Achondroplasia: Orocraniofacial Features and Orthodontic-Surgical Management Guidelines Proposal

Cephalometric Evaluation of Children with Short Stature of Genetic Etiology: A Review

Introduction: A plethora of biological molecules regulate chondrogenesis in the epiphyseal growth plate. Disruptions of the quantity and function of these molecules can manifest clinically as stature abnormalities of various etiologies. Traditionally, the growth hormone/insulin-like growth factor 1 (IGF1) axis represents the etiological centre of final stature attainment. Of note, little is known about the molecular events that dominate the growth of the craniofacial complex and its correlation with somatic stature. Aim: Given the paucity of relevant data, this review discusses available information regarding potential applications of lateral cephalometric radiography as a potential clinical indicator of genetic short stature in children. Materials and Methods: A literature search was conducted in the PubMed electronic database using the keywords: cephalometric analysis and short stature; cephalometric analysis and achondroplasia; cephalometric analysis and hypochondroplasia; cephalometric analysis and skeletal abnormalities; cephalometr* and SHOX; cephalometr* and CNP; cephalometr* and ACAN; cephalometr* and CNVs; cephalometr* and IHH; cephalometr* and FGFR3; cephalometr* and Noonan syndrome; cephalometr* and "Turner syndrome"; cephalometr* and achondroplasia. Results: In individuals with genetic syndromes causing short stature, linear growth of the craniofacial complex is confined, following the pattern of somatic short stature regardless of its aetiology. The angular and linear cephalometric measurements differ from the measurements of the average normal individuals and are suggestive of a posterior placement of the jaws and a vertical growth pattern of the face. Conclusions: The greater part of the existing literature regarding cephalometric measurements in short-statured children with genetic syndromes provides qualitative data. Furthermore, cephalometric data for individuals affected with specific rare genetic conditions causing short stature should be the focus of future studies. These quantitative data are required to potentially establish cut-off values for reference for genetic testing based on craniofacial phenotypes.

Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database

AIM

To build a facial image database and to explore the diagnostic efficacy and influencing factors of the artificial intelligence-based facial recognition (AI-FR) system for multiple endocrine and metabolic syndromes.

METHODS

Individuals with multiple endocrine and metabolic syndromes and healthy controls were included from public literature and databases. In this facial image database, facial images and clinical data were collected for each participant and dFRI (disease facial recognition intensity) was calculated to quantify facial complexity of each syndrome. AI-FR diagnosis models were trained for each disease using three algorithms: support vector machine (SVM), principal component analysis k-nearest neighbor (PCA-KNN), and adaptive boosting (AdaBoost). Diagnostic performance was evaluated. Optimal efficacy was achieved as the best index among the three models. Effect factors of AI-FR diagnosis were explored with regression analysis.

RESULTS

462 cases of 10 endocrine and metabolic syndromes and 2310 controls were included into the facial image database. The AI-FR diagnostic models showed diagnostic accuracies of 0.827-0.920 with SVM, 0.766-0.890 with PCA-KNN, and 0.818-0.935 with AdaBoost. Higher dFRI was associated with higher optimal area under the curve (AUC) (P = 0.035). No significant correlation was observed between the sample size of the training set and diagnostic performance.

CONCLUSIONS

A multi-ethnic, multi-regional, and multi-disease facial database for 10 endocrine and metabolic syndromes was built. AI-FR models displayed ideal diagnostic performance. dFRI proved associated with the diagnostic performance, suggesting inherent facial features might contribute to the performance of AI-FR models.

What to Expect of Feeding Abilities and Nutritional Aspects in Achondroplasia Patients: A Narrative Review

Achondroplasia is an autosomal dominant genetic disease representing the most common form of human skeletal dysplasia: almost all individuals with achondroplasia have identifiable mutations in the fibroblast growth factor receptor type 3 (FGFR3) gene. The cardinal features of this condition and its inheritance have been well-established, but the occurrence of feeding and nutritional complications has received little prominence. In infancy, the presence of floppiness and neurological injury due to foramen magnum stenosis may impair the feeding function of a newborn with achondroplasia. Along with growth, the optimal development of feeding skills may be affected by variable interactions between midface hypoplasia, sleep apnea disturbance, and structural anomalies. Anterior open bite, prognathic mandible, retrognathic maxilla, and relative macroglossia may adversely impact masticatory and respiratory functions. Independence during mealtimes in achondroplasia is usually achieved later than peers. Early supervision of nutritional intake should proceed into adolescence and adulthood because of the increased risk of obesity and respiratory problems and their resulting sequelae. Due to the multisystem involvement, oral motor dysfunction, nutrition, and gastrointestinal issues require special attention and personalized management to facilitate optimal outcomes, especially because of the novel therapeutic options in achondroplasia, which could alter the progression of this rare disease.

Best practice guidelines in managing the craniofacial aspects of skeletal dysplasia

Background

Recognition and appropriate management of the craniofacial manifestations of patients with skeletal dysplasia are challenging, due to the rarity of these conditions, and dearth of literature to support evidence-based clinical decision making.

Methods

Using the Delphi method, an international, multi-disciplinary group of individuals, with significant experience in the care of patients with skeletal dysplasia, convened to develop multi-disciplinary, best practice guidelines in the management of craniofacial aspects of these patients.

Results

After a comprehensive literature review, 23 initial statements were generated and critically discussed, with subsequent development of a list of 22 best practice guidelines after a second round voting.

Conclusions

The guidelines are presented and discussed to provide context and assistance for clinicians in their decision making in this important and challenging component of care for patients with skeletal dysplasia, in order standardize care and improve outcomes.