Safe zones of the maxillary alveolar bone in Down syndrome for orthodontic miniscrew placement assessed with cone-beam computed tomography.
Jacobo Limeres PosseMaría Teresa Abeleira PazosMaría Fernández CasadoMercedes Outumuro RialPedro Diz DiosMarcio Diniz-FreitasPublished in: Scientific reports (2019)
The aim of this study was to quantify the available maxillary alveolar bone in a group of individuals with Down syndrome (DS) to determine the best areas for orthodontic miniscrew placement. The study group consisted of 40 patients with DS aged 12-30 years. We also selected an age and sex-matched control group. All measurements were performed on cross-sectional images obtained with cone-beam computed tomography. The selected areas of interest were the 4 interradicular spaces between the distal wall of the canine and the mesial wall of the second molar, in both maxillary quadrants. We measured the vestibular-palatine (VP) and mesiodistal (MD) dimensions to depths of 3, 6 and 9 mm from the alveolar ridge. We also measured the bone density in the same interradicular spaces of interest to 6 mm of depth from the alveolar crest. VP measurements were longer in the more posterior sectors and as the distance from the alveolar ridge increased. MD measurements also increased progressively as the distance from the alveolar ridge increased. In general, both the VP and MD measurements in the DS group were similar among the male and female participants. As age increased, the MD distance increased, while the VP distance decreased. The VP distance was ≥6 mm in at least 75% of the DS group in practically all assessed interdental spaces. The MD distance was ≥2 mm in at least 75% of the DS group only between the first and second molar, to 9 mm of depth from the alveolar ridge. The safe area for inserting orthodontic miniscrews in DS patients is restricted to the most posterior and deepest area of the maxillary alveolar bone.
Keyphrases
- cone beam computed tomography
- bone mineral density
- molecular dynamics
- cross sectional
- end stage renal disease
- optical coherence tomography
- bone loss
- soft tissue
- ejection fraction
- newly diagnosed
- chronic kidney disease
- disease virus
- bone regeneration
- convolutional neural network
- postmenopausal women
- deep learning
- machine learning
- ultrasound guided
- patient reported outcomes
- hearing loss