ArticleClinical oral investigations2023
Accurate gingival recession quantification using 3D digital dental models.
Article in Clinical oral investigations, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Robot-Assisted Oral Examination: Challenges and Innovations.International dental journal · 2026Pooled it
- Mechanobiology and Molecular Regulation of Periodontal Tissue Remodeling During Orthodontic Tooth Movement: From Periodontal Phenotype to Precision Orthodontics-A Narrative Review.International journal of molecular sciences · 2026Review
- Modified Coronally Advanced Tunnel Technique With Porcine Dermal Matrix for Recession Treatment: 12-Month Follow-Up.Clinical and experimental dental research · 2025Article
- 3D palatal superimposition in adolescent orthodontic patients treated without extractions: method validation.Clinical oral investigations · 2025Article
- Incidence of Gingival Recessions in Adolescent Orthodontic Patients Treated With Fixed Appliances and Lingual Retainer.Journal of clinical periodontology · 2025Article
- Recent Advances in Intraoral Scanners.Journal of dental research · 2024Review
- Digital workflow to assess gingival recession coverage independently of the cemento-enamel Junction: a prospective clinical study using the modified coronally advanced tunnel technique with porcine dermal matrix.Clinical oral investigations · 2024Article
- Spontaneous Recession Repair after Orthodontic Treatment: Case Report with the Use of Digital Approach for Quantification of Soft Tissue Changes.Case reports in dentistry · 2023Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo develop and validate a method for accurate quantitative assessment of gingival recessions based on superimposition of serial 3D digital models. MATERIALS AND
methodsGingival 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.
resultsFor 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).
conclusionsThe 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.
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