Craniosynostosis, is the premature fusion of one or more cranial sutures which is the second most common cranial facial anomalies. The premature cranial sutures leads to deformity of skull shape and restricts the growth of brain, which might elicit severe neurologic damage. Craniosynostosis exhibit close correlations with a varieties of syndromes. During the past two decades, as the appliance of high throughput DNA sequencing techniques, steady progresses has been made in identifying gene mutations in both syndromic and nonsyndromic cases, which allow researchers to better understanding the genetic roles in the development of cranial vault. As the enrichment of known mutations involved in the pathogenic of premature sutures fusion, multiple signaling pathways have been investigated to dissect the underlying mechanisms beneath the disease. In addition to genetic etiology, environment factors, especially mechanics, have also been proposed to have vital roles during the pathophysiological of craniosynostosis. However, the influence of mechanics factors in the cranial development remains largely unknown. In this review, we present a brief overview of the updated genetic mutations and environmental factors identified in both syndromic and nonsyndromic craniosynostosis. Furthermore, potential molecular signaling pathways and its relations have been described.

Objective: To evaluate three-dimensional (3D) accuracy and reliability of nonradiographic dentofacial images integrated with a two-step method. Methods: 3D facial images, cone-beam computed tomography (CBCT) images and digital maxillary dental casts were obtained from 20 pre-orthodontic subjects. Digital dental casts were integrated into 3D facial images using a two-step method based on the anterior tooth area. 3D coordinate values of five dental landmarks were identified in both dentofacial images and CBCT images. The accuracy of the integration method was assessed with paired t -tests between dentofacial images and CBCT-based reference standards. Intraclass correlation coefficients (ICCs) were assessed for the reliability of dentofacial images and CBCT-based images. Analysis of variance and Kruskal-Wallis tests evaluated the accuracy of the method in different dimensions. Results: There was no statistical difference between dentofacial images and CBCT reference standards in both translational and rotational dimensions ( P > .05). Translational mean absolute errors for full dentitions were within 0.42 mm and ICCs were over 0.998 in x, y, and z directions. Rotational mean absolute errors for full dentitions were within 0.92° and ICCs over 0.734 in pitch, yaw, and roll orientations. Integration errors were significantly greater in the first molar, z -translation, and pitch rotation ( P < .05). Conclusions: Integrating 3D dentofacial images with the two-step method is precise and acceptable for clinical diagnostics and scientific purposes. Errors were greater in the molar region, z -translation, and pitch rotation.

Background: This study is aimed to (1) investigate the influence of sagittal and vertical patterns on mandibular cross-sectional morphology and to (2) provide visualized mandibular cross-sectional morphology in different groups with General Procrustes Analysis (GPA), canonical variance analysis (CVA) and discriminant function analysis (DFA).Methods: 324 cone-beam computed tomography (CBCT) images were collected to analyze mandibular cross-sectional morphology and were categorized into 12 groups according to sagittal and vertical pattern and gender. One-way analysis of variance (ANOVA) was used to compare the difference among the groups. Thirty equidistant points were marked along the contour of mandibular cross-section and GPA, CVA and DFA were applied.Results: (1) Mandibular height in hyperdivergent groups was significantly higher than that in normodivergent and hypodivergent groups (P < 0.05). (2) Hypodivergent groups showed significantly wider upper third of mandibular width from symphysis to molar region than that in hyperdivergent group (P < 0.05), except for the premolar and molar regions in male groups (P > 0.05). (3) Class II hyperdivergent group showed narrowest lower third width in the molar region, with the mean value of 12.03 mm in females and 11.98 mm in males. (4) For males and females, the ratio between height and lower third width at symphysis was significantly higher in Class II hyperdivergent group than that in Class I hyperdivergent group (P < 0.05).Conclusions: (1) The influence of vertical facial patterns on mandibular cross-sectional morphology is more obvious than that of sagittal skeletal pattern. (2) Subjects with increased vertical dimension presented with a remarkable “slimer” mandibular cross-sectional morphology at symphysis. (3) A deeper curve along the anterior contour of symphysis in Class II hyperdivergent group was noted with GPA.

Background: The aim of this study was to assess the difference of palatal morphology in different vertical patterns between skeletal Class I subjects and skeletal Class II subjects with retrusive mandible. Methods: Seventy-six skeletal Class II subjects with retrusive mandible (38 females, 38 males) and 85 skeletal Class I subjects (45 females, 40 males) were collected retrospectively and divided into hyperdivergent, normodivergent and hypodivergent groups. CBCT images of these subjects were reoriented by Dolphin 3D Imaging software. Three-dimensional (3D) maxilla was segmented by ProPlan software before using Geomagic Studio software to reconstruct 3D palatal morphology. Deviation patterns on 3D colored map analysis was performed to compare the difference of 3D palatal morphology between different groups. Results: 3D colored map analysis showed that male’s palate was higher and wider than that of female in the posterior part, regardless of different sagittal and vertical patterns. In skeletal Class II subjects with retrusive mandible, males with hyperdivergent and normodivergent showed higher and narrower in the posterior part of palate, while females with hyperdivergent and normodivergent had a higher but no obviously narrow palate compared with the hypodivergent subjects. Skeletal Class II subjects with retrusive mandible showed flatter and narrower in the posterior part of palate than that of skeletal Class I subjects. Conclusions: Sagittal and vertical patterns have great influence on the palatal morphology and as the vertical dimension increased, the palate tended to be higher and narrower.