Background: Fetal alcohol spectrum disorder (FASD) is a developmental disorder with severe negative lifetime consequences. Although knowledge about the harmfulness of alcohol consumption during pregnancy has spread, the prevalence of fetal alcohol spectrum disorder is very high. Our study aims at identifying fetal alcohol syndrome (FAS)-associated dental anomalies or habits, which need early attention. Methods: Sixty children (30 FAS; 30 controls) were examined prospectively. Swallowing pattern, oral habits, breastfeeding, speech therapy, ergotherapy, physiotherapy, exfoliation of teeth, DMFT (decayed, missing, filled teeth) index, modified DDE (developmental defects of enamel) index and otitis media were recorded. Results: Swallowing pattern, exfoliation of teeth, and otitis media were not significantly different. Significant differences could be found concerning mouthbreathing (p = 0.007), oral habits (p = 0.047), age at termination of habits (p = 0.009), speech treatment (p = 0.002), ergotherapy, physiotherapy, and breastfeeding (p ≤ 0.001). DMFT (p ≤ 0.001) and modified DDE (p = 0.001) index showed significantly higher values for children with fetal alcohol syndrome. Conclusions: Children with fetal alcohol syndrome have a higher need for early developmental promotion such as speech treatment, ergotherapy, and physiotherapy. Mouthbreathing, habits, and lack of breastfeeding may result in orthodontic treatment needs. High DMFT and modified DDE indexes hint at a higher treatment and prevention need in dentistry.

Objectives: The purpose of this systematic review was to search in literature in which severity unintended effects are caused by dental materials in magnetic resonance imaging (MRI), such as to evaluate whether these artifacts hamper the diagnosis in the head and neck region. Materials and Methods: Clinical studies showing the severity of artifacts which dental materials are capable of causing in MRI of head and neck, such as their influence on diagnostic accuracy, were included in this review. The searches were conducted in four electronic databases (PubMed/Medline, Embase, Scopus and Web of Science), and a manual search was made in the reference lists of papers screened for full-text reading. Risk of bias was assessed using “Quality Assessment Tool for Diagnostic Accuracy Studies-2” (QUADAS-2). The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used to assess the quality of evidence. Results: From 151 studies selected for full-reading, 19 were considered eligible for this review. Artifacts caused by orthodontic appliances were well-documented, and stainless steel brackets were the materials most likely to cause artifacts in MR imaging of head and neck. The literature was scarce for dental implants and restorations. Diagnoses within the oral cavity, but also those of the brain and craniofacial structures, were affected. Conclusion: Artifacts caused by orthodontic appliances may affect the diagnosis in oral cavity and craniofacial structures. Data regarding dental implants and prosthodontics restorations were inconclusive. The severity of artifacts in MRI and their influence on diagnosis is dependent on dental material features, location in the oral cavity, and magnetic resonance parameters.

The aim of this retrospective study was to analyse the treatment time and differences between the pre- and post-treatment peer assessment rating (PAR) index and aesthetic component (AC) of the index of orthodontic treatment need (IOTN) scores in children/adolescents with special health care needs (SHCNs), compared to non-special health care needs (NSHCNs) controls.

Background: Drinking alcohol during pregnancy can result in severe developmental disorders in the child. Symptoms of the fetal alcohol spectrum disorder (FASD) comprise growth deficiencies, abnormal facial phenotype and damage or dysfunction of the central nervous system. Numerous diagnostic methods for facial phenotyping in FASD exist, but diagnoses are still difficult. Our aim was to find additional and objective methods for the verification of FAS(D). Methods: Three-dimensional dental models of 60 children (30 FAS and 30 controls) were used to metrically determine maximum palatal depths at the median palatine raphe. Three-dimensional facial scans were taken, and vertical distances of the face were measured at five defined facial landmarks (FP1–FP5) for each child. Results: Mean palatal height, total facial length (FP1–FP5) as well as FP4–FP5 did not significantly differ between the FAS group and the control group. Comparing vertical facial subdivisions, however, resulted in significant differences for distances FP1 to FP2 (p = 0.042, FAS > controls), FP2 to FP3 (p < 0.001, FAS < controls), FP3 to FP4 (p < 0.001, FAS > controls) and FP3 to FP5 (p = 0.007, FAS > controls). Conclusions: Metric vertical measurements of the face can be used as additional objective criteria for FAS diagnoses. However, no significant differences were reported for palatal depth evaluation in the specific age range tested in the present study.

Introduction: The fetal alcohol spectrum disorder (FASD) is a complex and heterogeneous disorder, caused by gestational exposure to alcohol. Patients with fetal alcohol syndrome (FAS—most severe form of FASD) show abnormal facial features. The aim of our study was to use 3D- metric facial data of patients with FAS and identify machine learning methods, which could improve and objectify the diagnostic process. Material and Methods: Facial 3D scans of 30 children with FAS and 30 controls were analyzed. Skeletal, facial, dental and orthodontic parameters as collected in previous studies were used to evaluate their value for machine learning based diagnosis. Three machine learning methods, decision trees, support vector machine and k-nearest neighbors were tested with respect to their accuracy and clinical practicability. Results: All three of the above machine learning methods showed a high accuracy of 89.5%. The three predictors with the highest scores were: Midfacial length, palpebral fissure length of the right eye and nose breadth at sulcus nasi. Conclusions: With the parameters right palpebral fissure length, midfacial length and nose breadth at sulcus nasi, machine learning was an efficient method for the objective and reliable detection of patients with FAS within our patient group. Of the three tested methods, decision trees would be the most helpful and easiest to apply method for everyday clinical and private practice.