An interactive atlas of three-dimensional syndromic facial morphology.

Craniofacial phenotyping is critical for both syndrome delineation and diagnosis because craniofacial abnormalities occur in 30% of characterized genetic syndromes. Clinical reports, textbooks, and available software tools typically provide two-dimensional, static images and illustrations of the characteristic phenotypes of genetic syndromes. In this work, we provide an interactive web application that provides three-dimensional, dynamic visualizations for the characteristic craniofacial effects of 95 syndromes. Users can visualize syndrome facial appearance estimates quantified from data and easily compare craniofacial phenotypes of different syndromes. Our application also provides a map of morphological similarity between a target syndrome and other syndromes. Finally, users can upload 3D facial scans of individuals and compare them to our syndrome atlas estimates. In summary, we provide an interactive reference for the craniofacial phenotypes of syndromes that allows for precise, individual-specific comparisons of dysmorphology.

Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations.

Facial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Previous genome scans have revealed more than 100 genetic loci associated with different aspects of normal-range facial variation. Most of these loci have been detected in Europeans, with few studies focusing on other ancestral groups. Consequently, the degree to which facial traits share a common genetic basis across diverse sets of humans remains largely unknown. We therefore investigated the genetic basis of facial morphology in an East African cohort. We applied an open-ended data-driven phenotyping approach to a sample of 2,595 3D facial images collected on Tanzanian children. This approach segments the face into hierarchically arranged, multivariate features that capture the shape variation after adjusting for age, sex, height, weight, facial size and population stratification. Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10-8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation. Two of these associations were in highly conserved regions showing craniofacial-specific enhancer activity during embryological development (5q31.1 and 12q21.31). Six of the 20 loci surpassed a stricter threshold accounting for multiple phenotypes with study-wide significance (p < 6.25 × 10-10). Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci. Taken together, these results may point to both shared and population-specific components to the genetic architecture of facial variation.

Using data-driven phenotyping to investigate the impact of sex on 3D human facial surface morphology.

The effects of sex on human facial morphology have been widely documented. Because sexual dimorphism is relevant to a variety of scientific and applied disciplines, it is imperative to have a complete and accurate account of how and where male and female faces differ. We apply a comprehensive facial phenotyping strategy to a large set of existing 3D facial surface images. We investigate facial sexual dimorphism in terms of size, shape, and shape variance. We also assess the ability to correctly assign sex based on shape, both for the whole face and for subregions. We applied a predefined data-driven segmentation to partition the 3D facial surfaces of 2446 adults into 63 hierarchically linked regions, ranging from global (whole face) to highly localized subparts. Each facial region was then analyzed with spatially dense geometric morphometrics. To describe the major modes of shape variation, principal components analysis was applied to the Procrustes aligned 3D points comprising each of the 63 facial regions. Both nonparametric and permutation-based statistics were then used to quantify the facial size and shape differences and visualizations were generated. Males were significantly larger than females for all 63 facial regions. Statistically significant sex differences in shape were also seen in all regions and the effects tended to be more pronounced for the upper lip and forehead, with more subtle changes emerging as the facial regions became more granular. Males also showed greater levels of shape variance, with the largest effect observed for the central forehead. Classification accuracy was highest for the full face (97%), while most facial regions showed an accuracy of 75% or greater. In summary, sex differences in both size and shape were present across every part of the face. By breaking the face into subparts, some shape differences emerged that were not apparent when analyzing the face as a whole. The increase in facial shape variance suggests possible evolutionary origins and may offer insights for understanding congenital facial malformations. Our classification results indicate that a high degree of accuracy is possible with only parts of the face, which may have implications for biometrics applications.

Refining nosology by modelling variation among facial phenotypes: the RASopathies.

BACKGROUND: In clinical genetics, establishing an accurate nosology requires analysis of variations in both aetiology and the resulting phenotypes. At the phenotypic level, recognising typical facial gestalts has long supported clinical and molecular diagnosis; however, the objective analysis of facial phenotypic variation remains underdeveloped. In this work, we propose exploratory strategies for assessing facial phenotypic variation within and among clinical and molecular disease entities and deploy these techniques on cross-sectional samples of four RASopathies: Costello syndrome (CS), Noonan syndrome (NS), cardiofaciocutaneous syndrome (CFC) and neurofibromatosis type 1 (NF1). METHODS: From three-dimensional dense surface scans, we model the typical phenotypes of the four RASopathies as average 'facial signatures' and assess individual variation in terms of direction (what parts of the face are affected and in what ways) and severity of the facial effects. We also derive a metric of phenotypic agreement between the syndromes and a metric of differences in severity along similar phenotypes. RESULTS: CFC shows a relatively consistent facial phenotype in terms of both direction and severity that is similar to CS and NS, consistent with the known difficulty in discriminating CFC from NS based on the face. CS shows a consistent directional phenotype that varies in severity. Although NF1 is highly variable, on average, it shows a similar phenotype to CS. CONCLUSIONS: We established an approach that can be used in the future to quantify variations in facial phenotypes between and within clinical and molecular diagnoses to objectively define and support clinical nosologies.

Quantification and visualization of the tooth extraction effects on face with spatially dense geometric morphometrics.

PURPOSE: To apply geometric morphometrics and multivariate statistics to evaluate changes of the face for female Chinese patients who underwent orthodontic treatment with different type of anchorage control. METHODS: Forty-six adult female patients were enrolled including 33 four first premolar extraction cases (17 patients with mini-implants for maximum anchorage control and 16 patients without mini-implants) and 13 non-extraction cases with minimum treatment duration of 15 months. Spatially dense correspondence was established among all the images The pre-and post-treatment average faces of the two extraction groups and the non-extraction group were generated. Partial least squares regression was used to test the statistical significance of the effects of treatment for different anchorage choice. RESULTS: The upper and lower lips were retruded significantly after treatment in the extraction groups. In the maximum anchorage control group, the temple and cheek were depressed by approximately 1 mm, and the zygomatic regions were increased in the mid-face. However, these changes were not statistically significant. In comparison, no statistically significant facial changes occurred in the non-extraction group. CONCLUSIONS: The anchorage choice and the removal of four first premolar extraction influence lip shape as well as the perioral regions. However, extraction treatment does not impact the appearance of the cheeks and temples on a statistically level, as compared to orthodontic treatment without premolar extractions. Spatially dense geometric morphometric facilitates comprehensive treatment effect quantification and visualization on the full facial changes for improving orthodontic outcome evaluation.

Influence of age and diet consistency on the oral muscle pressure of orthodontically treated and untreated subjects with normal occlusion and comparison of their 3D facial shape.

OBJECTIVES: (1) To investigate the effect of age and diet consistency on maximum lips, tongue and cheek pressure of orthodontically treated and untreated subjects with normal, Class I dental occlusion, (2) to find out whether there is a muscle imbalance between anterior tongue and lip pressure in the same subjects at different ages and (3) to compare the 3D facial shape of treated and untreated individuals. MATERIAL AND METHODS: Subjects with normal occlusion were prospectively grouped into orthodontically treated/untreated and in children/adolescents/adults. Iowa Oral Performance Instrument was used to record the maximum muscle pressure. Two-way ANOVA and Tukey post hoc test analysed age-specific differences in muscle pressure. Two-way ANCOVA analysed the effect of diet consistency on muscle pressure. Lips and tongue imbalance was analysed using z-scores and 3D faces using a generalized Procrustes analysis. RESULTS: One hundred thirty-five orthodontically untreated and 114 treated participants were included. Muscle pressure was found to increase with age in both groups, except for the tongue in treated subjects. No differences in the balance between lips and tongue muscle pressure were found, but a higher cheek pressure in untreated adults (p<0.05) was observed. 3D facial shapes showed subtle differences. Untreated subjects with soft diet consistency showed lower lip pressure (p<0.05). CONCLUSION: Oral muscle pressure of orthodontically treated patients without relapse does not differ from that of untreated patients with Class-I occlusion. CLINICAL RELEVANCE: This study provides normative lip, tongue and cheek muscle pressure in subjects with normal occlusion, which can be used for diagnosis, treatment planning and stability.

A statistical shape model for estimating missing soft tissues of the face in a black South African population.

PURPOSE: Facial disfigurement may affect the quality of life of many patients. Facial prostheses are often used as an adjuvant to surgical intervention and may sometimes be the only viable treatment option. Traditional methods for designing soft-tissue facial prostheses are time-consuming and subjective, while existing digital techniques are based on mirroring of contralateral features of the patient, or the use of existing feature templates/models that may not be readily available. We aim to support the objective and semi-automated design of facial prostheses with primary application to midline or bilateral defect restoration where no contralateral features are present. Specifically, we developed and validated a statistical shape model (SSM) for estimating the shape of missing facial soft tissue segments, from any intact parts of the face. MATERIALS AND METHODS: An SSM of 3D facial variations was built from meshes extracted from computed tomography and cone beam computed tomography images of a black South African sample (n = 235) without facial disfigurement. Various types of facial defects were simulated, and the missing parts were estimated automatically by a weighted fit of each mesh to the SSM. The estimated regions were compared to the original regions using color maps and root-mean-square (RMS) distances. RESULTS: Root mean square errors (RMSE) for defect estimations of one orbit, partial nose, cheek, and lip were all below 1.71 mm. Errors for the full nose, bi-orbital defects, as well as small and large composite defects were between 2.10 and 2.58 mm. Statistically significant associations of age and type of defect with RMSE were observed, but not with sex or imaging modality. CONCLUSION: This method can support the objective and semi-automated design of facial prostheses, specifically for defects in the midline, crossing the midline or bilateral defects, by facilitating time-consuming and skill-dependent aspects of prosthesis design.

Nasal characteristics in patients with asymmetric mandibular prognathism.

INTRODUCTION: To objectively quantify nasal characteristics of patients with asymmetric mandibular prognathism and to evaluate the association between nasal asymmetry and dentofacial abnormalities. METHODS: Ninety adult patients with asymmetric mandibular prognathism were included. Images were captured during pretreatment using 3-dimensional stereophotogrammetry. A total of 7160 uniformly sampled quasi-landmarks were automatically identified on each facial image to establish correspondence using a template mapping technique. Fifteen commonly used anatomic landmarks were automatically located on each image through barycentric to Cartesian coordinate conversion. Nasal characteristics and asymmetry were quantified by anthropometric linear distances, angular measurements, and surface-based analysis. The degree of the nasal, chin, and periorbital asymmetry in a patient was scored using a root-mean-squared error between the left and right sides. The correlations among these regional asymmetries were evaluated. RESULTS: The nasal tip was significantly shifted to the deviated side of the chin, and the nostrils were asymmetrical. The location and degree of nasal asymmetry varied among patients with asymmetric mandibular prognathism. The level of nasal asymmetry was significantly and positively correlated with chin and periorbital asymmetry. CONCLUSIONS: Nasal asymmetry is present in asymmetric mandibular prognathism patients. Furthermore, it is positively associated with periorbital deviation and chin deviation. Individualized nasal asymmetry evaluation should be performed, and clinicians should inform patients about preexisting nasal asymmetry.

Automated assessment of mandibular shape asymmetry in 3-dimensions.

INTRODUCTION: This study aimed to develop an automatic pipeline for analyzing mandibular shape asymmetry in 3-dimensions. METHODS: Forty patients with skeletal Class I pattern and 80 patients with skeletal Class III pattern were used. The mandible was automatically segmented from the cone-beam computed tomography images using a U-net deep learning network. A total of 17,415 uniformly sampled quasi-landmarks were automatically identified on the mandibular surface via a template mapping technique. After alignment with the robust Procrustes superimposition, the pointwise surface-to-surface distance between original and reflected mandibles was visualized in a color-coded map, indicating the location of asymmetry. The degree of overall mandibular asymmetry and the asymmetry of subskeletal units were scored using the root-mean-squared-error between the left and right sides. These asymmetry parameters were compared between the skeletal Class I and skeletal Class III groups. RESULTS: The mandible shape was significantly more asymmetrical in patients with skeletal Class III pattern with positional asymmetry. The condyles were identified as the most asymmetric region in all groups, followed by the coronoid process and the ramus. CONCLUSIONS: This automated approach to quantify mandibular shape asymmetry will facilitate high-throughput image processing for big data analysis. The spatially-dense landmarks allow for evaluating mandibular asymmetry over the entire surface, which overcomes the information loss inherent in conventional linear distance or angular measurements. Precise quantification of the asymmetry can provide important information for individualized diagnosis and treatment planning in orthodontics and orthognathic surgery.

Facial asymmetry assessment in skeletal Class III patients with spatially-dense geometric morphometrics.

OBJECTIVE: Quantification and visualization of the location and magnitude of facial asymmetry is important for diagnosis and treatment planning. The objective of this study was to analyze the asymmetric features of the face for skeletal Class III patients using spatially-dense geometric morphometrics. METHODS: Three-dimensional facial images were obtained for 86 skeletal Class III patients. About 7160 uniformly sampled quasi-landmarks were automatically identified on each face using template mapping technique. The pointwise surface-to-surface distance between original and mirror face was measured and visualized for the whole face after robust Procrustes superimposition. The degree of overall asymmetry in an individual was scored using a root-mean-squared-error. Automatic partitioning of the face was obtained, and the severity of the asymmetry compared among seven facial regions. RESULTS: Facial asymmetry was mainly located on, but not limited to, the lower two-thirds of the face in skeletal Class III patients. The lower cheek and nose asymmetry were detected to have more extensive and of a greater magnitude of asymmetry than other facial anatomical regions but with various individual variations. The overall facial asymmetry index and the regional facial asymmetry indices were higher in males and patients with chin deviation. CONCLUSIONS: Soft tissue asymmetry is predominately presented in the lower-third of the face in skeletal Class III patients and with various variations on other facial anatomical regions. Morphometric techniques and computer intensive analysis have allowed sophisticated quantification and visualization of the pointwise asymmetry on the full face.

Automated landmarking for palatal shape analysis using geometric deep learning.

OBJECTIVES: To develop and evaluate a geometric deep-learning network to automatically place seven palatal landmarks on digitized maxillary dental casts. SETTINGS AND SAMPLE POPULATION: The sample comprised individuals with permanent dentition of various ethnicities. The network was trained from manual landmark annotations on 732 dental casts and evaluated on 104 dental casts. MATERIALS AND METHODS: A geometric deep-learning network was developed to hierarchically learn features from point-clouds representing the 3D surface of each cast. These features predict the locations of seven palatal landmarks. RESULTS: Repeat-measurement reliability was <0.3 mm for all landmarks on all casts. Accuracy is promising. The proportion of test subjects with errors less than 2 mm was between 0.93 and 0.68, depending on the landmark. Unusually shaped and large palates generate the highest errors. There was no evidence for a difference in mean palatal shape estimated from manual compared to the automatic landmarking. The automatic landmarking reduces sample variation around the mean and reduces measurements of palatal size. CONCLUSIONS: The automatic landmarking method shows excellent repeatability and promising accuracy, which can streamline patient assessment and research studies. However, landmark indications should be subject to visual quality control.

Exploring palatal and dental shape variation with 3D shape analysis and geometric deep learning.

OBJECTIVES: Palatal shape contains a lot of information that is of clinical interest. Moreover, palatal shape analysis can be used to guide or evaluate orthodontic treatments. A statistical shape model (SSM) is a tool that, by means of dimensionality reduction, aims at compactly modeling the variance of complex shapes for efficient analysis. In this report, we evaluate several competing approaches to constructing SSMs for the human palate. SETTING AND SAMPLE POPULATION: This study used a sample comprising digitized 3D maxillary dental casts from 1,324 individuals. MATERIALS AND METHODS: Principal component analysis (PCA) and autoencoders (AE) are popular approaches to construct SSMs. PCA is a dimension reduction technique that provides a compact description of shapes by uncorrelated variables. AEs are situated in the field of deep learning and provide a non-linear framework for dimension reduction. This work introduces the singular autoencoder (SAE), a hybrid approach that combines the most important properties of PCA and AEs. We assess the performance of the SAE using standard evaluation tools for SSMs, including accuracy, generalization, and specificity. RESULTS: We found that the SAE obtains equivalent results to PCA and AEs for all evaluation metrics. SAE scores were found to be uncorrelated and provided an optimally compact representation of the shapes. CONCLUSION: We conclude that the SAE is a promising tool for 3D palatal shape analysis, which effectively combines the power of PCA with the flexibility of deep learning. This opens future AI driven applications of shape analysis in orthodontics and other related clinical disciplines.

Determination of pre-arthropathy scapular anatomy with a statistical shape model: part I-rotator cuff tear arthropathy.

HYPOTHESIS AND BACKGROUND: Rotator cuff tear arthropathy (RCTA) is a pathology characterized by a massive rotator cuff tear combined with acromiohumeral and/or glenohumeral arthritis. The severity of RCTA can be staged according to the Hamada classification. Why RCTA develops in some patients is unknown. Furthermore, in RCTA patients, distinctly different articular damage patterns can develop on the glenoid side as categorized by the Sirveaux classification (glenoid erosion). The goal of this study was to determine whether an association exists between scapular anatomy and RCTA and different severity stages of RCTA, as well as the associated glenoid erosion types. METHODS: A statistical shape model of the scapula was constructed from a data set of 110 computed tomography scans using principal component analysis. Sixty-six patients with degenerative rotator cuff pathology formed the control group. The computed tomography scan images of 89 patients with RCTA were included and grouped according to the Hamada and Sirveaux classifications. A complete 3-dimensional scapular bone model was created, and statistical shape model reconstruction was performed. Next, automated 3-dimensional measurements of glenoid version and inclination, scapular offset, the critical shoulder angle (CSA), the posterior acromial slope (PAS), and the lateral acromial angle (LAA) were performed. All measurements were then compared between controls and RCTA patients. RESULTS: The control group had a median of 7° of retroversion (variance, 16°), 8° of superior inclination (variance, 19°), and 106 mm of scapular offset (variance, 58 mm). The median CSA, PAS, and LAA were 30° (variance, 14°), 65° (variance, 60°), and 90° (variance, 17°), respectively. In terms of inclination, version, scapular offset, and the PAS, we found no statistically significant differences between the RCTA and control groups. For RCTA patients, the median CSA and median LAA were 32° (P ≤ .01) and 86° (P ≤ .01), respectively. For all investigated parameters, we did not find any significant difference between the different stages of RCTA. Patients with type E3 erosion had a different pre-arthropathy anatomy with increased retroversion (12°, P = .006), an increased CSA (40°, P ≤ .001), and a reduced LAA (79°, P ≤ .001). DISCUSSION: Our results seem to indicate that a 4° more inferiorly tilted and 2° more laterally extended acromion is associated with RCTA. RCTA patients in whom type E3 erosion develops have a distinct pre-arthropathy scapular anatomy with a more laterally extended and more inferiorly tilted acromion and a more retroverted glenoid in comparison with RCTA patients with no erosion. The pre-arthropathy scapular anatomy does not seem to differ between patients with different stages of RCTA.

3D assessment of mandibular skeletal effects produced by the Herbst appliance.

BACKGROUND: A functional appliance is commonly used to optimize the development of the facial skeleton in the treatment of Class II malocclusion. Recent three-dimensional(3D) image-based analysis offers numerous advantages in quantitative measurement and visualization in orthodontics. The aim of this study was to localize in 3D the skeletal effect produced by the Herbst appliance on the mandible using the geometric morphometric technique. METHODS: Twenty patients treated with a Herbst appliance and subsequent fixed appliances were included. Cone-beam computed tomography (CBCT) images were taken before treatment (T1), 8 weeks after Herbst appliance removal (T2), and after subsequent fixed appliance treatment (T3). Spatially dense morphometric techniques were used to establish the corresponding points of the mandible. The mandibular morphological changes from T1-T2, T2-T3, and T1-T3 were calculated for each patient by superimposing two mandibular models at two time points with robust Procrustes superimposition. These changes were then compared to the morphological changes estimated from normative mandibular growth curves over the same period. The proportion of cases exceeding the growth expression for controls was compared to a normal population using a one tailed binomial test. RESULTS: Approximately 1.5-2 mm greater condylar changes and 0.5 mm greater changes in the chin occurred from Tl to T2. This effect lasted until the completion of treatment (T1-T3), but there was no obvious skeletal effect during the orthodontic phase (T2-T3). Approximately 40-50% of the patient sample exceeded condylar growth by > 1.5 mm compared to untreated controls (p < .05). However, changes at the chin were not statistically significant. CONCLUSIONS: The principal skeletal effect of Herbst appliance treatment was additional increase in condylar length for about half of the sample. This inconsistency may relate to the degree of mandibular growth suppression associated with a specific malocclusion.

Quantification of mandibular sexual dimorphism during adolescence.

The present study investigates how sexual dimorphism in the human mandible develops in three-dimensionally during adolescence. A cross-sectional sample of mandibular meshes of 268 males and 386 females, aged between 8.5 and 19.5 years of age, were derived from cone beam computed tomography and were analysed using geometric morphometric methods. Growth trajectories of the mandible in males and females were modelled separately using a recently developed non-linear kernel regression framework. Growth rate and direction at a dense array of points all over the mandibular surface were visualized within each group and compared between groups. We found that mandibular sexual dimorphism already exists at 9 years of age, but this is mostly in size not in shape. The differential growth rate and duration between the sexes during pubertal growth largely explained by adult sexual dimorphism: the growth direction in both males and females is similar but the male mandible changed more quickly and over a longer period than the female mandible, where the growth rate peaked and declined earlier. This results in increasing dimorphism in form, which is evident in both size and shape. The development of dimorphic features, concentrated in the chin and ramus, were further visualized. The dense morphometric approach provides detailed three-dimensional quantitative assessment of the development of sexual dimorphism of the mandible.

Spatially dense morphometrics of craniofacial sexual dimorphism in 1-year-olds.

Recent advances in the field of geometric morphometrics allow for powerful statistical hypothesis testing for effects of biological and environmental variables on anatomical shape. This study used partial least-squares regression (PLSR) and the recently developed bootstrapped response-based imputation modelling (BRIM) algorithm to test for sexual dimorphism in the craniofacial shape of 1-year-old humans. We observed a recession of the forehead in boys relative to girls, and differences in the nose, consistent with adult dimorphism. Results also suggest that the degree to which individuals express dimorphic traits is continuous throughout the population. This is also seen in adult dimorphism but in 1-year-olds the amount of overlap between groups is much higher, indicating the strength of dimorphism between sexes is lower. Our results demonstrate early sexual dimorphism that is not attributable to the influx of sex hormones at puberty. This highlights the need to look at very early ontogeny for the origins of sexual dimorphism. We suggest that future work look at potential mediating effects of this early dimorphism on the later impact of puberty. The subtle shape differences we have detected, may also be applied to sexing fossilised crania. A common artefact in 3D images of faces of young children is that they often have their mouths open to varying degrees, introducing variability in the data unrelated to anatomy. We describe two PLSR-based methods of correcting this. These methods may facilitate surgical planning and assessment of young children based on 3D images.

Automated 3D Landmarking of the Skull: A Novel Approach for Craniofacial Analysis.

Automatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising 9,999 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (>0.988), and automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.

A novel approach to craniofacial analysis using automated 3D landmarking of the skull.

Automatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising of 6707 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5 mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (> 0.988), with automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.

Ulnar shape of extant primates: Functional signals and covariation with triquetrum shape.

OBJECTIVES: In this study, we investigated the shape differences of the distal ulna in a phylogenetic context among a broad range of primate taxa. Furthermore, we evaluated covariation between ulnar and triquetrum shape and a possible association between ulnar shape and locomotor behavior. MATERIALS AND METHODS: We applied 3D geometric morphometrics on a large dataset comprising the distal ulna of 124 anthropoid primate specimens belonging to 12 different genera. For each species, a mean shape was calculated using 11 Procrustes-aligned surface landmarks on the distal ulna. These mean shapes are used in a bgPCA, pPCA, and PACA and 3D morphs were used to visualize more subtle differences between taxa. A p2B-PLS analysis was performed to test the covariance between distal ulnar and triquetrum shape. RESULTS: The results show that more closely related species exhibit a similar distal ulnar shape. Overall, extant hominid ulnae show a shape shift compared to those of extant monkeys and hylobatids. This includes a shortening of the ulnar styloid process and dorspalmarly widening of the ulnar head, shape characteristics that are independent of phylogeny. Within the hominids, Pongo pygmaeus seem to possess the most plesiomorphic distal ulnar shape, while Gorilla and Homo sapiens display the most derived distal ulna. Cercopithecoids, hylobatids, and P. pygmaeus are characterized by a relatively deep ECU groove, which is a shape trait dependent of phylogeny. Although there was no significant covariation between distal ulnar shape and triquetrum shape, the shape differences of the distal ulna between the different primate taxa reveal a possible link with locomotor behavior. CONCLUSIONS: The comparative analyses of this study reveal different shape trends in a phylogenetic context. Highly arboreal primates, such as hylobatids and Ateles fusciceps, show a distal ulnar morphology that appears to be adapted to tensile and torsional forces. In primates that use their wrist under more compressive conditions, such as quadrupedal cercopithecoids and great apes, the distal ulnar morphology seems to reflect increased compressive forces. In modern humans, the distal ulnar shape can be associated to enhanced manipulative skills and power grips. There was no significant covariation between distal ulnar shape and triquetrum shape, probably due to the variation in the amount of contact between the triquetrum and ulna. In combination with future research on wrist mobility in diverse primate taxa, the results of this study will allow us to establish form-function relationships of the primate wrist and contribute towards an evidence-based interpretation of fossil remains.

Mapping genes for human face shape: exploration of univariate phenotyping strategies.

Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author Summary: Advancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.