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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.)

Objective: Craniofacial measuring is valuable for diagnosis and evaluation of growth and treatment of positional skull deformities. Plagiocephalometry (PCM) quantifies skull deformities and is proven to be reliable and valid. However, PCM needs direct skin contact with thermoplastic material, is laborious and time-consuming. Therefore, Skully Care (SC) was developed to measure positional skull deformities with a smartphone application., Design: SC is retrospectively compared to PCM., Setting: Pediatric physiotherapy centers., Patients: Age ≤1 year, analyzed or treated for positional skull deformities., Interventions: A total of 60 skull shape analyses were performed., Main Outcome Measures: The main outcome measures employed are Pearson correlation coefficient between cranial vault asymmetry index (CVAI; in SC) and oblique diameter difference index (ODDI; in PCM) and between cranial index (CI; in SC) and cranial proportional index (CPI; in PCM). Mann-Whitney U test determined difference of time consumption between PCM and SC., Results: High correlation was found between CVAI and ODDI ( r  = 0.849; P  < .01) in positional plagiocephaly and very high correlation between CI and CPI ( r   =  0.938; P  < .01) in positional brachycephaly. SC is significantly faster than PCM ( P  < .001)., Conclusions: SC is valid in analyzing positional skull deformities and strongly correlates to PCM, the gold standard in daily physiotherapy practice. The combination of simplicity, validity, speed, and user and child convenience makes SC a promising craniofacial measuring method in daily practice. SC has potential to be the modern successor for analyzing positional skull deformities.

Objectives: Severity of trigonocephaly varies and potentially affects intracranial volume (ICV) and intracranial pressure (ICP). The aim of this study is to measure ICV in trigonocephaly patients and compare it to normative data and correlate ICV with the severity of the skull deformity according to UCSQ (Utrecht Cranial Shape Quantifier)., Design: Retrospective study., Setting: Primary craniofacial center., Patients, Participants: Nineteen preoperative patients with nonsyndromic trigonocephaly (age ≤12 months)., Intervention: Intracranial volume was measured on preoperative computed tomography (CT) scans by manual segmentation (OsiriX Fondation). Utrecht Cranial Shape Quantifier was used to quantify the severity of the skull deformity. When present, papilledema as sign of elevated ICP was noted., Main Outcome Measures(s): Measured ICV was compared to Lichtenberg normative cranial volume growth curves, and Pearson correlation coefficient was used to correlate UCSQ with the ICV., Results: Mean age at CT scan was 6 months (2-11). Mean measured ICV was 842 mL (579-1124). Thirteen of h19 patients (11/15 boys and 2/4 girls) had an ICV between ±2 SD curves of Lichtenberg, 2 of 19 (1/15 boys and 1/4 girls) had an ICV less than -2 SD and 4 of 19 (3/15 boys and 1/4 girls) had an ICV greater than +2 SD. Mean UCSQ severity of trigonocephaly was 2.40 (-622.65 to 1279.75). Correlation between severity and ICV was negligible (r = -0.11). No papilledema was reported., Conclusions: Measured ICV was within normal ranges for trigonocephaly patients, in both mild and severe cases. No correlation was found between severity of trigonocephaly and ICV.

Trigonocephaly is the result of premature fusion of the metopic suture and its severity can vary widely. However, there is no gold standard for quantification of the severity. This study was performed to quantify severity using the Utrecht Cranial Shape Quantifier (UCSQ) and to assess forehead symmetry. Nineteen preoperative non-syndromic trigonocephaly patients (age ≤1 year) were included for the analysis of severity and symmetry. Severity according to the UCSQ was based on the following combined variables: forehead width and relative skull elongation. The UCSQ was compared to the most established quantification methods. A high correlation was found between the UCSQ and visual score (r=0.71). Moderate to negligible correlation was found between the UCSQ and frontal angle, binocular distance, inter-ocular distance, and frontal stenosis. Additionally, correlation between the visual score and these established quantification methods was negligible. Assessment of the frontal peak (a)symmetry (ratio of right to left triangle area in the curve) showed a mean right versus left triangle area ratio of 1.4 (range 0.9-2.4). The results suggest that the UCSQ is appropriate for the quantification of severity based on the high correlation with clinical judgement. Furthermore, a larger triangle area right than left was unexpectedly found, indicating forehead asymmetry., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Premature fusion of both coronal sutures (anterior brachycephaly) alters skull shape and potentially affects intracranial volume (ICV). Currently little is known about preoperative ICV in anterior brachycephaly. Aim is to measure preoperative ICV and compare this with normative data. Additionally, ICV will be correlated to most used clinical method of quantification: cephalic index (CI)., Methods: Preoperative patients with anterior brachycephaly (age, ≤12 months) were included and categorized by syndrome (when present). Computed tomography scans were used for ICV measurement by manual segmentation (OsiriX (Fondation OsiriX, Geneva, Switzerland)). Intracranial volume of each subgroup was compared with Lichtenberg normative cranial volume growth curves for controls. Cephalic index was calculated and correlated to ICV using Pearson correlation coefficient., Results: Thirty-four patients with both syndromic and nonsyndromic anterior brachycephaly were included: 17 with Apert syndrome, 6 with Muenke syndrome, 5 with Saethre Chotzen syndrome, 3 with Crouzon, 1 with craniofrontonasal dysplasia, and 2 nonsyndromal. Mean age at preoperative computed tomography scan was 4 months (1-10 months). Mean ICV was 847.31 cm3 (473.91-1459.22 cm3). Nineteen of 34 patients had skull volumes between ±2 SD curves of Lichtenberg, none of the patients had an ICV smaller than -2 SD and 15 of 34 had an ICV larger than +2 SD. Mean ICV in Apert syndrome was 829.85 cm3 (473.91-1061.53 cm3), in Muenke syndrome 942.06 cm3 (768.02-1136.75 cm3), in Saethre Chotzen syndrome 779.72 cm3 (609.21-1002.95 cm3), in Crouzon syndrome 700.57 cm3 (652.31-784.32 cm3), in craniofrontonasal dysplasia 738.97 cm3, and in the nonsyndromal group 1154.64 cm3 (850.07-1459.22 cm3). Apert had a mean greater than +2SD above the mean, the other subgroups had a mean within normal ranges (±2 SD). Correlation between severity of brachycephaly and overall ICV was low (r = 0.42)., Conclusions: Mean preoperative ICV in both syndromic and nonsyndromic anterior brachycephaly was 847.31 cm3. Intracranial volume in anterior brachycephaly is in 55.9% between normal ranges (±2 SD). In 44.1% ICV was greater than +2 SD, especially in Apert syndrome (11/16 Apert patients). None of the included patients had a deviant small ICV of less than -2 SD. Additionally, low correlation between ICV and CI (r = 0.42) was found and therefore CI is not suitable for estimating ICV in anterior brachycephaly., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Objectives: Very few studies focus on the quantification of severity of synostotic anterior brachycephaly. Aim of this study is to implement Utrecht Cranial Shape Quantifier (UCSQ) in brachycephaly patients to objectively quantify severity for both clinical and research purposes., Design: Retrospective study., Setting: Primary craniofacial center., Patients and Participants: Fifteen preoperative patients with bilateral coronal craniosynostosis (age <1.5 years)., Intervention: Utrecht Cranial Shape Quantifier was used to quantify severity using the variables: width of frontal peak ratio, difference forehead peak and occiput peak, and width between sides of the head., Main Outcome Measure(s): The UCSQ variables were combined and related to Argenta clinical classification and cephalic index (CI) using 1-way analysis of variance (ANOVA). All parameters were derived from computed tomography scans., Results: Statistically significant differences were found between group means of UCSQ in the 3 categories of Argenta (ANOVA; F (2,12) = 22.461; P < .01). Tukey post hoc test showed a significant difference between Argenta types 1 and 2, types 1 and 3, and types 2 and 3 (all P < .01). Statistically significant differences were found between traditional CI and Argenta types ( F (2,12) = 4.956; P = .03). Tukey post hoc test showed significantly difference between Argenta type 1 and 3 ( P = .02). No differences were found between other types. Low correlation was found between UCSQ and CI ( r = 0.47)., Conclusions: Utrecht Cranial Shape Quantifier objectively captures and quantifies the shape of synostotic brachycephaly, and we therefore developed a suitable method to put severity of synostotic (anterior) brachycephaly into numbers.

Abstract: Severity of unilateral coronal synostosis (UCS) varies and can affect intracranial volume (ICV), and intracranial pressure. Correlation between ICV and severity according to Utrecht Cranial Shape Quantifier and presence of papilledema as sign of raised intracranial pressure is determined. The authors included patients with UCS (≤18 months). Intracranial volume was calculated on preoperative CT scans by manual segmentation (OsiriX [Fondation OsiriX, Geneva, Switzerland]). Calculated ICV was compared to Lichtenberg normative data for control patients. When present, papilledema was noted. Utrecht Cranial Shape Quantifier was used to quantify severity using the variables: asymmetry ratio of frontal peak and ratio of frontal peak gradient. Severity of UCS was correlated to ICV using Pearson correlation coefficient. Mean age at CT scan of patients with UCS was 7 months (1-18 months). Mean calculated ICV was 870.96 mL (617.31-1264.46 mL). All patients had ICV between ± 2 SD curves of Lichtenberg; 10 had an ICV between -1 SD and +1 SD. Majority of ICV in girls was at or larger than normative mean, in boys ICV was mostly lower than normative mean. Pearson correlation coefficient between severity of UCS and ICV was negligible (r = -0.28). Preoperative papilledema during fundoscopy was found in 4.5% (1/22; ICV 1003.88 mL; severe UCS). Therefore, severity of UCS does not correlate to ICV. Despite varying severity of UCS, ICV remains within normal ranges., Competing Interests: The authors report no conflicts of interest., (Copyright © 2021 by Mutaz B. Habal, MD.)

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.

Purpose: Unilateral coronal synostosis (UCS) results in an asymmetrical skull, including shallow and asymmetrical orbits, associated with reduced orbital volume and high prevalences of ophthalmic sequelae. Aim is to link orbital volumes in patients with UCS to severity according to UCSQ (Utrecht Cranial Shape Quantifier) and presence of ophthalmic sequelae., Methods: We included preoperative patients with UCS (≤ 18 months). Orbital volume was measured on CT scans by manual segmentation (Mimics software (Materialise, Leuven, Belgium)), and severity of UCS was determined by UCSQ. Orbital volume of affected side was compared to unaffected side using Wilcoxon signed rank test. Orbital volume ratio was calculated (affected/unaffected volume) and compared to the category of UCSQ by Kruskal-Wallis test. Opthalmic sequelae were noted., Results: We included 19 patients (mean age 7 months). Orbital volume on affected side was significantly lower (p = 0.001), mean orbital volume ratio was 0.93 (SD 0.03). No significant differences in group means of orbital volume ratio between different levels of severity of UCSQ were found (Kruskal-Wallis H (2) = 0.873; p > 0.05). Ophthalmic sequelae were found in 3 patients; one had adduction impairment and strabismus (mild UCS), one had astigmatism (moderate UCS), and one had abduction impairment (on both ipsi- and contralateral side) and vertical strabismus (severe UCS)., Conclusion: No association between orbital volume ratio and severity of UCS was found. Side-to-side asymmetry in orbital volume was noted. No association between either preoperative orbital volume ratio or severity of UCS and the presence of preoperative ophthalmic sequelae was found.

Purpose: The aim is to implement Utrecht Cranial Shape Quantificator (UCSQ) for quantification of severity of scaphocephaly and compare UCSQ with the most used quantification method, cranial index (CI). Additionally, severity is linked to intracranial volume (ICV)., Methods: Sinusoid curves of 21 pre-operative children (age < 2 years) with isolated scaphocephaly were created. Variables of UCSQ (width of skull and maximum occiput and forehead) were combined to determine severity. CI was calculated. Three raters performed visual scoring for clinical severity (rating of 6 items; total score of 12 represents most severe form). Pearson's correlation test was used for correlation between UCSQ and visual score and between both CIs. ICV was calculated using OsiriX. ICV was compared to normative values and correlated to severity., Results: Mean UCSQ was 22.00 (2.00-42.00). Mean traditional CI was 66.01 (57.36-78.58), and mean visual score was 9.1 (7-12). Correlations between both traditional CI and CI of UCSQ and overall visual scores were moderate and high (r = - 0.59; p = 0.005 vs. r = - 0.81; p < 0.000). Mean ICV was 910 mL (671-1303), and ICV varied from decreased to increased compared to normative values. Negligible correlation was found between ICV and UCSQ (r = 0.26; p > 0.05) and between ICV and CI and visual score (r = - 0.30; p > 0.05 and r = 0.17; p > 0.05, respectively)., Conclusion: Our current advice is to use traditional CI in clinical practice; it is easy to use and minimally invasive. However, UCSQ is more precise and objective and captures whole skull shape. Therefore, UCSQ is preferable for research. Additionally, more severe scaphocephaly does not result in more deviant skull volumes.

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.