Clear aligner therapy practices among orthodontists practicing in Canada.

BACKGROUND: The acceptability and preference for clear aligner therapy (CAT) has been increasing among orthodontists, but there is still a lack of consensus regarding CAT best practices. Consequently, this study aimed to investigate CAT practices among orthodontists practicing in Canada. METHODS: The survey was conducted among orthodontists practicing in Canada using a modified previously published survey. Sixty orthodontists participated (6.1% response rate). It consisted of 11 sections with open and closed questions related to demographic information and particularities about using or not using CAT. The survey responses were exported from REDCap to a Microsoft Excel (Microsoft, Redmond, Wash) spreadsheet, then statistically analyzed using SPSS software (SPSS for Windows, version 21.0; IBM Inc., Armonk, NY, USA). The comments were categorized under themes and subthemes. Data were organized in descriptive statistics, expressing frequencies and percentages. RESULTS: Almost 30% of the orthodontist's annual caseload was treated with CAT, most frequently prescribed to adult patients. Case complexity and patient cooperation were the factors that most influenced the decision to prescribe CAT. Almost half of orthodontists reported sometimes combining CAT with adjunctive fixed appliances. CONCLUSIONS: Most orthodontists prescribe CAT, and its use is based on the malocclusion's complexity. Orthodontists who do not prescribe CAT believe that fixed appliance therapy has superior treatment outcomes.

Binary decisions of artificial intelligence to classify third molar development around the legal age thresholds of 14, 16 and 18 years.

Third molar development is used for dental age estimation when all the other teeth are fully mature. In most medicolegal facilities, dental age estimation is an operator-dependent procedure. During the examination of unaccompanied and undocumented minors, this procedure may lead to binary decisions around age thresholds of legal interest, namely the ages of 14, 16 and 18 years. This study aimed to test the performance of artificial intelligence to classify individuals below and above the legal age thresholds of 14, 16 and 18 years using third molar development. The sample consisted of 11,640 panoramic radiographs (9680 used for training and 1960 used for validation) of males (n = 5400) and females (n = 6240) between 6 and 22.9 years. Computer-based image annotation was performed with V7 software (V7labs, London, UK). The region of interest was the mandibular left third molar (T38) outlined with a semi-automated contour. DenseNet121 was the Convolutional Neural Network (CNN) of choice and was used with Transfer Learning. After Receiver-operating characteristic curves, the area under the curve (AUC) was 0.87 and 0.86 to classify males and females below and above the age of 14, respectively. For the age threshold of 16, the AUC values were 0.88 (males) and 0.83 (females), while for the age of 18, AUC were 0.94 (males) and 0.83 (females). Specificity rates were always between 0.80 and 0.92. Artificial intelligence was able to classify male and females below and above the legal age thresholds of 14, 16 and 18 years with high accuracy.

Can rapid maxillary expansion affect speech sound production in growing patients? A systematic review.

Rapid maxillary expansion (RME) may change speech sound parameters due to the enlargement of oral and nasal cavities. This study aimed to systematically review the current evidence on speech changes as a side effect of RME. An electronic search was conducted in nine databases, and two of them accessed the 'grey literature'. The eligibility criteria included clinical studies assessing orthodontic patients with maxillary transverse deficiency and the relationship with speech alterations without restricting publication year or language. Only interventional studies were included. The JBI Critical Appraisal Tool assessed the risk of bias. The initial search provided 4853 studies. Seven articles (n = 200 patients) met the inclusion criteria and were analysed. The primary source of bias was the absence of a control group in four studies. RME altered speech production by changing vowel fundamental frequency and fricative phoneme formant frequency. Shimmer and jitter rates changed in one and two studies, respectively. Two studies presented deterioration during orthodontic treatment, but speech improved after appliance removal. Despite the limited evidence, RME affects speech during and after treatment.