Geometric growth of the normal human craniocervical junction from 0 to 18 years old.

The craniocervical junction (CCJ) forms the bridge between the skull and the spine, a highly mobile group of joints that allows the mobility of the head in every direction. The CCJ plays a major role in protecting the inferior brainstem (bulb) and spinal cord, therefore also requiring some stability. Children are subjected to multiple constitutive or acquired diseases involving the CCJ: primary bone diseases such as in FGFR-related craniosynostoses or acquired conditions such as congenital torticollis, cervical spine luxation, and neurological disorders. To design efficient treatment plans, it is crucial to understand the relationship between abnormalities of the craniofacial region and abnormalities of the CCJ. This can be approached by the study of control and abnormal growth patterns. Here we report a model of normal skull base growth by compiling a collection of geometric models in control children. Focused analyses highlighted specific developmental patterns for each CCJ bone, emphasizing rapid growth during infancy, followed by varying rates of growth and maturation during childhood and adolescence until reaching stability by 18 years of age. The focus was on the closure patterns of synchondroses and sutures in the occipital bone, revealing distinct closure trajectories for the anterior intra-occipital synchondroses and the occipitomastoid suture. The findings, although based on a limited dataset, showcased specific age-related changes in width and closure percentages, providing valuable insights into growth dynamics within the first 2 years of life. Integration analyses revealed intricate relationships between skull and neck structures, emphasizing coordinated growth at different stages. Specific bone covariation patterns, as found between the first and second cervical vertebrae (C1 and C2), indicated synchronized morphological changes. Our results provide initial data for designing inclusive CCJ geometric models to predict normal and abnormal growth dynamics.

New diagnostic criteria for metopic ridges and trigonocephaly: a 3D geometric approach.

BACKGROUND: Trigonocephaly occurs due to the premature fusion of the metopic suture, leading to a triangular forehead and hypotelorism. This condition often requires surgical correction for morphological and functional indications. Metopic ridges also originate from premature metopic closure but are only associated with mid-frontal bulging; their surgical correction is rarely required. Differential diagnosis between these two conditions can be challenging, especially in minor trigonocephaly. METHODS: Two hundred seven scans of patients with trigonocephaly (90), metopic rigdes (27), and controls (90) were collected. Geometric morphometrics were used to quantify skull and orbital morphology as well as the interfrontal angle and the cephalic index. An innovative method was developed to automatically compute the frontal curvature along the metopic suture. Different machine-learning algorithms were tested to assess the predictive power of morphological data in terms of classification. RESULTS: We showed that control patients, trigonocephaly and metopic rigdes have distinctive skull and orbital shapes. The 3D frontal curvature enabled a clear discrimination between groups (sensitivity and specificity > 92%). Furthermore, we reached an accuracy of 100% in group discrimination when combining 6 univariate measures. CONCLUSION: Two diagnostic tools were proposed and demonstrated to be successful in assisting differential diagnosis for patients with trigonocephaly or metopic ridges. Further clinical assessments are required to validate the practical clinical relevance of these tools.

Assessing craniofacial growth and form without landmarks: A new automatic approach based on spectral methods.

We present a novel method for the morphometric analysis of series of 3D shapes, and demonstrate its relevance for the detection and quantification of two craniofacial anomalies: trigonocephaly and metopic ridges, using CT-scans of young children. Our approach is fully automatic, and does not rely on manual landmark placement and annotations. Our approach furthermore allows to differentiate shape classes, enabling successful differential diagnosis between trigonocephaly and metopic ridges, two related conditions characterized by triangular foreheads. These results were obtained using recent developments in automatic nonrigid 3D shape correspondence methods and specifically spectral approaches based on the functional map framework. Our method can capture local changes in geometric structure, in contrast to methods based, for instance, on global shape descriptors. As such, our approach allows to perform automatic shape classification and provides visual feedback on shape regions associated with different classes of deformations. The flexibility and generality of our approach paves the way for the application of spectral methods in quantitative medicine.

Paediatric skull growth models: A systematic review of applications to normal skulls and craniosynostoses.

INTRODUCTION: Craniosynostoses affect 1/2000 births and their incidence is currently increasing. Without surgery, craniosynostosis can lead to neurological issues due to restrained brain growth and social stigma due to abnormal head shapes. Understanding growth patterns is essential to develop surgical planning approaches and predict short- and long-term post-operative results. Here we provide a systematic review of normal and pathological cranial vault growth models. MATERIAL AND METHODS: The systematic review of the literature identified descriptive and comprehensive skull growth models with the following criteria: full text articles dedicated to the skull vault of children under 2 years of age, without focus on molecular and cellular mechanisms. Models were analysed based on initial geometry, numerical method, age determination method and validation process. RESULTS: A total of 14 articles including 17 models was reviewed. Four descriptive models were assessed, including 3 models using statistical analyses and 1 based on deformational methods. Thirteen comprehensive models were assessed including 7 finite element models and 6 diffusion models. Results from the current literature showed that successful models combined analyses of cranial vault shape and suture bone formation. DISCUSSION: Growth modelling is central when assessing craniofacial architecture in young patients and will be a key factor in the development of future customized treatment strategies. Recurrent technical difficulties were encountered by most authors when generalizing a specific craniosynostosis model to all types of craniosynostoses, when assessing the role of the brain and when attempting to relate the age with different stages of growth.