An open-source, three-dimensional growth model of the mandible.

The available reference data for the mandible and mandibular growth consists primarily of two-dimensional linear or angular measurements. The aim of this study was to create the first open-source, three-dimensional statistical shape model of the mandible that spans the complete growth period. Computed tomography scans of 678 mandibles from children and young adults between 0 and 22 years old were included in the model. The mandibles were segmented using a semi-automatic or automatic (artificial intelligence-based) segmentation method. Point correspondence among the samples was achieved by rigid registration, followed by non-rigid registration of a symmetrical template onto each sample. The registration process was validated with adequate results. Principal component analysis was used to gain insight in the variation within the dataset and to investigate age-related changes and sexual dimorphism. The presented growth model is accessible globally and free-of-charge for scientists, physicians and forensic investigators for any kind of purpose deemed suitable. The versatility of the model opens up new possibilities in the fields of oral and maxillofacial surgery, forensic sciences or biological anthropology. In clinical settings, the model may aid diagnostic decision-making, treatment planning and treatment evaluation.

Development and external validation of prediction models for critical outcomes of unvaccinated COVID-19 patients based on demographics, medical conditions and dental status.

Background: Multiple prediction models were developed for critical outcomes of COVID-19. However, prediction models using predictors which can be easily obtained in clinical practice and on dental status are scarce. Aim: The study aimed to develop and externally validate prediction models for critical outcomes of COVID-19 for unvaccinated adult patients in hospital settings based on demographics, medical conditions, and dental status. Methods: A total of 285 and 352 patients from two hospitals in the Netherlands were retrospectively included as derivation and validation cohorts. Demographics, medical conditions, and dental status were considered potential predictors. The critical outcomes (death and ICU admission) were considered endpoints. Logistic regression analyses were used to develop two models: for death alone and for critical outcomes. The performance and clinical values of the models were determined in both cohorts. Results: Age, number of teeth, chronic kidney disease, hypertension, diabetes, and chronic obstructive pulmonary diseases were the significant independent predictors. The models showed good to excellent calibration with observed: expected (O:E) ratios of 0.98 (95%CI: 0.76 to 1.25) and 1.00 (95%CI: 0.80 to 1.24), and discrimination with shrunken area under the curve (AUC) values of 0.85 and 0.79, based on the derivation cohort. In the validation cohort, the models showed good to excellent discrimination with AUC values of 0.85 (95%CI: 0.80 to 0.90) and 0.78 (95%CI: 0.73 to 0.83), but an overestimation in calibration with O:E ratios of 0.65 (95%CI: 0.49 to 0.85) and 0.67 (95%CI: 0.52 to 0.84). Conclusion: The performance of the models was acceptable in both derivation and validation cohorts. Number of teeth was an additive important predictor of critical outcomes of COVID-19. It is an easy-to-apply tool in hospitals for risk stratification of COVID-19 prognosis.

Normal variation of mandibular asymmetry in children.

OBJECTIVE: To explore the normal variation of asymmetry in mandibles of children in the age group of 1 to 12 years. MATERIALS AND METHODS: The study group consisted of 92 cadaveric mandibles of children with a dental age of 1 to 12 years old in possession of ACTA (Academic Centre for Dentistry Amsterdam), Faculty of Dentistry, the Netherlands. 3D models of the mandibles were obtained from CT-scans and hemimandibular volumes of all mandibles were calculated. The condylar height, ramus height, mandibular body length and the gonial angle were bilaterally determined using a novel landmark-based method, and the degree of asymmetry was calculated. RESULTS: No relationship was found between dental age and asymmetry of the studied parameters (P < .05). The highest degree of asymmetry was found in the ramus height, whereas the gonial angle presented the lowest degree of asymmetry. A positive correlation was found between the asymmetry of the hemimandibular volume vs the height of the ramus (P < .05) and the length of the mandibular body (P < .05). An inverse correlation was found between the asymmetry of the ramus height vs the condylar height (P < .05), mandibular body length (P < .05) and gonial angle (P < .05). CONCLUSIONS: Mandibular asymmetries in children did occur (9.8% of the included mandibles presented with a relevant overall asymmetry of ≥3%) and were unrelated to age. The different segments of the mandible seem to compensate for each other, in order to maintain a functional equilibrium.