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.

BounTI (boundary-preserving threshold iteration): A user-friendly tool for automatic hard tissue segmentation.

X-ray Computed Tomography (CT) images are widely used in various fields of natural, physical, and biological sciences. 3D reconstruction of the images involves segmentation of the structures of interest. Manual segmentation has been widely used in the field of biological sciences for complex structures composed of several sub-parts and can be a time-consuming process. Many tools have been developed to automate the segmentation process, all with various limitations and advantages, however, multipart segmentation remains a largely manual process. The aim of this study was to develop an open-access and user-friendly tool for the automatic segmentation of calcified tissues, specifically focusing on craniofacial bones. Here we describe BounTI, a novel segmentation algorithm which preserves boundaries between separate segments through iterative thresholding. This study outlines the working principles behind this algorithm, investigates the effect of several input parameters on its outcome, and then tests its versatility on CT images of the craniofacial system from different species (e.g. a snake, a lizard, an amphibian, a mouse and a human skull) with various scan qualities. The case studies demonstrate that this algorithm can be effectively used to segment the craniofacial system of a range of species automatically. High-resolution microCT images resulted in more accurate boundary-preserved segmentation, nonetheless significantly lower-quality clinical images could still be segmented using the proposed algorithm. Methods for manual intervention are included in this tool when the scan quality is insufficient to achieve the desired segmentation results. While the focus here was on the craniofacial system, BounTI can be used to automatically segment any hard tissue. The tool presented here is available as an Avizo/Amira add-on, a stand-alone Windows executable, and a Python library. We believe this accessible and user-friendly segmentation tool can benefit the wider anatomical community.

Treatment techniques for rectovaginal fistulas after low rectal resection for deep endometriosis.

Endometriosis is a benign gynecologic affection that may lead to major surgeries, such as colorectal resections. Rectovaginal fistulas (RVF) are among the possible complications. When they occur, it is necessary to adapt the repair surgery as best as possible to limit their functional consequences. This video shows three different techniques for correcting RVF after rectal resection for endometriosis, with a combination of perineal surgery and laparoscopy: a mucosal flap, a transanal transection and single stapled anastomosis (TTSS) and a pull through. Supplementary file1 (MP4 469658 KB).

Artificial intelligence-based diagnosis in fetal pathology using external ear shapes.

OBJECTIVE: Here we trained an automatic phenotype assessment tool to recognize syndromic ears in two syndromes in fetuses-=CHARGE and Mandibulo-Facial Dysostosis Guion Almeida type (MFDGA)-versus controls. METHOD: We trained an automatic model on all profile pictures of children diagnosed with genetically confirmed MFDGA and CHARGE syndromes, and a cohort of control patients, collected from 1981 to 2023 in Necker Hospital (Paris) with a visible external ear. The model consisted in extracting landmarks from photographs of external ears, in applying geometric morphometry methods, and in a classification step using machine learning. The approach was then tested on photographs of two groups of fetuses: controls and fetuses with CHARGE and MFDGA syndromes. RESULTS: The training set contained a total of 1489 ear photographs from 526 children. The validation set contained a total of 51 ear photographs from 51 fetuses. The overall accuracy was 72.6% (58.3%-84.1%, p < 0.001), and 76.4%, 74.9%, and 86.2% respectively for CHARGE, control and MFDGA fetuses. The area under the curves were 86.8%, 87.5%, and 90.3% respectively for CHARGE, controls, and MFDGA fetuses. CONCLUSION: We report the first automatic fetal ear phenotyping model, with satisfactory classification performances. Further validations are required before using this approach as a diagnostic tool.

The fractal geometry of polymeric materials surfaces: surface area and fractal length scales.

Using three common polymeric materials (polypropylene (PP), polytetrafluoroethylene (PTFE) and polycaprolactone (PCL)), a standard oxygen-plasma treatment and atomic force microscopy (AFM), we performed a scaling analysis of the modified surfaces yielding effective Hurst exponents (H ≃ 0.77 ± 0.02 (PP), ≃0.75 ± 0.02 (PTFE), and ≃0.83 ± 0.02 (PCL)), for the one-dimensional profiles, corresponding to the transversal sections of the surface, by averaging over all possible profiles. The surface fractal dimensions are given by ds = 3 - H, corresponding to ds ≃ 2.23, 2.25, and 2.17, respectively. We present a simple method to obtain the surface area from the AFM images stored in a matrix of 512 × 512 pixels. We show that the considerable increase found in the surface areas of the treated samples w.r.t. to the non-treated ones (43% for PP, 85% for PTFE, and 25% for PCL, with errors of about 2.5% on samples of 2 µm × 2 µm) is consistent with the observed increase in the length scales of the fractal regime to determine H, typically by a factor of about 2, extending from a few to hundreds of nanometres. We stipulate that the intrinsic roughness already present in the original non-treated material surfaces may serve as 'fractal' seeds undergoing significant height fluctuations during plasma treatment, suggesting a pathway for the future development of advanced material interfaces with large surface areas at the nanoscale.

A European multicenter outcome study on the different perioperative airway management policies following midface surgery in syndromic craniosynostosis: a proposal for a Standard Operating Procedure.

BACKGROUND: Perioperative airway management following midface advancements in children with Apert and Crouzon/Pfeiffer syndrome can be challenging, and protocols often differ. This study examined airway management following midface advancements and postoperative respiratory complications. METHODS: A multicenter, retrospective cohort study was performed to obtain information about the timing of extubation, perioperative airway management, and respiratory complications after monobloc / le Fort III procedures. RESULTS: Ultimately, 275 patients (129 monobloc and 146 Le Fort III) were included; 62 received immediate extubation and 162 delayed extubation; 42 had long-term tracheostomies and nine perioperative short-term tracheostomies. Short-term tracheostomies were in most centers reserved for selected cases. Patients with delayed extubation remained intubated for three days (IQR 2 - 5). The rate of no or only oxygen support after extubation was comparable between patients with immediate and delayed extubation, 58/62 (94%) and 137/162 (85%) patients, respectively. However, patients with immediate extubation developed less postoperative pneumonia than those with delayed, 0/62 (0%) versus 24/161 (15%) (P = 0.001), respectively. Immediate extubation also appeared safe in moderate/severe OSA since 19/20 (95%) required either no or only oxygen support after extubation. The odds of developing intubation-related complications increased by 21% with every extra day of intubation. CONCLUSIONS: Immediate extubation following midface advancements was found to be a safe option, as it was not associated with respiratory insufficiency but did lead to fewer complications. Immediate extubation should be considered routine management in patients with no/mild OSA and should be the aim in moderate/severe OSA after careful assessment.

Next generation phenotyping for diagnosis and phenotype-genotype correlations in Kabuki syndrome.

The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photographs and distinguish KS1 (KS type 1, KMT2D-related) from KS2 (KS type 2, KDM6A-related). We included retrospectively and prospectively, from 1998 to 2023, all frontal and lateral pictures of patients with a molecular confirmation of KS. After automatic preprocessing, we extracted geometric and textural features. After incorporation of age, gender, and ethnicity, we used XGboost (eXtreme Gradient Boosting), a supervised machine learning classifier. The model was tested on an independent validation set. Finally, we compared the performances of our model with DeepGestalt (Face2Gene). The study included 1448 frontal and lateral facial photographs from 6 centers, corresponding to 634 patients (527 controls, 107 KS); 82 (78%) of KS patients had a variation in the KMT2D gene (KS1) and 23 (22%) in the KDM6A gene (KS2). We were able to distinguish KS from controls in the independent validation group with an accuracy of 95.8% (78.9-99.9%, p < 0.001) and distinguish KS1 from KS2 with an empirical Area Under the Curve (AUC) of 0.805 (0.729-0.880, p < 0.001). We report an automatic detection model for KS with high performances (AUC 0.993 and accuracy 95.8%). We were able to distinguish patients with KS1 from KS2, with an AUC of 0.805. These results outperform the current commercial AI-based solutions and expert clinicians.

AI-based diagnosis in mandibulofacial dysostosis with microcephaly using external ear shapes.

Introduction: Mandibulo-Facial Dysostosis with Microcephaly (MFDM) is a rare disease with a broad spectrum of symptoms, characterized by zygomatic and mandibular hypoplasia, microcephaly, and ear abnormalities. Here, we aimed at describing the external ear phenotype of MFDM patients, and train an Artificial Intelligence (AI)-based model to differentiate MFDM ears from non-syndromic control ears (binary classification), and from ears of the main differential diagnoses of this condition (multi-class classification): Treacher Collins (TC), Nager (NAFD) and CHARGE syndromes. Methods: The training set contained 1,592 ear photographs, corresponding to 550 patients. We extracted 48 patients completely independent of the training set, with only one photograph per ear per patient. After a CNN-(Convolutional Neural Network) based ear detection, the images were automatically landmarked. Generalized Procrustes Analysis was then performed, along with a dimension reduction using PCA (Principal Component Analysis). The principal components were used as inputs in an eXtreme Gradient Boosting (XGBoost) model, optimized using a 5-fold cross-validation. Finally, the model was tested on an independent validation set. Results: We trained the model on 1,592 ear photographs, corresponding to 1,296 control ears, 105 MFDM, 33 NAFD, 70 TC and 88 CHARGE syndrome ears. The model detected MFDM with an accuracy of 0.969 [0.838-0.999] (p < 0.001) and an AUC (Area Under the Curve) of 0.975 within controls (binary classification). Balanced accuracies were 0.811 [0.648-0.920] (p = 0.002) in a first multiclass design (MFDM vs. controls and differential diagnoses) and 0.813 [0.544-0.960] (p = 0.003) in a second multiclass design (MFDM vs. differential diagnoses). Conclusion: This is the first AI-based syndrome detection model in dysmorphology based on the external ear, opening promising clinical applications both for local care and referral, and for expert centers.

Toward the Definition of a Soundscape Ranking Index (SRI) in an Urban Park Using Machine Learning Techniques.

The goal of estimating a soundscape index, aimed at evaluating the contribution of the environmental sound components, is to provide an accurate "acoustic quality" assessment of a complex habitat. Such an index can prove to be a powerful ecological tool associated with both rapid on-site and remote surveys. The soundscape ranking index (SRI), introduced by us recently, can empirically account for the contribution of different sound sources by assigning a positive weight to natural sounds (biophony) and a negative weight to anthropogenic ones. The optimization of such weights was performed by training four machine learning algorithms (decision tree, DT; random forest, RF; adaptive boosting, AdaBoost; support vector machine, SVM) over a relatively small fraction of a labeled sound recording dataset. The sound recordings were taken at 16 sites distributed over an area of approximately 22 hectares at Parco Nord (Northern Park) of the city Milan (Italy). From the audio recordings, we extracted four different spectral features: two based on ecoacoustic indices and the other two based on mel-frequency cepstral coefficients (MFCCs). The labeling was focused on the identification of sounds belonging to biophonies and anthropophonies. This preliminary approach revealed that two classification models, DT and AdaBoost, trained by using 84 extracted features from each recording, are able to provide a set of weights characterized by a rather good classification performance (F1-score = 0.70, 0.71). The present results are in quantitative agreement with a self-consistent estimation of the mean SRI values at each site that was recently obtained by us using a different statistical approach.

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.

Normal human craniofacial growth and development from 0 to 4 years.

Knowledge of human craniofacial growth (increase in size) and development (change in shape) is important in the clinical treatment of a range of conditions that affects it. This study uses an extensive collection of clinical CT scans to investigate craniofacial growth and development over the first 48 months of life, detail how the cranium changes in form (size and shape) in each sex and how these changes are associated with the growth and development of various soft tissues such as the brain, eyes and tongue and the expansion of the nasal cavity. This is achieved through multivariate analyses of cranial form based on 3D landmarks and semi-landmarks and by analyses of linear dimensions, and cranial volumes. The results highlight accelerations and decelerations in cranial form changes throughout early childhood. They show that from 0 to 12 months, the cranium undergoes greater changes in form than from 12 to 48 months. However, in terms of the development of overall cranial shape, there is no significant sexual dimorphism in the age range considered in this study. In consequence a single model of human craniofacial growth and development is presented for future studies to examine the physio-mechanical interactions of the craniofacial growth.

Brain resident memory T cells rapidly expand and initiate neuroinflammatory responses following CNS viral infection.

The contribution of circulating verses tissue resident memory T cells (TRMs) to clinical neuropathology is an enduring question due to a lack of mechanistic insights. The prevailing view is TRMs are protective against pathogens in the brain. However, the extent to which antigen-specific TRMs induce neuropathology upon reactivation is understudied. Using the described phenotype of TRMs, we found that brains of naïve mice harbor populations of CD69+ CD103- T cells. Notably, numbers of CD69+ CD103- TRMs rapidly increase following neurological insults of various origins. This TRM expansion precedes infiltration of virus antigen-specific CD8 T cells and is due to proliferation of T cells within the brain. We next evaluated the capacity of antigen-specific TRMs in the brain to induce significant neuroinflammation post virus clearance, including infiltration of inflammatory myeloid cells, activation of T cells in the brain, microglial activation, and significant blood brain barrier disruption. These neuroinflammatory events were induced by TRMs, as depletion of peripheral T cells or blocking T cell trafficking using FTY720 did not change the neuroinflammatory course. Depletion of all CD8 T cells, however, completely abrogated the neuroinflammatory response. Reactivation of antigen-specific TRMs in the brain also induced profound lymphopenia within the blood compartment. We have therefore determined that antigen-specific TRMs can induce significant neuroinflammation, neuropathology, and peripheral immunosuppression. The use of cognate antigen to reactivate CD8 TRMs enables us to isolate the neuropathologic effects induced by this cell type independently of other branches of immunological memory, differentiating this work from studies employing whole pathogen re-challenge. This study also demonstrates the capacity for CD8 TRMs to contribute to pathology associated with neurodegenerative disorders and long-term complications associated with viral infections. Understanding functions of brain TRMs is crucial in investigating their role in neurodegenerative disorders including MS, CNS cancers, and long-term complications associated with viral infections including COVID-19.

Self-Consistent Soundscape Ranking Index: The Case of an Urban Park.

We have performed a detailed analysis of the soundscape inside an urban park (located in the city of Milan) based on simultaneous sound recordings at 16 locations within the park. The sound sensors were deployed over a regular grid covering an area of about 22 hectares, surrounded by a variety of anthropophonic sources. The recordings span 3.5 h each over a period of four consecutive days. We aimed at determining a soundscape ranking index (SRI) evaluated at each site in the grid by introducing 4 unknown parameters. To this end, a careful aural survey from a single day was performed in order to identify the presence of 19 predefined sound categories within a minute, every 3 minutes of recording. It is found that all SRI values fluctuate considerably within the 70 time intervals considered. The corresponding histograms were used to define a dissimilarity function for each pair of sites. Dissimilarity was found to increase significantly with the inter-site distance in space. Optimal values of the 4 parameters were obtained by minimizing the standard deviation of the data, consistent with a fifth parameter describing the variation of dissimilarity with distance. As a result, we classify the sites into three main categories: "poor", "medium" and "good" environmental sound quality. This study can be useful to assess the quality of a soundscape in general situations.

Recent innovations in the technology and applications of low-dimensional CuO nanostructures for sensing, energy and catalysis.

Low-dimensional copper oxide nanostructures are very promising building blocks for various functional materials targeting high-demanded applications, including energy harvesting and transformation systems, sensing and catalysis. Featuring a very high surface-to-volume ratio and high chemical reactivity, these materials have attracted wide interest from researchers. Currently, extensive research on the fabrication and applications of copper oxide nanostructures ensures the fast progression of this technology. In this article we briefly outline some of the most recent, mostly within the past two years, innovations in well-established fabrication technologies, including oxygen plasma-based methods, self-assembly and electric-field assisted growth, electrospinning and thermal oxidation approaches. Recent progress in several key types of leading-edge applications of CuO nanostructures, mostly for energy, sensing and catalysis, is also reviewed. Besides, we briefly outline and stress novel insights into the effect of various process parameters on the growth of low-dimensional copper oxide nanostructures, such as the heating rate, oxygen flow, and roughness of the substrates. These insights play a key role in establishing links between the structure, properties and performance of the nanomaterials, as well as finding the cost-and-benefit balance for techniques that are capable of fabricating low-dimensional CuO with the desired properties and facilitating their integration into more intricate material architectures and devices without the loss of original properties and function.

Toward an understanding of the conformational plasticity of S100A8 and S100A9 Ca2+-binding proteins.

S100A8 and S100A9 are small, human, Ca2+-binding proteins with multiple intracellular and extracellular functions in signaling, regulation, and defense. The two proteins are not detected as monomers but form various noncovalent homo- or hetero-oligomers related to specific activities in human physiology. Because of their significant roles in numerous medical conditions, there has been intense research on the conformational properties of various S100A8 and S100A9 proteoforms as essential targets of drug discovery. NMR or crystal structures are currently available only for mutated or truncated protein complexes, mainly with bound metal ions, that may well reflect the proteins' properties outside cells but not in other biological contexts in which they perform. Here, we used structural mass spectrometry methods combined with molecular dynamics simulations to compare the conformations of wildtype full-length S100A8 and S100A9 subunits in biologically relevant homo- and heterodimers and in higher oligomers formed in the presence of calcium or zinc ions. We provide, first, rationales for their functional response to changing environmental conditions, by elucidating differences between proteoforms in flexible protein regions that may provide the plasticity of the binding sites for the multiple targets, and second, the key factors contributing to the variable stability of the oligomers. The described methods and a systematic view of the conformational properties of S100A8 and S100A9 complexes provide a basis for further research to characterize and modulate their functions for basic science and therapies.

Icex: Advances in the automatic extraction and volume calculation of cranial cavities.

The use of non-destructive approaches for digital acquisition (e.g. computerised tomography-CT) allows detailed qualitative and quantitative study of internal structures of skeletal material. Here, we present a new R-based software tool, Icex, applicable to the study of the sizes and shapes of skeletal cavities and fossae in 3D digital images. Traditional methods of volume extraction involve the manual labelling (i.e. segmentation) of the areas of interest on each section of the image stack. This is time-consuming, error-prone and challenging to apply to complex cavities. Icex facilitates rapid quantification of such structures. We describe and detail its application to the isolation and calculation of volumes of various cranial cavities. The R tool is used here to automatically extract the orbital volumes, the paranasal sinuses, the nasal cavity and the upper oral volumes, based on the coordinates of 18 cranial anatomical points used to define their limits, from 3D cranial surface meshes obtained by segmenting CT scans. Icex includes an algorithm (Icv) for the calculation of volumes by defining a 3D convex hull of the extracted cavity. We demonstrate the use of Icex on an ontogenetic sample (0-19 years) of modern humans and on the fossil hominin crania Kabwe (Broken Hill) 1, Gibraltar (Forbes' Quarry) and Guattari 1. We also test the tool on three species of non-human primates. In the modern human subsample, Icex allowed us to perform a preliminary analysis on the absolute and relative expansion of cranial sinuses and pneumatisations during growth. The performance of Icex, applied to diverse crania, shows the potential for an extensive evaluation of the developmental and/or evolutionary significance of hollow cranial structures. Furthermore, being open source, Icex is a fully customisable tool, easily applicable to other taxa and skeletal regions.

Assessment of Chimeric Antigen Receptor T Cell-Associated Toxicities Using an Acute Lymphoblastic Leukemia Patient-derived Xenograft Mouse Model.

Chimeric antigen receptor T (CART) cell therapy has emerged as a powerful tool for the treatment of multiple types of CD19+ malignancies, which has led to the recent FDA approval of several CD19-targeted CART (CART19) cell therapies. However, CART cell therapy is associated with a unique set of toxicities that carry their own morbidity and mortality. This includes cytokine release syndrome (CRS) and neuroinflammation (NI). The use of preclinical mouse models has been crucial in the research and development of CART technology for assessing both CART efficacy and CART toxicity. The available preclinical models to test this adoptive cellular immunotherapy include syngeneic, xenograft, transgenic, and humanized mouse models. There is no single model that seamlessly mirrors the human immune system, and each model has strengths and weaknesses. This methods paper aims to describe a patient-derived xenograft model using leukemic blasts from patients with acute lymphoblastic leukemia as a strategy to assess CART19-associated toxicities, CRS, and NI. This model has been shown to recapitulate CART19-associated toxicities as well as therapeutic efficacy as seen in the clinic.

First-line surgery vs first-line ART to manage infertility in women with deep endometriosis without bowel involvement: A multi-centric propensity-score matching comparison.

OBJECTIVE: To compare first-line surgery with first-line assisted reproductive techniques (ART) in infertile women with deep infiltrating endometriosis (DIE) without colorectal involvement. STUDY DESIGN: A retrospective comparative cohort study with a propensity-score matching analysis, in four tertiary-care referral centers. The population was infertile women with DIE without colorectal involvement. The patients were managed either by first-line surgery followed by spontaneous conception attempts and/or ART, or by first-line ART. 284 patients were extracted from the databases. After matching, 92 patients were compared in each group. Clinical pregnancy rates (PR) and live-birth rates (LBR) were the primary outcomes, and cumulative pregnancy rate (CPR) and cumulative live birth rate (CLBR) were the secondary outcomes. RESULTS: The mean number of IVF-ICSI cycles per patient was 1.4, with a significant difference between the groups: 1.6 in the first-line ART group and 1.2 in the first-line surgery group (p = 0.006). The PR was significantly higher in the first-line surgery group (72 % vs 35 %; p < 0.001). In the first-line surgery group, non-ART pregnancies occurred in 18 % (17/92) while no non-ART pregnancies was noted in the first-line ART group. The LBR was significantly higher in the first-line surgery group (61 % vs 24 %; p < 0.001). After ART, the CPR were 72 % (47/67) in the first-line surgery group, and 35 % (32/92) in the first-line ART group (p < 0.001). CONCLUSION: After matching, our results support that first-line surgery offer higher pregnancy and live-birth rates than first-line ART in patients with DIE without colorectal involvement.

A preliminary analysis of replicating the biomechanics of helmet therapy for sagittal craniosynostosis.

PURPOSE: The aim of this study was to investigate the biomechanics of endoscopically assisted strip craniectomy treatment for the management of sagittal craniosynostosis while undergoing three different durations of postoperative helmet therapy using a computational approach. METHODS: A previously developed 3D model of a 4-month-old sagittal craniosynostosis patient was used. The strip craniectomy incisions were replicated across the segmented parietal bones. Areas across the calvarial were selected and constrained to represent the helmet placement after surgery. Skull growth was modelled and three variations of helmet therapy were investigated, where the timings of helmet removal alternated between 2, 5, and 8 months after surgery. RESULTS: The predicted outcomes suggest that the prolonging of helmet placement has perhaps a beneficial impact on the postoperative long-term morphology of the skull. No considerable difference was found on the pattern of contact pressure at the interface of growing intracranial volume and the skull between the considered helmeting durations. CONCLUSION: Although the validation of these simulations could not be performed, these simulations showed that the duration of helmet therapy after endoscopically assisted strip craniectomy influenced the cephalic index at 36 months. Further studies require to validate these preliminary findings yet this study can lay the foundations for further studies to advance our fundamental understanding of mechanics of helmet therapy.