Background: Superimposition of three-dimensional (3D) digital models offers great opportunities to assess tooth movement during time. In the literature, several superimposition techniques are described.
Objectives: To summarize and critically assess the available evidence from studies on serial digital 3D dental model superimposition.
Search methods: MEDLINE via Ovid and PubMed, EMBASE via Ovid, Cochrane Register of Diagnostic Test Accuracy Studies, and Google Scholar were searched with no time limit (last update: December 2018). Hand and unpublished literature searches were also performed.
Selection criteria: Studies of any design that had a sample size ≥5 and tested superimposition of serial 3D digital dental models to assess tooth movement were included.
Data collection and analysis: Study selection, data extraction, and risk of bias assessment were performed independently by the authors.
Results: Twelve studies met the eligibility criteria. The total risk of bias (QUADAS-2 tool) of 10 studies was high, whereas only 2 studies had unclear bias. Ten studies had high and two studies low overall applicability concerns. From these, one study tested the mandibular alveolar bone area, three studies the rugae area, nine studies a larger palatal area, and two studies the incisive papilla area. The high heterogeneity in samples, outcomes, and methods did not allow for synthesis of a considerable amount of studies in any case.
Limitations: The high heterogeneity among studies and the limited evidence did not allow for solid conclusions.
Conclusions and implications: The following areas of the maxilla could provide reliable outcomes: (1) the medial two-thirds of the third rugae and the area 5 mm dorsal to them and (2) an area including all rugae, with the lateral margins located at least 5 mm from the gingival margins and a distal margin that does not extend beyond the first molars. No recommendation is possible for other regions of the mouth. There is an urgent need for further research in the field.
Registration: PROSPERO (CRD42019124365).
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