DNA-guided transcription factor cooperativity shapes face and limb mesenchyme.

Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest that it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how "Coordinator," a long DNA motif composed of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines the regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, whereas HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in the shared regulation of genes involved in cell-type and positional identities and ultimately shapes facial morphology and evolution.

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.

Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping.

Unsupervised learning, particularly clustering, plays a pivotal role in disease subtyping and patient stratification, especially with the abundance of large-scale multi-omics data. Deep learning models, such as variational autoencoders (VAEs), can enhance clustering algorithms by leveraging inter-individual heterogeneity. However, the impact of confounders-external factors unrelated to the condition, e.g. batch effect or age-on clustering is often overlooked, introducing bias and spurious biological conclusions. In this work, we introduce four novel VAE-based deconfounding frameworks tailored for clustering multi-omics data. These frameworks effectively mitigate confounding effects while preserving genuine biological patterns. The deconfounding strategies employed include (i) removal of latent features correlated with confounders, (ii) a conditional VAE, (iii) adversarial training, and (iv) adding a regularization term to the loss function. Using real-life multi-omics data from The Cancer Genome Atlas, we simulated various confounding effects (linear, nonlinear, categorical, mixed) and assessed model performance across 50 repetitions based on reconstruction error, clustering stability, and deconfounding efficacy. Our results demonstrate that our novel models, particularly the conditional multi-omics VAE (cXVAE), successfully handle simulated confounding effects and recover biologically driven clustering structures. cXVAE accurately identifies patient labels and unveils meaningful pathological associations among cancer types, validating deconfounded representations. Furthermore, our study suggests that some of the proposed strategies, such as adversarial training, prove insufficient in confounder removal. In summary, our study contributes by proposing innovative frameworks for simultaneous multi-omics data integration, dimensionality reduction, and deconfounding in clustering. Benchmarking on open-access data offers guidance to end-users, facilitating meaningful patient stratification for optimized precision medicine.

Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morphology.

Variations in the form of the human face, which plays a role in our individual identities and societal interactions, have fascinated scientists and artists alike. Here, we review our current understanding of the genetics underlying variation in craniofacial morphology and disease-associated dysmorphology, synthesizing decades of progress on Mendelian syndromes in addition to more recent results from genome-wide association studies of human facial shape and disease risk. We also discuss the various approaches used to phenotype and quantify facial shape, which are of particular importance due to the complex, multipartite nature of the craniofacial form. We close by discussing how experimental studies have contributed and will further contribute to our understanding of human genetic variation and then proposing future directions and applications for the field.

TWIST1 interacts with ß/δ-catenins during neural tube development and regulates fate transition in cranial neural crest cells.

Cell fate determination is a necessary and tightly regulated process for producing different cell types and structures during development. Cranial neural crest cells (CNCCs) are unique to vertebrate embryos and emerge from the neural plate borders into multiple cell lineages that differentiate into bone, cartilage, neurons and glial cells. We have previously reported that Irf6 genetically interacts with Twist1 during CNCC-derived tissue formation. Here, we have investigated the mechanistic role of Twist1 and Irf6 at early stages of craniofacial development. Our data indicate that TWIST1 is expressed in endocytic vesicles at the apical surface and interacts with ß/δ-catenins during neural tube closure, and Irf6 is involved in defining neural fold borders by restricting AP2α expression. Twist1 suppresses Irf6 and other epithelial genes in CNCCs during the epithelial-to-mesenchymal transition (EMT) process and cell migration. Conversely, a loss of Twist1 leads to a sustained expression of epithelial and cell adhesion markers in migratory CNCCs. Disruption of TWIST1 phosphorylation in vivo leads to epidermal blebbing, edema, neural tube defects and CNCC-derived structural abnormalities. Altogether, this study describes a previously uncharacterized function of mammalian Twist1 and Irf6 in the neural tube and CNCCs, and provides new target genes for Twist1 that are involved in cytoskeletal remodeling.

Toward 3D facial analysis for recognizing Mendelian causes of autism spectrum disorder.

Recognizing Mendelian causes is crucial in molecular diagnostics and counseling for patients with autism spectrum disorder (ASD). We explored facial dysmorphism and facial asymmetry in relation to genetic causes in ASD patients and studied the potential of objective facial phenotyping in discriminating between Mendelian and multifactorial ASD. In a cohort of 152 ASD patients, 3D facial images were used to calculate three metrics: a computational dysmorphism score, a computational asymmetry score, and an expert dysmorphism score. High scores for each of the three metrics were associated with Mendelian causes of ASD. The computational dysmorphism score showed a significant correlation with the average expert dysmorphism score. However, in some patients, different dysmorphism aspects were captured making the metrics potentially complementary. The computational dysmorphism and asymmetry scores both enhanced the individual expert dysmorphism scores in differentiating Mendelian from non-Mendelian cases. Furthermore, the computational asymmetry score enhanced the average expert opinion in predicting a Mendelian cause. By design, our study does not allow to draw conclusions on the actual point-of-care use of 3D facial analysis. Nevertheless, 3D morphometric analysis is promising for developing clinical dysmorphology applications in diagnostics and training.

Artificial intelligence and dental age estimation: development and validation of an automated stage allocation technique on all mandibular tooth types in panoramic radiographs.

Age estimation in forensic odontology is mainly based on the development of permanent teeth. To register the developmental status of an examined tooth, staging techniques were developed. However, due to inappropriate calibration, uncertainties during stage allocation, and lack of experience, non-uniformity in stage allocation exists between expert observers. As a consequence, related age estimation results are inconsistent. An automated staging technique applicable to all tooth types can overcome this drawback.This study aimed to establish an integrated automated technique to stage the development of all mandibular tooth types and to compare their staging performances.Calibrated observers staged FDI teeth 31, 33, 34, 37 and 38 according to a ten-stage modified Demirjian staging technique. According to a standardised bounding box around each examined tooth, the retrospectively collected panoramic radiographs were cropped using Photoshop CC 2021® software (Adobe®, version 23.0). A gold standard set of 1639 radiographs were selected (n31 = 259, n33 = 282, n34 = 308, n37 = 390, n38 = 400) and input into a convolutional neural network (CNN) trained for optimal staging accuracy. The performance evaluation of the network was conducted in a five-fold cross-validation scheme. In each fold, the entire dataset was split into a training and a test set in a non-overlapping fashion between the folds (i.e., 80% and 20% of the dataset, respectively). Staging performances were calculated per tooth type and overall (accuracy, mean absolute difference, linearly weighted Cohen's Kappa and intra-class correlation coefficient). Overall, these metrics equalled 0.53, 0.71, 0.71, and 0.89, respectively. All staging performance indices were best for 37 and worst for 31. The highest number of misclassified stages were associated to adjacent stages. Most misclassifications were observed in all available stages of 31.Our findings suggest that the developmental status of mandibular molars can be taken into account in an automated approach for age estimation, while taking incisors into account may hinder age estimation.

3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies.

The analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.

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.

Facial masculinity does not appear to be a condition-dependent male ornament and does not reflect MHC heterozygosity in humans.

Recent studies have called into question the idea that facial masculinity is a condition-dependent male ornament that indicates immunocompetence in humans. We add to this growing body of research by calculating an objective measure of facial masculinity/femininity using 3D images in a large sample (n = 1,233) of people of European ancestry. We show that facial masculinity is positively correlated with adult height in both males and females. However, facial masculinity scales with growth similarly in males and females, suggesting that facial masculinity is not exclusively a male ornament, as male ornaments are typically more sensitive to growth in males compared with females. Additionally, we measured immunocompetence via heterozygosity at the major histocompatibility complex (MHC), a widely-used genetic marker of immunity. We show that, while height is positively correlated with MHC heterozygosity, facial masculinity is not. Thus, facial masculinity does not reflect immunocompetence measured by MHC heterozygosity in humans. Overall, we find no support for the idea that facial masculinity is a condition-dependent male ornament that has evolved to indicate immunocompetence.

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.

Population genomics of Mesolithic Scandinavia: Investigating early postglacial migration routes and high-latitude adaptation.

Scandinavia was one of the last geographic areas in Europe to become habitable for humans after the Last Glacial Maximum (LGM). However, the routes and genetic composition of these postglacial migrants remain unclear. We sequenced the genomes, up to 57× coverage, of seven hunter-gatherers excavated across Scandinavia and dated from 9,500-6,000 years before present (BP). Surprisingly, among the Scandinavian Mesolithic individuals, the genetic data display an east-west genetic gradient that opposes the pattern seen in other parts of Mesolithic Europe. Our results suggest two different early postglacial migrations into Scandinavia: initially from the south, and later, from the northeast. The latter followed the ice-free Norwegian north Atlantic coast, along which novel and advanced pressure-blade stone-tool techniques may have spread. These two groups met and mixed in Scandinavia, creating a genetically diverse population, which shows patterns of genetic adaptation to high latitude environments. These potential adaptations include high frequencies of low pigmentation variants and a gene region associated with physical performance, which shows strong continuity into modern-day northern Europeans.

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.