Summary: Background: Superimposition of serial cephalometric radiographs enables the assessment of craniofacial changes over time, and therefore, several methods have been suggested in the literature. Objective: The aim of the present study is to summarize and critically evaluate the available evidence on the reliability of methods used to superimpose serial cephalometric radiographs. Search methods: Electronic searches were performed in MEDLINE, EMBASE, Google Scholar, and Cochrane Databases, without time limit (last update: 1 November 2020). Unpublished literature was searched on the Open Grey and Grey Literature Report databases. Selection criteria: Studies that tested the accuracy, precision, or agreement between different cephalometric superimposition techniques, used to evaluate the craniofacial changes due treatment or growth. Data collection and analysis: Reference lists of relevant articles were screened and authors were contacted, if needed. All study selection steps, data extraction, and risk of bias (QUADAS-2 tool) assessments were performed independently by two authors on predefined forms. Results: There were 27 eligible studies. From these, 17 tested superimpositions methods on the anterior cranial base, 10 on the maxilla and 12 on the mandible. There were three studies that compared superimpositions on the cranial base with those on the maxilla and one that compared the cranial base with the mandibular superimposition. There was high heterogeneity among studies in terms of sample size, growth, radiographic machines, selection criteria, superimposition methods, references, and outcomes measured. Furthermore, almost all studies presented important methodological limitations, with only two studies having unclear risk of bias and the rest 25 presenting high risk. Conclusions: Currently, there is no cephalometric superimposition method that has been proved to deliver accurate results. There is an urgent need for further research in this topic, since this is a primary assessment method to assess craniofacial changes over time for several relevant disciplines. Registration: PROSPERO (CRD42020200349).

Objectives: To develop and validate a method for accurate quantitative assessment of gingival recessions based on superimposition of serial 3D digital models. Materials and methods: Gingival recessions of mild (0.5–2 mm) and increased (3–7 mm) severity were simulated on stone casts and surface models were created. The outlines of the gingival margins of the mild (A) and severe recessions (B) were compared to the original gingival margins following 3D best fit superimposition through a gold standard technique (GS), which used intact adjacent structures, and the tested method (CC), which used single tooth crowns at the position of recessions, as superimposition reference. The primary outcome was the distance between the most apical point of each corresponding gingival margin along the respective tooth long axis. Results: For mild recessions, the median difference of the test methods (CC_A) from the reference method (GS_A) was 0.008 mm (IQR: 0.093; range: − 0.143, 0.147). For severe recessions, the median difference of the test method (CC_B) from the reference method (GS_B) was 0.009 mm (IQR: 0.091; range: − 0.170, 0.198). The proposed method (CC) showed very high intra- and inter-operator reproducibility (median: 0.025 and 0.033 mm, respectively). Conclusions: The suggested method offers highly accurate monitoring of gingival margin changes and diagnosis of gingival recessions using 3D digital dental models. The method is applicable irrespective of changes in tooth position or form, allowing for assessments over any time span. Clinical relevance: The accurate detection and visualization of gingival margin changes in 3D will enhance diagnosis and patient-doctor communication.

Early diagnosis and timely management of tooth or dental material wear is imperative to avoid extensive restorations. Previous studies suggested different methods for tooth wear assessment, but no study has developed a three-dimensional (3D) superimposition technique applicable in cases where tooth surfaces, other than the occlusal, undergo extensive morphological changes. Here, we manually grinded plaster incisors and canines to simulate occlusal tooth wear of varying severity in teeth that received a wire retainer bonded on their lingual surfaces, during the assessment period. The corresponding dental casts were scanned using a surface scanner. The modified tooth crowns were best-fit approximated to the original crowns using seven 3D superimposition techniques (two reference areas with varying settings) and the gold standard technique (GS: intact adjacent teeth and alveolar processes as superimposition reference), which provided the true value. Only a specific technique (complete crown with 20% estimated overlap of meshes), which is applicable in actual clinical data, showed perfect agreement with the GS technique in all cases (median difference: −0.002, max absolute difference: 0.178 mm³). The outcomes of the suggested and the GS technique were highly reproducible (max difference < 0.040 mm³). The presented technique offers low cost, convenient, accurate, and risk-free tooth wear assessment.

Three-dimensional surface scans of skeletal structures have various clinical and research applications in medicine, anthropology, and other relevant fields. The aim of this study was to test the precision of a widely used hand-held surface scanner and the associated software’s 3D model generation-error in both dry and wet skeletal surfaces. Ten human dry skulls and ten mandibles (dry and wet conditions) were scanned twice with an industrial scanner (Artec Space Spider) by one operator. Following a best-fit superimposition of corresponding surface model pairs, the mean absolute distance (MAD) between them was calculated on ten anatomical regions on the skulls and six on the mandibles. The software’s 3D model generation process was repeated for the same scan of four dry skulls and four mandibles (wet and dry conditions), and the results were compared in a similar manner. The median scanner precision was 31 μm for the skulls and 25 μm for the mandibles in dry conditions, whereas in wet conditions it was slightly lower at 40 μm for the mandibles. The 3D model generation-error was negligible (range: 5–10 μm). The Artec Space Spider scanner exhibits very high precision in the scanning of dry and wet skeletal surfaces.