinical condition called, sagittal craniosynostosis. calvarial reconstruction is the most common treatment option for this condition with a range of techniques being developed by different groups. Computer simulations have a huge potential to predict the calvarial growth and optimise the management of this condition. However, these models need to be validated. The aim of this study was to develop a validated patient-specific finite element model of a sagittal craniosynostosis. Here, the finite element method was used to predict the calvarial morphology of a patient based on its preoperative morphology and the planned surgical techniques. A series of sensitivity tests and hypothetical models were carried out and developed to understand the effect of various input parameters on the result. Sensitivity tests highlighted that the models are sensitive to the choice of input parameter. the hypothetical models highlighted the potential of the approach in testing different reconstruction techniques. The patient-specific model highlighted that a comparable pattern of calvarial morphology to the follow up ct data could be obtained. this study forms the foundation for further studies to use the approach described here to optimise the management of sagittal craniosynostosis.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Predicting calvarial morphology in sagittal craniosynostosis

Malde

Cross

Lim

et al. 2020

Sci Rep

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“…In summary, we think the modeling approach presented here has potential in the modeling of calvarial growth. This could provide significant advancement in terms of comparing different reconstruction methods for the treatment of craniosynostosis and understanding the optimum management of various forms of this condition [32], which in the long term could reduce the complications currently associated with the treatment of craniosynostosis.…”

Section: P3mentioning

confidence: 99%

Characterizing and Modeling Bone Formation during Mouse Calvarial Development

et al. 2019

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The newborn mammalian cranial vault consists of five flat bones that are joined together along their edges by soft fibrous tissues called sutures. Early fusion of these sutures leads to a medical condition known as craniosynostosis. The mechanobiology of normal and craniosynostotic skull growth is not well understood. In a series of previous studies, we characterized and modeled radial expansion of normal and craniosynostotic (Crouzon) mice. Here, we describe a new modeling algorithm to simulate bone formation at the sutures in normal and craniosynostotic mice. Our results demonstrate that our modeling approach is capable of predicting the observed ex vivo pattern of bone formation at the sutures in the aforementioned mice. The same approach can be used to model different calvarial reconstruction in children with craniosynostosis to assist in the management of this complex condition.

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“…Finite element (FE) analyses have already been utilised to simulate correction of cranial deformities. For instance, Wolanski et al focused on sagittal and metopic craniosynostosis correction 28 ; Borghi et al simulated spring assisted correction of sagittal craniosynostosis in patient-specific models 29 ; Malde et al developed a patient-specific FE model of sagittal craniosynostosis to predict calvarial morphology 30 ; and Bozkurt et al evaluated potential correction methods for unicoronal craniosynostosis using a patient-specific FE skull model 31 . Numerical studies aiming to simulate skull correction focus on common craniosynostosis types such as sagittal, unicoronal or metopic synostosis.…”

Section: Introductionmentioning

confidence: 99%

Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction

Bozkurt

Borghi

Lande

et al. 2020

Sci Rep

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Lambdoid craniosynostosis (LC) is a rare non-syndromic craniosynostosis characterised by fusion of the lambdoid sutures at the back of the head. Surgical correction including the spring assisted cranioplasty is the only option to correct the asymmetry at the skull in LC. However, the aesthetic outcome from spring assisted cranioplasty may remain suboptimal. The aim of this study is to develop a parametric finite element (FE) model of the LC skulls that could be used in the future to optimise spring surgery. The skull geometries from three different LC patients who underwent spring correction were reconstructed from the pre-operative computed tomography (CT) in Simpleware ScanIP. Initially, the skull growth between the pre-operative CT imaging and surgical intervention was simulated using MSC Marc. The osteotomies and spring implantation were performed to simulate the skull expansion due to the spring forces and skull growth between surgery and post-operative CT imaging in MSC Marc. Surface deviation between the FE models and post-operative skull models reconstructed from CT images changed between ± 5 mm over the skull geometries. Replicating spring assisted cranioplasty in LC patients allow to tune the parameters for surgical planning, which may help to improve outcomes in LC surgeries in the future.

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An Overview of Modelling Craniosynostosis Using the Finite Element Method

Cited by 23 publications

References 64 publications

Predicting calvarial morphology in sagittal craniosynostosis

Predicting calvarial morphology in sagittal craniosynostosis

Characterizing and Modeling Bone Formation during Mouse Calvarial Development

Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction

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