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Objective: Objective differentiation between unilateral coronal synostosis (UCS) and positional posterior plagiocephaly (PPP) based on 3D photogrammetry according to Utrecht Cranial Shape Quantificator (UCSQ)., Design: Retrospective study., Setting: Primary craniofacial center., Patients, Participants: Thirty-two unoperated patients (17 UCS; 15 PPP) (age < 1 year)., Interventions: Extraction of variables from sinusoid curves derived using UCSQ: asymmetry ratio forehead and occiput peak, ratio of gradient forehead and occiput peak, location forehead and occiput peak., Main Outcome Measure(s): Variables, derived using 3D photogrammetry, were analyzed for differentiation between UCS and PPP., Results: Frontal peak was shifted to the right side of the head in left-sided UCS (mean x -value 207 [192-220]), and right-sided PPP (mean x -value 210 [200-216]), and to the left in right-sided UCS (mean x -value 161 [156-166]), and left-sided PPP (mean x -value 150 [144-154]). Occipital peak was significantly shifted to the right side of the head in left-sided PPP (mean x -value 338 [336-340]) and to the left in right-sided PPP (mean x -value 23 [14-32]). Mean x -value of occipital peak was 9 (354-30) in left- and 2 (350-12) in right-sided UCS. Calculated ratio of gradient of the frontal peak is, in combination with the calculated asymmetry ratio of the frontal peak, a distinctive finding., Conclusions: UCSQ objectively captures shape of synostotic and positional plagiocephaly using 3D photogrammetry, we therefore developed a suitable method to objectively differentiate UCS from PPP using radiation-free methods.

Implementation of the Utrecht Cranial Shape Quantificator (UCSQ) classification method on 3D photogrammetry in patients with different types of craniosynostosis is the aim of the present study. Five children (age <1 year) of every group of the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, right-sided and left-sided anterior plagiocephaly) were randomly included. The program 3-Matic (v13.0) was used to import and analyze the included 3dMD photos. Three external landmarks were placed. Using the landmarks, a base plane was created, as well as a plane 4 cm superior to the base plane. Using UCSQ, we created sinusoid curves of the patients, the resulting curves were analyzed and values were extracted for calculations. Results per patient were run through a diagnostic flowchart in order to determine correctness of the flowchart when using 3D photogrammetry. Each of the patients (n=25) of the different craniosynostosis subgroups is diagnosed correctly based on the different steps in the flowchart. This study proposes and implements a diagnostic approach of craniosynostosis based on 3D photogrammetry. By using a diagnostic flowchart based on specific characteristics for every type of craniosynostosis related to specific skull deformities, diagnosis can be established. All variables are expressed in number and are therefore objective., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 by Mutaz B. Habal, MD.)

Background: Children with trigonocephaly are at risk for neurodevelopmental disorders. The aim of this study is to investigate white matter properties of the frontal lobes in young, unoperated patients with metopic synostosis as compared to healthy controls using diffusion tension imaging (DTI)., Methods: Preoperative DTI data sets of 46 patients with trigonocephaly with a median age of 0.49 (interquartile range: 0.38) years were compared with 21 controls with a median age of 1.44 (0.98) years. White matter metrics of the tracts in the frontal lobe were calculated using FMRIB Software Library (FSL). The mean value of tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were estimated for each subject and compared to healthy controls. By linear regression, FA and MD values per tract were assessed by trigonocephaly, sex, and age., Results: The mean FA and MD values in the frontal lobe tracts of untreated trigonocephaly patients, younger than 3 years, were not significantly different in comparison to controls, where age showed to be a significant associated factor., Conclusions: Microstructural parameters of white matter tracts of the frontal lobe of patients with trigonocephaly are comparable to those of controls aged 0-3 years., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aim: To assess the relationship of surface area of the cerebral cortex to intracranial volume (ICV) in syndromic craniosynostosis., Method: Records of 140 patients (64 males, 76 females; mean age 8y 6mo [SD 5y 6mo], range 1y 2mo-24y 2mo) with syndromic craniosynostosis were reviewed to include clinical and imaging data. Two hundred and three total magnetic resonance imaging (MRI) scans were evaluated in this study (148 patients with fibroblast growth factor receptor [FGFR], 19 patients with TWIST1, and 36 controls). MRIs were processed via FreeSurfer pipeline to determine total ICV and cortical surface area (CSA). Scaling coefficients were calculated from log-transformed data via mixed regression to account for multiple measurements, sex, syndrome, and age. Educational outcomes were reported by syndrome., Results: Mean ICV was greater in patients with FGFR (1519cm 3 , SD 269cm 3 , p=0.016) than in patients with TWIST1 (1304cm 3 , SD 145cm 3 ) or controls (1405cm 3 , SD 158cm 3 ). CSA was related to ICV by a scaling law with an exponent of 0.68 (95% confidence interval [CI] 0.61-0.76) in patients with FGFR compared to 0.81 (95% CI 0.50-1.12) in patients with TWIST1 and 0.77 (95% CI 0.61-0.93) in controls. Lobar analysis revealed reduced scaling in the parietal (0.50, 95% CI 0.42-0.59) and occipital (0.67, 95% CI 0.54-0.80) lobes of patients with FGFR compared with controls. Modified learning environments were needed more often in patients with FGFR., Interpretation: Despite adequate ICV in FGFR-mediated craniosynostosis, CSA development is reduced, indicating maldevelopment, particularly in parietal and occipital lobes. Modified education is also more common in patients with FGFR., (© 2021 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.)

Objectives: Severity of unilateral coronal synostosis (UCS) can vary. Quantification is important for treatment, expectations of treatment and natural outcome, and education of the patient and parents., Design: Retrospective study., Setting: Primary craniofacial center., Patients, Participants: Twenty-three preoperative patients with unilateral coronal craniosynostosis (age < 2 years)., Intervention: Utrecht Cranial Shape Quantifier (UCSQ) was used to quantify severity using the variables: asymmetry ratio of frontal peak and ratio of frontal peak gradient., Main Outcome Measures(s): The UCSQ variables were combined and related to visual score using Pearson correlation coefficient; UCSQ and visual score were additionally compared to Di Rocco classification by one-way analysis of variance or Kruskal-Wallis test. All measurements were made on computed tomography scans., Results: Good correlation between UCSQ and visual score was found ( r = 0.67). No statistically significant differences were found between group means of UCSQ in the 3 categories of Di Rocco classification ( F 2,20 = 0.047; P > .05). Kruskal-Wallis test showed no significant differences between group means of visual score in the 3 categories of Di Rocco classification (Kruskal-Wallis H (2) = 0.871; P > .05)., Conclusions: Using UCSQ, we can quantify UCS according to severity using characteristics, it outperforms traditional methods and captures the whole skull shape. In future research, we can apply UCSQ to 3D-photogrammetry due to the utilization of external landmarks.

In this study, we diagnose skull shape deformities by analysing sinusoid curves obtained from standardized computed tomography (CT) slices of the skull for the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, right- and left-sided anterior plagiocephaly). Scaphocephaly has a high forehead peak and low troughs, in contrast to brachycephaly. Anterior plagiocephaly has asymmetry and shifting of the forehead peak. Trigonocephaly has a high and narrow frontal peak. Control patients have a symmetrical skull shape with low troughs and a high and broader frontal peak. Firstly, we included 5 children of every group of the common craniosynostoses and additionally 5 controls for extraction and calculation of characteristics. A diagnostic flowchart was developed. Secondly, we included a total of 51 craniosynostosis patients to validate the flowchart. All patients were correctly classified using the flowchart.Conclusion: Our study proposes and implements a new diagnostic approach of craniosynostosis. We describe a diagnostic flowchart based on specific characteristics for every type of craniosynostosis related to the specific skull deformities and control patients. All variables are expressed in number; therefore, we are able to use these variables in future research to quantify the different types of craniosynostosis. What is Known: • Premature fusion of one or more cranial sutures results in a specific cranial shape. • Clinical diagnosis is relatively simple; however, objective diagnosis based on distinctive values is difficult. What is New: • Using external landmarks and curve analysis, distinctive variables, and values for every type of craniosynostosis related to the specific skull deformities were determined and used to create a diagnostic flowchart for diagnosis. • Validation with an independent data set of 51 patients showed that all patients were correctly classified.

We present a novel technique for classification of skull deformities due to most common craniosynostosis. We included 5 children of every group of the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, and right- and left-sided anterior plagiocephaly) and additionally 5 controls. Our outline-based classification method is described, using the software programs OsiriX, MeVisLab, and Matlab. These programs were used to identify chosen landmarks (porion and exocanthion), create a base plane and a plane at 4 cm, segment outlines, and plot resulting graphs. We measured repeatability and reproducibility, and mean curves of groups were analyzed. All raters achieved excellent intraclass correlation scores (0.994-1.000) and interclass correlation scores (0.989-1.000) for identifying the external landmarks. Controls, scaphocephaly, trigonocephaly, and brachycephaly all have the peak of the forehead in the middle of the curve (180°). In contrary, in anterior plagiocephaly, the peak is shifted (to the left of graph in right-sided and vice versa). Additionally, controls, scaphocephaly, and trigonocephaly have a high peak of the forehead; scaphocephaly has the lowest troughs; in brachycephaly, the width/frontal peak ratio has the highest value with a low frontal peak.Conclusion: We introduced a preliminary study showing an objective and reproducible methodology using CT scans for the analysis of craniosynostosis and potential application of our method to 3D photogrammetry. What is Known: • Diagnosis of craniosynostosis is relatively simple; however, classification of craniosynostosis is difficult and current techniques are not widely applicable. What is New: • We introduce a novel technique for classification of skull deformities due to craniosynostosis, an objective and reproducible methodology using CT scans resulting in characteristic curves. The method is applicable to all 3D-surface rendering techniques. • Using external landmarks and curve analysis, specific and characteristic curves for every type of craniosynostosis related to the specific skull deformities are found.

Aim: To evaluate the impact of risk factors for intracranial hypertension (ICH) on cerebral cortex thickness in syndromic craniosynostosis., Method: ICH risk factors including papilloedema, hydrocephalus, obstructive sleep apnea (OSA), cerebellar tonsillar position, occipitofrontal circumference (OFC) curve deflection, age, and sex were collected from the records of patients with syndromic craniosynostosis (Apert, Crouzon, Pfeiffer, Muenke, Saethre-Chotzen syndromes) and imaging. Magnetic resonance images were analysed and exported for statistical analysis. A linear mixed model was developed to determine correlations with cerebral cortex thickness changes., Results: In total, 171 scans from 107 patients (83 males, 88 females [including repeated scans], mean age 8y 10mo, range 1y 1mo-34y, SD 5y 9mo) were evaluated. Mean cortical thickness in this cohort was 2.78mm (SD 0.17). Previous findings of papilloedema (p=0.036) and of hydrocephalus (p=0.007) were independently associated with cortical thinning. Cortical thickness did not vary significantly by sex (p=0.534), syndrome (p=0.896), OSA (p=0.464), OFC (p=0.375), or tonsillar position (p=0.682)., Interpretation: Detection of papilloedema or hydrocephalus in syndromic craniosynostosis is associated with significant changes in cortical thickness, supporting the need for preventative rather than reactive treatment strategies., What This Paper Adds: Papilloedema is associated with thinning of the cerebral cortex in syndromic craniosynostosis, independently of hydrocephalus., (© 2020 Mac Keith Press.)

Objective: Objective differentiation between unilateral coronal synostosis (UCS) and positional posterior plagiocephaly (PPP) based on 3D photogrammetry according to Utrecht Cranial Shape Quantificator (UCSQ). Design: Retrospective study. Setting: Primary craniofacial center. Patients, Participants: Thirty-two unoperated patients (17 UCS; 15 PPP) (age < 1 year). Interventions: Extraction of variables from sinusoid curves derived using UCSQ: asymmetry ratio forehead and occiput peak, ratio of gradient forehead and occiput peak, location forehead and occiput peak. Main Outcome Measure(s): Variables, derived using 3D photogrammetry, were analyzed for differentiation between UCS and PPP. Results: Frontal peak was shifted to the right side of the head in left-sided UCS (mean x -value 207 [192-220]), and right-sided PPP (mean x -value 210 [200-216]), and to the left in right-sided UCS (mean x -value 161 [156-166]), and left-sided PPP (mean x -value 150 [144-154]). Occipital peak was significantly shifted to the right side of the head in left-sided PPP (mean x -value 338 [336-340]) and to the left in right-sided PPP (mean x -value 23 [14-32]). Mean x -value of occipital peak was 9 (354-30) in left- and 2 (350-12) in right-sided UCS. Calculated ratio of gradient of the frontal peak is, in combination with the calculated asymmetry ratio of the frontal peak, a distinctive finding. Conclusions: UCSQ objectively captures shape of synostotic and positional plagiocephaly using 3D photogrammetry, we therefore developed a suitable method to objectively differentiate UCS from PPP using radiation-free methods. [ABSTRACT FROM AUTHOR]

Objectives: Severity of unilateral coronal synostosis (UCS) can vary. Quantification is important for treatment, expectations of treatment and natural outcome, and education of the patient and parents. Design: Retrospective study. Setting: Primary craniofacial center. Patients, Participants: Twenty-three preoperative patients with unilateral coronal craniosynostosis (age < 2 years). Intervention: Utrecht Cranial Shape Quantifier (UCSQ) was used to quantify severity using the variables: asymmetry ratio of frontal peak and ratio of frontal peak gradient. Main Outcome Measures(s): The UCSQ variables were combined and related to visual score using Pearson correlation coefficient; UCSQ and visual score were additionally compared to Di Rocco classification by one-way analysis of variance or Kruskal-Wallis test. All measurements were made on computed tomography scans. Results: Good correlation between UCSQ and visual score was found (r = 0.67). No statistically significant differences were found between group means of UCSQ in the 3 categories of Di Rocco classification (F 2,20 = 0.047; P >.05). Kruskal-Wallis test showed no significant differences between group means of visual score in the 3 categories of Di Rocco classification (Kruskal-Wallis H (2) = 0.871; P >.05). Conclusions: Using UCSQ, we can quantify UCS according to severity using characteristics, it outperforms traditional methods and captures the whole skull shape. In future research, we can apply UCSQ to 3D-photogrammetry due to the utilization of external landmarks. [ABSTRACT FROM AUTHOR]