Predicting and comparing three corrective techniques for sagittal craniosynostosis

Sagittal synostosis is the most occurring form of craniosynostosis, resulting in calvarial deformation and possible long-term neurocognitive deficits. Several surgical techniques have been developed to correct these issues. Debates as to the most optimal approach are still ongoing. Finite element method is a computational tool that’s shown to assist with the management of craniosynostosis. The aim of this study was to compare and predict the outcomes of three reconstruction methods for sagittal craniosynostosis. Here, a generic finite element model was developed based on a patient at 4 months of age and was virtually reconstructed under all three different techniques. Calvarial growth was simulated to predict the skull morphology and the impact of different reconstruction techniques on the brain growth up to 60 months of age. Predicted morphology was then compared with in vivo and literature data. Our results show a promising resemblance to morphological outcomes at follow up. Morphological characteristics between considered techniques were also captured in our predictions. Pressure outcomes across the brain highlight the potential impact that different techniques have on growth. This study lays the foundation for further investigation into additional reconstructive techniques for sagittal synostosis with the long-term vision of optimizing the management of craniosynostosis

A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis

The neonate skull consists of several bony plates, connected by fibrous soft tissue called sutures. Premature fusion of sutures is a medical condition known as craniosynostosis. Sagittal synostosis, caused by premature fusion of the sagittal suture, is the most common form of this condition. The optimum management of this condition is an ongoing debate in the craniofacial community while aspects of the biomechanics and mechanobiology are not well understood. Here, we describe a computational framework that enables us to predict and compare the calvarial growth following different reconstruction techniques for the management of sagittal synostosis. Our results demonstrate how different reconstruction techniques interact with the increasing intracranial volume. The framework proposed here can be used to inform optimum management of different forms of craniosynostosis, minimising the risk of functional consequences and secondary surgery

Management of sagittal craniosynostosis morphological comparison of 8 surgical techniques

The aim of this study was to carry out a retrospective multicenter study comparing the morphological outcome of 8 techniques used for the management of sagittal synostosis versus a large cohort of control patients. Computed tomography (CT) images were obtained from children CT-scanned for non-craniosynostosis related events (n=241) and SS patients at pre-operative and post-operative follow-up stages (n=101). No significant difference in morphological outcomes was observed between the techniques considered in this study. However, the majority of techniques showed a tendency for relapse. Further, the more invasive procedures at older ages seem to lead to larger intracranial volume compared to less invasive techniques at younger ages. This study can be a first step towards future multicenter studies, comparing surgical results and offering a possibility for objective benchmarking of outcomes between methods and centers

A Photo Score for Aesthetic Outcome in Sagittal Synostosis:An ERN CRANIO Collaboration

European Reference Network (ERN) CRANIO is focused on optimizing care for patients with rare or complex craniofacial anomalies, including craniosynostosis and/or rare ear, nose, and throat disorders. The main goal of ERN CRANIO is to collect uniform data on treatment outcomes for multicenter comparison. We aimed to develop a reproducible and reliable suture-specific photo score that can be used for cross-center comparison of phenotypical severity of sagittal synostosis and aesthetic outcome of treatment. We conducted a retrospective study among nonsyndromic sagittal synostosis patients aged &lt;19 years. We included preoperative and postoperative photo sets from 6 ERN CRANIO centers. Photo sets included bird's eye, lateral, and anterior-posterior views. The sagittal synostosis photo score was discussed in the working group, and consensus was obtained on its contents. Interrater agreement was assessed with weighted Fleiss' Kappa and intraclass correlation coefficients.The photo score consisted of frontal bossing, elongated skull, biparietal narrowness, temporal hollowing, vertex line depression, occipital bullet, and overall phenotype. Each item was scored as normal, mild, moderate, or severe. Results from 36 scaphocephaly patients scored by 20 raters showed kappa values ranging from 0.38 [95% bootstrap CI: 0.31, 0.45] for biparietal narrowness to 0.56 [95% bootstrap CI: 0.47, 0.64] for frontal bossing. Agreement was highest for the sum score of individual items [intraclass correlation coefficients agreement 0.69 [95% CI: 0.57, 0.82]. This is the first large-scale multicenter study in which experts investigated a photo score to assess the severity of sagittal synostosis phenotypical characteristics. Agreement on phenotypical characteristics was suboptimal (fair-moderate agreement) and highest for the summed score of individual photo score items (substantial agreement), indicating that although experts interpret phenotypical characteristics differently, there is consensus on overall phenotypical severity.</p

Mutations in TFAP2B and previously unimplicated genes of the BMP, Wnt, and Hedgehog pathways in syndromic craniosynostosis

Craniosynostosis (CS) is a frequent congenital anomaly featuring the premature fusion of 1 or more sutures of the cranial vault. Syndromic cases, featuring additional congenital anomalies, make up 15% of CS. While many genes underlying syndromic CS have been identified, the cause of many syndromic cases remains unknown. We performed exome sequencing of 12 syndromic CS cases and their parents, in whom previous genetic evaluations were unrevealing. Damaging de novo or transmitted loss of function (LOF) mutations were found in 8 genes that are highly intolerant to LOF mutation (P = 4.0 × 10^{-8}); additionally, a rare damaging mutation in SOX11, which has a lower level of intolerance, was identified. Four probands had rare damaging mutations (2 de novo) in TFAP2B, a transcription factor that orchestrates neural crest cell migration and differentiation; this mutation burden is highly significant (P = 8.2 × 10^{-12}). Three probands had rare damaging mutations in GLI2, SOX11, or GPC4, which function in the Hedgehog, BMP, and Wnt signaling pathways; other genes in these pathways have previously been implicated in syndromic CS. Similarly, damaging de novo mutations were identified in genes encoding the chromatin modifier KAT6A, and CTNNA1, encoding catenin α-1. These findings establish TFAP2B as a CS gene, have implications for assessing risk to subsequent children in these families, and provide evidence implicating other genes in syndromic CS. This high yield indicates the value of performing exome sequencing of syndromic CS patients when sequencing of known disease loci is unrevealing

A population-specific material model for sagittal craniosynostosis to predict surgical shape outcomes

Sagittal craniosynostosis consists of premature fusion (ossification) of the sagittal suture during infancy, resulting in head deformity and brain growth restriction. Spring-assisted cranioplasty (SAC) entails skull incisions to free the fused suture and insertion of two springs (metallic distractors) to promote cranial reshaping. Although safe and effective, SAC outcomes remain uncertain. We aimed hereby to obtain and validate a skull material model for SAC outcome prediction. Computed tomography data relative to 18 patients were processed to simulate surgical cuts and spring location. A rescaling model for age matching was created using retrospective data and validated. Design of experiments was used to assess the effect of different material property parameters on the model output. Subsequent material optimization—using retrospective clinical spring measurements—was performed for nine patients. A population-derived material model was obtained and applied to the whole population. Results showed that bone Young’s modulus and relaxation modulus had the largest effect on the model predictions: the use of the population-derived material model had a negligible effect on improving the prediction of on-table opening while significantly improved the prediction of spring kinematics at follow-up. The model was validated using on-table 3D scans for nine patients: the predicted head shape approximated within 2 mm the 3D scan model in 80% of the surface points, in 8 out of 9 patients. The accuracy and reliability of the developed computational model of SAC were increased using population data: this tool is now ready for prospective clinical application

Method for the identification of material properties the skull bone children

Celem badań było opracowanie metody wyznaczania parametrów wytrzymałościowych kości czaszek dzieci. Identyfikacja własności materiałowych obejmowała wyznaczenie modułu sprężystości i granicy wytrzymałości podczas próby rozciągania. Otrzymane wyniki z przeprowadzonych prób porównano z danymi literaturowymi oraz posłużyły do analitycznego wyliczenia modułu Younga. Na tej podstawie zastały określone odpowiednie warunki przeprowadzania badań i sposoby przygotowania próbek kości ze względu na rodzaj testu oraz ich wpływ na wyniki badań