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Midpalatal Suture Maturation Method for the Assessment of Maturation before Maxillary Expansion: A Systematic Review.

Anis ShayaniHéctor Paulo Sandoval-VidalIvonne Garay CarrascoMarco Merino Gerlach
Published in: Diagnostics (Basel, Switzerland) (2022)
Assessment of midpalatal suture maturation is crucial before deciding which type of maxillary expansion technique will be performed to treat transverse discrepancies. In 2013, Angelieri et al. proposed a new method to evaluate midpalatal maturation using cone-beam computed tomography. The aim of this study was to systematically identify, evaluate, and provide a synthesis of the existing literature about this new method and to rigorously assess the methodological quality of these articles. A bibliographic search was carried out using PubMed, Cochrane Library, SciELO, LILACS, Web of Science, and Scopus using the terms midpalatal suture, cranial sutures, palate, maturation, interdigitation, ossification, maxillary expansion, evaluation, assessment, and assess. Quality assessment was performed using the Observational Cohort and Cross-Sectional Studies tool developed by the National Heart, Lung, and Blood Institute. Hence, 56 articles were obtained, of which only 10 met the selection criteria. We could not include any of the data into an analysis because of the large variation of the data collected and high methodological heterogeneity found among studies. Of all the studies included, 10% had poor quality, 70% fair, and 20% good quality, respectively. Even though age and sex play a role in midpalatal suture obliteration, there is a poor correlation between these variables. Thus, every patient should be assessed individually before choosing the best protocol for maxillary expansion. The midpalatal suture maturation method has the potential to be used for diagnostic purposes, but clinicians should be cautious of routinely using it because an extensive training and calibration program should be performed prior.
Keyphrases
  • cone beam computed tomography
  • quality improvement
  • cross sectional
  • systematic review
  • case control
  • big data
  • machine learning
  • single cell
  • case report
  • artificial intelligence